# The Daring Creatives > Behind-the-scenes breakdowns of how real AI creators make their work — the process, tools, and decisions behind standout AI art, film, and animation Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts. Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`). ## Pages ### Calling All Daring Creatives URL: https://www.thedaringcreatives.com/about/ Last updated: 2026-07-06T13:47:02.000Z There's a group of people out there quietly figuring out how to make real creative work with AI. Designers, writers, musicians, filmmakers, storytellers. They're not waiting for permission and they're not pretending it's simple. They're just doing it, and getting good at it. I call them The Daring Creatives. This site is where I break down how they actually do it. The tools, the process, the stuff that worked and the stuff that wasted a weekend. Less theory, more "here's the thing I made and here's exactly how." I'm doing it right alongside you. I've spent my career building brands and making the videos, photos, and design that make them work, and now I'm learning how AI changes that craft. I share my own journey here too, including the times I got it wrong, because that's the useful part. You don't need to master everything. You need enough familiarity across formats to direct them, and the nerve to try before you feel ready. If that sounds like you, you're already one of us. ### Helping creative people URL: https://www.thedaringcreatives.com/home/ Last updated: 2026-04-02T15:45:01.000Z _No content available._ ### How to Teach AI to Write in Your Voice URL: https://www.thedaringcreatives.com/teach-ai-brand-voice/ Last updated: 2026-02-19T23:09:38.000Z AI can be an incredible creative partner, but if you just type a few words into ChatGPT or Gemini, you’ll often get back something that sounds… generic. Safe. A little too polished. And if you care about your voice — the way you tell stories, the way your words make people *feel* — you can’t settle for that. You need a way to make the AI sound like *you*. This guide gives you a simple roadmap for teaching AI your style so it delivers writing that feels like it came from your brain — [without requiring a computer science degree](https://www.thedaringcreatives.com/conversations-with-code/code-capri-sun-and-late-night-breakthroughs-when-development-gets-messy/). ## Why Your Voice Matters Your voice is your fingerprint. It’s the rhythm of your sentences, the words you choose, the jokes you slip in, even the level of formality you lean toward. It’s what makes someone say, “This sounds like you.” AI tools start with a default style — formal, neat, a little bit academic. That’s great for research papers, but it can make your writing feel lifeless. Guiding or training AI to match your style strips away those “AI-isms” and gives you drafts that need way less editing. ## Two Paths to Get There You’ve got two main ways to teach an AI your voice: **Projects (contextual training)** or **prompting with examples.** ### Option 1: Teaching Through Projects (Your AI Workspace) You don’t have to install anything or host your own model. ChatGPT’s **Projects** feature (and similar tools elsewhere) let you upload your writing and build a little creative studio that always remembers your style. **Example workflow:** - **Create a project called “My Writing Voice.”** - **Upload your best samples** — blog posts, captions, newsletters, even emails that sound like you. - **Add context** about who you are, who you write for, and what inspires you. - **Start a conversation inside that project.** Now, every time you open it, the AI has your style and context right there. ### Option 2: Prompting with Context (Quick & Flexible) Not ready to set up a project? You can still get great results with [smart prompting](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/): 1. **Describe your style.** “Make this casual, like a coffee chat.” 2. **Give examples.** Paste one or two of your best paragraphs. 3. **Coach it.** “Try again, but make it sound more playful.” This is fast and interactive — perfect for one-off pieces or experimenting with new ideas. ## Teaching AI Your World, Not Just Your Words Your writing voice isn’t floating in a vacuum — it’s shaped by your life, your tastes, and your audience. AI does its best work when it knows those things. [Good context](https://www.thedaringcreatives.com/context-is-your-creative-edge/) includes: - **Your perspective:** The big ideas you care about. - **Your inspirations:** The books, creators, and artists who shape how you think. - **Your audience:** Who you’re writing for — clients, peers, beginners. - **Your mood:** Bold? Playful? Reflective? Tell the AI so it matches your energy. ## Make It a Conversation Don’t treat AI like a vending machine. Share what sparked your idea, why it matters, and what tone you want. Point out when something feels off. The back-and-forth is where the magic happens — the AI sharpens its output every time you respond. ## My Personal Tips - **Save a style prompt.** Drop it into ChatGPT whenever you start fresh. - **Show before-and-after edits.** This teaches the AI fast. - **Mix it up.** Add new samples so it doesn’t overuse your favorite phrases. - **Keep it fresh.** Your voice evolves — keep your AI up to date. ## The Real Payoff When you get AI tuned to your voice, it stops feeling like a tool and starts feeling like a [creative collaborator](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/). You save time, get unstuck faster, and spend more energy on your best ideas. ## Ready to Build Your AI Voice? I help creatives set up their first ChatGPT Project, upload their writing samples, and teach the AI to sound just like them — so they can create faster and more confidently. ### AI Character Consistency: Same Character in Every Image (2026) URL: https://www.thedaringcreatives.com/ai-image-consistency/ Last updated: 2026-07-16T12:13:55.000Z If you're here, you're probably a creative — maybe a designer, illustrator, brand builder, or storyteller — and you're dabbling (or diving) into AI-generated visuals. Awesome. It's a powerful tool, but let's be real: getting one good image is fun. Getting a *series* of images that actually look like they belong together? Whole different story. This guide is your crash course in maintaining character consistency with AI image generation — across the tools people actually use right now: ChatGPT, Google's Gemini (Nano Banana), Grok's Aurora, and Midjourney. It's not about pressing "generate" and hoping for the best. It's about feeding the machine the right info, with intention. I'll walk you through the why, the how, and my go-to techniques that'll save you from reinventing the visual wheel every time. If you want a head-to-head breakdown of which tool locks a character best, I go tool-by-tool in [AI Character Consistency: Grok Aurora vs ChatGPT vs Gemini](https://www.thedaringcreatives.com/grok-aurora-vs-chatgpt-vs-gemini-ai-character-consistency-guide/). ![Character sheet of The Man in Yellow Sunglasses: the same character in six consistent poses — front, profile, walking, and arms crossed — in a black cap, yellow sunglasses, and a gray hoodie.](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/man-in-yellow-sunglasses-character-sheet-sm.jpg) A character sheet for The Daring Creatives’ own Man in Yellow Sunglasses. This is the goal: one character, same face and outfit, holding steady across every shot. ## Why Character Consistency Matters Whether you're creating a character-driven comic, a branded product series, or just building a cohesive visual vibe across your work, consistency is what holds it together. We're talking: - **Character consistency** — same face, outfit, vibe across scenes - **Style consistency** — same brush strokes, same lighting, same medium - **Scene logic** — settings that make sense together (sunset doesn't jump back to midday unless it's a time-travel story) Older models forgot everything between prompts. Today's tools — Gemini's Nano Banana, ChatGPT, Grok Aurora, and Midjourney's character reference — give you real levers to lock a character in place, if you use them right. ## Best Practices (for Non-Techies Who Want Pro Results) ### 1\. Create a "Prompt Template" Think of this like a brand style guide, but for AI. Start your session with a detailed prompt that locks in your key features. Example: > "Generate an illustration of Luna, a red-haired pilot with green goggles and a leather jacket, in a flat pastel art style." Then — here's the trick — use this exact phrasing across every image prompt. Copy/paste and just change the scene. Repeat her full description every time. Don't assume the model remembers. Be your own prompt parrot. ### 2\. Use Iterative Refinement Instead of Starting Over If an image isn't quite right, don't throw it out and start fresh. That's how you lose consistency. With ChatGPT or Gemini, you can say things like: > "Great, but can you make her hair a bit more orange and keep everything else the same?" This method — called multi-turn generation — helps the AI evolve the image while keeping all the locked-in details stable. The catch: stay in the *same* thread. Open a fresh chat for each scene and you lose the context that's holding your character together. ### 3\. Use Reference Images (Even Rough Sketches Work) You can upload a prior image and say "use this as reference." This helps a ton with character appearance and styling — even screenshots of previous generations work as anchors. Gemini (Nano Banana) and Grok's Aurora are especially strong here; both take uploaded reference images directly. With Nano Banana you can fuse multiple inputs at once: > "Use this character and place her in this background." You can build whole storyboards this way. Decide on one "canon" image of your character, commit to it, and never re-roll it — that image becomes the source of truth for every future scene. ### 4\. Stick with One Model Per Project Don't mix ChatGPT with Midjourney and then toss in Gemini or Grok. Each model has its own "look," even with the same prompt. If you're building a brand kit, product series, or comic strip — pick one and ride it through. ### 5\. Be Consistent with Your Style Phrasing Want all images to look like watercolor or flat vector? Pick your words and stick to them. Example: ✅ "in a minimalist flat vector art style with pastel colors" 🚫 "in a flat style" then later "in a simple art style" These models are picky. Even subtle wording changes can throw off the look — "wavy red hair" and "curly auburn hair" will hand you two different characters. ## 6\. Lock the Face with a Reference Photo The fastest way to lose a character is to let the face drift. The fix: pick one "canon" image of your character's face and feed it back as a reference on every generation. Gemini's Nano Banana (and the newer Nano Banana Pro 2) and Grok's Aurora both take an uploaded reference directly — "same person, same face, new scene." Working from a real person? A clean, front-facing photo locks far better than a busy or angled one. The clearer the reference, the tighter the lock. ## 7\. Build a Scene Series One Shot at a Time For a storyboard, comic, or product series, don't batch-generate the whole set and hope. Go scene by scene: lock your character in the first image, then carry that exact image forward as the reference for the next one, changing only the background or the action. Each shot inherits the last one's look instead of drifting. Slower than generating ten at once, but it's the difference between a coherent series and five strangers wearing the same jacket. ## Which Tool Holds a Character Best in 2026 The models aren't equal at this, and it's changed a lot in the last year: | Tool | Best for | How you lock the character | Holds consistency | | ------------------------------ | ------------------------------- | ----------------------------------------- | ------------------------ | | **Gemini Nano Banana / Pro 2** | Fusing a character into a scene | Upload character + scene, let it fuse | ★★★★★ Strongest | | **Grok Aurora** | Photorealism, real-person refs | Upload a reference, stay in one chat | ★★★★☆ Strong | | **ChatGPT** | Multi-turn edits in one thread | “Keep the same character from this image” | ★★★★☆ Strong (in-thread) | | **Midjourney v7** | Stylized comic / product series | \--cref pointed at your canon image | ★★★☆☆ Good | **Gemini Nano Banana / Nano Banana Pro 2** — strongest at multi-image input. Upload your character and a scene and it fuses them. My default for character work. **Grok Aurora** — great with reference photos and photorealism. Stay in one chat and it holds the look. **ChatGPT** — best inside a single thread using multi-turn. Upload your prior images and say "keep the same character from this one." **Midjourney v7** — use the --cref (character reference) flag pointed at your canon image. Whatever you pick, stay in it for the whole project (see #4). If you want the full head-to-head, I broke each tool down here: [AI Character Consistency: Grok Aurora vs ChatGPT vs Gemini](https://www.thedaringcreatives.com/grok-aurora-vs-chatgpt-vs-gemini-ai-character-consistency-guide/). ## My Tips from the Trenches - 💡 Give your characters names in the prompt, even if they're just "Mascot Bunny" or "Pilot Girl." It helps lock the model onto a specific visual identity. - 💡 Ask for alternate angles of the same scene. ChatGPT is great at this. - 💡 Visual compare. Put your images side-by-side before publishing. Is one slightly off? Fix just that detail: "Move her goggles to the forehead like the last image" is a valid prompt. - 💡 Save your prompt text like source files. Track your inputs, reference images, and versions. Future You will thank you. 💡 Once you've got a repeatable process, you can automate it. I did exactly that — [here's the system that keeps my characters consistent while I sleep](https://www.thedaringcreatives.com/how-i-finally-solved-ai-image-consistency-while-i-sleep/). ## A Quick Recap Workflow 1. **Initial prompt:** define the subject + style. 2. **Generate image:** lock in the look. 3. **Refine:** fix anything off without starting from scratch. 4. **Extend:** create more scenes — repeating key traits + style. 5. **Review & tweak:** side-by-side comparison for continuity. 6. **Repeat with intention.** Bonus: in ChatGPT, upload previous images into the thread and say "keep the same character from this image" — it holds context during that session. In Midjourney, the `--cref` flag does the same job from a reference URL. ## Quick Answers **What's the best AI image generator for consistent characters?** In 2026, Gemini's Nano Banana (or Nano Banana Pro 2) and Grok Aurora are the easiest for most people, because they take a reference image directly. Midjourney v7 works well with --cref. Honestly, the "best" tool is the one you commit to for the whole project — switching mid-way is what breaks consistency. **How do I keep a character's face consistent?** Pick one canon image of the face and pass it back as a reference on every generation (technique #6). A clean, front-facing reference locks better than a busy one. **Do reference images actually work?** Yes — they're the most reliable method there is. Uploading a "use this character" image beats describing the same face in words every time. **Can I keep a character consistent across a whole scene series?** Yes, but go one shot at a time (technique #7): carry the previous image forward as the reference and change only the scene. ## Final Thought: Consistency = Professionalism You don't need to be a technical wizard to make this work. You just need a repeatable process, some visual discipline, and a little bit of storytelling glue. Consistency builds trust. Whether it's your brand, your story, or your style, when your visuals line up, people believe you. Now go make something cohesive — and cool. ### ChatGPT Mascot: Create Yours in 10 Minutes (Free) URL: https://www.thedaringcreatives.com/create-ai-character-mascot/ Last updated: 2026-08-11T11:26:40.000Z You don’t need to be an AI expert to create a fun, useful character that represents your brand. You just need: - A clear idea of what your brand is about - A willingness to play with words - And ChatGPT. That’s it. This guide will show you how to go from “vibe” to “mascot” using ChatGPT, without touching a design tool or learning any complex prompt engineering stuff. Let’s go. ## Why Characters Work (Even for Small Brands) People don’t fall in love with products. They fall in love with personalities. A good character or mascot can: - Make your brand more memorable - Help you explain things in a fun, human way - Build trust and recognition over time Even if it’s simple. A cozy little owl that shares your brand tips. A nerdy robot that answers questions. A talking piece of toast who shows up in your videos. Characters stick. Especially when they feel intentional. ### Step 1: Start With What Your Brand *Is* Before you open ChatGPT, get a notebook or open a blank doc and jot this down: - What do I want my brand to feel like? (e.g. friendly, smart, edgy, warm) - Who am I trying to reach? - What values or beliefs are central to what I do? - If my brand was a person, what would they sound like? You don’t need to overthink it. Just get a general feel. That’s what we’re going to feed into ChatGPT next. ### Step 2: Ask ChatGPT to Help You Brainstorm Here’s the easiest way to get started. Go to ChatGPT and type something like this: > “You’re a creative brand strategist. I want help coming up with a mascot or character for my brand. My brand is \[describe your vibe, values, audience\]. I’m thinking something [fun and memorable](https://www.thedaringcreatives.com/sharing-your-work-is-still-less-risky-than/) that I can use in my content. Can you give me 3 character ideas?” ChatGPT might give you: - A curious fox who explains complex topics - A cosmic cat who represents creativity and wonder - A coffee bean who tells short stories and morning mantras Now you can ask for more: “Make the fox idea more unique” or “Tell me what the cosmic cat’s personality is like” or “Give me a short backstory for the coffee bean” You’re not fishing for a perfect answer. You’re shaping clay. You’re finding a *spark*. ### Step 3: Build Out Your Character’s Personality Once you’ve found a concept you like, ask ChatGPT to help flesh it out. Prompt example: > “Can you describe this character in more detail? What do they look like? What’s their personality? What are 3 traits they’re known for? What’s their little backstory?” Then you can follow up with: - “How would this character introduce themselves in a social media post?” - “What’s a funny or memorable catchphrase they’d say?” - “Write a short paragraph of them talking to a customer.” Now your [character has *a voice*](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/)—not just a name or look. And that voice can help you make better content, consistently. ### Step 4: Use the Character in Your Brand This is where most people stop. Don’t. Once you’ve got the character, use them: - As a narrator for your videos or posts - In your newsletter intros or customer emails - On your website to explain your process - As a “guide” in your digital products or onboarding Characters give you a built-in tone. They remove the pressure of always speaking in “brand voice.” You can say things through your character that would feel weird if it came straight from you. > Personal tip: When I feel stuck writing, I ask, “How would the character explain this?” It makes things *way* more fun—and easier. ### Step 5: Keep It Consistent Once you decide on your character: - Save the description - Save the phrases or example messages - Re-use that same personality and vibe again and again That’s how people start to recognize the character as part of your brand. You don’t need 50 versions. You just need *one character used well*. ### Optional: Visuals Can Come Later This page is about ChatGPT, not image generation. But if you *do* want to [create a visual version](https://www.thedaringcreatives.com/ai-image-consistency-guide/) of your character later, you can take your written description and use a tool like DALL·E, Midjourney, or work with a designer. ChatGPT can help you write the prompt for that too. No pressure. You don’t need the picture to start using the character. ## Final Thoughts You don’t need to be “good at AI” to use ChatGPT well. You just need to know your brand and be willing to play. This kind of stuff used to take branding agencies weeks. Now? You can sit down with ChatGPT for 30 minutes and walk away with a solid character, a voice, and a vibe you can build on. That’s power. And if you ever want help turning your idea into a story, content plan, or visual identity—I do that. Let’s build something weird, sticky, and unmistakably *you*. ### Build Apps Without Being a Coder: The Beginner’s Guide to Vibe Coding URL: https://www.thedaringcreatives.com/beginners-guide-vibe-coding/ Last updated: 2026-02-19T23:09:37.000Z Let’s be honest: the speed of AI can feel like standing in front of a firehose. One minute you’re reading about ChatGPT helping people code; the next minute there’s an entirely new tool, a new framework, and it feels like you’re already behind. Here’s the thing: you don’t have to be a “coder” to start building. You don’t need to learn algorithms, data structures, or remember what `for (i=0; i “Write me a script that takes my iOS contacts, converts them to CSV, and then lets me search for them against a database.” That one request turned into a working app i could run on my mac on the first try, and saved me $50 because that's what apps that did this conversion costed in the App Store. ## The Vibe Coding Workflow The core loop is simple. 1. **Describe the Goal** – Tell the AI what you want, like: “Create a webpage with a black background, a big headline that says ‘My Portfolio’, and a grid of three image placeholders.” 2. **Generate & Test** – Copy the code, run it, see what happens. 3. **Refine** – Tell the AI what to fix: “Make the text larger and centered,” or “Connect this to a Google Sheet so I can update it without touching code.” 4. **Repeat** – Iterate until it feels right. The magic is that you never have to write perfect code — you just keep steering. ## Terms You’ll Hear (Without the Jargon Overload) - **Frontend**: Everything your users see (buttons, layouts, animations). Think of it like your website’s storefront. - **Backend**: The behind-the-scenes engine — databases, authentication, file storage. - **API**: A bridge that lets your frontend talk to your backend. Example: when you click “submit,” the API is what sends that data somewhere. - **React**: A popular way to build frontends using components (reusable pieces). - **Node.js**: Lets you write backend code in JavaScript so you don’t have to learn another language. - **Prompt Engineering**: Fancy way of saying “ask better questions.” [The clearer your prompt, the better your results](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/). ## What You Could Build The possibilities are endless, but here are a few starter ideas: - **Personal Tools** – Automate repetitive work (like I did with my contacts). - **Portfolio Sites** – AI can scaffold a React site in minutes, so you can focus on design. - **Mini-Dashboards** – Track projects, finances, or habits with a simple web app. - **Email Tools** – Build a form that collects leads and drops them into a Google Sheet. Start small. You’ll be shocked how quickly this turns into real, usable tools. ## A Word on “Agentic Coding” This is where things get really interesting. Tools like Claude Sonnet and [Warp](https://www.thedaringcreatives.com/conversations-with-code/code-capri-sun-and-late-night-breakthroughs-when-development-gets-messy/) are starting to behave like junior developers who can plan, edit, and test entire codebases for you. Warp, for example, is a terminal (a developer’s command center) that lets you just type in natural language like: > “Build me a website that helps me attract creatives who are curious about AI but don't know where to start.” And it does the setup for you. This is next-level vibe coding — instead of just snippets, you’re orchestrating whole features. I’ll write a deeper dive on this in the future, but keep it on your radar. ## The Mindset Shift The hardest part isn’t learning tools — it’s letting go of the idea that you have to know everything first. Your job isn’t to be the computer. [Your job is to be the **director**](https://www.thedaringcreatives.com/directing-the-machine/): to give clear instructions, keep an eye on the big picture, and decide when the code is “good enough.” You’re orchestrating the AI, not fighting it. If you start with a low-stakes project — a portfolio, a tool for yourself, a silly experiment — you’ll build confidence. And once you build one thing, you’ll start to see opportunities everywhere. ### Digest Archive URL: https://www.thedaringcreatives.com/archive/ Last updated: 2025-10-05T01:24:47.000Z _No content available._ ### William Smith URL: https://www.thedaringcreatives.com/william/ Last updated: 2026-07-06T22:20:48.000Z I’m a brand storyteller. I’ve spent my career learning how to build brands from the ground up, then getting my hands dirty actually making the things—the videos, the photos, and the design assets—that make those brands work. I help people communicate their complex ideas in a way that’s relatable and understandable, handling the technical side so you can focus on running your business. ### Any Industry, Any Challenge Whether I’m working on a complex technical project, a physical space, or a person’s life story, I’m always up for a challenge. My goal is to find the interesting parts of what you do and turn them into something people actually want to engage with. I specialize in: - **Finding the Story:** Taking a complex idea or a dry set of facts and turning them into a narrative that feels human and approachable. - **Making it Happen:** Handling the actual production—from camera setups to design workflows—so that high-quality content becomes a regular habit for your brand, not a one-off event. - **Getting Found:** Making sure the work is built correctly for how people actually use the internet today. I ensure your brand shows up where your audience is already looking. ### Art at The Geode Fine Art Gallery URL: https://www.thedaringcreatives.com/eichinger-sculpture-studio/ Last updated: 2026-02-16T02:49:30.000Z ### The Challenge Martin Eichinger is a master sculptor who spent over 40 years building a global reputation in bronze. My challenge was to take that storied legacy and help him pivot into a completely new medium: epoxy resin. I’m most proud of developing a cohesive brand that popularized this "Amorphous Polymer" work, effectively bridging the gap between his traditional bronze masterpieces and his new, space-inspired fine art. I helped collectors see the same level of mastery in the resin that they had admired in his bronze for decades. ### **The Process** - **Rebrand & Web Architecture:** I built a search-first website designed to showcase the light and depth of the resin pieces while maintaining a dedicated space for his legacy bronze collections. - **Full-Funnel Marketing:** I manage everything from organic search and paid social ads to email marketing and high-end print collateral. - **Content Systems:** I developed a blog and social strategy focused on "educational storytelling"—explaining the complexity of epoxy as a fine art medium to help long-time collectors embrace the new work. ### **The Results** - **Successful Market Pivot:** Successfully introduced a new product line to a 40-year-old brand without alienating the existing fan base. - **Digital Authority:** Established the gallery as a top-ranking destination for both bronze sculpture and contemporary resin art through aggressive SEO and targeted social campaigns. /examples/ ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Helping-Hand-Bust-front-detail.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/nebular-explosion-wide.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/IMG_2322.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Adrenaline-Rising-final.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Eichinger-sculpture-studio-website.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Screenshot-2025-11-12-at-9.10.00---PM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Eichinger-Long-Form-Copy-example.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/eichinger-long-form-copy-example-2.png) /social/ http://instagram.com/artatthegeode ### The Daring Creatives URL: https://www.thedaringcreatives.com/the-daring-creatives/ Last updated: 2026-04-02T15:30:56.000Z ## **Case Study: Building a Multimodal Creative Ecosystem** *The Daring Creatives* is a live creative lab and digital publication designed to demonstrate the practical integration of AI into professional creative workflows. I serve as the Founder and Lead Strategist, managing every aspect from technical architecture to community engagement. ### **The Challenge** To create a high-fidelity "zine" and community hub that overcomes the stigma of AI in creative industries by prioritizing "Principles over Buttons". ### **Technical Execution & Innovation** - **Vibe-Coded Architecture:** Built a professional-grade web platform using **Ghost.io** and a custom **Casper** theme, managed entirely through a terminal agent (**Warp**). - **Agentic Workflows:** Developed custom scripts for automated content zipping, JWT authentication, and API deployments to ensure a seamless, professional-grade deployment system. - **AI Asset Production:** Integrated **Kling AI**, **Midjourney**, and **Udio** to create a unified brand aesthetic (Neon-Noir), proving that AI can maintain high-fidelity visual and audio consistency. - **Content Systems:** Established a "Monthly Issue" rhythm to move away from the "Blog Feed" noise, focusing on curated, deep-dive articles that demonstrate industry thought leadership. ### **Key Results** - **Proof of Concept:** Demonstrated that a "Company of One" can leverage AI to perform the work of an entire creative agency. - **Community Trust:** Built a dedicated following on Meta’s **Threads**, using real-time dialogue to move beyond the "AI Slop" narrative and focus on "Intellectual Curiosity". - **Educational Authority:** Published "The Prompt Playbook," a high-utility digital guide that translates abstract AI concepts into actionable creative frameworks. /examples/ ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/the-daring-creatives-red-angular-1.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Screenshot-2025-11-12-at-12.48.00---PM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/556bc261-fbf1-404b-9ee9-ca757258e7f9.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/3bd14388-c1f5-49ac-9f21-e1aa087d9928.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/b7599788-3bcb-45e7-a684-c402601ce2ed.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/ecf60e95-ffc3-4607-a4e7-b6227f028d55.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Screenshot-2025-11-12-at-12.43.55---PM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/Screenshot-2025-11-12-at-12.43.41---PM.png) This website was vibe coded using Ghost.io as the underlying web cms, with a [custom casper theme](https://www.thedaringcreatives.com/conversations-with-code/css-spacing-and-two-year-revelations-when-homepage-tweaks-lead-to-life-philosophy/) for the front end. Most of my interactions with this site is done [using a terminal agent](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/), which in this case was Warp. The website isn't overly complicated, but does fit my brand aesthetic. My goal was to build a professional looking 'zine that caters to artists, designers, musicians, and storytellers. It also would need to highly leverage ai created assets and ai-assisted content. Above you can see some screenshots of initial wireframes (done in ChatGPT), as well as some character development work for my digital alter egos. /social/ Threads: [https://www.threads.com/@thedaringcreatives](https://www.threads.com/@thedaringcreatives?ref=thedaringcreatives.com) Instagram: [https://www.instagram.com/thedaringcreatives/](https://www.instagram.com/thedaringcreatives/?ref=thedaringcreatives.com) ### Bourbon Lore URL: https://www.thedaringcreatives.com/bourbon-lore/ Last updated: 2026-04-15T15:53:37.000Z ## **Case Study: Embedded Content Strategy & Documentary Filmmaking** I served as an embedded creative partner for Bourbon Lore, a luxury lifestyle brand focused on high-end spirits and exclusive collector events. My objective was to move beyond standard event coverage and create a "first-person" documentary style that allowed the audience to experience the brand’s intimacy and craft. ### **The Challenge** Capturing the high-energy, exclusive nature of live events and translating that "lightning in a bottle" into a cohesive, evergreen digital narrative for YouTube and social media. ### **My Approach & Execution** - **The "William Smith Filter":** Applied a signature first-person approach, documenting the experience through the eyes of an intellectually curious participant rather than a detached observer. - **Narrative Discovery:** Conducted on-site interviews with founders and distillers, hunting for the "emotional core" of their stories by focusing on physical details and vulnerability. - **Cinematic Production:** Managed the end-to-end production of polished YouTube content, focusing on atmosphere, rhythm, and the human elements that make a brand feel relatable. - **Social Storytelling:** Developed a "bold, cinematic" visual style for social clips that prioritized "Presence > Perfection," ensuring the brand stayed top-of-mind for its audience. ### **Key Results** - **Brand Affinity:** Created a content library that humanized the luxury brand, fostering a deeper connection with the collector community. - **Systematized Content:** Established a reliable workflow for capturing and shipping high-quality video assets from high-pressure live environments. - **High-Fidelity Archive:** Built a "Live Archive" of the brand’s energy that continues to serve as a marketing asset for future event recruitment. /examples/ /social/ ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/bourbon-lore-social.png) ### Noctel Fiber URL: https://www.thedaringcreatives.com/noctel-fiber/ Last updated: 2026-02-15T01:04:05.000Z ## **Case Study: Brand Advocacy & Growth Marketing Campaign** ## I worked as an embedded creative strategist within Noctel Fiber’s team to identify and articulate the unique value proposition of their network infrastructure. By shifting the focus from technical specs to community impact, we developed a narrative that positioned Noctel as a vital alternative to legacy telecom providers. ### **The Challenge** Communicating the value of rural connectivity in a way that resonates emotionally with underserved communities while competing against the massive marketing budgets of national telecom giants. ### **My Approach & Execution** - **The "Fiber to the Forgotten" Campaign:** Spearheaded the development of a mission-driven campaign that highlighted the specific rural communities ignored by big telecoms, turning Noctel’s smaller scale into a competitive advantage. - **Story Discovery:** Conducted deep-dive interviews within the Noctel team to uncover the "internal conflict" and real-world success stories of their network rollout. - **Multimodal Assets:** Developed a cross-platform content system—including video testimonials, long-form community spotlights, and social storytelling—to clarify the network's value. - **Strategic Clarity:** Translated complex technical capabilities into plainspoken language that built immediate trust with founders and rural stakeholders. ### **Key Results** - **Market Differentiation:** Successfully carved out a unique brand identity for Noctel based on advocacy and "forgotten" community support. - **Stakeholder Trust:** Clarified the brand story to increase buy-in from both current users and potential community partners. - **Resilient Brand Assets:** Created a high-utility content library that demonstrates the network’s value through long-term, repeatable storytelling. /examples/ ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/38C82F92-6959-46EB-B1E9-A80CB1767EFD_1_105_c-1.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/518245D2-B5E6-4E4F-B3F2-0BB61F1DF0F9_1_105_c.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/1A177B86-50C7-4A4F-8ECE-460E651BB415_1_105_c-1.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/638A2092-EC1A-4709-B8BE-7D1362C8E5FC_1_105_c-1.jpeg) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/C452FCDE-CDA4-4686-8894-66A599CC08FA_1_105_c-1.jpeg) ### The Geode URL: https://www.thedaringcreatives.com/the-geode/ Last updated: 2026-02-16T02:34:17.000Z ### The Challenge A commercial building is more than just square footage; it’s a creative ecosystem. My job is to ensure **The Geode** is recognized as the premier hub for makers and professionals in SE Portland. I solve the problem of vacancy by keeping the building’s brand active, inviting, and highly visible to the right tenants. ### **The Process** - **Strategic Promotion:** I lead the marketing efforts to keep the building leased out, working closely with brokers and vendors to move suites quickly. - **Production & Media:** I handle all photography and videography for the property, moving away from "stock" real estate shots in favor of cinematic tours that highlight the building's soul. - **Presence Management:** I run the building’s social channels, turning the physical address into a digital brand that potential tenants actually want to follow. ### **The Results** - **Consistent Occupancy:** Maintained high occupancy rates by positioning the building as a "must-have" address for the local creative class. - **High-Utility Archive:** Created a robust library of visual assets that allows for rapid marketing whenever a new space becomes available, reducing the time a unit sits empty. /examples/ ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/suite_201_202_floor_plan_onyx-2.webp) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/new_geode_photo-2.webp) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/2w1a9819_hdr-1.webp) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/geode_lease_flyer_1-1.webp) 0:00 /0:27 1× ### Lincoln Design Co. URL: https://www.thedaringcreatives.com/lincoln-design-co/ Last updated: 2026-02-16T04:47:12.000Z ### The Challenge The central tension was capturing high-end content without interrupting the flow of a fast-paced, "working studio." The team leaned toward a raw, street-level aesthetic shot entirely on GoPros, while I was operating with a high-end cinema camera background. My goal was to respect their operational boundaries while ensuring the final product met professional standards. ### My Approach & Execution - **Hybrid Workflow**: Instead of choosing one style, I elevated the production by blending both worlds—pairing my cinematic footage with their "run-and-gun" GoPro clips to create a textured, authentic look. - **Operational Integration**: I developed a methodology that allowed content creation to fit seamlessly into their existing workflow, ensuring the cameras were always rolling but never in the way. - **Stealth Directing & Cheerleading**: To maintain the studio's focus, I prioritized psychological safety over technical procedure, using music and humor to make the team comfortable enough to be their authentic selves on camera. - **High-Volume Discipline**: Managing 50 episodes required a relentless commitment to shipping, solidifying my belief that "Presence > Perfection" is the key to maintaining long-term audience engagement. ### Key Results - **Series Success**: Produced a cohesive, 50-episode run that defined the brand’s digital voice and showed the world the "messy middle" of a top-tier design agency. - **The Lincoln Unlock**: The experience of working fast and light completely changed my production style, teaching me how to produce edgy, professional content with a lean footprint. - **Scalable Authenticity**: Proved that you can achieve cinematic results in a non-traditional environment by embracing the chaos rather than trying to control it. ### Audigy URL: https://www.thedaringcreatives.com/william-projects-audigy/ Last updated: 2026-04-14T04:17:51.000Z ## The Challenge Audigy helps independent hearing care practices grow their businesses. When I joined in 2012 as a marketing manager, the company had big ambitions but its marketing infrastructure wasn't built to scale. They needed someone who could handle the full spectrum — web, video, podcasting, brand — across a network that would eventually span over 250 member practices, each with their own needs and audiences. ## My Approach & Execution - **Web at Scale**: I built and managed the web development systems that powered 250+ sub-websites for Audigy's member practices. Each site had to feel personalized while staying on-brand. - **Podcast Network**: I built a podcast network from scratch — 5 recurring shows, over 250 episodes. The content served existing members, recruited new practices into the network, and positioned Audigy as the authority in the private practice hearing space. - **AGX Rebrand**: Led the digital consumer-facing rebrand for AGX, Audigy's hearing aid product line. This was a different challenge — translating a B2B company's credibility into something a consumer could feel and trust. - **Video Production**: I developed what I'd later understand as my core methodology — prioritizing psychological safety over technical procedure. If the person doesn't feel comfortable, the footage is going to be stiff and unusable. So I made every shoot feel like the most fun part of their day. ## The Role That Kept Growing I started as a marketing manager and grew into a senior strategist. That trajectory wasn't planned — it happened because I kept finding problems I could solve. ## What I Took With Me This is where I fell in love with helping small businesses. I learned every aspect of how a business actually works — not just the marketing silo, but the full picture. And I discovered that my real skill wasn't video or podcasting or web development. It was making people comfortable enough to be authentic, and then building systems around that authenticity so it could scale. ### Cardone Ventures URL: https://www.thedaringcreatives.com/cardone-ventures/ Last updated: 2026-07-06T21:05:33.000Z ## The Challenge When Brandon Dawson exited Audigy and launched what would become Cardone Ventures, he had the operational blueprint for scaling businesses but needed the content infrastructure to match. COVID had just hit, personal branding was suddenly everything, and the company needed to go from zero to a full-scale media operation — fast. Brandon called me as one of the first people on the team. I walked in on the ground floor with no playbook and a mandate to build the content engine that would power everything. ## My Approach & Execution - **E-Learning Platform**: Helped build a digital education platform delivering leadership and business content that generates $11M annually. This wasn't just recording a few courses — it was building a scalable content system from scratch. - **Live Production**: Managed live-streamed shows that put Brandon, Natalie Dawson, and Grant Cardone in front of their audiences in real time. Live content is unforgiving — there's no "fix it in post." Every show was a high-wire act. - **Studio Management & Videography**: Ran the studio and served as the primary videographer. The content volume was massive — podcasts, YouTube, social clips, event coverage — and it all had to ship on a schedule that matched Grant Cardone's intensity. - **YouTube & Podcast**: Built out the channel strategy and podcast production. The goal was positioning Cardone Ventures as the go-to resource for business owners who wanted to scale, not just dream about it. - **Documenting the Build**: For about a year, I had uncommon access to what was happening behind the scenes — three founders building a brand empire on social media. ## What I Took With Me This experience rewired how I think about access and opportunity. Grant had a rule I heard repeated constantly: "If you want to be in business with me, you have to do business with me." Brandon and Natalie lived that — they didn't ask for Grant's attention, they earned proximity by showing up with skin in the game. That lesson stuck with me long after I left. Stop asking gatekeepers for permission. Stop waiting to be discovered. Either make yourself undeniable or build your own room. I watched a company go from a concept to a multi-million dollar platform, and the engine behind it was content — the same content I was building every day. ### Portfolio — William Smith URL: https://www.thedaringcreatives.com/william-portfolio/ Last updated: 2026-07-09T20:27:42.000Z This page is rendered by the page-william-portfolio theme template. ## Posts ### Sara Shakeel Crystallizes It Digitally, Then 80 Artisans Sew It by Hand URL: https://www.thedaringcreatives.com/creator-stories/sara-shakeel-crystals-digital-to-embroidery/ Last updated: 2026-08-14T10:32:26.000Z An Earth hangs in a dark room, and every wave on it is a stitch. The oceans are lines of blue thread laid by hand, the clouds are white swirls of it, the continents are gold and green and studded with cut glass that grabs whatever light is in the room. A moon floats beside it, pocked in silver. A sun burns orange behind them both, covered in embroidered flowers. Get close and you can see the needle marks. That's the work Sara Shakeel put into Two Taikoo Place in Hong Kong last spring, and the numbers behind it are the part that stops you: over 3.9 million vintage glass crystals, sewn by 80 artisans in Pakistan, across sculptures running from a metre and a half to seven metres tall. It ran March 22 to April 27, 2025 as part of Swire Properties' Arts Month. In the lobby next door she hung a tent of crystal-flecked fabric that pooled on the floor like a gown. None of it started in a workshop. It started on a Samsung. ![Two Sara Shakeel crystal collages side by side: a snake made of glittering crystals coiled around a hand, and a cheeseburger whose filling is a mass of sparkling gems](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/sara-shakeel-crystal-collages-snake-burger.jpg) Sara Shakeel — crystal collages, via [Colossal](https://www.thisiscolossal.com/2019/07/sara-shakeel-collages/?ref=thedaringcreatives.com) ## It Started With a Stylus and a Phone App She has told the story the same way in several places, and it stays refreshingly unglamorous. *"I never knew that I was an artist,"* she said in [an interview with designboom](https://www.designboom.com/art/sara-shakeel-evian-interview-nft-04-04-2022/?ref=thedaringcreatives.com). *"But one day, accidentally, out of nowhere, I took out my phone — Samsung note 3 with a pen — and it just happened that I opened an application and starting adding pictures, making collages, and uploading these works on Instagram."* For the first one she picked a crystal pattern and dropped it onto a set of lipsticks. It went off overnight. People wanted to buy the lipsticks, magazines wrote in asking where to find them, and she had to keep explaining that the product did not exist and never had. She didn't have the software yet, either. *"I never knew what Photoshop was,"* she told designboom. *"One of my artworks — the crystal lipsticks — went viral, and people wanted them, as in the physical object... So I googled it, downloaded it and taught myself how to use it."* That's the whole origin: a stylus, a collage app, and a Google search for the tool everyone assumed she already owned. I love that she says it out loud. The subjects settled fast — food, landscapes, women's bodies, ordinary bathroom fixtures. Crystals stand in for water coming out of a tap, for the melt in a cheeseburger, for the scales on a snake, for windows on a skyscraper. Her glitter stretch marks series came out of the same instinct, putting light on the parts of a body people are told to cover. ![Two Sara Shakeel crystal collages: a pink bathtub filling with sparkling crystal water, and a pair of Reebok sneakers and socks encrusted in glitter](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/sara-shakeel-crystal-collages-bath-reebok.jpg) Sara Shakeel — crystal collages, including her 2019 Reebok collaboration, via [Colossal](https://www.thisiscolossal.com/2019/07/sara-shakeel-collages/?ref=thedaringcreatives.com) ## The Crystals Come From Her Grandmother Ask her why crystals and she goes straight to the house she grew up in. *"When it comes to crystals, my grandmother used to collect a lot of Swarovski crystals,"* she told designboom. *"So, in one way or another they had been present always, throughout my life."* Then, plainly: *"I love how a clear thing has so many colors to it."* She has also given the material a longer meaning. Speaking to Tatler Asia around the Hong Kong show, she described crystals, gemstones and diamonds as a metaphor for resilience — something that went through immense pressure and time to become something brilliant. She talked about beauty as a way in, the thing that makes somebody stop and feel something, and about what you get to say once you have their attention. That's a working theory of her own audience, and it's held up for six years. ## Chance the Rapper Made Her Build One in Real Life In 2019 she posted a digital image of a transparent CD glittering with crystals. Chance the Rapper messaged her about it. *"Like, all of a sudden I saw someone, like, messaging me, Chance the Rapper, saying, 'Hey, Sara, I love your work,'"* she said in [a Yahoo Lifestyle piece on the collaboration](https://www.yahoo.com/lifestyle/instagram-famous-artist-made-chance-190000661.html?ref=thedaringcreatives.com). He wanted it as the cover of *The Big Day*, which meant the imaginary object had to become a real one. It took about three trials. She built a mold, set clear resin into it, and embedded 20 to 30 diamond-cut Swarovski crystals. The mold and pour took a day. The resin took roughly a week to harden. Then she photographed it and did the only digital work left in the job, enhancing the flashes coming off the gems. She also designed The Big Store, the pop-up that ran alongside the record, with crystal-covered furniture and objects in it. Around the same stretch came the Reebok body-image campaign, the Browns capsule collection, and The Great Supper at NOW Gallery in London — a full dining table, chairs, plates, food and candlesticks, all of it crystallized, which won the gallery's annual Young Artist Commission. ![A tall circular tent of dark crystal-flecked fabric standing in a glass office lobby at dusk, its skirt pooling on the floor, with people walking past in motion blur](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/sara-shakeel-jewel-system-taikoo-place.jpg) Sara Shakeel — installation at Two Taikoo Place, Hong Kong, 2025\. Via [designboom](https://www.designboom.com/art/artistree-selects-the-jewel-system-sara-shakeel-swire-properties-hong-kong-talk-04-02-2025/?ref=thedaringcreatives.com) ## Eighty Embroiderers and Four Named Stitches The Hong Kong work is where the digital practice and the craft practice finally met on the same object. The planets were hand-embroidered in Pakistan using techniques with their own names: zardozi, resham, dabka, mukesh. Metallic thread work and crystal embellishment, done by 80 artisans, over 3.9 million crystals, on forms big enough to walk under. The companion piece pushed the same materials toward the beginning of everything, layers of embroidered fabric and suspended crystals hung inside a sweeping black net. Look at the detail shots and the two halves of her career sit right on top of each other. A spiral of beadwork on black tulle reads exactly like one of her collages — a shape traced in points of light against a dark field — except a person sat with it and put every point there. ![Close detail of a spiral of multicoloured crystals hand-beaded onto black netting, lit from behind](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/sara-shakeel-crystal-embroidery-detail.jpg) Sara Shakeel — crystal embroidery detail, Hong Kong, 2025\. Via [designboom](https://www.designboom.com/art/artistree-selects-the-jewel-system-sara-shakeel-swire-properties-hong-kong-talk-04-02-2025/?ref=thedaringcreatives.com) ## What She Says About AI She used AI in the concepting for the Hong Kong installation, and she was asked about it on stage there. Her answer was short. *"AI is just another tool for an artist — just like a sculptor's chisel or a painter's brush."* Then she put a limit on it in the same breath. *"AI has no soul, so it needs an artist's touch to give it life, which I tried to do by creating The Jewel System."* And on why the work ended up as thread and glass instead of a file: *"As human beings, we need to have that tactile sensation with something you can touch, feel, see, and experience."* Then she put the condition on it. *"There should always be an intention behind what you create. If it comes from a clear place, AI will help you create the most beautiful thing."* She's describing a workflow where the machine sits in the middle and never at either end. The intention is hers at the front. Eighty pairs of hands finish it at the back. [STR4NGETHING works a similar seam](https://www.thedaringcreatives.com/creator-stories/str4ngething-wrong-era/), building an aesthetic that's fully worked out before the tool gets a say in it. ## What the Dentistry Gave Her She calls herself an ex-dentist on [her own site](https://sarashakeel.com/?ref=thedaringcreatives.com), where the current job title is artrepreneur, creative director and digital artist. She's said she was steered toward a practical career instead of art school. She doesn't treat those years as lost time. *"Dentists master the art of sculpting teeth, a process akin to what traditional sculptors undergo,"* she told Art Plugged. *"My dental training equipped me with skills that now resonate in my artistic pursuits."* There's something to that beyond a nice line. Dentistry is close work, done under a light, at millimetre scale, where the result has to look right and feel right to a person who did not ask to be there. Six years of crystal placement is the same job with the pain part removed. Her stated mission on the wall of her own site is about as unguarded as an artist statement gets: to show the world through hope, joy and optimism. The work is still going up on [her Instagram](https://www.instagram.com/sarashakeel/?ref=thedaringcreatives.com), one crystallized ordinary object at a time, next to photographs of planets that took 80 people to sew. ### Gorgon Soup Is Building a Cosmic Horror Universe One Weekly Short at a Time URL: https://www.thedaringcreatives.com/creator-stories/gorgon-soup-sector-9-process/ Last updated: 2026-08-12T13:00:00.000Z A corporate priest in a wet leather coat stands under something enormous and organic, lit from above in a green that doesn't occur in nature. Red status lights blink in the dark behind him like the walls are running diagnostics on themselves. He looks directly into the lens. Whatever is above him is breathing. That's a fifteen-second vertical video. There are dozens more, and they all take place in the same room, the same shaft, the same station. Gorgon Soup calls the place [SECTOR 9](https://gorgonsoup.com/?ref=thedaringcreatives.com), and describes it in one line: a mining outpost in the furthest corner of human ambition. The station belongs to Morland Industries. The crew extracts a crystal called Abyssite, a volatile thing with quantum properties nobody on the payroll fully understands. The work is brutal, the isolation is total, and the company has an answer for that. Gorgon Soup — "Welcome to SECTOR 9," via YouTube ([@gorgon\_\_soup](https://www.youtube.com/@gorgon%5F%5Fsoup?ref=thedaringcreatives.com)) ## The world has a spine before it has a shot Most AI video accounts are a mood. Gorgon Soup wrote a premise first, and you can read it on the site in three numbered sections. The company's answer to the isolation is a promise called The Great Return. Mine enough crystal, the doctrine goes, and the universe achieves full consciousness. In that moment reality shifts, the need for resources vanishes, the need for labor ends, and everybody finally gets to rest. Sacred labor as a comp package. Then mental stability starts collapsing. The crew reports shared nightmares and memories that belong to other people. Shadows on the walls that follow. A parasitic organism. A figure with red eyes. It's worst in the lower parts of C-Block, and the miners cope by working, because the routine of the drill is the only thing holding them together. ![Cutaway schematic of the SECTOR 9 mining facility: a domed surface station above three descending levels, labelled A-Block control, B-Block habitation, and the C-Block core shaft ending in an off-limits zone marked "mapping incomplete".](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/gorgon-soup-sector9-facility-schematic.jpg) Gorgon Soup — the SECTOR 9 facility schematic: A-Block control, B-Block habitation, and the C-Block core shaft running down into the off-limits zone. Via [gorgonsoup.com](https://gorgonsoup.com/?ref=thedaringcreatives.com) Productivity flatlines anyway. Quotas get missed. So Morland Industries sends help, and the help is not engineers or soldiers. They send a Spi-G. A Spiritual Guide. His name is Rook, a Corporate Priest-Psychologist whose written orders are to optimize the miners' mental state for maximum output. The site is blunt about the gap between what he was hired for and what he thinks he's doing: the corporation sent him to fix the numbers, Rook intends to save their souls. That's a real story engine. Nobody needs a generation tool to come up with a company that responds to a mental health crisis by shipping in a chaplain with a productivity mandate. ## The tools are listed in the footer Here's the part I didn't expect. Scroll to the bottom of gorgonsoup.com and there's a section headed GENERATION TOOLS, with the stack printed out. Not a vague "made with AI." The actual list. Tools Gorgon Soup credits on their own site - [Kling](https://www.klingai.com/?ref=thedaringcreatives.com) — video generation - Nano Banana Pro — image work - [ElevenLabs](https://elevenlabs.io/?ref=thedaringcreatives.com) — audio and voice - Midjourney — image generation - [DaVinci Resolve](https://www.blackmagicdesign.com/products/davinciresolve?ref=thedaringcreatives.com) — editing and color - [Ableton](https://www.ableton.com/?ref=thedaringcreatives.com) — music Two of those six predate the whole AI wave. Resolve is the edit and the color grade, Ableton is the score, and both have been sitting on film students' laptops for years. The other four are the new part: Midjourney and Nano Banana Pro make the frames, Kling moves them, ElevenLabs gives everyone a voice. So the AI covers image, motion, and audio. Everything downstream of that is a person in an edit bay deciding what goes where and how long the silence runs before the cut. Publishing the list at all is a generous choice. Plenty of people in this space treat their stack like a trade secret, and I get why. A stack has never been much of a moat though, and Gorgon Soup seems to have worked that out already. Gorgon Soup — SECTOR 9, "Operation Rescue Rook," via YouTube ([@gorgon\_\_soup](https://www.youtube.com/@gorgon%5F%5Fsoup?ref=thedaringcreatives.com)) ## The release schedule is doing a lot of the work Every video description on the [SECTOR 9 channel](https://www.youtube.com/@gorgon%5F%5Fsoup?ref=thedaringcreatives.com) carries the same line: new AI videos every week, subscribe to follow the descent. That's the format. Fifteen entries went up on YouTube between early June and the end of July alone, all under titles that read like incident reports. The Recalibration Centers. Gossip in the Throat. The C-2-20 Incident. Dr. Malone assesses an Awakened subject. Leland meets the Miles Gang. Rook ventures deeper. Watch a few in order and the naming starts to pay off. Characters recur. Locations recur. "The Throat" shows up as a place people go down into, and it keeps meaning the same thing. Each clip is short enough to have been generated in an afternoon and specific enough that it has to sit somewhere on a timeline that already exists. Serialization covers for the tool, too. A fifteen-second scene doesn't have to hold a character's face for ninety seconds, which is still where these models fall apart. Episode length matched to what the generator can actually keep stable is a craft decision, and it's an old one — TV figured it out with the commercial break. [agris\_red files a daily field log](https://www.thedaringcreatives.com/creator-stories/agris-red-industrial-field-log/) from a numbered industrial wasteland using the same basic move, and one of the locations there is also called Sector 9\. Different artist, unrelated project, and a decent sign that the shift-report format is becoming its own genre in AI video. Gorgon Soup — SECTOR 9, "The Recalibration Centers," via YouTube ([@gorgon\_\_soup](https://www.youtube.com/@gorgon%5F%5Fsoup?ref=thedaringcreatives.com)) ## What Gorgon Soup hasn't said No process interview has surfaced. No breakdown video, no prompt dumps, no shot-by-shot. There's a stack list, a story bible, a weekly upload, and that's the public record. Which means anything about how the character consistency gets held together, or how much regeneration sits behind a single usable ten seconds, would be me guessing. I'd rather point at what's actually verifiable: the same faces keep coming back across months of uploads, the color grade never wanders, and the audio has been mixed by somebody with an opinion about low end. The account bio on [Instagram](https://www.instagram.com/gorgon%5Fsoup/?ref=thedaringcreatives.com) is four lines long and three of them are in-world. ## The novel, and the shareholders Two things are being built on top of the shorts. A full novel is in progress, and the video descriptions have been putting a date on it since at least early summer: the novel is coming, November 2026\. The site is slightly softer about it and says late 2026. The other thing is the [Patreon](https://www.patreon.com/gorgonsoup?ref=thedaringcreatives.com). Supporters get listed on the site under a heading that reads SECTOR 9 — EXTERNAL INVESTOR REGISTRY, each name stamped EXTERNAL INVESTOR — CLASS A, STATUS: ACTIVE. The call to action underneath is written in the company's voice, in all caps, the way a recruitment poster would be. Even the monetization stays inside the story. The corporate mantra printed on the site is the same one the miners live under: your labor serves a higher purpose. ![Morland Industries' Unified Consciousness Charter drawn as a glowing green pyramid, rising from The Worker through Output, Labor and Alignment to Unified Consciousness at the apex, over the line 'the universe will remember you'.](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/gorgon-soup-unified-consciousness-charter.jpg) Gorgon Soup — Morland Industries' Unified Consciousness Charter, the doctrine the miners work under. Via [gorgonsoup.com](https://gorgonsoup.com/?ref=thedaringcreatives.com) Next entry goes up this week. ### YACHT Fed Their Own Back Catalog to a Machine and Sang What Came Out URL: https://www.thedaringcreatives.com/creator-stories/yacht-chain-tripping-machine-learning-album/ Last updated: 2026-08-08T10:02:24.000Z The songs on *Chain Tripping* move like pop songs that learned the rules from a transcript. The hooks land, the basslines walk, and then a phrase runs four bars longer than it should and resolves somewhere you weren't expecting. The lyrics have the cadence of sense without quite arriving at it. That's the sound of a band handing its own catalog to a machine and then spending three years editing the results by hand. YACHT is Claire L. Evans, Jona Bechtolt, and Rob Kieswetter. For the 2019 record they took all 82 songs in their back catalog, converted them into MIDI data, and fed that data into machine learning models — mainly Google's MusicVAE. They ran the same process on songs by their peers and influences, and pushed their lyrics through a separate text model. Then came the hard part, which was all of it. YACHT — *Chain Tripping* (DFA Records), on Bandcamp ## The model gave them sheet music, not songs The thing that comes back from a MIDI model is not a track. It's notation, and somebody has to decide what it's for. "So it's just like getting sheet music," Bechtolt [told The Skinny in 2019](https://www.theskinny.co.uk/music/interviews/yacht-on-using-ai-on-their-new-record-chain-tripping?ref=thedaringcreatives.com). "We got all this sheet music back and then we had to decide what music went with which instrument, so if there was a bass line or a guitar line or a vocal melody." Evans has been blunt about how much human labor sits between the model and the record. "It's not something where you put information in and get information out, and then use it as is," she said in the same interview. "We're not at a point in the technology where that is feasible or aesthetically interesting at all; there really have to be the humans in the loop." The method they landed on was closer to panning for gold — stitching usable fragments together out of enormous fields of generated material until a song appeared. ## They expected the future and got a toy Part of what makes the story worth reading is how unimpressed they were at first. Google's NSynth, a neural synthesizer, was pitched to them as something formidable. "It was sold to us as this insanely complex process," Bechtolt said. "Under the hood it's really impressive, but — the output at first — we were like 'shouldn't this sound more futuristic if so much money and time is going into it?'" The disappointment turned into the aesthetic. "When we first started playing around with it, we thought it was kind of a joke," Evans said. "And then we kind of fell in love with it because we realised that it was this sort of high-tech, lo-fi object and that is exactly who we are, and it's exactly what we're doing." Her summary of where the technology actually sat is the most useful sentence in the whole interview: "We're at this point in machine learning where technology is really mind-blowingly sophisticated and requires a huge amount of computing power but, at the same time, you can't just press a button and make a song; it's not possible yet." YACHT explaining how and why they used machine learning to write the record — on YouTube ## The constraint was sounding like themselves The rule they set was strict, and it's the reason the album works as an album rather than a demo. "We wanted to make songs that were undeniably YACHT songs; that sounded like us, but maybe a little bit off or a little bit weird," Bechtolt said. Feeding a band its own catalog and asking a model to extend it is a strange kind of self-portrait. What came back broke habits they didn't know they had — by their account, the generative process pulled them out of tidy four-bar patterns and into longer, wandering riffs they wouldn't have written on their own. The band performed the record live afterward, which meant learning parts a machine had arranged. YACHT — Chain Tripping Tour footage, on YouTube *Chain Tripping* came out on [DFA Records](https://store.dfarecords.com/products/dfa2650?ref=thedaringcreatives.com) in 2019, three years after they started. For a comparison in the other direction, [imoliver's songwriting method](https://www.thedaringcreatives.com/creator-stories/imoliver-suno-songwriter/) keeps the words entirely human and generates the performance — YACHT did close to the inverse, generating the raw musical material and then performing and arranging it themselves. The band has kept the process documented rather than mystified, which is rarer than it should be. The sheet music came from a model. Everything after that was three people deciding what to keep. ### Jonas Peterson Directs the AI the Way a Director Talks to an Actor URL: https://www.thedaringcreatives.com/creator-stories/jonas-peterson-directs-ai-way/ Last updated: 2026-08-07T21:11:48.000Z A crowd walks up a beach in pale blue robes, and the robes keep going. They lift off the shoulders, gather, stack, and pile into a wave three stories high that curls over the rocks at the edge of the frame. Half of it reads as fabric. Half of it reads as water. Nobody in the picture is looking at it. They're just walking. That one is called *The Human Tide*, and it went up in [the Summer 2026 print release](https://jonaspetersonprintshop.com/collections/summer-2026?ref=thedaringcreatives.com) on Jonas Peterson's shop, alongside a cowboy, a cowgirl, a set of roller girls and a reef. Peterson made it with AI. He'll tell you that much, and then he'd rather talk about something else. ## The old people are the heroes The series that got him noticed is *Youth Is Wasted On The Young*: elderly people photographed like a fashion campaign. A woman with a white halo of hair stands against a cracked concrete wall in a mustard coat, a second coat over her shoulder covered in pom-poms, harlequin tights, one orange cowboy boot forward, amber glasses the size of saucers. Her hand is in her hair and her expression says she has done this before and is a little bored of it. The clothes don't exist. Neither does she. > "The idea behind 'Youth is wasted on the young' was to celebrate the so called old, a comment on ageism if you want. A positive quiet homage to people who've seen more than us, been there, done that and I wanted their confidence and pride to be seen. I used fashion to show off their personalities, their attitude and inner rebels shining through the facade of age." That's Peterson on [the process page of his print shop](https://jonaspetersonprintshop.com/pages/process?ref=thedaringcreatives.com), where he also puts it flatly: "these are not actual photos and the clothes are not real." ![An elderly woman in a mustard coat covered in pom-poms, harlequin tights and orange cowboy boots, posing against a concrete wall](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/emb1.jpg) Jonas Peterson — "Youth 018," from *Youth Is Wasted On The Young* (jonaspetersonprintshop.com) [His artist bio](https://jonaspetersonprintshop.com/pages/artist-bio?ref=thedaringcreatives.com) says the limited edition prints from that first series sold out in a few hours. The shop has kept going since: *This Desert Bloom*, *Varanasi*, *Aye, Aye, captain?*, *To Protect Me*, *Bon Voyage*, *Salt*, *22 Mermaids*, *Guardians*, *Cat Ladies*, *Havana Yogis*. Some of them run to forty prints. ## He gives it direction, and it comes back wrong Here is the whole method, in his words: > "I give specific direction using words only to a program, lenses, angles, camera choice, color theme, colors, styling, backgrounds, attitude and overall look and the artificial intelligence goes to work, it sends back suggestions and more often than not it's completely wrong, so I try other ways to describe what I'm after, change wording, move phrases around and try to get the AI to understand the mood." Then the part that most people skip when they quote him: > "It's frustrating mostly, the AI is still learning, but getting any collaborator to understand you can be difficult no matter if it's a human or a machine." He calls the next stage curation — picking the renders that belong together until a series exists. Then a pass through other software to finish them. "To me the process is similar to that of a film director's, I direct the AI the same way they would talk to an actor or set designer, it's a process, we try over and over again until we get it right." Asked whether he should get the credit, he answers his own question: "God, no, the AI creates with my help and direction, it's a collaboration between a real brain and an artificial one." ![An elderly couple in pink and grey standing forehead to forehead on a wooden platform over still water, framed by a pink archway](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/emb2.jpg) Jonas Peterson — "Varanasi 004," from *Varanasi* (jonaspetersonprintshop.com) ## He stopped answering the how question The tool never gets named — no model, no version, no list of the apps he finishes in. That's deliberate, and he's said why more than once. > "I've answered so many questions about this, but no matter how many times I said it was created using artificial intelligence, other people asked the exact same thing over and over again, so I've simply stopped. I'm not here to debate the process, I'm a professional photographer, writer and artist myself, I understand the implications, how this will affect many creative fields in the future. I'm simply using a tool available to me to tell stories, the same way I've always told stories — to move people. To me that is the point of this, not how I did it." The process page ends on one line by itself: "Dissecting something will almost always kill it." He gave [Dolce Magazine](https://dolcemag.com/beauty/jonas-peterson-art-reimagined-by-ai/46889?ref=thedaringcreatives.com) a warmer version of the same position in April 2023: "I combine everything I've learned and put it to use, but I'm not interested in lifting the veil and sharing exactly what it is I do." And then the line that explains the whole stance in one image: "I want people to enjoy what they're eating — sharing what pan I used to fry the fish isn't interesting to me." Plenty of AI artists publish their prompts. He's picked the opposite house rule and stuck to it for years, which at least makes him easy to read: the work is the argument, and there's no appendix. ## Twenty-five years of pointing a camera at real people Before any of this, Peterson was a photographer, and he still is. [His wedding portfolio](https://jonaspeterson.com/?ref=thedaringcreatives.com) is a destination photography site full of real couples in Big Sur and Sicily and the Maasai Mara, with a line on it that sounds like the same person who made the elders: "I believe in the healing power of having your story told." He's Swedish, and he lives in Austin, Texas. His bio counts twenty-five years across writing, filmmaking, creative direction and photography, and it shows up in how he talks about the AI work — in lenses, angles, camera choice, styling, attitude. That's a shot list. He's still calling the shots he was calling before, at people who happen not to exist. That background is why the pictures hold together as series instead of as a feed of one-offs. Which is a pattern worth watching across this whole scene: [what a photographer brings to AI art](https://www.thedaringcreatives.com/creator-stories/vagabond-diary-photographer-ai-art/) tends to be the part that prompts alone don't cover. ![A small blonde child in a white lace dress standing beside a very large black Great Dane against a cream backdrop](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/08/emb3.jpg) Jonas Peterson — "Guardians 014," from *Guardians* (jonaspetersonprintshop.com) *Guardians* is children and dogs, mostly enormous dogs, shot against studio backdrops in a soft cream light that makes them look like plates from a book nobody printed. His bio says the series has been viewed more than seven million times. *Bon Voyage* was shown to the public in Milan. The shop is still moving. Collections went up in November 2025, in the spring, and again this summer, and the archive behind them runs past a hundred and thirty prints. Next month there will probably be more cowboys. ### Delphi Motion Pictures Makes AI Films Where the Same Face Comes Back URL: https://www.thedaringcreatives.com/creator-stories/delphi-motion-pictures-character-consistency/ Last updated: 2026-08-06T21:00:00.000Z A woman in a black veil sits on a gold throne with a crown pinned over her covered face. She lifts one hand, palm out, like she's stopping whoever is walking toward her. The wall behind her is hammered metal, and the whole shot is graded like a print that's been sitting in a European vault since 1972. That's maybe six seconds of the teaser for CANTICLE OF THE HOLLOW, which is where I'd start with Delphi Motion Pictures. The rest of it: masked knights, candles floating on black water, a horse standing over a skull, a figure in gold robes climbing cathedral stairs. Two minutes, no dialogue, one line of narration at a time. All of it is generated. Delphi Motion Pictures is a studio created by Alexander D. Hagentorn, and the end cards on the films read DIRECTED BY ALEXANDER D. HAGENTORN over a small logo that says PASADENA, CA underneath. The [channel's own description](https://www.youtube.com/@delphimotionpictures?ref=thedaringcreatives.com) says each piece is "created, edited, and transformed with AI tools—blurring the line between cinema and code, myth and motion." On Threads the bio is shorter: "A studio dedicated to exploring the future of storytelling | © MMXXVI." Delphi Motion Pictures — "CANTICLE OF THE HOLLOW | OFFICIAL TEASER TRAILER," on YouTube ## The same face keeps coming back The clearest example is INDEX 8, a forty-six-second concept trailer for something dystopian and clinical. A bald man somewhere past sixty, deep brow lines, heavy-lidded eyes, stares straight into the lens under green fluorescents. A subtitle says: "Mr. Charles… Do you remember why you are here?" Then he's on a residential street at dusk with power lines behind him. Then in a white room full of identical white-robed figures. Then lying on a couch while someone in a lab coat leans over him. Then screaming into the camera, close enough that you can see his teeth. It reads as the same man every time. Same skull shape, same ears, same way the light falls into the sockets of his eyes. That's the part people who make this stuff will tell you is hard. A video model has no memory between generations, so unless you're forcing the issue with reference images or keyframes, every new shot is a fresh guess at who this person is. Holding a face across a dozen cuts in a dozen different lighting setups is work, and Delphi does it well enough that you stop noticing it, which is the whole point. Delphi Motion Pictures — "INDEX 8 | Official Concept Trailer Wide," on YouTube ## The worlds have factions, and the factions have names CANTICLE OF THE HOLLOW is the bigger project, and it's built in chapters. "The Osmogenesia" is a ninety-six-second piece narrated entirely in subtitles, and it turns out to be a mother talking about her dead son. "Oh, my fair Hyacinth," it opens. "The sweetest smell filled the room for ten days, a sign that life continued even within decay." Then the groups start arriving. The Order of the Quiet Dawn lays out flowers in his honour. The Templars of the Dark Feast "applied their science, trying to fix the moment in time and capture the scent in a bottle." The Monist Priests pray to their father. It closes with "gold haired Apollo was appeased," which puts the whole thing on top of the Hyacinthus myth without ever announcing that it's doing that. None of those factions get explained. They just have names and specific robes, and they show up doing specific things, and you're left to work out the theology yourself. Delphi Motion Pictures — "CANTICLE OF THE HOLLOW: The Osmogenesia," on YouTube Another chapter, "Agathor's Dream," runs on the same trick. Banners in a field, an armored figure slumped on a stone throne, a hand reaching through a curtain, knights in a courtyard at night with bats coming off a dead tree. The subtitles do the plot: "Before the Hollow learned to speak." "They borrow a face." "Not every sign is instruction." One of those lines is "Authority fractures when images replace judgement," which is a thing to put in a film you made out of generated images. The period look is doing a lot of the work too. Soft focus falloff, grain, that slightly green shadow you get off old stock. It's the same instinct behind [GEDDYRUXPIN's found-VHS short films](https://www.thedaringcreatives.com/creator-stories/geddyruxpin-ai-short-films/) — pick a decade the audience already trusts, and let the format sell the rest. ## What he hasn't shown There's no tools page. No breakdown video, no prompt dumps, no "how I made this" thread that I could find anywhere across the channel, Instagram, or Threads. The method is closed. What he does publish, on every film, is the same line at the bottom of the description: "DISCLAIMER: This video uses a variety of AI animation techniques. THIS IS NOT REALITY." So the label is loud and the recipe is quiet. For work this concerned with prophecy and false signs, that's a reasonable place to draw the line, and it also means the only thing you can judge is the footage. ## Where the rest of it lives The [YouTube channel](https://www.youtube.com/watch?v=5eju9Fw7UMY&ref=thedaringcreatives.com) holds six films right now, including a piece called "KNOW THYSELF, 2024" and a Canticle chapter called "Hymn to the Reindeer." Most of the recent output is on [Delphi's Instagram](https://www.instagram.com/delphimotionpictures/?ref=thedaringcreatives.com), where the story highlights are sorted into four worlds: CANTICLE, 3-ALPHA, INDEX 8, and PORTS. There's a Discord and an X account linked from the [Delphi link hub](https://link.me/delphimotionpictures?ref=thedaringcreatives.com). The newer Canticle chapters — "The Grove," "The Gate of Ivory," "l'Antifonia," "The Ninth Year" — are going up [on Threads](https://www.threads.com/@delphimotionpictures?ref=thedaringcreatives.com) and Instagram first, one at a time, with the same veils and the same gold. ### Dadabots Trained a Neural Net on Death Metal and Never Turned It Off URL: https://www.thedaringcreatives.com/creator-stories/dadabots-neural-network-death-metal/ Last updated: 2026-08-06T16:59:59.000Z The guitars are real guitars, sort of. The blast beats hold together for a bar and a half and then smear. A vocal that sounds like a throat arrives somewhere behind the mix, says nothing in particular, and dissolves back into the cymbals. It never stops, and it never repeats, because nobody wrote it down. That's Dadabots, and it has been playing more or less continuously since 2019. Dadabots is CJ Carr and Zack Zukowski, two musicians and programmers who met at Berklee. They describe themselves on [their own site](https://dadabots.com/?ref=thedaringcreatives.com) as "music hackers" working with "diy neural nets." What they built is a system that listens to a metal album until it can hallucinate more of it, then streams the hallucination live. The technical choice underneath it matters more than it sounds. They generate raw audio rather than notation. DADABOTS — *Coditany of Timeness*, generated from Krallice, on Bandcamp ## No MIDI, no tabs, just the waveform Most machine-generated music works with symbols — notes, chords, a grid. Dadabots skipped that layer and pointed the model at the audio file itself. Their 2018 paper, [*Generating Albums with SampleRNN to Imitate Metal, Rock, and Punk Bands*](https://arxiv.org/abs/1811.06633?ref=thedaringcreatives.com), states the method in one line: "Raw audio is generated autoregressively in the time-domain using an unconditional SampleRNN. We create six albums this way." Autoregressive in the time domain means the network predicts the next slice of waveform, then the next, then the next — sample by sample, with no concept of a note. Everything you hear is a byproduct of it guessing what comes next in the audio stream. The distortion, the cymbal wash, the room tone of the original recording all get modeled together, which is why the output has that specific quality of sounding like a bad bootleg of a band that doesn't exist. Training on a single album, over and over, is the whole method. *Coditany of Timeness* came from Krallice. *Calculating Calculating Infinity* came from Dillinger Escape Plan. *Inorganimate* came from Meshuggah. DADABOTS — *Calculating Calculating Infinity*, generated from Dillinger Escape Plan, on Bandcamp ## Most of it failed, and they said so The part of this story that separates it from a demo reel is how openly they've talked about the models that didn't work. "Most nets we trained made shitty music. Music soup," Carr [told VICE in 2019](https://www.vice.com/en/article/this-youtube-channel-streams-ai-generated-black-metal-247/?ref=thedaringcreatives.com). "The songs would destabilize and fall apart. This one was special though." The one that was special was trained on technical death metal band Archspire, and Carr's theory about why it held together is a genuinely useful piece of craft knowledge: the tempo is so fast and so relentless that it gives the network less room to drift. Their paper puts the same idea in gentler language. "While we set out to achieve a realistic recreation of the original data, we were delighted by the aesthetic merit of its imperfections." The imperfections are the record. A model that perfectly reproduced Archspire would be a copy of Archspire, and useless. DADABOTS — "Relentless Doppelganger," the 24/7 stream, on YouTube ## Nobody is curating the stream The livestream is unsupervised in the literal sense. There is no queue of approved takes. "It's autonomous, running on a linux server somewhere in South Carolina," Carr told VICE. "You're hearing everything it makes." Everything, including the parts that fall apart. That's a harder position to hold than it sounds — it means the bad output is part of the published work, permanently, with no edit pass between the model and the listener. They generated the album art and song titles with models too, trained on the original bands' back catalogs, and tested both fully-automated and human-curated versions of that process. DADABOTS — "PIZZAFIRE," their origin-story documentary, on YouTube ## They kept going The 2019 death metal stream is the thing people know, but the project didn't stop there. They put out a *WOW LOL EP* in 2024, described on their own site as kawaii deathcore drill and bass, and released the *PIZZAFIRE* documentary in 2023\. They perform live, using PyTorch, Ableton, and Hydra for visuals. If you want a neighbor in this territory, [the Frog Mage's original music](https://www.thedaringcreatives.com/creator-stories/frog-mage-dark-fantasy/) sits in a different genre entirely but shares the willingness to publish the weird result rather than sand it down. Carr and Zukowski have been running the same experiment for years now: pick a band, train on the raw waveform, publish what the network does with it. The server in South Carolina is still going. ### Surreailist Makes AI Films He Calls "Psychological Descents" URL: https://www.thedaringcreatives.com/creator-stories/surreailist-lukas-nowacki-psychological-descents/ Last updated: 2026-08-06T13:00:39.000Z A brick tower stands in a field of birch trees under a flat grey sky, and clinging to it are a dozen robed figures with the skulls of goats. Nothing moves except the fog. The color is wrong in the specific way that expired film stock goes wrong, greens gone sickly, blacks gone brown, everything one generation too many away from the negative. That's the opening of a piece called "Sirens," and it lasts about eighteen seconds. It was made by Lukas Nowacki, who posts as [surreailist on Instagram](https://www.instagram.com/surreailist/?ref=thedaringcreatives.com). His account is over two hundred of these things, each one a short vertical loop with a two-word title and no explanation attached. Bat Country. Fire Sermon. Khaos Ark. House Always Wins. The Raven of Odin. Moomintrolls. You scroll past a wall of them and it reads like the shot list for a film nobody finished. surreailist — "Sirens," on Instagram The Berlin Music Video Awards put him on their 2026 jury and described his work as breaking traditional narrative in favor of what he calls "psychological descents": short, hypnotic loops that feel like unsettling horror fairy tales. Their [2026 jury announcement](https://www.berlinmva.com/event/meet-the-new-faces-of-our-2026-jury/?ref=thedaringcreatives.com) adds that he draws on surrealism and transgressive cinema to build worlds where care morphs into a threat and beauty becomes overwhelming. That last part is the thing you notice once you've watched a few. The threat is usually wearing something soft. ## The loops are the trailer, not the film Nowacki has been fairly direct about how he wants the reels understood. On his [free Patreon page](https://www.patreon.com/cw/surreailist?ref=thedaringcreatives.com) he writes that "the brief visual sequences you see on my instagram are just the tip of the iceberg. They are fleeting projections onto a wall, glimpses through a keyhole of a much larger, often darker cinematic universe." He set the Patreon up as a place to explain the what, the why and the how, and he calls it "an invitation to step inside my subconscious and dissect how a lifetime of obscure influences is formalized into polished visual art." The membership is free. There's a $5 tier on top of it, but the door is open without paying. So the eighteen-second horror clip is a keyhole. The room behind it is where he actually lives. surreailist — "Khaos Ark," on Instagram "Khaos Ark" is a good example of the lifetime-of-obscure-influences claim doing real work. A red ship rides a sea made of human hands. There's a woman with a clock built into her headdress. There are pigs in gilded cages and a chandelier the size of a cathedral. If you've spent any time with Bosch, or with Jan Švankmajer, or with the Quay Brothers, the vocabulary is familiar even though the images are new. ## What he actually names The tool he credits by name is [the Kinovi generation platform](https://kinovi.ai/?ref=thedaringcreatives.com). He lists it in his Instagram bio, and a piece he posted this week carries the caption "Created with @kinovi.ai." Worth knowing what that credit actually points at, because Kinovi doesn't build models. It's a studio and a REST API sitting on top of other companies' models, with one credit balance covering both. [Its published model catalog](https://kinovi.ai/models?ref=thedaringcreatives.com) lists ByteDance's Seedance 2.0, Seedance 2.0 Fast, Seedance 2.0 Mini, and HappyHorse; Kuaishou's Kling 3.0; ByteDance's Seedream 5.0 Pro and OpenAI's GPT Image 2 for stills; Midjourney V8 and Niji V7; Google's Nano Banana Pro; and four Suno endpoints for audio. Pricing is per second of footage rather than per clip. Seedance 2.0 runs $0.0707 a second at 480p and $0.4239 a second at 1080p, which puts an eighteen-second piece like "Sirens" somewhere between a dollar and eight dollars of generation depending on the tier — before counting the takes that didn't make it. So a "Created with @kinovi.ai" caption most likely means Seedance underneath, which is the same ByteDance model [four other creators we've profiled are running through four different apps](https://www.thedaringcreatives.com/creator-stories/four-creators-seedance-four-apps/). The interesting part is that the same model produces wildly different work depending on who's driving it — none of those four look anything like a Polish folk-horror fever dream. The platform's pitch is reference-driven rather than prompt-driven: you feed it images, clips, and audio to steer a shot instead of describing what you want and hoping. Video models expose a duration in seconds, a canvas resolution, and reference media as URLs. That's a plausible fit for how his pieces hold together. Each film keeps one palette and one world across a dozen cuts — "Sirens" stays in the same grey Polish village from the tower to the goats to the girls in white — while the next piece jumps somewhere else entirely. Holding a look that tightly inside a single film, then dropping it completely for the next one, is the shape you'd expect from reference frames rather than a text prompt repeated. Beyond that, he doesn't publish his stack in the feed. The captions are almost always just the title. One recent post is captioned "Jehovah is strength. Lucifer is light. Satan is separation. Christ is unification," and another is a line of alchemical text about a green and golden lion in whom the secrets of the philosophers are hidden. Neither of those tells you what model he ran. The breakdowns go on Patreon instead, which is a deliberate split. The feed is the film, the Patreon is the commentary track, and his most recent post there is titled "Viral Transmutation: The Alchemy Behind the Reel." surreailist — "Frequency Vortex," on Instagram "Frequency Vortex" is the one I'd point at if somebody asked what he does. A small child kneels on a wet concrete floor in a peeling blue room, facing an old CRT television. A doorway behind them glows pink. A figure in a long coat with a gramophone horn where its head should be walks into that doorway and stops. Later there's a creature that's mostly a human ear, playing a trumpet against a flat teal void. Nobody explains any of it. That's the register. ## The commercial side is a separate door His site at [the surreailist.art contact page](http://surreailist.art/?ref=thedaringcreatives.com) runs about four lines long. It says he's "crafting surreal music videos, bespoke digital art, and immersive visual campaigns and storytelling," and describes the work as "bridging the gap between the organic and the artificial." There's an email address on it and not much else. That squares with the jury seat. The Berlin Music Video Awards brought him in specifically to help judge how generative tools are showing up in music videos, which is a working-director job rather than a poster-artist one. surreailist — "Moomintrolls," on Instagram If this territory interests you, we've covered neighbors. [Gloomstomper's dark fantasy work](https://www.thedaringcreatives.com/creator-stories/gloomstomper-voidstomper-dark-fantasy/) sits in a similar register with a different palette, and [GEDDYRUXPIN's AI short films](https://www.thedaringcreatives.com/creator-stories/geddyruxpin-ai-short-films/) run the same one-artist-one-feed model at a longer length. Nowacki describes his own account as a "subversive AI kamp" and says he's deconstructing the artificial mind. He's been shipping a new descent every few days. ### Holly Herndon Trained an AI on Her Own Voice, Then Gave It Away URL: https://www.thedaringcreatives.com/creator-stories/holly-herndon-voice-model-holly-plus/ Last updated: 2026-08-06T03:01:09.000Z The voice comes in slightly wrong. It has the shape of a human singing — vibrato, breath, the small catch at the top of a phrase — but the edges are soft in a way no throat produces. Stack four of them and you get a choir that never stood in a room together. That's Holly+, and the voice belongs to Holly Herndon, except when it doesn't. Herndon has been building machine-learning instruments and singing with them since well before the current wave. She is a composer with a doctorate from Stanford's computer music program, and her work keeps circling one question: what happens to a voice when it can be copied, and who should own the copy. Her answer has been to build the copy herself, and then hand out the keys. Holly Herndon — "Jolene (feat. Holly+)," on YouTube That's her 2022 cover of Dolly Parton's "Jolene," sung by her own digital twin. The instrumentation is by Ryan Norris and the video is by Sam Rolfes, who motion-captured a 3D model of Herndon to make the thing on screen move. The lead vocal was generated by feeding a modified score into Holly+ and letting the model sing it in her voice. ## Spawn took six months to stop being boring Before Holly+ there was Spawn, an AI she and Mat Dryhurst built for the 2019 album *PROTO*. Spawn was not an API call. It was hardware. "We bought Spawn's parts and built her in our studio," Herndon [told The FADER in 2019](https://www.thefader.com/2019/05/21/holly-herndon-proto-ai-spawn-interview?ref=thedaringcreatives.com). "Jules installed an operating system and some software, we created our own training sets, and we started listening to the outcome." Jules is Jules LaPlace, the developer who worked on the ensemble alongside them. And the outcome, for a long stretch, was nothing much. "We had about six months of boring results before we started to get interesting results," she said. The turn came on a specific piece of audio. "The spoken part of 'Birth,' which is trained on my voice, was the first time we were like, 'You can hear the logic of the neural network at work,'" Herndon told the same interview. Holly Herndon — "Eternal," official video, on YouTube The part that gets lost when *PROTO* is described as an AI album is how much of it is people. Herndon assembled a vocal ensemble in Berlin and ran live training sessions, where singers performed and Spawn listened. "After touring *Platform* for years, we were really missing communal music-making," she said. "We put together this motley crew of individuals in Berlin and started experimenting." She has put a number on the machine's share of the record. "It really only makes up 20% of the audio." ## Training on herself was the ethical shortcut The path from Spawn to Holly+ came out of a decision about training data, and she has been direct about why. "We realized we could create a naturalistic likeness and the only approach that we felt comfortable with, was training on ourselves directly," she [told Ars Electronica in 2022](https://ars.electronica.art/aeblog/en/2022/06/15/hollyplus/?ref=thedaringcreatives.com). "That's when I started just using my own training data and Holly+ was born." The instruments were built with Herndon Dryhurst Studio, Never Before Heard Sounds, and Voctro Labs. The result is a model anyone can sing through, hosted at [the Holly+ project site](https://holly.plus/?ref=thedaringcreatives.com). Giving it away was the point, and she said so when she announced it. "I am releasing Holly+ in collaboration with Never Before Heard Sounds, the first tool of many to allow for others to make artwork with my voice," she wrote, in [remarks quoted by MusicTech](https://musictech.com/news/music/holly-herndon-ai-powered-cover-dolly-partons-jolene-holly-plus/?ref=thedaringcreatives.com). "My voice is precious to me! It is 1 of 1." Both things at once. Precious, and handed out. Dryhurst described the mechanism plainly: "The novel idea was, what if we gave that model to everybody to be able to use and wrapped it in a protocol that would share profits from any media created with her voice 50-50 back to Holly?" ## She calls the model the artwork The framing Herndon uses for all of this puts the weight on the training set rather than the output. "We focus so much on the models and their outputs, but we often forget to talk about all the training data that goes into the models," she [told Art Basel in October 2024](https://www.artbasel.com/stories/ai-holly-herndon-mat-dryhurst-data-training-art-making?ref=thedaringcreatives.com). In the same conversation she said something that reframes what she thinks she's making: "The model is the artwork … It's the model that can generate infinite artworks, in any kind of medium." And on why ownership gets complicated: "AI models require large amounts of data to work well. They are collective accomplishments that require experiments in collective ownership and compensation." She has also described the training data itself in generational terms — "we like to think about the training data as children that we're sending into the future because it will be training models for decades and decades to come." Holly Herndon's TED talk on singing in someone else's voice — on YouTube If you want the adjacent territory, [imoliver's songwriting process](https://www.thedaringcreatives.com/creator-stories/imoliver-suno-songwriter/) sits at the opposite end of the same problem — he writes every word himself and generates the performance, where Herndon built the performer and let other people write. Herndon and Dryhurst are still working the data question rather than the output question. The voice is out there, the protocol splits the money, and the model keeps being the thing she points at when someone asks what she made. ### Grace Green Puts the Same Girl in a New Impossible Situation Every Week URL: https://www.thedaringcreatives.com/creator-stories/grace-green-space-puts-same/ Last updated: 2026-08-05T00:08:43.000Z A girl in a dark red dress walks across an empty field, holding a leash. At the end of the leash is her own shadow, gone four-legged, hunched, trotting along behind her like something that has agreed to the arrangement for now. The sky is huge and pale and completely uninterested. Her face gives away nothing at all. The caption underneath reads: *"I no longer run from what I am, I keep it under control."* That's a [Grace Green space](https://www.instagram.com/p/DZDWR2JsTe3/?ref=thedaringcreatives.com), and once you've seen a few, you can spot one across a room. Same girl every time — black bob, blunt bangs, blue eyes, freckles across the nose. Same painterly surface, thick and slightly waxy, the way oil looks when it hasn't fully dried. Same enormous skies full of pastel clouds doing most of the emotional work in the frame. What changes is the situation she's been dropped into. ## The Same Girl, a New Predicament Each Time In one, she's crossing a tightrope in a pink party dress, carrying a battered leather suitcase, doves scattering around her, nothing under the rope but weather. In another, a slot machine has replaced her eyes and the reels have landed on a word you can guess. In another, there's a small white door cut into her t-shirt, hanging open, and behind it a human heart is bleeding down the front of her skirt. None of these are subtle, and none of them are trying to be. The pieces work the way a good children's book illustration works, which is to say they hand you one image that contains the whole feeling, and they don't explain it afterward. The tightrope one is titled *Learning to Balance / Imparare l'equilibrio*. That's it. That's the note. grace\_green\_space — "Learning to Balance / Imparare l'equilibrio," via Instagram ([@grace\_green\_space](https://www.instagram.com/grace%5Fgreen%5Fspace/?ref=thedaringcreatives.com)) ## She Writes Every Caption Twice English first, then Italian. Sometimes a single line, sometimes four or five paragraphs of it. She posts from Lecce, down in the heel of Italy, and her [Threads bio](https://www.threads.com/@grace%5Fgreen%5Fspace?ref=thedaringcreatives.com) says *"Delle mie fragilità ne faccio bellezza"* — out of my fragilities I make beauty. The longer captions read like diary entries she decided to publish. Under a piece called *Goodbye, Old Me / Addio, vecchia me*, she wrote: *"Some versions of ourselves are not meant to stay forever. They are only meant to carry us until we become someone they could never imagine."* Then the whole thing again in Italian, for the people who'd rather have it that way. grace\_green\_space — "Goodbye, Old Me / Addio, vecchia me," via Instagram ([@grace\_green\_space](https://www.instagram.com/grace%5Fgreen%5Fspace/?ref=thedaringcreatives.com)) A recent one goes harder. A vending machine, the kind that would sell you a bag of crisps, except every slot holds a person — a face, a collar, a set of pearls — and every slot has a price tag in euros. €87\. €122\. €99\. The caption, [titled *PRICE OF A SOUL*](https://www.instagram.com/p/DbJBQD9MlRH/?ref=thedaringcreatives.com), runs long: > *"We live in a world where people are no longer simply seen — they are evaluated. We measure beauty, status, attention and success as if human beings were products placed on a shelf, waiting for someone to choose them. We ask 'What do you have to offer?' before asking 'Who are you?'"* grace\_green\_space — "PRICE OF A SOUL / Il prezzo di un'anima," via Instagram ([@grace\_green\_space](https://www.instagram.com/grace%5Fgreen%5Fspace/?ref=thedaringcreatives.com)) ## What She's Said About the AI Her [Instagram bio](https://www.instagram.com/grace%5Fgreen%5Fspace/?ref=thedaringcreatives.com) is two lines, and they carry the entire public account of her method: > *"Collage • Photomanipulation • Digital Painting since 2016* *AI integrated into my creative workflow since 2025"* No tools named, no prompts posted, no process reel, no interview I could find anywhere. She tags the work `#surrealismo`, `#surreal`, `#conceptartwork`, answers commission DMs, and otherwise lets the pictures go out on their own. I want to be precise about what she actually claims, because it's easy to flatten. She says AI is *integrated into* a workflow that already existed for nine years. Not that the workflow is now AI. Nine years of collage, photomanipulation and digital painting came first, and something from 2025 got folded into the middle of it. ## The Same Face Comes Back Every Time Since she hasn't explained the method, the pictures have to answer for it, and they do say a few things. The girl holds. Across piece after piece the same face returns at the same angles, with the same freckle pattern and the same specific blue in the eyes. Anyone who has spent an afternoon trying to get a generative model to produce one consistent character twice in a row knows what it costs to hold a face steady that long. It's a house style enforced hard enough that a stranger can identify an unlabeled image. The compositions hold too. A formal habit runs underneath all of them — figure dead center, low horizon, big sky, one object carrying the whole metaphor. Suitcase, leash, barcode, door. It's the discipline of somebody who spent years cutting things out and placing them, and it survived whatever got added to the process in 2025. ## Where to Find Her She's posting a couple of times a week, mostly on [her Instagram feed](https://www.instagram.com/grace%5Fgreen%5Fspace/?ref=thedaringcreatives.com), with the same pieces going up on Threads. Commissions go through her DMs. The bio has said the same thing about AI since she added it, and she hasn't walked it back or elaborated on it. The most recent one I saw was called *YOU CAN'T DROWN THIS.* Italian underneath: *Questo non puoi affogarlo.* ### Agris Red Files a Daily Field Log From a World That Doesn't Exist URL: https://www.thedaringcreatives.com/creator-stories/agris-red-industrial-field-log/ Last updated: 2026-08-04T13:14:54.000Z A woman in a yellow skirt stands on a broken platform, looking down into a valley made entirely of scrap. A furnace the size of an office block burns orange through the haze on her left. Below her, cranes and catwalks and rusted spires stack up on each other until the whole thing dissolves into smog, and every light in the frame is either fire or a safety beacon. It's a fifteen-second Instagram reel. The caption talks about gloves and filters. That's the register the whole account runs in. [Agris Red](https://www.instagram.com/agris%5Fred/?ref=thedaringcreatives.com) writes from inside the place, every day, in the voice of somebody who clocked in there this morning. The bio says "AI Visual Artist. Cinematic Industrial Worldbuilding." Under that, three words that do a lot of work: **Strictly AI.** ## Every post is a shift report The format never breaks. Each caption opens with "Field Log:" and a location — Entering Sector 9, The Deep-Sector Canyons, The Endless Scrap Ocean, Shift Cycle 04 — and then reports conditions like you're crew. > "Mornings start with draining toxic condensation from your intake valves before stepping out onto the oxidizing catwalks. By midday, the heavy steam vents clear just enough to reveal the true scale of the corroded spires above." Gloves on and filters tight. That line, or some version of it, closes a lot of them. agris\_red — "Field Log: Entering Sector 9," on Instagram The second-person address is the whole trick. You get briefed before you go out in it, and a scroll quietly turns into a job. ## The world has a map, and it's getting filled in The sectors are numbered, and the numbers hold. Sector 4 is the canyon floor of a mega-city where the sun never reaches the lower streets and everything lives under amber beacon light. Sector 7 is where the automated war units patrol. Sector 9 is the rust — oxidized iron, high-pressure steam, catwalks. Sector 10 is bright dust flats. Sector 12 is a horizon of dead excavators being swallowed by slag. Then there's a burn basin off the grid entirely, where the ground is soft grey powder that looks like snow and doesn't melt. The design rule got written out loud in one caption: *"Dystopia is defined by hard borders and sharp contrasts."* agris\_red — "Field Log: The White Silence," on Instagram That's why the ash basin sits comfortably next to the rust sector next to the corporate spires. Each one has its own weather, its own palette, and its own reason you'd be standing in it, and the feed moves between them like a route. ## Nobody's been told how it's made There's no process breakdown on the account, no named model, no tools page, no interview I could find. Just "Strictly AI" and 237 posts. So the work has to say it. And what the work keeps saying is photography. The character frames sit at portrait focal lengths with real background fall-off — a face in a dust-caked headwrap, eyes sharp, the ridge behind her gone to mush. The lighting is almost always available light doing something specific: a furnace working as a practical, or a sun so high and clean it flattens white powder into pure contrast against black concrete. There's no neon anywhere. A cyberpunk feed gets lit in magenta and cyan; this one is lit in rust, bone, slate, and amber, which is a decision somebody made and then kept making 237 times. agris\_red — "Field Log: The Endless Scrap Ocean," on Instagram The consistency is the hard part. Anyone can generate one gorgeous rusted spire. Holding the same grade, the same grain, the same lens feel and the same sky across a run of daily posts is a continuity problem, and it's the same problem a DP solves on a shoot. ## There's a camera in this somewhere Which stops being a guess when you follow the link off the account. [The agrisred.com photography portfolio](https://www.agrisred.com/?ref=thedaringcreatives.com) lists this same Instagram as its social. It's a working photographer's site — Northamptonshire, weddings, street photography — under the same name, with no AI anywhere on it. Somebody was framing people in available light before any of this started. I'd steelman the skeptic here, because the objection is real: a prompt is not a camera, and nobody stood in Sector 9\. Fair enough. But the eye that decides the furnace goes camera-left, that the subject faces away, that you're looking at her back instead of her face — that eye got trained on wedding receptions and street corners, and it's doing the same job now. Same taste, different shutter. If you liked what [GLOOMSTOMPER did by turning a glitch into a whole territory](https://www.thedaringcreatives.com/creator-stories/gloomstomper-voidstomper-dark-fantasy/), this is the industrial-realism version of that instinct. ## The score is in-house too The music comes from the same place. There's an [Agris Red artist page on Spotify](https://open.spotify.com/artist/3o3KMLCXtiBKO8vnLhjM5S?ref=thedaringcreatives.com) carrying a run of 2026 singles, and when "Most Wanted" dropped it got announced on the same feed, in the same voice, as *Field Log: Audio Grid Locked* — heavy basslines, gritty synth loops, distortion "designed for the deepest industrial sectors." Visuals, lore, and score all coming out of one person explains why the account feels sealed. Nothing in it was borrowed. The 100,000-follower mark landed on July 31, 2026, and got posted the way everything else does — as a field log, thanking the crew, noting that the operation keeps moving. Subscribers get a long-form cut every week, 3 minutes and up. The daily dispatches keep coming from whichever sector comes next. ### Ozavry Has Posted Ninety-Two Chapters of One World, All in the Same Two Colors URL: https://www.thedaringcreatives.com/creator-stories/ozavry-dark-fantasy/ Last updated: 2026-08-03T15:34:37.000Z A robed figure stands at the foot of a tree the size of a cathedral. The canopy above him isn't leaves — it's a hot magenta nebula, lit from inside, stars burning through the branches. The ground he's standing on glows the same pink. Everything else in the frame is a deep, cold violet-blue. He is very small and he is not moving. That's the whole shot. That's the first entry in the World of Ozavry, and about ninety chapters later the palette hasn't moved an inch. Bruised magenta against blue-black, every time, in a series that has now passed **Pt. 92** — "Tavern Tales of the Night." It runs on [TikTok as @ozavry](https://www.tiktok.com/@ozavry?ref=thedaringcreatives.com), tagged the same way every post: `#darkfantasy #aivisuals #fantasyworld #worldbuilding #fantasyart`. Ozavry — "Welcome to the world of Ozavry," via TikTok ([@ozavry](https://www.tiktok.com/@ozavry?ref=thedaringcreatives.com)) ## The Colors Are the Whole Signature Most people working in AI fantasy art let the palette wander. A different prompt gets a different look, and a feed ends up as a pile of nice individual images that don't belong to each other. Ozavry doesn't do that. The same two-color system carries every chapter: a saturated magenta doing all the emitting — canopies, ground fog, embers, the glow under a doorway — sitting inside a violet-blue that swallows the rest of the frame. Nothing is neutral. There are no daylight shots, no greens, no browns. It's a bold constraint, because two-color night scenes are exactly where AI image tools go muddy. Push saturation that hard and the shadows usually collapse into a purple smear. His don't. The dark parts stay readable — you can still see bark texture on a trunk that's rendered almost entirely in silhouette, and the ground holds detail three shades down from the brightest pink. Whatever's happening in the grade, the separation between the glow and the dark is being managed deliberately, not accepted as whatever the model returned. ## Scale, and One Small Person The other constant is a compositional habit. Almost every frame has something enormous — a tree, an arch, a moon, a hall — and one human figure placed near the bottom, usually with their back to us. That's an old fantasy-illustration move and it does two jobs at once. It gives the eye a scale reference, so the tree reads as *cathedral-sized* rather than just *a tree*. And it hands you a stand-in: you're behind that figure looking up at the same thing. Ozavry — "World of Ozavry Pt. 92: Tavern Tales of the Night," via TikTok ([@ozavry](https://www.tiktok.com/@ozavry?ref=thedaringcreatives.com)) By Pt. 92 the entries have picked up subtitles — "Tavern Tales of the Night" is a place, not just a picture. The numbering is doing real work there. A single striking image scrolls past and is gone; ninety-two of them, numbered, in one palette, with recurring locations, reads as somewhere that exists and is being surveyed a chapter at a time. ## What Isn't Known Here's the honest part: **no process account exists.** No interview, no breakdown video, no tools page, no captions naming a model or a workflow. The only technical claim anywhere on the work is the hashtag `#aivisuals`, which tells you it's AI and nothing else. So I can't tell you which generator makes those trees, whether the color is prompted or graded afterward, or how the motion is produced. Anyone who tells you otherwise about this account is guessing. What the work itself says is narrower but real. The palette discipline across ninety-plus posts is not something you get by accident from a text prompt — that's either a locked reference workflow, a consistent grade applied after generation, or both. The compositional repetition points the same way: figure low, subject vast, camera looking slightly up. Somebody made those calls once and then kept them. Ozavry — "World of Ozavry Pt. 20," via TikTok ([@ozavry](https://www.tiktok.com/@ozavry?ref=thedaringcreatives.com)) ## Where Else He Posts TikTok is the main channel by a distance. There's a [YouTube channel under the name Ozavry](https://www.youtube.com/@Ozavry-f3i?ref=thedaringcreatives.com) carrying four vertical dark-fantasy shorts, the most recent from May 2026, and an Instagram account at [@ozavry\_](https://www.instagram.com/ozavry%5F?ref=thedaringcreatives.com). The numbered series lives on TikTok and the rest reads as spillover. That's a reasonable way to run it. The chapter format suits a feed you scroll, and a numbered series gives a returning viewer somewhere to pick up. For a comparison in the same territory, [The Frog Mage works the dark-fantasy register with a similar silence about method](https://www.thedaringcreatives.com/creator-stories/the%5Ffrog%5Fmage-makes-dark-fantasy-memes-original-music-and-very-little-explanation-of-how/) — memes and original music instead of worldbuilding, and equally little explanation of how. [GLOOMSTOMPER's world](https://www.thedaringcreatives.com/creator-stories/gloomstomper-voidstomper-dark-fantasy/) is the other nearby one, built out of glitch rather than glow. ### Four Creators We've Profiled Are All Using Seedance — Through Four Different Apps URL: https://www.thedaringcreatives.com/creator-stories/four-creators-seedance-four-apps/ Last updated: 2026-08-03T12:59:59.000Z PJ Ace posted a feature film teaser today. Kelly Boesch posted two test videos last weekend. Neural Viz listed his toolchain in a description back in May. Mr Relative put out a short action movie in February with the model's name in the title. None of them mention each other, but all four are using Seedance. I noticed because I built something this week that watches the YouTube feeds of every creator we've published a profile on, and keeps track of any new work. It surfaced thirteen uploads in one morning. Four of the names attached to them kept saying the same word. ## What each of them actually did [PJ Ace, who made an NBA Finals ad for $2,000](https://www.thedaringcreatives.com/creator-stories/pj-ace-made-an-nba-finals-ad-for-2-000-and-published-the-prompts/), has been on a run. In June he put out a five-minute teaser for *Nexus*, his hybrid feature, and wrote that it was "made by 3 people in 2 weeks" using Dreamina and Seedance 2.0\. On July 1st, episode two — "made this with a small team in 6 days," this time crediting "Seedance 2.0 4K in CapCut Video Studio." This week, a third teaser, made with Seedance 2.5. Three films in eight weeks, which is pretty insane. PJ Ace — the newest “Nexus” teaser, made with Seedance 2.5\. [Watch it on YouTube](https://www.youtube.com/watch?v=F7LLRFMBuPM&ref=thedaringcreatives.com). [Kelly Boesch, whose whole studio is one person](https://www.thedaringcreatives.com/creator-stories/how-kelly-boesch-built-a-studio-of-one-with-ai/), was doing something smaller and more interesting. She watched the trailer for *The Odyssey*, wanted to know whether a model could reproduce one shot from it — the sea with the massive whirlpool — and made a whole trailer to find out. Her words on the result: "It came out insane." The same weekend she ran a Blade Runner-style image-to-video test, and described that one as "using #Seedance 2.0 in #RunwayML." Kelly Boesch — the trailer she made to test one shot from “The Odyssey.” [Watch it on YouTube](https://www.youtube.com/watch?v=rtRIgiHrMY4&ref=thedaringcreatives.com). [Neural Viz, who runs an entire TV universe](https://www.thedaringcreatives.com/creator-stories/the-showrunner-how-neural-viz-makes-an-entire-tv-universe-with-ai/), is the one who tips his hand least. On "Breaking Into Black Holes" in May, the description is a list with no punctuation: *Runway Seedance Nano Banana Eleven Labs Suno*. Five tools, one film, no explanation. And [Mr Relative, who put his AI work in a physical room this summer](https://www.thedaringcreatives.com/creator-stories/mr-relative-ai-this-is-humanity/), got there first, back in February, with a short film that says "made with Seedance 2.0" right in the title. Neural Viz — “Breaking Into Black Holes.” The description is a five-word tool list. [Watch it on YouTube](https://www.youtube.com/watch?v=7tfcGFt6m%5FQ&ref=thedaringcreatives.com). Mr. Relative — “RECLAMATION,” February 2026\. [Watch it on YouTube](https://www.youtube.com/watch?v=C4H0mPeI6fE&ref=thedaringcreatives.com). ## Nobody went looking for it Not one of these people went to a website called Seedance and signed up. PJ Ace found it inside CapCut and inside Dreamina. Kelly found it inside Runway. Neural Viz has it sitting in a stack next to Suno and ElevenLabs. Seedance is ByteDance's video model, and Dreamina and CapCut are both ByteDance products — [TechCrunch reported in March](https://techcrunch.com/2026/03/26/bytedances-new-ai-video-generation-model-dreamina-seedance-2-0-comes-to-capcut/?ref=thedaringcreatives.com) that Dreamina Seedance 2.0 was rolling into CapCut, starting with users in Brazil, Indonesia, Malaysia, Mexico, the Philippines, Thailand, and Vietnam. So four artists, working separately, on different continents' worth of tooling, all ended up pointed at the same model. Three of them got there through an app they already had open. Now, you could argue this just means ByteDance has excellent distribution, and honestly — yes. That's what happened. I think it's the most useful thing here for anyone making work of their own. In most of these cases nobody ran a comparison at all. It was sitting in the editor they already had open, on the day they had an idea. I don't think that's a small thing. I've watched a lot of people pick tools, myself included, and "it was already in the app" beats "it scored higher" more often than any of us like to admit. ## You may already have it If you edit in CapCut, or you've been paying for Runway, there's a decent chance you already have access to the thing four working artists have been shipping films with. Worth ten minutes finding out before you buy another subscription. The version numbers are a mess, though, and I'd rather say so than pretend otherwise. In the space of five months these four have named Seedance 2.0, Seedance 2.0 4K, and Seedance 2.5, and there's a Seedance 2.0 Omni floating around in the tutorial world. Whatever's inside your app may not be what PJ Ace was using this week. Check before you assume the result you saw is the result you'll get. Two more caveats, because they matter. PJ Ace said Dreamina gave him access — "@Dreaminaofficial gave us access to Dreamina Seedance 2.5." That's an early-access relationship, and it belongs in the frame when you're reading his enthusiasm. The films are real either way. But he started from a place a normal account doesn't, and you should weigh his results against that. And four is four. We've profiled a dozen creators with channels, and eight of them aren't mentioned in this piece at all. I noticed a pattern. Somebody with a bigger sample might find it doesn't hold. ## I can't tell whether any of them chose it What I can't tell from a YouTube description is whether any of them *chose* it. Kelly's posts read like genuine curiosity — she saw a shot in a trailer, wondered if she could get it, and posted the attempt. That's a person testing a tool. PJ Ace's read like a production schedule. Neural Viz's five-word list reads like a man who has stopped caring which logo is on the thing and simply grabs whichever one makes the shot. That last one might be where this ends up for most people. A shelf of models, and enough taste to know which one to reach for. I'd love to hear from any of them on that, honestly. If you're reading this and you're one of the four — did you pick it, or did it just turn up? ### Kavan the Kid Builds the Masks by Hand Before the AI Ever Sees Them URL: https://www.thedaringcreatives.com/creator-stories/kavan-the-kid-ai-films/ Last updated: 2026-08-16T10:25:01.000Z A knight stands on a ridge in bad weather, dirt streaked down one side of his face, holding a woman's cheek in an armored glove. The sky behind them is doing that heavy pre-storm thing. It plays like a scene from a mid-budget fantasy film — two people, a held beat, a camera that knows where to sit. Nobody stood on that ridge. There is no ridge. That shot is from Chapter Two of *The Chronicles of Bone*, which Kavan the Kid has been putting out on YouTube at roughly one episode a month since late 2025\. Episodes run ten to fifteen minutes. The series pulls Robin Hood, King Arthur, Captain Hook, Captain Nemo and the Lost Boys into one collapsed world run by vampires — and his vampires don't want blood, they want control. A bite makes you theirs permanently. He's written five seasons of it. Every major beat, start to finish, before the first episode shipped. Kavan the Kid — "The Chronicles of Bone," Chapter One: A Vengeful Fairy, via YouTube (@kavanthekid) ## The Masks Are Real Here's the part I hadn't seen anyone else do. Before a frame gets generated, Kavan puts on a costume he actually owns, photographs himself in it, and feeds that photo in as the starting point. The masks his characters wear exist. He built or bought them, he wore them, and the AI works from a real object under real light rather than from a description of one. From there he tags the details through Freepik's NanoBanana and iterates until the character locks. Then that character gets a visual reference sheet, which is what keeps a face consistent across a fifteen-minute episode instead of drifting into somebody else by the third act. It's a strange inversion. The tool most people reach for to skip the physical part of production, and he's smuggling the physical part back in through the front door. ## Scripts First, Generation After The order of operations is old-fashioned on purpose. Script, then storyboards, then blocking, then generation, then a normal post workflow — Premiere Pro to cut, DaVinci Resolve to grade, After Effects and Blender for effects. His way of putting it, [talking to Creative Bloq about the rules of cinema](https://www.creativebloq.com/ai/ai-filmmaking-is-a-gimmick-if-you-dont-know-the-rules-of-cinema?ref=thedaringcreatives.com): *"AI is basically the set. The pre- and post-production still follow the same rules. You still need storyboards, blocking, continuity, editing rhythm."* He goes further than that when pushed on what the tools can't do. *"AI doesn't replace filmmaking. It replaces the physical shoot. Everything else — writing, editing, story, performance — that's still human-led."* On Freepik specifically: *"It's a creative toolkit, not a writer or director. The story, the shots, the emotional beats, that's all us."* And the line that explains why so much of this stuff looks the way it looks: *"If you don't understand the basics, AI visuals look like student films."* He is, by the way, doing all of it himself. Writing, directing, animation, sound design, music. One person, monthly, at episode length. ## Ten Years of Making $20,000 Look Like $80,000 Kavan Cardoza went to film school in Florida and then spent years in Los Angeles shooting music videos for indie and hip-hop artists, which is where the relevant skill actually got built. *"I became known as the guy who could take a $20,000 or $30,000 budget and make it look three or four times bigger,"* he says. *"I had a house in South Central where I'd literally build set pieces from scratch."* That's the same job he's doing now with different equipment. Stretch a small budget across a big-looking frame by knowing exactly where to spend and where to cheat. Lighting, camera placement, production design, editing — the stuff that decides whether a shot lands, none of which a model has an opinion about. His start was as rough as anyone's. Early Midjourney, trying to get a recognizable character out of it: *"I remember generating Deadpool and thinking, 'I can kind of see Deadpool in this blob.'"* In 2024 he made a ten-minute Batman fan film — long, for AI video at the time — which went viral and then got taken down on copyright. Public domain characters make a lot more sense after that happens to you once. Kavan the Kid — "Echo Hunter: A Memory Too Far," via YouTube (@kavanthekid) ## The SAG-AFTRA One *Echo Hunter: A Memory Too Far* is the one people bring up first, because it went through SAG-AFTRA. Actors' likenesses were digitally replicated with consent, which made it the first AI film cleared that way and gave everyone downstream a template to point at. It stars King Bach and Carlye Tamaren, was presented by Kling AI, and was produced under Kavan's own studio, Phantom X. The story is standard-issue good sci-fi: the wealthy harvest clones for parts, an enforcer starts asking why, it goes badly. What matters for anyone trying to work this way is the paperwork, not the plot. A real union process, real consent from real performers, on a film with no physical shoot. That existed as an argument before *Echo Hunter*; afterward it existed as a credit. ## Somebody Bought the Universe In 2026, [Freepik acquired the remaining prologues and all of Season 1](https://aicinema.substack.com/p/how-an-ai-film-series-gets-sold-kavan) of *The Chronicles of Bone*, running through November. That's a distribution deal for an original IP built by one person at a desk. Not a brand partnership, not a sponsored short — a company buying a season of a serialized show. His other recent film, *Last Recall*, was made for Beyond The Loop Season 2 at Wonder Studios with invideo as executive producer. If you want to know what "AI filmmaker" means as a job rather than a hobby, that's the shape of it right now: own the IP, ship on a schedule, sell the season. Kavan the Kid — "Last Recall," a Wonder Studios original, via YouTube (@kavanthekid) ## Where the Craft Argument Lands There's a version of Kavan's position that comes off as gatekeeping, and he doesn't quite go there. His claim is narrower and more useful: the tools generate shots, and shots are not a film. *"AI can generate shots. But it doesn't understand story, pacing, or emotion."* You can hear that as "learn the rules first," which would be discouraging, or as "the part you already know how to do still counts," which is closer to what his own path shows. He learned blocking on a $20,000 music video, not in a prompt window. The blocking is what transferred. [YZA Voku's award-winning short films](https://www.thedaringcreatives.com/creator-stories/yza-voku-ai-films-voku-studio/) come out of a similar place — directing instincts first, generation second. Chapter Three went up in July. The [Chronicles of Bone](https://www.youtube.com/@kavanthekid?ref=thedaringcreatives.com) episodes keep landing about monthly, and the rest of his work — including a Nike spec ad and a Star Wars fan film — sits on [his films page](http://www.kavanthekid.com/films?ref=thedaringcreatives.com). Tools Kavan credits himself - **Freepik** and its **NanoBanana** image model — character design and world-building - [**Kling AI**](https://klingai.com/?ref=thedaringcreatives.com) — presenting partner on *Echo Hunter* - **Adobe Premiere Pro** — editing - [**DaVinci Resolve**](https://www.blackmagicdesign.com/products/davinciresolve?ref=thedaringcreatives.com) — color grading - **Adobe After Effects** and [**Blender**](https://www.blender.org/?ref=thedaringcreatives.com) — effects - [**Suno**](https://suno.com/?ref=thedaringcreatives.com) — music Adobe, Freepik and NanoBanana are named unlinked — their sites block automated checks, so we couldn't confirm the destination. ### Niceaunties Makes the Image First, Then Teaches It to Move URL: https://www.thedaringcreatives.com/creator-stories/niceaunties-auntieverse/ Last updated: 2026-07-31T11:55:53.000Z Eight older women are sitting in a bathtub-sized bowl of ramen. Their hair has been blown into enormous grey clouds by the steam. There's a fried egg the size of a manhole cover floating next to them, a wall of spinach, and behind the whole thing a working noodle factory where other women in chef whites are calmly plating sushi like none of this is unusual. They're laughing. Not the scale of the bowl, the fact that everyone in the frame is having a great time. That's the Auntieverse, which the Singapore artist niceaunties has been building since January 2023\. Elsewhere in it: two aunties in chef's hats slicing a salmon fillet the size of a dining table while a giant frog watches from behind two moons. A mirror-tiled cat head the size of a house, parked in the middle of a garden party. A kitchen where every surface, appliance and wire is the same shade of yellow, and one woman in purple is quietly cooking dinner in the middle of it while a cat hangs off the wall. The rules are consistent even when nothing else is. Ageing women are the main characters, food is usually the setting, and nobody in the frame is surprised. ![Two older women in chef's whites slicing an enormous salmon fillet under two moons, with a giant frog behind them](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/nasa-web.jpg) niceaunties — from the Auntieverse series, via [niceaunties.com](https://www.niceaunties.com/?ref=thedaringcreatives.com) ## The Image Comes First She's been unusually specific about how a piece gets made, which is rarer than it should be. *"I always start with the image,"* she said in [a long interview about her practice](https://www.96layers.ai/p/the-weird-wonderful-ai-art-of-niceaunties?ref=thedaringcreatives.com). *"So I make an image, and then I animate it, and then a sequence of this footage comes together to become a video."* That's the whole spine of it, and it's the opposite of how most people approach AI video — start with a shot description, generate motion, hope the frames hold together. She builds a still she's happy with, brings that still to life, and only then thinks about sequence. The iteration count is the other number worth knowing. *"For one video, I will have at least 25 to 30 prompts to get to what you see."* Turnaround runs from a few hours to a month, and half a day is the floor. On prompting itself she's matter-of-fact: *"Prompting is basically the language you use to communicate with the program, the machine. So to get a good prompt you need to experiment and iterate a lot."* The part that comes before any of that is the part she says takes the longest. *"I spend a lot of time dreaming and marinating ideas before I prompt."* That squares with how the pictures are put together. *"My art tends to be a collage of things and objects that do not typically exist together"* — which is a decision made in advance, not a thing a model hands you. [Manuela Klauser works the same way round](https://www.thedaringcreatives.com/creator-stories/manuela-klauser-knew-what-she-was-making-before-she-let-the-ai-near-it/), settling what the piece is before the tool gets involved. ![An all-yellow kitchen packed with appliances and pipes, an older woman in purple cooking at the centre](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/ikea-web.jpg) niceaunties — from the Auntieverse series, via [niceaunties.com](https://www.niceaunties.com/?ref=thedaringcreatives.com) ## Nineteen Years of Drawing Buildings Wenhui Lim spent nineteen years in architecture before any of this. You can see where it went. The compositions are frequently sectional — a whole environment cut open so you can see every level of it at once, the factory floor and the mezzanine and the bowl all legible in a single frame. That's an architectural drawing convention applied to a picture of women in soup. Multiple vantage points held in one image, everything readable, nothing hidden behind anything else. She's described the shift in what starts a project. *"Working in architecture, you're always working with a developer,"* she told [STIR in a piece on the Barcelona show](https://www.stirworld.com/think-opinions-auntiescapes-at-load-gallery-asks-can-the-hyperreal-impact-social-reality?ref=thedaringcreatives.com). *"But in the Auntieverse, it didn't start from that place. I was thinking about this character of the aunty and how to reframe her."* Same drafting instincts, no client. The brief is hers now. She got into it the way a lot of people did — saw images on Instagram in late 2022, found out they were Midjourney, went down the hole. By July 2023 she'd made something on the order of 40,000 images, a figure worth reading as a snapshot of that first stretch rather than a current count. ![A mirror-tiled cat head the size of a building sitting in a courtyard full of people at a garden party](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/moma-web.jpg) niceaunties — from the Auntieverse series, via [niceaunties.com](https://www.niceaunties.com/?ref=thedaringcreatives.com) ## Where the Aunties Have Ended Up The list is longer than you'd expect for a practice three years old. A TED talk in Vancouver in 2024\. The Louisiana Museum of Modern Art in Denmark. The V&A in London during its 2024 Digital Art Weekend. The AI Action Summit at the Grand Palais in Paris in 2025\. Christie's Art + Tech conference in New York. Paris Photo. Work with Swatch and L'Oréal. There's also been a billboard on Sunset Boulevard in Los Angeles — *Aunties on Sunset* — which is a genuinely funny place for this material to land. Ageing Asian women at monumental scale on the same stretch of road that sells everything else. Right now the main thing is *Auntiescapes* at Load Gallery in Barcelona, running May 7 to August 15, 2026\. At its centre is an interactive piece called *Mirror into the Auntieverse*, where your reflection is replaced by an auntie who tells you what she thinks. Other works in the show include *Cycles*, *Auntiecity* and *Auntlantis*. Her own summary of the project is one sentence: *"There is an auntie in all of us. I'm building the Auntieverse to understand what that means."* The Barcelona show has a few weeks left on it, and the [portfolio](https://www.niceaunties.com/?ref=thedaringcreatives.com) is where the rest lives. Tools niceaunties credits herself - **Midjourney** and **DALL·E 3** — image generation - **Magnific.ai** — upscaling - [**Runway**](https://runwayml.com/?ref=thedaringcreatives.com) and [**Pika**](https://pika.art/?ref=thedaringcreatives.com) — animating the stills - [**Suno**](https://suno.com/?ref=thedaringcreatives.com) — music Midjourney, DALL·E 3 and Magnific are named unlinked — their sites block automated checks, so we couldn't confirm the destination. ### Desktop Pets for Mac That Report What Actually Broke URL: https://www.thedaringcreatives.com/mascots-live-on-my-dock/ Last updated: 2026-07-31T16:16:43.000Z I have two brands and two mascots. Daring Strategy has a boxy little robot with a filing cabinet for a torso. The Daring Creatives has Sherman, who is a real dog, a Rottweiler mix who wears red goggles and runs Central Dispatch. Both of them existed as artwork. Illustrations in guides, faces on a page, characters in the fiction. Now they live on my Dock, and somewhere along the way they stopped being decoration. They are the thing that tells me when work I sent from my phone actually landed, and when it didn't. ![Sherman the pixel dog pacing on the macOS Dock with a small thought bubble beside him reading the subject of the note he is working on](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/shot-desktop-1.jpg) Mid-dispatch. He paces, and the bubble says what he is on and for how long. That is not a mockup. Sherman is pacing because a note I sent from my phone is being worked on right now, and the little bubble says what it is. ## Two characters, two completely different ways to draw them The robot I drew in code. Not by hand in a drawing app, in actual code: a script that says put a rectangle here, put a circle there, shade this side with a checkerboard pattern. It sounds insane, and it took a few rounds of "that looks nothing like him" before it did. But once it works you get something worth having, which is a character you can pose. Want him to blink? Change one value. Want his arm up? Change another. I ended up with 26 different frames of that robot out of one script — walking, sitting, yawning, reading a file out of his own belly drawer. ![Twelve frames of the Daring Strategy pixel robot laid out in two rows: idle, blinking, looking around, walking, sitting, hopping, alert and dancing](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/sprites-robot-1.jpg) Twelve poses, one script. Every frame is the same code with different numbers. Sherman I could not do that way. He is a real dog with a real face, and a script that draws rectangles is never going to get there. So I used an image model instead, feeding it actual photos of him as reference and asking for pixel art. I asked for four different looks first and put them side by side. I picked one and immediately caught something that had been missed: Sherman has a docked nub tail, and every generated version had given him a full one. That is the whole reason to show options before building anything. One glance from the person who knows the subject beat any amount of being careful. ## A walk is four pictures This is the most reusable thing here. A walk cycle is four drawings. Front leg forward, legs gathered underneath, other leg forward, gathered again. Play those four on a loop while sliding the whole character sideways, and your brain does the rest. It reads as walking. ![Sherman's seven sprite frames in two rows: standing, sitting, lying down, and four walking poses](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/sprites-sherman-1.jpg) Seven pictures is a whole personality. Seven frames total for Sherman: standing, sitting, lying down, and four walking. Walking left is the same four frames flipped horizontally, which is free and means he can never accidentally look like a different dog facing the other way. ## They became the notification system Here is the part I did not plan. I send work to these businesses from my phone. I hit a button, talk into it, and a pipeline on my Mac picks the note up, works it, and files the result. When I built that, it announced itself through a push service. Which I never once opened. That turned out to matter more than it sounds. Every dispatch I sent for a week failed within about five seconds of starting, and I found out seven notes later. The push notifications had all fired perfectly into an app I do not look at. So the pets became the channel instead, because the Dock is the thing I actually see. ## What a dispatch looks like now The moment a note lands, the pet belonging to that business turns and says *Got it*, with my own words read back to me. That answers the only question I have in the first ten seconds, which is whether the thing heard me at all. Then he starts pacing. Not the usual amble — a busier walk, no sitting, no lying down, and a small thought bubble next to him with the subject of the note and how long he has been at it. `AGRIS red profile 4m…` That number matters more than it looks. A pet that just says "working" for twenty minutes is indistinguishable from a pet that is stuck. When it finishes he stops, settles, and tells me what happened — with a button that opens whatever got made. If it failed, he says that instead, in those words, because a failure that looks like a success is the whole problem I was trying to solve. ## Only the right dog answers Both pets read the same file, which meant early on that every note lit up both of them. A note about Daring Strategy had Sherman pacing about it too. Now the pipeline reads the note for which business I named and tags it, and each pet only answers for its own. If I name neither, or name both, they both still react — a missed receipt is worse than a duplicated one, and I would rather two pets tell me than watch the wrong one. ## The bugs, which were the useful part **The app froze and there was no error.** macOS had put up a permission box asking if the app could read my Documents folder, and I had never clicked it. The app was politely waiting for an answer that was never coming. Nothing crashed, nothing logged. The fix was to read files in the background so a pending question can never freeze the character. **A test that could not fail.** After a click bug I added an automatic check that the buttons were where they were drawn. It passed. Then I deliberately broke the layout to make sure the check would catch it, and it passed again. It was comparing the code to itself. A test that cannot fail is worse than no test, because it tells you everything is fine while you sleep. **The error message thrown on the floor.** This is the one that cost a week. When a dispatch failed, the script logged `FAILED (rc=1)` and discarded what the agent actually said, because that text went to a different output stream than the one being recorded. Seven failures, no evidence. I added one line to log it, re-ran, and the answer was sitting there immediately: an API key had run out of credit. Five minutes of diagnosis, hidden behind a week of silence. **Two supervisors for one thing.** The Command Center server would not stay dead. Killing it brought it back in 34 milliseconds. It turned out a system-level launch daemon had been keeping it alive since April, and months later I had added a second watchdog on a timer to solve a restart problem that was already solved. Neither knew about the other. **Forget did not forget.** The pets can be told to drop an observation. It never stuck, and the reason is that each observation was identified by a string with its own numbers baked in — `list-conversion:8:45:21`. Dismiss it, the analytics refresh, the numbers move, and it comes back as a new item wearing the same face. It now keys on the part that says what it is rather than what it currently measures. **A label that said nothing.** The thought bubble picks the subject out of the note. My first version took the first few meaningful words, which works until you notice how people actually talk. My notes open with "This is for the daring creatives, I want…" — so the bubble read `This item is`. Word position cannot tell you what something is about. It takes an actual summary, so now it gets one. ## What I actually took from this Most of these bugs share a shape. Something failed, something aged, something got dropped — and the part that was supposed to tell me was either pointed at a surface I do not look at, or had quietly thrown the evidence away. The mascots did not fix that by being clever. They fixed it by being somewhere I cannot avoid looking, and by being specific when they speak. A number in a dashboard is easy to ignore. A dog you recognise, pacing, with your own words in a bubble over his back, is harder to walk past. ### Micah Alhadeff Builds Bodies Out of Error, Then Teaches It at a University URL: https://www.thedaringcreatives.com/creator-stories/micah-alhadeff-glitch-3d/ Last updated: 2026-07-27T20:59:59.000Z A figure stands at the center of the frame wearing a crown of spines. The spines are made of something between fern, feather, and circuit trace, in acid yellow and green, and they radiate out far enough that you lose track of where the body stops. The face is there, sort of. It's been overgrown. The piece is called "Spined Venus." The title is doing real work — Venus is the oldest subject in Western art, and this one has been colonized by whatever the machine grew on top of her. ![A dark human form on black, its surface breaking into scattered white and blue shards](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/micah-alhadeff-echo.jpg) "Echo" (2025) by Micah Alhadeff — via [micahalhadeff.com](https://www.micahalhadeff.com/portfolio?ref=thedaringcreatives.com) ## Error as the Method Alhadeff describes himself as an artist working with 3D animation, AI, code, and game engines, drawing on glitch aesthetics, queer theory, and video game culture. The operating principle he states is that he introduces error and instability into technological systems on purpose, corrupting the familiar into something that sits between the organic, the mechanical, and the artificial. His faculty bio puts the same idea in four words: error becomes generative. That's a stronger claim than it first sounds. Most work in this space treats the model's failures as a tax — something to prompt around, regenerate past, clean up in post. Alhadeff runs the tools until they break and then builds the piece out of the wreckage, which requires knowing precisely how each system fails and being able to reproduce it. You can't harvest an error you can't summon twice. The titles track it: *Glitch Dolls*, *Fractures*, *Splinters*, *Spectral Remnants*, *In Flux*, *Transgressions*. Fifteen projects on his portfolio going back to 2022, and the through-line is bodies that won't hold their shape. ![A luminous fractured figure surrounded by teal and yellow floral bloom against darkness](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/micah-alhadeff-glitch-dolls.jpg) "Glitch Dolls" (2022) by Micah Alhadeff — via [micahalhadeff.com](https://www.micahalhadeff.com/portfolio?ref=thedaringcreatives.com) ## The Toolchain Is Not Just Prompting The stack he works in is listed plainly: video, game engines, motion capture, and experimental 3D processes. Not one model with a text box — a pipeline, with a body actually captured in motion at one end of it. That's the part worth stealing. Motion capture means a real performance is in there. Game engines mean the piece can be lit, staged, and moved through rather than described and hoped for. AI is one instrument in the rack instead of the whole band, which is exactly why the output doesn't look like everyone else's. He came to it from a background that explains the compositions: a BFA in graphic design and a BA in art history and criticism, then an MFA in Electronic Integrated Arts from Alfred University. The symmetry in "Spined Venus," the way a figure gets centered and framed like an altarpiece — that's someone who studied how images have been built for six hundred years and then handed the job to a machine that doesn't know any of it. ![A green-skinned masked figure amid red spikes and neon scaffolding](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/micah-alhadeff-sandin-vibes.jpg) "Sandin Vibes" (2024) by Micah Alhadeff — via [micahalhadeff.com](https://www.micahalhadeff.com/portfolio?ref=thedaringcreatives.com) ## Where the Work Has Actually Been The exhibition list on his faculty page is long and specific: Sotheby's in New York, The Royal Institute in London, NFT.NYC, NFC Lisbon, NFT Show Europe in Valencia, Tech Contemporary in Copenhagen, Artverse Gallery in Paris. And then this one, which is a different kind of venue entirely: across 1,000 billboards in Belgium, through Art Crush Gallery and Clear Channel. Work built out of deliberate system failure, printed at highway scale, seen by people who did not come to look at art. ## The Teaching Part Since 2025 he's been Assistant Professor of Kinetic Imaging at Western Michigan University's Gwen Frostic School of Art, in Kalamazoo, where he teaches experimental approaches to game engines, worldbuilding, and emerging technologies. That's the detail that separates him from most people making work like this. The aesthetic is being taught — with critique, with a syllabus, to students who will graduate knowing how to break a render on purpose. Whatever this becomes in five years, some of it will trace back to a classroom in Michigan. His [portfolio](https://www.micahalhadeff.com/portfolio?ref=thedaringcreatives.com) is the place to see the range; the newest project, "Contestants for a Pageant That No Longer Exists," is dated 2026 and is where the work is heading now. ### YZA Voku Makes Award-Winning AI Short Films, and Commercial Work for The Weeknd and The Sphere URL: https://www.thedaringcreatives.com/creator-stories/yza-voku-ai-films/ Last updated: 2026-08-16T10:25:02.000Z A figure in a habit and veil stands against a pale wall, and its face is coming apart into a swarm — small dark fragments lifting off the cheekbones and drifting into the air around the head. It's black and white, high contrast, held long enough that you start looking for where the face ends and the swarm begins. That's a frame from "SUTURA.", and it's a fair introduction to how YZA Voku works: one strong image, very few elements, held until it does something to you. His films run in black and white more often than not. A silhouette with smoke curling off it. A face lit so hard the eyes read as lamps. A single figure crossing the floor of an enormous empty arena. There's almost never a crowd, almost never a busy frame — the compositions are closer to fashion photography or a stage than to a movie. YZA Voku — "SUTURA.", an AI short film, via [YouTube](https://www.youtube.com/@yzavoku?ref=thedaringcreatives.com) ## The Competition Record Voku has been a repeat presence at Runway's Gen:48, the 48-hour AI film competition — and his own channel labels the results. "LAPSE" took Best Craft in the second edition. "TO THE VOID" was a jury selection in the Aleph edition. "Antonomasia" made the finals; "Ext. Delirium" ran in the third edition. Best Craft is a telling award to win at a 48-hour competition. Everyone there is fighting the same tools against the same clock, and most of what comes out the other end looks like it. Craft is the category for whoever managed to make deliberate choices anyway. YZA Voku — "LAPSE," which his channel lists as the Gen:48 Best Craft winner, 2nd edition ## The Studio Underneath The films aren't a hobby running alongside a day job. They're the portfolio for one. Voku.Studio was founded in 2022 and describes itself as a creative studio focused on crafting with AI, based in Andalucía with international reach. Its services are listed as creative direction, post-production, AI generation, and design — the same four things a conventional production company sells, with generation slotted in where a shoot would be. The tagline across the top of the site is *Not Real, Yet.* The Works page is the part that stops you. It lists projects under names including The Weeknd, Cara Delevingne, The Sphere, Swedish House Mafia, Anyma x Solomun, Helena Rubinstein, XG, Hï Ibiza, Ex Nihilo Paris, Songzio, Dellafuente, LaLiga, and Premios Goya — Spain's national film awards. The categories they're filed under are music video, film, fashion, branding, commercial, and artifacts. Take that at what it is: a Works page, not a press release, so it says these are projects the studio did rather than explaining each engagement. But the roster is specific, it's named, and it spans music, luxury fashion, sport, and a national awards show. That's a working commercial practice, not an experiment. YZA Voku — "TO THE VOID," a jury selection at Gen:48 Aleph Edition ## What He Says He's Doing Voku's own site describes him as a director and visual artist in Andalucía who blends generative AI with traditional art and filmmaking, and puts the goal as work that blurs the line between the organic and the synthetic. He names his influences plainly: surreal minimalism, performance photography, avant-garde cinema. Those are three references that have nothing to do with AI, and it shows in the output. The films look like someone who already had taste in images and picked up a new way to produce them — the restraint in the frames is the kind of thing you learn from photography, not from a model. The studio's own framing runs the same direction: expanding the boundaries of traditional narrative, with the unknown as its stated identity. It's positioned as a research practice that happens to take commercial work, rather than an agency that added an AI service line. ## Where to Watch It The short films live on [his YouTube channel](https://www.youtube.com/@yzavoku?ref=thedaringcreatives.com); the commercial work is on [voku.studio](https://voku.studio/projects/?ref=thedaringcreatives.com), and the day-to-day is on [Instagram](https://www.instagram.com/yzavoku/?ref=thedaringcreatives.com). Clanker Magazine featured a run of clips from a recent project in May, which is where a lot of people found him. The next Gen:48 will tell you whether the competition record keeps extending. The Works page will tell you whether the client list does. ### GLOOMSTOMPER Is Voidstomper's Other Account, Where the Glitch Became a World URL: https://www.thedaringcreatives.com/creator-stories/gloomstomper-voidstomper-dark-fantasy/ Last updated: 2026-08-16T10:25:03.000Z A king in dented armor stands in a stone chamber, torchlight going amber on the walls, and a woman in a grey gown holds onto his arm while he says he promised he'd never come back to this place. It's a scene with a before and an after. Someone wants something, someone is afraid of it, and the room they're standing in has history. That's GLOOMSTOMPER, and it's a different job than melting a face for six seconds. The work runs dark fantasy in two registers — that live-action film on one side, VHS-era anime on the other, worms and dragons and resurrection across both — built with the same generative video tools that made the artist's other account famous for nightmare fuel. Same hands, same broken machine, aimed somewhere else entirely. [ ![A blond knight in white-and-gold armor holds up his helmet in a golden hall, subtitled “it worked”](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/gloomstomper-cost-of-resurrection-still.jpg) ](https://www.youtube.com/watch?v=%5FukEZsFBsbo&ref=thedaringcreatives.com) gloomstomper — from “The Cost of Resurrection.” [Watch it on YouTube](https://www.youtube.com/watch?v=%5FukEZsFBsbo&ref=thedaringcreatives.com). ## Same Artist, Different Assignment GLOOMSTOMPER is run by the anonymous artist behind [Voidstomper](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/), whose short loops of melting faces and impossible bodies — captioned, every time, "AI Generated Nightmare Fuel" — did more than anything else to define AI horrorcore. The two accounts have always been linked in public: the [gloomstomper Linktree](https://linktr.ee/voidstomper?ref=thedaringcreatives.com) is the voidstomper Linktree, and the YouTube channel's own description reads "interdimensional dark fantasy from the mind of @voidstomper." That description is worth pausing on, because it used to say something else. When we [wrote about Voidstomper in April](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/), the second account was billing itself as *interdimensional cartoons* — the same sentence, one word different. Cartoons became dark fantasy. That's a small edit to a bio and a large change in what the work is trying to be. The artist has described the split himself. In [an April feature by Clanker Magazine](https://www.instagram.com/p/DXwwZ2jjarR/?ref=thedaringcreatives.com), posted as a collaboration with the GLOOMSTOMPER account, he frames Voidstomper as chaos mining and GLOOMSTOMPER as world building — and puts the reason plainly: shock worked when generated video was still rare enough to startle people, and the feed has since filled up with strange. Impact stops being a strategy when everyone has the same button. ## What World Building Actually Costs Him "The Cost of Resurrection" runs about a minute, which is not much longer than a Voidstomper loop. The difference is what's inside it. There are characters who want opposing things. There's dialogue, subtitled across the bottom of the frame, which means someone wrote lines and then made a model deliver them with faces that hold still enough to act. There's a title, which implies the thing is a piece rather than a post. YouTube stamps its "AI" altered-content label on it, so the disclosure is sitting right there next to the play button. None of that is required to go viral. A loop of something horrible sliding across a beach will out-perform a plot most days. Making a short film with a beginning and an end is a decision to be judged as a filmmaker instead of as a feed, and the tools are worse at it — continuity between shots is exactly where generative video still falls apart. ## The Shorts Are Still the Engine The channel is mostly Shorts — 168 videos, almost all vertical, with the short film as the outlier. The titles are lowercase and deadpan: *worm lord*, *eat your vegetables*, *i slay dragons*, *wake up*. [ ![Cel-animated armored figure screaming against a red sky, in the style of an 80s OVA](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/gloomstomper-worm-lord.jpg) ](https://www.youtube.com/shorts/kV2yGHLYeYg?ref=thedaringcreatives.com) gloomstomper — [“worm lord”](https://www.youtube.com/shorts/kV2yGHLYeYg?ref=thedaringcreatives.com) [ ![Cel-animated vegetables with human teeth holding knives, subtitled “eat your vegetables”](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/gloomstomper-eat-your-vegetables.jpg) ](https://www.youtube.com/shorts/SlbfXNcYVCk?ref=thedaringcreatives.com) gloomstomper — [“eat your vegetables”](https://www.youtube.com/shorts/SlbfXNcYVCk?ref=thedaringcreatives.com) They also look nothing like the short film. Where "The Cost of Resurrection" is shot like an 80s live-action fantasy picture — practical armor, torchlit stone, actors emoting — the Shorts are cel animation: heavy black outlines, flat cartoon color, the grain and slightly-off registration of a VHS-era OVA. A mecha-armored figure screaming against a red sky. A gang of vegetables with human teeth holding knives. A cartoon dragon with blushing cheeks and enormous eyelashes. A blue demon with too many eyes crouched over a woman in a ballgown. The subject matter swings from genuinely cute to genuinely grotesque, sometimes inside the same clip. What holds it together is the era. Both halves of the channel are pastiche of the same decade — the anime you'd catch on a third-generation tape and the fantasy movie that played endlessly on cable — and that gives the AI's weirdness a place to sit. A body coming apart in a 1987 OVA reads as a curse. The same distortion in a clean modern render reads as a bug. ## Where the Process Lives The artist has never given a real name — no face, no origin story, just output. But the process isn't a secret so much as a product. The Linktree's top entry is a Patreon, labeled by the artist as exclusive, behind the scenes, and tutorials. That's a coherent position for someone whose whole aesthetic is built on knowing exactly where the model breaks. If the finished clip can be copied by anyone with the same tools, the thing worth charging for is the method — which is the same conclusion he reached when he sold a PDF of ten prompts, and the same one Voidstomper has been testing since the beginning. ## What He's Making Next The bio still points back to Voidstomper, so the horror account isn't being retired for the dark fantasy one. Both universes are running. What's new is that one of them now has a short film in it, a title card, and characters who talk. The Shorts keep coming — [the channel](https://www.youtube.com/channel/UCNeSaqNYwvjnhMmXKVbi8JA?ref=thedaringcreatives.com) and [the Instagram](https://www.instagram.com/gloomstomper/?ref=thedaringcreatives.com) are where the next piece of the world shows up. ### Gossip Goblin Released Pomegranate for Free the Same Day He Announced a Theatrical Run URL: https://www.thedaringcreatives.com/creator-stories/gossip-goblin-pomegranate/ Last updated: 2026-08-16T10:25:04.000Z An old man sits in a workshop with gold filament stitched through his face. There's a port in the side of his neck with a cable running out of it, and he's wearing something cream-colored and embroidered that looks expensive in a way that stopped meaning anything a long time ago. He's bored. He has been bored for centuries. That's the setup for "Pomegranate," which Gossip Goblin put on YouTube on July 22\. His own description of it: "After centuries of simulated wars, wives, and wonders, a jaded aristocrat visits his neighborhood dreamspool dealer in search of something, anything, that still feels real." It runs 27 minutes and 56 seconds. It's free. And, it's glorious. "Pomegranate" — @Gossip.Goblin on YouTube Before the animation, look at the credit roll he put at the end of the description. It names fifteen people. Sam Dale, Ben Kersley, Oscar Merry and Ayça Özkan on voices. Alexandru Mihai as animation lead, with Benjamín Muñoz Alonso, Alberto Alepuz Fernandez and Nowell Englund animating. Răzvan Ilinca edited it and supervised post. Anne-Sophie Versnaeyen and Juan Torán wrote the score. Ștefania Grigorescu graded it. Marian Bălan did sound design and the re-recording mix. Zack London wrote, directed, and produced, alongside Edward Saatchi and Fable Studio. Most coverage of AI film doesn't print the crew, which is a shame, because the crew is the argument. His studio [says it plainly on its own site](https://www.gossipgoblin.studio/?ref=thedaringcreatives.com): "Every story is imagined, written, and directed by humans. AI is just our force multiplier." ## Nineteen days of rollout for a free short Here's the part I hadn't seen anyone lay out. Pomegranate didn't just appear — it was released like something with a marketing budget, and the schedule is sitting right there in the channel's upload history. - **July 3** — "Pomegranate - Official Trailer (2026)" - **July 14** — "Pomegranate: Make Me Feel" - **July 15** — "Pomegranate: Trailer 3" - **July 17** — "Pomegranate - Trailer 4" - **July 18** — "Pomegranate - Sneak Peek" - **July 21** — "Pomegranate - Trailer 5" - **July 22** — the film, as a scheduled live premiere, plus a livestream - **July 23** — "A True Swordsman (Pomegranate)" - **July 24** — "Pomegranate - Out Now!" Six drops before release. A premiere with a live chat, not a quiet upload. Then two more cutdowns after, on the days when a new release is actually getting shared. The official trailer, posted July 3 — @Gossip.Goblin on YouTube And then there's the date. July 22 is also the day [Variety](https://variety.com/2026/film/news/gossip-goblin-ai-film-gods-dont-give-gifts-theaters-1236818068/?ref=thedaringcreatives.com), [Forbes](https://www.forbes.com/sites/maureenkerr/2026/07/22/youtuber-gossip-goblin-will-debut-ai-film-in-us-theaters/?ref=thedaringcreatives.com) and IndieWire all reported that his feature, "Gods Don't Give Gifts," is getting a limited U.S. theatrical release on October 30. So the trade press ran a story about a movie nobody can see yet, and on the same morning, 28 minutes of finished work from the same world went up for free where anyone reading that story could watch it immediately. By July 26 it had passed 1.1 million views. That's a distribution decision, and it's a good one. If you're asking people to buy a ticket for an AI feature in October — and plenty of them have already decided how they feel about that phrase — the strongest thing you can hand them is a long, finished, unpaywalled piece of the same thing. ## What he actually does to make one of these Pomegranate lives in the same world as "The Patchwright," his 21-minute cyberpunk short from earlier this year. Both are set in what he calls the Second Cycle of Humanity, and the Pomegranate title card even stamps the same location on it — Niiro Cradle, the city from Patchwright. "THE PATCHWRIGHT" — @Gossip.Goblin on YouTube He walked through the Patchwright method in detail [in an interview with PJ Ace](https://pjace.beehiiv.com/p/gossip-goblin-s-crazy-workflow-for-building-original-worlds-200m-views?ref=thedaringcreatives.com) in May, and the specifics are more stubborn than you'd guess. Every shot starts as a still in Midjourney — and he was working in v7, not the newer version, because he thinks v7 sits closer to the ceiling of what the tool can actually do. He builds custom profile codes rather than leaning on prompt syntax. Nano Banana comes after, never first: *"no image starts in nano banana. Nano banana is just our photoshop."* His reason for avoiding the defaults is the most useful sentence in the whole interview. *"Whatever the default agent gives you is going to look like what it gave the next thousand people who asked."* So the interrogation room in Patchwright is a circular panopticon instead of the gray table you'd get for free. He explores each location separately — penthouse, ship interior, mid-air city, street level, wet market — locks a few hero shots per environment to set the light, then fills the connecting frames from those anchors. Roughly 90% of the final color grade is baked into the stills before anything moves. Animation is Kling, all of it, with Sync Labs patching some lip-sync. He deliberately skipped the omni-reference and multi-shot features that would have sped this up, because he wanted to control every frame — a choice he reckons cost him a couple of months. Before Nano Banana Pro existed, he hand-painted directly on images for a nine-minute scene, drawing arrows and marking cables to feed the notes back in, hundreds of angles one at a time. No upscalers, because of the artifacts and oversharpening. Grain added on purpose, to fight the waxy too-clean surface the models default to. Real voice actors on every discernible line. Paid composers. *"AI is not going to behave the way you want,"* he told PJ Ace. *"It's like wet clay. You understand the medium, you know how to manipulate it, but it has a mind of its own."* None of that is a shortcut. Patchwright took four months by his own count in the PJ Ace interview, and five by the figure Forbes and The Hollywood Reporter both used — either way, months, for twenty-one minutes of film. That tracks with what turned up the first time we went through [the work hidden inside Gossip Goblin's worlds](https://www.thedaringcreatives.com/creator-stories/the-work-hidden-inside-gossipgoblins-worlds/), where he'd run 400 prompts and 1,600 images just to lock one set of faces. Tools he credits himself (Patchwright era, May 2026) - **Midjourney** (v7) — every shot starts here as a still; custom profile codes over prompt syntax - **Nano Banana** — the editing step, never the generation step - [**Kling**](https://klingai.com/?ref=thedaringcreatives.com) — all animation - [**Sync Labs**](https://sync.so/?ref=thedaringcreatives.com) — supplemental lip-sync - [**DaVinci Resolve**](https://www.blackmagicdesign.com/products/davinciresolve?ref=thedaringcreatives.com) — edit and finish His stack has shifted between films — an earlier breakdown had Seedream, Veo 3, Runway Act Two and HeyGen in it. This is what he described for Patchwright. ## The theatrical one "Gods Don't Give Gifts" opens in limited U.S. theaters on October 30\. It's an anthology — four stories — co-produced with Edward Saatchi's Fable, and it sits in the same transhumanist future, where bodies are upgradeable and memory is something you can buy. London's framing of it: the film is about "what happens to ordinary human hungers" once the physical limits come off. Forbes reported it came together in about two months with roughly ten artists, and that he employed voice actors, musicians and a Foley artist — performance and sound being the parts he doesn't want to hand off. There's also a $15,000 contest for the best fan-made short set inside the same universe, with the winner announced on release day. Which is a fairly clever way to turn the people who liked Pomegranate into the people making more of it. ## About that George Lucas line If you read around on him you'll hit the George Lucas comparison a lot, usually presented as something he says about himself. It isn't. It came from Seth Abramovitch [in The Hollywood Reporter](https://www.hollywoodreporter.com/movies/movie-news/gossip-goblin-zack-london-ai-films-watch-1236544634/?ref=thedaringcreatives.com), who put it to him as a question — that someone is going to be the George Lucas of this, and wouldn't it be interesting if it were him. London's answer was to duck it: that's what they're telling investors, but he doesn't want to jinx it. Worth getting right, because the version where he's crowning himself makes him sound like a completely different person than the one who spent nine minutes of screen time hand-painting arrows onto stills. The rest of the background is less quoted and more interesting. He's 35, from Los Angeles, studied sculpture and anthropology at Pitzer, and worked as a product designer before doing VR at Facebook and Oculus. He moved to Sweden about four years ago. He started on AI tools around three and a half years ago, beginning with a fictional travel series in Midjourney before video generation existed, and he now moves between somewhere in the range of fifteen to twenty-five tools. It's also worth remembering he's the one who said there's [zero skill involved in generating AI images](https://www.thedaringcreatives.com/creator-stories/what-zack-london-actually-means-when-he-says-there-is-zero-skill-in-ai/) — a line that reads very differently once you've seen the workflow it came from. His studio describes itself as "a storytelling studio creating original universes and mythologies for the modern age," with more than 600 episodes released in two years. The pinned comment under Pomegranate, from him: "Pomegranate is just the beginning. Bigger, more delightfully provocative announcements coming soon!" ### GEDDYRUXPIN Is Making AI Short Films That Feel Like They Were Buried in a VHS Vault Since 1963 URL: https://www.thedaringcreatives.com/creator-stories/geddyruxpin-ai-short-films/ Last updated: 2026-08-16T10:25:05.000Z A GEDDYRUXPIN film looks like something that shouldn't have survived. Mid-century television, colors pushed a shade too far, the tape warped somewhere between then and now. Alien henchmen in business suits. A cereal commercial for a product nobody ever ate. A puppet segment that seems to have aired once, very late, and then stopped being mentioned by anyone. Most of them run under a minute. All of them are built to feel found rather than made. The signature series is The Glunkies — those henchmen, recurring, always in the suits, always mid-errand in somebody else's sci-fi plot. Around it sit horror trailers cut like 1966 TV promos and psychedelic puppet clips that look like they came off a water-damaged tape someone pulled out of a garage. One world, consistent rules, and every rule borrowed from a narrow corner of American television. Nobody knows who makes it. The films go out as GEDDYRUXPIN, the project is called Stressed Quest, and no verified name is attached to either. That's worth sitting with rather than solving. The work presents itself as an artifact — something found, not authored — and artifacts don't come with a byline. The anonymity is doing the same job as the film grain. GEDDYRUXPIN — "I dream of glunkies," via YouTube (@StressedQuest) ## Why the Era Does the Work Picking 1963 buys a lot. Film stock that already degrades, color that was never accurate to begin with, broadcast standards nobody alive remembers well enough to fact-check. It's a period the audience recognizes without being able to check the receipts — close enough to familiar that the eye relaxes, far enough back that anything strange reads as a quirk of the format. Then the characters morph. Faces shift between cuts, proportions slide, a body reorganizes itself while the scene keeps playing like nothing happened. None of that was physically possible on a soundstage in 1963, which is exactly why it registers. The frame promises an old artifact and the motion breaks the promise. The films look precisely as wrong as they're supposed to look. That slippage is the material. ## Working With the Weirdness Instead of Around It Most people using these tools spend their effort steering away from what the model does badly. The morphing hands, the faces that won't hold still, the physics that slides halfway through a shot — prompt it away, crop it out, regenerate until the thing behaves. The goal is to get the AI to stop looking like AI. GEDDYRUXPIN is doing the opposite, and they're not the first to figure out it pays. [Voidstomper built one of the largest audiences in AI-native art](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/) by hunting for the exact places where the model breaks down and building an entire horror aesthetic out of the breakage. Same bet, different register: Voidstomper aims the wrongness at nightmare fuel, GEDDYRUXPIN aims it at 1963 television. There's a practical logic to it. A face that morphs mid-sentence is a failure if you're making a car commercial. It's an asset if you're making something that's supposed to feel like a degraded tape of a puppet show nobody remembers airing. The limitation stops being a limitation once the thing you're making has room for it. ## What I Like About It I found GEDDYRUXPIN doomscrolling Instagram after a few edibles. Incredible experience. I've lost plenty of evenings to that feed and gotten nothing back — this one I'd do again. What hooks me is how the scenes are built. It opens on something completely ordinary. People in a diner, eating, talking, nothing happening. Then a robot comes through the front door and destroys everything. The surreal part doesn't get its own separate world to live in — it crashes into a normal one, and the normal one keeps behaving like it's still a normal one. GEDDYRUXPIN — the diner, via Instagram ([@geddyruxpin](https://www.instagram.com/geddyruxpin/?ref=thedaringcreatives.com)) That contrast is doing the work. If the whole video were chaos, it'd be noise, and there's already plenty of that. The diner has to be believable first. It's a setup-and-payoff structure, and it's the kind of thing you can only pull off if you're actually thinking about the shot rather than just generating until something cool falls out. ## The Tools They Credit GEDDYRUXPIN tags their posts with `#sora2pro` — pointing to OpenAI's Sora as the primary generation tool. Kling shows up in the tags too. The [Stressed Quest print shop](https://stressed.quest/?ref=thedaringcreatives.com) sells the imagery as physical prints, so the stills exist as objects outside the films. No formal process interview has surfaced publicly. What's visible is consistent: a recurring universe (The Glunkies), regular releases inside it, and a body of work where the same instability shows up on purpose every time. GEDDYRUXPIN — "Night of the Atomic Neon Goblin," via YouTube (@StressedQuest) ## A Music Video on Sub Pop Records In 2024, GEDDYRUXPIN animated the official music video for J Mascis's "Old Friends" on Sub Pop Records. Kirby Ferguson — filmmaker behind *Everything Is a Remix* — publicly credited GEDDYRUXPIN for the animation. J Mascis is a Dinosaur Jr. institution. Sub Pop is Sub Pop. Ferguson has a real following in creative-process circles and tends to be careful about who he credits. An anonymous AI video artist getting a verified attribution in that chain, within a couple years of these video tools existing — that's a concrete thing to point at. GEDDYRUXPIN — animation for J Mascis "Old Friends" (Sub Pop Records, 2024) ## The Name and the Project The original Teddy Ruxpin was a cassette-powered animatronic bear — pre-programmed stories on a tape, a mouth and eyes moving in sync, the performance slightly mechanized. GEDDYRUXPIN is working in that territory: characters that move like they're running on something you can't see, programmed, slightly off, close enough to familiar that the wrongness registers. Looper covered their work in a piece on "the most horrifying AI kids' puppet show" — accurate description, undersells the craft. The horror isn't accidental. The Glunkies keep coming. The [Instagram](https://www.instagram.com/geddyruxpin/?ref=thedaringcreatives.com) and [YouTube channel](https://www.youtube.com/@StressedQuest?ref=thedaringcreatives.com) are the places to watch it develop. Tools GEDDYRUXPIN credits themselves - [**Sora**](https://sora.com/?ref=thedaringcreatives.com) (OpenAI) — primary video generation tool, tagged consistently as `#sora2pro` - **Kling** — appears in post tags alongside Sora ### How Animaj Trained Its Animation AI on 300,000 Pocoyo Sketches. URL: https://www.thedaringcreatives.com/creator-stories/animaj-pocoyo-disney-jr/ Last updated: 2026-08-04T14:22:37.000Z On Wednesday, July 15, two episodes of a preschool series called Ozzy Fox appeared on YouTube. No press release. No launch coverage. The CEO of the studio behind it marked the occasion with a LinkedIn post, and that was about it. Which is a strange way to launch what [Cartoon Brew reports](https://www.cartoonbrew.com/series/disney-jr-animaj-ozzy-youtube-264646.html?ref=thedaringcreatives.com) is Disney Jr's first preschool series made for YouTube — co-developed with Animaj, a company whose entire public identity is AI-accelerated animation. The two episodes pulled roughly 800,000 combined views in their first two days, and they're past 1.4 million as I write this. Most of the studios we cover here are one person and a stack of subscriptions. Animaj is the other end of the spectrum: 85 million dollars in funding, offices in London, Paris, and Madrid, and ownership of Pocoyo — the kids' franchise it bought in 2023 and then used as training data. It's the first studio deconstruction we've done, and Animaj makes it easy in one specific way: they publish their pipeline like an engineering blog. Ozzy Fox — "The Floor Is Lava!," episode 1, on YouTube ## Is Pocoyo AI? The original series wasn't. Animaj bought the Pocoyo franchise in 2023 and inherited four seasons of conventionally animated footage, which became the training data for everything the studio built next — 300,000 sketch-and-pose pairs and 298 episodes, fed into the two models described below. Pocoyo's sixth season runs on that pipeline. The murkier case is Ozzy Fox, the Disney Jr series Animaj co-developed: neither company has said what role the AI tools played in making it. ## The studio that bought its own training data Animaj was founded in May 2022 by Sixte de Vauplane and Grégory Dray, an ex-YouTube executive. The move that defines them came a year later: they acquired Pocoyo, the Spanish preschool franchise, outright. They now co-own Maya the Bee with Studio 100, run the HeyKids and Kidibli channels, and claim over 22 billion YouTube views a year across their properties. Two-thirds of their revenue reportedly comes from YouTube. Buying Pocoyo got them a beloved character. It also got them four seasons of professionally animated footage they own outright — which turned out to be the foundation for everything they built next. De Vauplane has been open about the ambition. He told [Sifted in an interview](https://sifted.eu/articles/interview-sixte-de-vauplane-animaj?ref=thedaringcreatives.com) that the goal is building kids' franchises on the scale of Pokémon, Peppa Pig, and PAW Patrol — his framing was that they're trying to build what Disney built a century ago, on AI-era economics. The backers apparently agree: the $85M round announced in June 2025 was led by HarbourView and Bpifrance, and the company has since joined both the Disney Accelerator and Google's AI Futures Fund. ## The pipeline they actually published Here's what makes Animaj coverable in a way most AI studios aren't. In November 2024 they unveiled a system called Sketch-to-Motion and wrote up [how the first model works](https://www.animaj.com/post/animaj-sketch-to-motion-model?ref=thedaringcreatives.com) in real technical detail. The system is two models in sequence. Sketch-to-Pose takes a storyboard artist's rough drawing and predicts the values of the character's 3D rig — head rotation, hand positions, elbow angles — so the sketch becomes a posed character without an animator translating it by hand. It was trained on more than 300,000 sketch-and-pose pairs mined from four full seasons of Pocoyo. Their published numbers: posing a two-minute animation dropped from 14-plus hours to about six. The second model, [Motion In-Betweening](https://www.animaj.com/post/animaj-sketch-to-motion-workflow-part-2-2?ref=thedaringcreatives.com), fills the frames between key poses. It's a bidirectional LSTM trained on 298 Pocoyo episodes — over 770,000 frames — and it learned the animation-school fundamentals from the footage itself: ease-in and ease-out, anticipation, overshoot. That step went from 339 minutes to 113 for a two-minute piece. The division of labor in their telling: humans keep the scripts, the storyboards, the key creative poses, and the final refinement pass. The models do the translation and the filling-in. De Vauplane's line at the [Sketch-to-Motion unveiling](https://worldscreen.com/tvkids/animaj-introduces-sketch-to-motion-ai-tool/?ref=thedaringcreatives.com): "Sketch-to-Motion changes everything about how we create animations. It's not just faster; it's smarter. Artists now have the freedom to iterate endlessly and see their ideas come to life instantly. This tool isn't replacing creative artists—it's empowering them." Their stated productivity target puts a number on the ambition: from roughly 30 seconds of finished animation per animator per day toward 500 seconds within three years. ## So what is Ozzy Fox? A music-driven preschool show about a five-year-old fox whose imagination turns chores into games — cleanup songs, potty training, that register. The pedigree is legitimately strong: it was created by Jennifer Oxley, whose credits include Peg + Cat and Wonder Pets!, and developed by Guillermo García-Carsí, the co-creator of Pocoyo himself, who's been Animaj's creative director since 2023. [C21Media reports it](https://www.c21media.net/news/disney-jr-launches-first-preschool-series-on-youtube-in-partnership-with-animaj/?ref=thedaringcreatives.com) as jointly developed by Disney Jr and Animaj — a partnership that grew out of Animaj's slot in the 2025 Disney Accelerator — with a broader platform rollout planned in the coming months. The episodes themselves run about two and a half minutes. Ozzy Fox — "Potty Party Dance Break!," episode 2, on YouTube ## Neither company has said what the AI did Here's the detail Cartoon Brew zeroed in on, and the reason this launch is interesting beyond preschool music videos: neither Disney nor Animaj has said what role Animaj's AI tools actually played in making Ozzy Fox. That's worth sitting with. Animaj publishes engineering posts about its models. De Vauplane talks about AI acceleration in every interview. The company's own positioning line — verbatim from their site — is that they're "pioneering a new category of studios where creators lead, data informs creation, AI accelerates production, and distribution is built in from day one." And yet the one production with Disney's name on it arrived with no methodology talk at all. I can't tell you whether Sketch-to-Motion touched this show, because nobody involved has said. Cartoon Brew reads the silence as part of a trend: as these tools normalize inside studios, disclosure is shrinking, not growing. Two years ago an AI-assisted show was an announcement. Now it's a quiet Wednesday upload. The critics filled the vacuum anyway. Kotaku's write-up was scathing about the look of the episodes — too smooth, too shiny, background details that don't hold up. Creative Bloq's angle was that the criticism itself is driving the view counts. For what it's worth, the loudest objections so far have come from industry press, and the view counters keep climbing. ## What's verifiable, and what to watch To be fair to the humans in this pipeline: a show created by the person behind Wonder Pets! and developed by Pocoyo's co-creator is a real creative team, whatever the production stack looks like. The steelman for Animaj's approach is in their own published numbers — the models handle posing and in-betweening, the stages animators tend to describe as labor rather than authorship. Whether that's how it played out on this particular show is exactly the thing nobody has disclosed. What happens next is checkable. Pocoyo's sixth season runs on the published pipeline. Maya the Bee digital content starts this year. Ozzy Fox has its broader rollout coming, and the channel sits at three videos as I write this. For the other end of the production-scale spectrum, our Creator Stories collection covers the one-person versions of this same story — including [Neural Viz's one-person TV network](the-showrunner-how-neural-viz-makes-an-entire-tv-universe-with-ai/), which gets to a finished episode with a webcam and about a hundred bucks a month. ### How Do AI Creators Actually Make Their Videos? URL: https://www.thedaringcreatives.com/creator-stories/how-ai-creators-make-videos/ Last updated: 2026-08-01T21:35:21.000Z Somebody watches a Gossip Goblin short or a cursejourney reel, and the first thing they type into Google is some version of the same question: how does he actually make these? I know because I typed it myself, more than once, before I started asking the creators directly. The assumption behind the question is usually "there's a magic prompt." There never is. Every process we've deconstructed starts somewhere old-fashioned — a script, a storyboard, a world that existed before the tools did — and then runs through a stack of tools handing off to each other, with a human throwing away most of what the machines produce. The tools change month to month. The shape doesn't. Here are five of the processes we've pulled apart, each with a link to the full breakdown. ## How does Gossip Goblin make his videos? Zack London's answer is the bluntest one we've collected: "Every video starts with a script." Not a prompt, not a mood board — a script. The worlds he builds, from cyborg aristocrats to entire goblin civilizations, hang off the writing, and everything downstream exists to serve it. Then comes the part that never shows up in the finished video. For one set of characters he ran "probably 400 prompts / 1600 images" just to get the faces right. Environments are worse — he's said flatly that "this part is not enjoyable," describing generating a mountain of background shots just to get something he could force his characters into. Animation brings its own grind: lip sync is "a colossal headache," camera movement is manual, and a single 90-second dialogue scene took "about 150 generations." The stack is half a dozen specialists handing off: Midjourney for characters and costumes, Seedream to blend characters into environments, Veo 3 for dialogue-heavy scenes, Runway and HeyGen for performance and lip-sync passes, ElevenLabs for voices, and CapCut to cut it — a choice he jokes about, but it assembles a dozen moving parts fine. End to end, one piece takes him 12–14 hours. The full breakdown is in [the work hidden inside Gossip Goblin's worlds](the-work-hidden-inside-gossipgoblins-worlds/). "Pomegranate," Gossip Goblin's newest short film — @Gossip.Goblin on YouTube ## How does Neural Viz make the Monoverse? Josh Kerrigan was a filmmaker for over a decade before any of this — film school, years of LA production work, a TV pilot he's said he sold before going full-time on Neural Viz in early 2025\. That background shows up in the design of the world itself: he studied what the models are bad at and built a show that hides it. AI struggles with realistic humans, so his characters are bulbous cartoon aliens your brain never expects to look real. Clean 4K makes rendering artifacts scream, so everything is graded like a worn-out 20th-century broadcast — VHS noise, soft focus, a tape copied one too many times. The workflow underneath is a writers' room, not a prompt box. He writes a full script — slug lines, blocking, the whole format — then storyboards every shot and generates a still per panel, mostly in Midjourney, holding lighting and sight lines consistent so the cuts don't fall apart. The signature move: he acts the scenes out in front of his webcam, and Runway's Act-One maps his real performance — the timing, the head turns, the delivery — onto the alien characters. Hedra handles lip-sync, ElevenLabs does voices (sometimes layered over his own), and Premiere cuts it like any other edit. His own numbers: about twelve hours and roughly a hundred bucks a month in subscriptions for a two-to-three-minute episode. And he's clear about where the result actually comes from: "Everything I do within these tools is a skill set that's been built up over a decade plus." The full breakdown is in [The Showrunner: how Neural Viz makes an entire TV universe](the-showrunner-how-neural-viz-makes-an-entire-tv-universe-with-ai/). "Human Hunters," from the Monoverse — @NeuralViz on YouTube ## How does Kelly Boesch make her AI films? Boesch spent 17 years at IMAX — graphic design, film production, marketing, the development decks that convince studios to fund projects. When she picked up AI generation three years ago, she arrived already knowing what a cinematic image is supposed to feel like. That training is why her method runs opposite to how most people approach AI video. Most people go text-first: describe the scene, generate, hope. Boesch works image-first. She generates a still in Midjourney, gets the composition exactly right, then animates from that image using Runway, Pika, Higgsfield, or Veo 3 depending on what the scene needs — each tool behaves differently, and she moves between them. Image-to-video keeps the art direction in her hands where text-to-video would hand it to chance. Her line on where the human work lives: "You can't just let the AI do the work — the editing, color correction, and sound mixing are where the human touch turns a clip into a story." The same pipeline thinking extends past video — her debut album *Fairytale* came out on a real label last year, lyrics written by her, music produced through Suno under her direction. The full breakdown is in [how Kelly Boesch built a studio of one](how-kelly-boesch-built-a-studio-of-one-with-ai/). "Not Made For The Cage," a 4K AI film by Kelly Boesch — @kellyeld2323 on YouTube, kellyboesch.com ## How does cursejourney get that found-footage look? Mike Chhay has been making cursejourney since August 2023: AI horror styled to look like photographs you weren't supposed to come across — demons, gods, and monsters rendered sepia-toned and grainy, like documentation instead of generation. The insight is that the "close but wrong" quality most people fight to remove is exactly what horror can use. His flagship series is literally called "photos i found in the basement." He publishes the pipeline on a public tools page, and it's seven tools deep for a single short. Midjourney generates the base image — "the AI image generator that has created the majority of my cursed old photo series," in his words. Before anything moves, Magnific upscales the still so the animation starts from a high-resolution frame — that's what keeps faces and details consistent. Photoshop handles cropping, color, and filters. Then Kling animates most shots — "the tool you want to use for the majority of the time" — with Seedance held back for "epic transformations and action scenes." Premiere assembles, Suno scores, ElevenLabs adds voice and sound, and Topaz upscales the finish to 4K — the same class of tool used to restore old blurry footage, which fits work meant to look dug up rather than made. The lineup keeps shifting (his 2024 pieces ran on Luma before Kling took over), and the one thing he keeps loose is the exact recipe for the aged sepia-grain look. That lives in the edit and the concept. It's worked well beyond the horror crowd, too — his animated "cursejourney cat" was selected for AIGA Arizona's Best of 2025, with over 140 million views on Instagram alone. The full breakdown is in [cursejourney makes AI horror that looks like found footage](cursejourney-ai-horror-found-footage/). "photos i found in the basement" — @cursejourney on YouTube, cursejourney.com ## How does The Archive In Between publish four stories a week? The Archive is a sci-fi, horror, and fantasy anthology — human-written stories paired with AI imagery, framed as transmissions from a library that sits between worlds. It runs across TikTok, Instagram, YouTube, Substack, Patreon, Discord, and Spotify, publishing around four stories a week, one of them long-form. That's a lot of finished narrative for a project run by one person — and it's the Curator's full-time income now, funded by readers through Patreon and book sales rather than ads. Their art is also the cover image on this piece. The labor split is the sharpest we've documented. Every story is human-written — no model drafts a sentence. "ChatGPT is the best thesaurus in the entire world. That is the extent of my use of AI in the writing." The imagery is the opposite: generated in volume, then ruthlessly culled. They describe that side of the work as sifting — picking the passable out of a mountain of output — and they refuse the word "artist" for it entirely: "The artistry comes across in the writing part of it." The perspective comes from experience on both sides. The Curator worked about four years as a professional illustrator and designer before generative tools arrived, and credits the project's traction to "50% luck in timing and 50% my perspective." The words are authored, the images are selected, and they keep that line deliberately unblurred. The full breakdown is in [the Curator behind The Archive In Between won't call the AI part art](the-curator-behind-the-archive-in-between-wont-call-the-ai-part-art/). "The Starfall Initiative" — @thearchiveinbetween on YouTube ## The pattern, if you're looking for one Read these processes side by side and the same shape keeps showing up. The work starts before the AI does — a script, a storyboard, years of writing, a trained eye. The generation step is a volume game everyone describes with mild exhaustion: 400 prompts, 150 generations, a mountain sifted for the passable. And the finish is old-fashioned post-production — editing, color, sound — which more than one of them names as the place the human touch actually lives. The tool names in these breakdowns will be stale within a year. I update them when the creators do. These five are a sample, not the whole shelf — every process we've pulled apart lives in the [Creator Stories](https://www.thedaringcreatives.com/creator-stories/) collection, and there are more coming. If there's a creator whose process you want deconstructed, I want to hear about it. ### The Frog Mage Makes Dark Fantasy Memes, Original Music, and Very Little Explanation of How URL: https://www.thedaringcreatives.com/creator-stories/frog-mage-dark-fantasy/ Last updated: 2026-08-16T10:25:06.000Z The Frog Mage is a dark fantasy content creator with a consistent premise: a frog wizard in a medieval world, rendered in enough detail that it functions less like a character concept and more like a universe. The account has over 375,000 followers on [Instagram](https://www.instagram.com/the%5Ffrog%5Fmage/?ref=thedaringcreatives.com) and individual TikTok videos clearing hundreds of thousands of likes. It's also a music project — original tracks on [Spotify](https://open.spotify.com/artist/3y17xiOrYQINqJBCC9Ko5w?ref=thedaringcreatives.com), Apple Music, and other streaming platforms under the same name. The whole operation runs under a parent brand called Not Sad Media. ## The music The tracks sit in a self-described genre of "arcane lofi, ancient melodies, and dark fantasy hymns." *Frostbite*, *The Realm*, *Dreamweaver*, *Mistmaker* — the titles read like chapter headings from the same book the visual content is building. *Frostbite* has cleared over 22,000 streams on Spotify, which is real traction for an account primarily known for short-form visual work. The [YouTube channel](https://www.youtube.com/@TheFrogMage?ref=thedaringcreatives.com) carries official music videos — full animated narratives, not lyric cards. Each one extends the world the Instagram and TikTok posts establish. The Frog Mage — "Frostbite," official music video on YouTube The collab record shows up on *Hide & Seek*, which features a character called Emo Bot 9000\. Emo Bot 9000 also appears on the Not Sad Media merch line — so either a separate creator or a project alias that's been given enough of its own presence to show up on a hoodie. The Frog Mage — "Hide & Seek" ft. Emo Bot 9000, on YouTube ## The content side The short-form work on Instagram and TikTok is where the audience found them. These are meme-format posts set inside the frog mage's world — humor running through a consistent lore rather than floating free of it. *Rain Dance* is a good example: a short narrative reel where the frog mage gets summoned to break a drought, with a full quest arc compressed into a couple of minutes. > [View on Instagram](https://www.instagram.com/reel/C-Im4Rrp707/?ref=thedaringcreatives.com) The Frog Mage — "Rain Dance," on Instagram The character design holds across both the short-form posts and the full music video productions. Same frog, same world, same visual language — whether the format is a quick meme or a multi-minute animated story. That consistency across formats is the thing that makes it feel like a universe rather than a channel. ## Is The Frog Mage AI? The one AI tool The Frog Mage has publicly attached to their name is Runway. Their [Linktree](https://linktr.ee/notsadmedia?ref=thedaringcreatives.com) lists a Runway affiliate partnership — a 25% discount code, which is about as close to "I use this tool" as a creator gets without writing a breakdown. On Threads, people who follow the account have noted the AI involvement in the visual work. The creator hasn't published any detailed account of their pipeline. That's not unusual. A lot of creators who build a commercial operation around AI-assisted work keep the specifics quiet. What's publicly visible points at Runway for video, with the rest of the stack undisclosed. Disclosed tools - [Runway](https://runwayml.com/?ref=thedaringcreatives.com) — confirmed via Linktree affiliate partnership (25% discount code) Only tools the creator has publicly credited. The broader visual and production stack hasn't been described. ## Not Sad Media Underneath the content operation is [Not Sad Media](https://www.notsadmedia.com/?ref=thedaringcreatives.com), the brand running the back office. Music goes through DistroKid to streaming platforms. Merch runs through Etsy — t-shirts, stickers, and plushes for both the frog mage and Emo Bot 9000\. Custom dark fantasy pet portrait commissions are also live: someone's actual pet, rendered into the frog mage's world. The\_frog\_mage on Instagram is the front door. Not Sad Media is the store, the label, and the studio. It's a fuller creative operation than most accounts at that follower count — music distribution, active commission work, merch that spans two characters, and video production that runs from meme-length to proper music video. The process behind it hasn't been written up anywhere. What's been built, though, is visible. ### Caspar Jade Posted a Fictional Person Every Day for 15 Months URL: https://www.thedaringcreatives.com/creator-stories/caspar-jade-fictional-portraits/ Last updated: 2026-08-01T19:42:02.000Z Caspar Jade makes AI portraits that read like editorial photography — cinematic, narrative, built around a face. The tagline on [his site](https://www.casparjade.com/about?ref=thedaringcreatives.com) reads: "All images are AI generated. But the emotions they create are real." And his most obsessive project, [The Unreal People](https://www.theunrealpeople.com/about?ref=thedaringcreatives.com), pushed that idea to 471 portraits: a new fictional person every day from March 2024 to June 2025, each with a first-person life story — a 36-year-old Australian footballer facing retirement, a 69-year-old Ankara shopkeeper watching inflation eat her shop. None of them exist. Caspar Jade — "Becoming Leaf," on Instagram ## Two names, never mixed Caspar Jade is the alias of Hannes Caspar, a portrait photographer based in Berlin. Per [his agency](https://easydoesit.de/talents/caspar-jade?ref=thedaringcreatives.com), he spent 16 years photographing people from film, music, and fashion, shooting covers for Stern, Die Zeit, and Playboy, plus album covers for artists like Namika and Yvonne Catterfeld. That's the craft underneath the AI work — he was directing faces and light for magazines long before a model could render them. When he launched the alias in July 2023, he explained the split in the announcement post on his photography account: "I think that AI images and real images should never mix, that's why I separate it with two different names and accounts. I still enjoy shoots a lot. There is no substitute for the intimate collaboration with people." He's kept that firewall since — two names, two portfolios, two Instagram accounts. The AI one, @caspar.jade, has grown to 238K followers. Hannes Caspar — the 2023 post announcing his Caspar Jade alter ego, on Instagram ## 471 people who never existed The Unreal People ran as a daily blog: one photorealistic portrait, one short first-person story "completed with the help of artificial intelligence," as the site puts it. Each character comes from a different country — the image files are literally named turkey.jpg, finnland.jpg, chad.jpg. The project's stated point is the mirror it holds up: "None of it is real. And yet, it holds up a mirror to us. It invites reflection on identity: Who are we? What defines us?" It also became a science collaboration — the site partnered with the AFC Lab of cognitive neuroscientist Prof. Dr. Meike Ramon, whose research focuses on how we visually process and recognize faces. Fictional faces that fool people daily turn out to be useful to someone studying exactly that. What the run gave him personally, [he told L'Officiel Monaco](https://lofficielmonaco.com/art-culture/caspar-jade-blending-art-technology-and-storytelling?ref=thedaringcreatives.com): "Even though the project has something grotesque and provocative about it, I immerse myself in other realities and learn a lot about our world and different cultures… It teaches empathy and makes me realize again and again how incredibly privileged we are in the Western world." The daily streak stopped in June 2025, with no announcement — the archive just ends at portrait number 471. ## Decisions, not prompts His description of the actual work is the least mystical explanation of AI art you'll find: "It is the computer that generates the images, but I make the many small decisions that have significant impact on the effect of an image." He's never named his generator on his own pages. His site's image files tell on him a little, though — the gallery uploads carry raw Midjourney output filenames, prompt fragments intact, and they read like a photographer typing: "Fashion Photography of woman…", "Polaroid of a woman wearing clothes made entirely of…", "Pinhole portrait photography of a bizarre haunting eerie…" The prompts are camera language. His sharpest observation is about what the tools do to everyone using them, [from the MOD Magazine interview](https://modmagazine.com/ai-in-fashion-caspar-jade-exclusive-interview/?ref=thedaringcreatives.com): "It is the algorithms of the respective tools that dictate an aesthetic direction, which means that the images resemble each other regardless of who generated them. It is more difficult than in photography to express oneself individually. But it is definitely possible!" Caspar Jade — "Flowers Without Flowers," on Instagram ## The photographer's bet on photography For someone this deep into generated portraits, his prediction for the real kind is generous: "In individual portrait photography, not so much will change. I think there will even be a countermovement, the real and authentic will get a special value again." The AI work keeps compounding anyway. He showed in the AI Creative Showcase at London's Cluster Photography & Print Fair in April 2025, shot an AI cover story for MOD Magazine, and his Inner Bloom series — motion-filled fine-art portraits, wind and fabric everywhere — got a 24-image feature this past February. And the photography career keeps running next door under his real name, exactly as he set it up: two names, never mixed. Caspar Jade — "Passing Through," on Instagram ### Tropland Universe Runs a Circus Where No Animal Is Real URL: https://www.thedaringcreatives.com/creator-stories/tropland-universe-circus/ Last updated: 2026-08-16T10:25:06.000Z Tropland Universe posts photoreal lions, tigers, and jaguars doing things no animal could ever safely do — riding high wires, embracing ringmasters, headlining a circus — and every caption tells you the same two things: the animals are AI, and that's the point. The current era of the account is a serialized "Digital Animal Circus," and the caption formula repeats like a ritual: "No real animals were used in the performance. My videos are made with the help of AI," followed by a bolded line that no animal should ever be subjected to cruelty. It's the project of Josh Gottsegen, an LA-based creative director who's been building this world since before image generators existed. His verified Instagram has passed 1.2 million followers and is still climbing, and Feedspot's list of top AI artist influencers has ranked him number one two years running. His site puts the full picture at 3.5 million followers across fifty countries and 2 billion content views — with a single video, a lion couple's wake-up call, accounting for 267 million of them. Tropland Universe — a Digital Animal Circus performance, on Instagram ## It started as a juice bar book The Tropland IP predates the AI wave by nearly a decade. Gottsegen wrote Joosh's Juice Bar, a children's picture-book series set in Tropland Forest, starting in the early 2010s — his site dates the IP to 2013\. Then came The Adventures of Rockford T. Honeypot, a middle-grade novel about a bookish chipmunk, published in June 2020\. In [an interview from that book's release](https://mamasgeeky.com/2020/07/rockford-t-honeypot-author-josh-gottsegen.html?ref=thedaringcreatives.com), he described the grind plainly: "From start to finish, it took four years. In between my real job of running my own creative / marketing company, it took about two years to complete the first draft." He also wrote it chapter-by-chapter for a close friend recovering in the hospital, which tells you something about how he relates to this universe — it was never a content play first. Tropland Universe — "Out on a Limb," a Rockford T. Honeypot short film, on YouTube ## The books gave the AI something to render When generative tools arrived, he didn't start from zero — he started from a fictional world with ten years of characters and settings. He was generating Tropland concept art with Midjourney as far back as 2022, telling [LA Wire](https://lawire.com/onelight-studios-takes-viewers-on-an-adventure-through-ai-art-to-the-magical-and-vibrant-tropland-universe/?ref=thedaringcreatives.com) at the time: "Combining my previous stories with current projects in development, I can explore new levels of storytelling and get real-time feedback across social media. The Spirit Realm opens magical doors that didn't exist in my previous books but are very much a part of Tropland." The current circus reels carry a fresher tool credit: they tag Dreamina, ByteDance's AI creative suite, where he's part of the creator-partner program. His [founder page](https://www.troplanduniverse.com/llm/founder?ref=thedaringcreatives.com) says he's collaborated with Meta, Adobe, OpenAI, Sora, Kling, and Topaz Labs — his claims, but consistent with a generate-upscale-edit video pipeline. What he emphasizes everywhere is the human layer: his brand-safety page states that Tropland "does not generate content autonomously" and that every piece runs through deliberate choices about narrative, composition, and emotional tone. Tropland Universe — "The Greatest Illusion in the Universe," on Instagram ## Run like an IP business, not a feed This is the part most AI accounts don't have. Tropland has a licensing agency (All-American Licensing), a claimed library of over 50,000 visual assets ready for consumer products and apparel, a [Patreon](https://www.patreon.com/TroplandUniverse?ref=thedaringcreatives.com) where members vote on where the story goes next, and a published brand-safety doctrine that rules out shock content and misleading AI claims — "Long-term IP integrity prioritized over viral reach," in his site's words. He even publishes an llms.txt documentation suite for AI crawlers, which might make him the first AI artist optimizing his press kit for the machines that will summarize him. The animal-welfare framing doubles as the brand's heart. From one of his own captions in June: "Making these videos brings me joy. Every act in the Tropland circus, and not one animal caged, trained, or harmed." Tropland Universe — photoreal lion stills, image post on Instagram ## Where it's pointed The stated ambition hasn't changed since 2022: "I plan to expand my creative output utilizing AI art to assist in developing my future books, animated television series, and film storylines. It's been a dream for many years, and I feel I'm getting closer." An animated Rockford series was reported in development back in 2023; the short film above is the proof-of-concept that already exists. Meanwhile the circus keeps adding acts — a new impossible performance every few days, each one disclosed, each one harmless by design. ### PJ Ace Made an NBA Finals Ad for $2,000 and Published the Prompts URL: https://www.thedaringcreatives.com/creator-stories/pj-ace-nba-finals-ad/ Last updated: 2026-08-16T10:25:07.000Z PJ Ace is the AI filmmaker behind the ad most people point to when they argue about whether AI commercials are actually here: the unhinged Kalshi spot that aired during Game 3 of the 2025 NBA Finals. Made with Google's Veo 3 for [about $2,000 in AI production costs](https://www.npr.org/2025/06/23/nx-s1-5432712/ai-video-ad-kalshi-advertising-nba-finals?ref=thedaringcreatives.com), idea to on-air in two to three days, working mostly alone. Within a week it had over 3 million views on Kalshi's X account. The part that makes him worth profiling is what he did next: he posted the whole recipe. PJ Ace — the Kalshi NBA Finals ad, on his YouTube channel ## The workflow, in his own words PJ Ace is PJ Accetturo, a director with 15-plus years in commercials and TV before AI tools showed up — Toyota, Red Bull, the Atlanta Braves, and co-creating the animated series Ghosts of Ruin. After the Kalshi ad aired, he broke down the process in an [X thread](https://x.com/PJaccetturo/status/1932893260399456513?ref=thedaringcreatives.com) that NPR and Business Insider both picked apart. The script comes first, co-written with an LLM: "I co-write with Gemini (or ChatGPT) asking it for ideas, picking the best ones, and shaping them into a simple script." For Kalshi, the client handed him lines of dialogue they wanted included, and he invented the characters to say them. Then the script becomes prompts — with a constraint he's specific about: "I always tell it to return 5 prompts at a time — any more than that and the quality starts to slip." Each prompt describes its scene completely, as if Veo has no memory of the shot before or after it, which is what keeps characters and settings consistent. Then volume. "This took about 300–400 generations to get 15 usable clips." When a generation misses, the prompt goes back into Gemini with a request for changes. The final edit and music happen in ordinary editing software. PJ Ace — his behind-the-scenes breakdown of the Kalshi ad, on YouTube ## The $500 spec ad that started it Three weeks before Kalshi, he posted Puppramin — a fake pharmaceutical commercial for a pill that summons puppies. His caption on it, from [the X post](https://x.com/PJaccetturo/status/1925464847900352590?ref=thedaringcreatives.com): "I used to shoot $500k pharmaceutical commercials. I made this for $500 in Veo 3 credits in less than a day. What's the argument for spending $500K now?" That's the spec ad that reportedly got Kalshi's attention. But he pushes back on the idea that cheap means easy — "Just because this was cheap doesn't mean anyone can do it. I've been a director 15+ years." His take on where the leverage moved, [via PetaPixel](https://petapixel.com/2025/06/12/the-most-unhinged-ai-generated-gambling-ad-ran-during-the-nba-finals/?ref=thedaringcreatives.com): "Right now the most valuable skill in entertainment and advertising is comedy writing." PJ Ace — "Puppramin," the pre-Kalshi spec ad, on YouTube ## Now it's an agency He runs Genre AI, an AI-native ad agency built as "pods" of writers, directors, cinematographers, and editors with traditional film backgrounds. Per [an interview with The brAIn](https://themediabrain.substack.com/p/ais-disruption-of-advertising-and), the client list grew to Popeyes, Qatar Airways, Oracle, and David Beckham's supplement brand IM8\. The Popeyes job was an AI diss-track ad answering McDonald's Snack Wrap relaunch, built in about three days with Veo 3 and Suno. The Qatar Airways job is the one that shows how far the workflow has evolved past "prompt and pray." Per [his own case study](https://pjace.beehiiv.com/p/qatar-airways?ref=thedaringcreatives.com), he made two ads in 14 hours aboard a live flight: reference photography of the real cabin ("CRITICAL in getting near-perfect details"), shots laid out in Figma, characters composited into base frames with Nano Banana over dozens of iterations, animation in Veo 3.1 — "Simple prompts work best" — and a Suno music bed that human musicians then customized. "Sky Studio: Above the Clouds," made by PJ Ace's team — via Qatar Airways' official YouTube channel The PJ Ace stack — tools he credits himself - [Gemini](https://gemini.google.com/?ref=thedaringcreatives.com) / [ChatGPT](https://openai.com/chatgpt/?ref=thedaringcreatives.com) — script co-writing, then converting shots into prompts (5 at a time) - [Veo 3 / 3.1](https://deepmind.google/models/veo/?ref=thedaringcreatives.com) — video generation, hundreds of takes per spot - **Nano Banana** — compositing characters into base shots (Qatar Airways workflow) - [Figma](https://www.figma.com/?ref=thedaringcreatives.com) — shot layout - [Suno](https://suno.com/?ref=thedaringcreatives.com) — first-pass music beds, refined by human musicians - [After Effects](https://www.adobe.com/products/aftereffects.html?ref=thedaringcreatives.com) — transitions and finishing - **Seedance 2.0** and [Kling](https://www.klingai.com/?ref=thedaringcreatives.com) — the newer additions, per his 2026 newsletter guides From his own X threads and newsletter case studies. Nano Banana and Seedance left unlinked pending confirmed official URLs. ## What he says no to He turned down a Super Bowl ad for a big brand because they wanted a tearjerker, and in his view the models can't deliver one yet — "AI is not meant for every campaign." The line from the same interview that sums up his position on why experienced directors aren't obsolete: "We cannot teach taste in a day." He keeps publishing, though. The prompts, the budgets, the workflow changes — all of it lands in [his newsletter](https://pjace.beehiiv.com/?ref=thedaringcreatives.com), most recently guides to Seedance 2.0\. For anyone building things with AI video, it's one of the few places where a working director shows the receipts while the work is still shipping. ### imoliver Writes the Words and Generates the Rest URL: https://www.thedaringcreatives.com/creator-stories/imoliver-suno-songwriter/ Last updated: 2026-08-16T10:25:07.000Z imoliver makes indie-pop, electro-soul, and the occasional country-rap track, and he'll tell you up front what he can't do. "I have no musical talent at all. I can't sing, I can't play instruments, and I have no musical background at all," he told the [Associated Press](https://apnews.com/article/artificial-intelligence-ai-music-suno-udio-551308748c84c774c3c5ecd89aa93904?ref=thedaringcreatives.com). What he does have: his own lyrics, a visual design background, and enough patience to generate a hundred versions of a song before one feels right. In July 2025 that combination made him the first person a traditional record label ever signed for making music with an AI platform. Hallwood Media — the company run by former Geffen Records president Neil Jacobson — announced the deal and billed him as [the most-streamed creator on Suno](https://www.hollywoodreporter.com/music/music-industry-news/hallwood-inks-record-deal-ai-music-designer-imoliver-1236328964/?ref=thedaringcreatives.com). His single "Stone" had over 3 million plays on the platform when the deal landed. The industry term Hallwood invented for the job: "AI music designer." imoliver — "Stone," official video on YouTube ## The lyrics stay human imoliver is Oliver McCann, 37, from the UK, and his path into this was a designer's, not a musician's. Per the AP, he started experimenting with AI to see if it could boost his creativity and "bring some of my lyrics to life" — the words existed before the tool did. He keeps writing them himself for a practical reason, not a sentimental one: "AI lyrics tend to come out quite cliche and quite boring." So the split is clean. He writes the words, then uses Suno to shape them into songs — his own site describes it as "making AI music as a craft, not slop." He also directs his own videos and handles his own marketing, per his [press kit](https://imoliver.com/press?ref=thedaringcreatives.com). imoliver — "Can You Feel It," from the album "Io," on YouTube ## A hundred takes per song The most concrete process detail on record comes from that AP feature: McCann will often create up to 100 different versions of a song, prompting and re-prompting before he's satisfied. That's the job — not typing "write me a hit" once, but generating, listening, rejecting, adjusting, and generating again until the take exists. Anyone who's iterated on AI images knows exactly this loop; he's running it on audio. Jacobson's pitch for why that's worth a record deal: "He's a music designer who stands at the intersection of craftwork and taste. As we share his journey, the world will see the dexterity behind his work and what makes it so special." McCann's own read on the moment, from the [signing announcement](https://www.musicradar.com/music-tech/a-huge-moment-not-just-for-me-but-for-the-future-of-music-ai-creator-signs-record-deal-with-hallwood-media?ref=thedaringcreatives.com): "Signing with Hallwood is a huge moment, not just for me, but for the future of music. It's a sign the industry is ready to embrace new ideas and new ways of creating. This isn't about replacing artists, it's about expanding what's possible." imoliver — "Stone," on Spotify ## What shipped since Hallwood re-released "Stone" on all platforms on August 8, 2025, and the debut album "Io" followed on October 24 — 16 tracks, a mix of reimagined older songs and new ones. Singles kept arriving between the two: "Waiting for the Weekend" in September, "Bury Me with My Phone" in October. His [Suno profile](https://suno.com/@imoliver?ref=thedaringcreatives.com) stays active alongside the label releases; the press kit's running counters put his total streams there past 7.8 million. imoliver — "Waiting For The Weekend," official video on YouTube Where he thinks it goes, from the same AP interview: "I think we're entering a world where anyone, anywhere could make the next big hit… As AI becomes more widely accepted among people as a musical art form, I think it opens up the possibility for AI music to be featured in charts." He said that in August 2025\. By November, another Suno-built act — Xania Monet, whose process we've also profiled — was on a Billboard radio chart. The world he described showed up fast. ### How Xania Monet's Music Actually Gets Made URL: https://www.thedaringcreatives.com/creator-stories/xania-monet-music-made/ Last updated: 2026-08-16T10:25:08.000Z Xania Monet is an R&B singer with Billboard chart entries, a debut album on a real label, and a reported multimillion-dollar deal behind her. She is also generated — the voice, the face, all of it. The songs start with Telisha "Nikki" Jones, a poet from Mississippi who writes every lyric herself and has been doing it since she was 24. The run happened fast. In September 2025, "How Was I Supposed to Know" hit No. 1 on Billboard's [R&B Digital Song Sales chart](https://www.billboard.com/pro/ai-music-artist-xania-monet-multimillion-dollar-record-deal/?ref=thedaringcreatives.com), with the catalog pulling around 9.8 million U.S. on-demand streams. Then in November the same song debuted at No. 30 on Adult R&B Airplay — [Billboard called it](https://www.billboard.com/music/chart-beat/ai-artist-xania-monet-debut-adult-rb-airplay-chart-1236102665/?ref=thedaringcreatives.com) "the first known instance of an AI-based act to earn a spot on a Billboard radio chart," with 15 of the panel's 57 stations playing it. In between, Hallwood Media — run by former Interscope executive Neil Jacobson — signed her after a bidding war Billboard reported reached $3 million. Xania Monet — "How Was I Supposed to Know?", official video on YouTube ## The poems come first Jones revealed herself as the person behind Xania Monet in a [CBS Mornings interview](https://www.cbsnews.com/news/meet-the-woman-behind-chart-topping-ai-artist-xania-monet-i-look-at-her-as-a-real-person/?ref=thedaringcreatives.com) with Gayle King in November 2025, and she walked through the process plainly. "I scroll through my list of poems to see which one I want to turn into a song. Then I put the lyrics into an A.I. music generator, add prompts like 'slow tempo R&B,' 'female soulful vocals,' 'light guitar,' and 'heavy drums,' and then I just click create." The generator is Suno. The poems are hers — a collection she's been building for years, most of it autobiographical. "Whether it was stuff I went through, a close family member, or a close friend, I wrote about it," she told CBS. "How Was I Supposed to Know" came out of losing her father when she was eight. Her manager, Romel Murphy, told Billboard that 90% of the lyrics are her own true stories. That division of labor is written into the paperwork, too: Billboard reported Jones retains full songwriting and production credits on the album. Xania Monet — "The Things I Didn't Say" (Hallwood, 2026), on Spotify ## Building a singer who isn't there Jones is 31, runs a design studio out of Olive Branch, Mississippi, and according to [MS NOW's reporting](https://www.ms.now/opinion/msnbc-opinion/xania-monet-ai-song-telisha-jones-billboard-hit-rcna242478?ref=thedaringcreatives.com) taught herself the toolchain — CapCut and fal.ai for the visual persona, Suno for the music — roughly four months before the song broke. She's not a singer, and she's never pretended the voice is hers. What she pushes back on is the idea that the persona makes it fake. "Xania is an extension of me, so I look at her as a real person," she told CBS. And on the technology itself: "I just feel like AI… it's the new era that we're in. And I look at it as a tool, as an instrument, and utilize it." Xania Monet — "Unfolded" (2025), the breakout album, on Spotify ## The pushback Not everyone was fine with it. Kehlani, in a since-deleted TikTok [reported by Forbes](https://www.forbes.com/sites/conormurray/2025/11/05/creator-behind-billboard-charting-ai-artist-xania-monet-defends-her-music-against-backlash-from-kehlani-and-more/?ref=thedaringcreatives.com), said nothing could justify AI to her, pointing at models trained on uncredited copyrighted work. The major labels mostly sat out the bidding war for the same reason — the copyright suits against Suno are still pending. Jones didn't swing back. "Everyone is entitled to their own opinion," she said on CBS. "Technology is evolving. Everybody has different ways of putting in the work to get to where they're at. I don't feel a way about it. I still love Kehlani's music. I still listen to her music every day." Telisha Jones on building Xania Monet — interview via CBS Mornings, on YouTube ## Where it stands The Hallwood debut, "The Things I Didn't Say," landed January 9, 2026 — 21 tracks, all of them starting the same way everything else in the catalog started: a poem in Jones's collection, picked out, pasted in, and prompted into a song. The notebook is still doing the writing. ### The Archive In Between Won't Call the AI Part "Art" URL: https://www.thedaringcreatives.com/creator-stories/archive-in-between-ai-art/ Last updated: 2026-08-16T10:25:08.000Z Most people who make images with AI reach for the word "artist" pretty quickly. The person running The Archive In Between goes the other way. They stay anonymous, sign everything as the "Head Curator," and when the subject of artistry comes up, they draw a hard line down the middle of their own work: the writing is theirs, the images are curated. "I would never attach the title of 'artist' to myself as it relates to the use of AI," they told The Daily Egg — in what is, as far as I can find, the only interview they have ever given. That's worth pausing on. This is a project with 145,000 YouTube subscribers, roughly 394,000 on TikTok, hundreds of thousands more on Instagram, and a five-thousand-member Discord — and the person behind it has spoken to the press exactly once in four years. The channel description carries their whole public position in one standing sentence: "All images are created with digital illustration and AI, and all words are written by a human hand." The Archive is a sci-fi, horror, and fantasy anthology — human-written stories paired with AI-generated imagery, all framed as transmissions from a library that sits between worlds. Stories arrive as carousels, short videos, and long-form pieces, stitched into one interconnected universe across TikTok, Instagram, YouTube, Substack, Patreon, and Discord. "The Starfall Initiative," the Archive's newest long-form story — @thearchiveinbetween on YouTube ## It started with propaganda posters about aliens The Archive began in late 2022 — the YouTube channel was created December 17, the Patreon two days later — and TikTok came first: "TikTok is where I first started posting because I thought it was a better platform at the time." The first story is a nice little time capsule of the era. "My very first story used Stable Diffusion to generate these images that looked like old 50s-style retro posters. Then I went into Photoshop and added captions to these posters, and it was a series about aliens coming to Earth through the lens of propaganda posters. The first two posters said not to trust these things, like 'Vote against the first contact authorization act, don't engage.' Then the next two said, 'They're here to help: let them help us.'" The library frame came from a practical problem: a drawer full of unrelated stories. "I had all these little stories written down, and I did not want to box myself into one genre. So I had to create a narrative structure that would allow for all of those stories to exist without feeling completely disorganized. Then the idea came to me that, 'Hey, what if there was this library that sat in the middle of all these universes?'" They describe the moment physically: "I remember sitting in my garden, and I felt like I got hit by a lightning bolt when I thought, 'This is it.'" ## The library between worlds The frame does real work, and four years in it has grown into a genuine mythology. The Archive is a great library residing in the space between dimensions, run by the Head Curator. Every story is a document pulled from its shelves, tagged with an alphanumeric annex code — our own baseline universe is A-0001A, and the further a code drifts from it, the stranger the universe it points to. Around that spine sit recurring factions. The Pale Lodge — interdimensional adventurers broadcasting safety PSAs from a white stone citadel, whose "Stride safe folks!" sign-off recurs across the Shorts. The Patchwork City Visitation Authority, issuing educational transmissions from a pocket-dimension metropolis. The Interloper Repellent Brigade, running in-world recruitment ads. Entities like the Rain Walkers — mirage-giants on the horizon — and gods inverted by "aspect decay." Fans maintain a whole wiki cataloging it, filed in the analog-horror lineage of Local 58 with a strong dose of SCP-style catalog fiction. "The Starfall Initiative," the long-form that went up this week, shows the current shape of the machine: a researcher's account from Annex B-9619U, free on YouTube — with its sequel, "The Cost of War," waiting on Patreon. Free story, paid continuation. That funnel is the business model in miniature. "The Day AI Took Over" — @thearchiveinbetween on YouTube ## Four stories a week, written by hand The part of the process the Curator will claim is the prose, and it's all theirs. "The writing is 100% human-done. I write every word myself. I will say though, ChatGPT is the best thesaurus in the entire world. That is the extent of my use of AI in the writing." The cadence is fixed and self-imposed: "I just have to post four stories a week. I have to post one long-form story per week. If I'm rocking it, I get those done a week in advance." Before a vacation: "I will lock myself in my office and not come out for five days straight, hammering these things out." The ideas come from somewhere deliberately analog. "I truly think that your best resource is your own lived experience," they said, along with a habit of getting to places without cell reception. "Learning how to look at what's in front of you, even if it's just outside your front door, and twisting it from a slightly different perspective, is invaluable." ## Script first, then images, then layout The pipeline never starts with a generation. "I always start with the script, and then I create the images after that. I drop it all into a Google Slide. Then I pull it all into InDesign and do the actual design, make sure the text is aligned properly so it's sitting nicely within the image and it's not obscuring the subject of the image." A carousel takes two and a half to five hours; a video runs one to two, because "the editing workflow on Premiere is a bit easier than what I do in InDesign." The image tool has changed over the years. They ran Stable Diffusion for a long time, and their explanation for leaving is the most businesslike tool review you'll read: "Stable Diffusion took a bit of a shit as a business. They didn't monetize... They stopped maintaining their website. They stopped adding new models. It wasn't working for me anymore, so I moved over to Midjourney." The turning point on the new tool was specific: "There's a feature called SREF Codes. The minute I learned to use those was the minute I figured out how to use Midjourney." The newest videos carry a fuller credit line — "The Starfall Initiative" discloses it was made with Midjourney, ElevenLabs, Runway, Adobe Audition, and Premiere. That answers a question I had going in: the narration on the videos is an ElevenLabs voice, not the Curator's own. There's an audio side to the world, too — an in-universe ambient music series called Interdimensional Radio, plus a curated "Auditory Annex" playlist on Spotify. The Archive's stack — tools they credit themselves - [Midjourney](https://www.midjourney.com/?ref=thedaringcreatives.com) — imagery (switched from Stable Diffusion; SREF codes were the unlock) - [ChatGPT](https://chatgpt.com/?ref=thedaringcreatives.com) — "the best thesaurus in the entire world" — the full extent of AI in the writing - [InDesign](https://www.adobe.com/products/indesign.html?ref=thedaringcreatives.com) — carousel layout (staged first in Google Slides) - [ElevenLabs](https://elevenlabs.io/?ref=thedaringcreatives.com) — video narration - [Runway](https://runwayml.com/?ref=thedaringcreatives.com) — motion - [Audition](https://www.adobe.com/products/audition.html?ref=thedaringcreatives.com) \+ [Premiere](https://www.adobe.com/products/premiere.html?ref=thedaringcreatives.com) — audio post and edit From the Daily Egg interview and the credit line on "The Starfall Initiative." ## "Less like an artist and more like a curator" The stance that gives this profile its title is not a throwaway line — they've reasoned it through. On generating: "When I use AI, I feel less like an artist and more like a curator. It's like I'm sifting through shit because there's a lot of it and I'm picking out what looks passable and enhances the storytelling." Their cleanest version of the argument involves a kitten: "I made no conscious choice that this kitten is an orange tabby, a gray tabby, a tuxedo cat, and a black cat. I didn't choose what the rug looks like... There is a level of decision-making that is not happening." And then, in the same conversation, the counterweight — because this isn't someone dismissing craft: "While I stand by not really viewing myself as an artist for creating AI imagery, I would be remiss not to mention that one of the reasons I've been able to create pretty compelling imagery is because I have an informed background as an artist. I know the language." ## The illustrator behind the Curator That background is professional. Before the Archive, they spent about four years as an illustrator and designer at a digital marketing agency, plus a stretch at a Southern California apparel company. When generative imagery arrived, they watched it go from joke to threat in real time: "Everybody was making those awful little images of, like, Will Smith eating spaghetti... It was such a joke. And then all of a sudden it wasn't." The response was characteristic: "I thought this could be an existential threat, as an illustrator. But I wouldn't be doing my job as an artist or as an entrepreneur if I didn't investigate this technology before I cast judgment upon it." Asked why the project worked, they split the credit evenly: "I think it's 50% luck in timing and 50% my perspective. I was really lucky to be one of the first people that did it. The space is saturated now." And beneath the entrepreneur read, something simpler: "I never lost that little kid in me who was trying to play make-believe. He slept for a while, but he was always there." ## Reader-funded, and full-time The Archive pays the bills, and it does it without ads. Ranked in their own words: "Patreon. Purely by the fact that it's more familiar to most people than Substack right now. I was a little late to the Substack game. Behind that is direct sales. I sell collected volumes of these short stories and expanded versions in these books... I use Amazon as a print publisher because people really want paperbacks." The Patreon — running since December 2022, starting at $2 a month — carries exclusive stories in print and audio, wallpapers, and behind-the-scenes material, with a little over two thousand paying members by public tracker estimates. The catalog now includes two print Compendium volumes (April and November 2023), eBooks sold directly, and — the part I didn't expect — a solo tabletop RPG: the "Deep Space Explorer Handbook & Mission Log," which turns the universe into something you can play alone. There's a gift shop with a Pale Lodge collection and an in-world poster series. It replaced a career, though not instantly: "I'm not making as much as I was when I worked in marketing. But I am steadily climbing back towards that." The freelance clients got let go — with an exception "for close friends or people who want to pay me, like, a lot of money." The pricing philosophy gets stated with unusual care: "I'm still finding the right balance because I don't want to box people out. I don't want the people who have been loyal readers, but for whatever reason can't afford it, to feel like they're left out. But I need to meet my needs, and I need to grow as a storyteller." > [@thearchiveinbetween](https://www.tiktok.com/@thearchiveinbetween?refer=embed&ref=thedaringcreatives.com "@thearchiveinbetween") Announcing Volume 1 of the Archive Compendium — @thearchiveinbetween on TikTok ## One interview in four years For an operation this size, the public record is strikingly small. The Daily Egg interview — granted on condition of anonymity — is the entire press footprint. No podcasts, no AMAs, no follow-ups. The interviewer reportedly approached other AI creators who all declined; the Curator was the one who said yes, once, and then went back to posting. What fills the space instead is the community: the fan-maintained lore wiki, the Discord, a fan-compiled ambient playlist. The Curator declines to be a spokesperson even when handed the microphone: "I refuse to speak for the rest of the people making this kind of content." The advice they do offer is the least gatekept version possible: "YouTube is the best thing. YouTube and Reddit. You can learn almost anything you want using those two platforms." Four years in, the machine keeps its rhythm — four stories a week, one long-form, 347 videos and counting, every one of them carrying the same standing sentence about human words and generated images. "I have big, big dreams for this," they told their one interviewer. "I have a vision for this that extends beyond posting stories on Instagram." For an adjacent register of AI horror built on a completely different bet — leaning into the machine's errors instead of curating past them — see [our cursejourney deconstruction](https://www.thedaringcreatives.com/creator-stories/cursejourney-ai-horror-found-footage/). The Archive's own transmissions are at [thearchiveinbetween.com](https://www.thearchiveinbetween.com/?ref=thedaringcreatives.com), the long-form stories on [their Substack](https://thearchiveinbetween.substack.com/), and the reporting here draws throughout on ["The Honest AI Artist" in The Daily Egg](https://thedailyegg.substack.com/p/the-honest-ai-artist). ### daejin.creates Makes AI Art That Goes Inward URL: https://www.thedaringcreatives.com/creator-stories/daejin-creates-ai-art/ Last updated: 2026-08-01T19:42:03.000Z Scroll through AI art long enough and the patterns become familiar: photorealistic faces, cinematic landscapes, fever-dream composites. daejin.creates is doing something different. The Korean artist describes their practice as "Design × Psychology × AI" — and that framing, design as the method and psychology as the material, isn't how most AI artists talk about what they're doing. They work across [Instagram](https://www.instagram.com/daejin.creates/?ref=thedaringcreatives.com) and [Threads](https://www.threads.com/@daejin.creates?ref=thedaringcreatives.com), and lately the work is as much AI *video* as it is still image — short, quiet motion pieces built with tools like Dreamina and Seedance, often starting from a frame composed in Midjourney. The output feels less like a demonstration of what a model can do and more like an ongoing inquiry into interiority — how we carry emotion, how identity shifts, what happens in the space between a feeling and a form. daejin.creates — "The Traveler of Afterimages," stills built in Midjourney 8.2 and animated with Dreamina ## Design × Psychology × AI The framework is precise even if the images are open. Design provides the structure — intentional composition, a sense of craft in how each piece is built. Psychology provides the subject matter — the inner life, the nonlinear experience of being a person. AI gives daejin a way to picture things that resist ordinary images: a state of mind that doesn't have a visual precedent, a mood that evaporates the moment you try to describe it directly. You can feel that intent in a single frame. One recent piece sets a figure in headphones inside a swirling tunnel of light and reflection, under a line the artist wrote: "When the world's noise fades, my own voice becomes clear." It's a picture of a feeling most people only have words for — and a lot of AI artists lead with the tool instead, what it can do, how far they pushed it. daejin.creates seems more interested in the question the tool is being used to ask. daejin.creates — "When the world's noise fades, my own voice becomes clear." ## From a Still to a Moving Image You can usually reconstruct daejin's process from the posts themselves. The still comes first — composed in Midjourney, where the framing, palette, and mood get locked. Then the image is set in motion with an AI video tool, most often Dreamina or Seedance, turning a fixed portrait into a few seconds of drifting, breathing footage. A recent piece all but named the effect — "The Traveler of Afterimages" — a title that doubles as a description of the method: an image that keeps moving after you'd expect it to stop. That two-step is where the *design* in "Design × Psychology × AI" shows up. The motion is never busy. A figure holds still while the world behind them turns; light shifts across a face; a scene settles rather than performs. In a medium that mostly rewards spectacle, the restraint is the craft. ## Tradition as a Living Algorithm Some of the strongest recent work reaches back into Korean visual tradition and runs it forward through the tools. One piece pairs Dancheong — the intricate, saturated color-work that decorates Korean temples and palaces — with the image of a double helix, under a line the artist wrote plainly: if DNA remembers life, Dancheong remembers culture. The idea underneath it is that tradition isn't a relic to keep behind glass but, in their words, "a living algorithm that continues to evolve." The same instinct shows up quieter elsewhere — a sunlit hanok courtyard, a red-hooded figure lost in thought — heritage and interiority folded into the same frame. daejin.creates — "Dancheong remembers culture," tradition reimagined as a living algorithm ## Part of a Real Creative Community daejin.creates is a member of the Korean AI Creators Association — a community organized around the serious practice of AI art. That context matters. This isn't an artist working in isolation; it's someone embedded in ongoing conversations about what AI art can actually be when the person making it has a perspective to start with. It also shows up in the sheer steadiness of the output: this is a working practice, not a one-off experiment. Follow the work at [daejin.creates on Instagram](https://www.instagram.com/daejin.creates/?ref=thedaringcreatives.com) and [on Threads](https://www.threads.com/@daejin.creates?ref=thedaringcreatives.com). ### Brain Racked (Ryan McCoy) Builds Alien Civilizations using AI. URL: https://www.thedaringcreatives.com/creator-stories/ryan-mccoy-brainracked/ Last updated: 2026-08-16T10:25:09.000Z Ryan McCoy has been imagining alien civilizations for most of his professional life. More than two decades as a VFX artist and Creative Director in film and animation — the kind of career where your job is literally to describe what things look like before they exist. AI image generation showed up, and Ryan — who posts as [@brain\_racked](https://www.instagram.com/brain%5Fracked/?ref=thedaringcreatives.com) on Instagram — ran with it. The worlds Ryan builds under the BRAINRACKED handle are not the kind you dash off in five minutes. Elaborate sci-fi civilizations, alien architectures, spaceships and characters with the kind of weight and specificity that you only get from someone who has been thinking about this stuff for a really long time. Around 440,000 followers on Instagram have found this. The number keeps growing. BRAINRACKED — “Unfinished business in the country of Parth” BRAINRACKED — “Unfinished business in the country of Parth” ## The two-day prompt Ryan has described spending two full workdays on a single character design. Not hours. Days. The typical AI art workflow is not this. Generate fast, post what looks good, move on. Volume is the strategy. Ryan is doing something close to the opposite — the prompting is the work, and the AI is rendering something that has already been thought through thoroughly. The tools Ryan uses — Kling AI for generation, Magnific AI for enhancement — are fine but not unusual. Plenty of people have access to them. What's unusual is the pace, and I think that's the whole thing. ## What the years actually bought Professional VFX work builds a specific kind of skill: a vocabulary for describing what things look like before they exist. Surface materials. Lighting conditions. Structural logic. The geometry of something that has never been photographed because it has never been real. That is exactly the skill that makes AI generation powerful in the right hands. The model can synthesize plausible visual outputs from language — but the language still has to describe something specific enough to actually generate. General descriptions produce general images. Ryan's sci-fi worlds look like a real universe because Ryan is being specific in ways that take years to develop. You can't prompt your way to that specificity without first having it. ## The skeptic's case You can make a fair argument that the tools are doing the heavy lifting here. The visual quality people respond to on Instagram is coming from Kling and Magnific — that with good enough models, what you bring as an artist is increasingly curation, and the craft part matters less than it used to. I genuinely think about this. It's not an unfair read. What I keep noticing, though: generic prompts produce generic output. The specificity that makes BRAINRACKED's work feel like a coherent universe rather than a collection of cool images — that's not coming from the model. The model does not know what "the country of Parth" means until Ryan tells it. That's the 20 years doing real work. ## What I keep thinking about There's a specific kind of person who has been quietly building a very particular imaginative world for most of their career, and never quite had the tools to get it out the way they pictured it. I think Ryan McCoy is that person. And I suspect there are a lot more people like that — where AI didn't give them new ideas so much as it finally gave their existing ideas somewhere to land. The BRAINRACKED [Substack](https://brainracked.substack.com/) is worth reading if you're after this kind of process writing. The [YouTube channel](https://www.youtube.com/@brain%5Fracked?ref=thedaringcreatives.com) is early, but the work carries. ### STR4NGETHING Made the Wrong Era Look Right URL: https://www.thedaringcreatives.com/creator-stories/str4ngething-wrong-era/ Last updated: 2026-08-01T19:42:04.000Z STR4NGETHING is an anonymous AI artist who, in the fall of 2022, put Nike on a 15th-century Florentine and watched the internet collapse. The series — Renaissance portraits in full modern streetwear — hit [Hypebeast](https://hypebeast.com/2022/10/str4ngething-ai-generated-nike-outfits-info?ref=thedaringcreatives.com), Complex, Vogue Italia, and Vogue Business in quick succession. It was the kind of thing you shared because something about it felt true, even though it clearly wasn't. ![STR4NGETHING artwork: a figure in a maroon Nike sweatsuit posed as a Renaissance portrait in a doorway](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/str4ngething-maroon-renaissance.jpg) STR4NGETHING — from the artist’s press kit That feeling is the whole concept. STR4NGETHING's practice is built around the Mandela Effect — the cultural phenomenon where collective memory diverges from the historical record. The idea: if your brain can "remember" a movie line that was never actually spoken that way, it can probably also look at a Florentine merchant in a Nike tracksuit and find it weirdly plausible. Your brain fills in the gap and signs off on it. ![A grid of nine STR4NGETHING works: Renaissance figures in modern Nike streetwear](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/str4ngething-series-grid.jpg) A range of STR4NGETHING’s series — from the artist’s press kit Their series *WR0NG ER4* places contemporary gear — Nike, Louis Vuitton, Stussy, Trapstar, Tommy Hilfiger, Chanel — into Renaissance and Baroque painting compositions. It reads as plausible, every time, in a way that's hard to fully explain. ## The process isn't quick STR4NGETHING works with Stable Diffusion, Midjourney, and DALL-E. That's the same toolkit thousands of people have access to. What separates the work isn't tool access; it's prompt depth. "We can take a long time building specific prompts for the AI that we hold close to us," they told [Sneaker Freaker](https://www.sneakerfreaker.com/features/str4ngething-ai-artist/?ref=thedaringcreatives.com) in a November 2022 interview. "There needs to be human input — a human's imagination to create these prompts." That sounds obvious until you've actually tried to get an image generator to do something specific to you. The gap between what you pictured and what comes out is where the real work lives. "You will soon be up until the AM in no time trying to get the AI to understand exactly what you have imagined." STR4NGETHING keeps their identity and location anonymous. What they haven't kept quiet is how they frame the practice: they call themselves an "Artist/Designer" — "which is very controversial in the traditional art world," they noted — and they operate on the tagline "I Don't use AI... I Am AI!" They've also been upfront about the brands they feature. "I am not purporting to be Nike or affiliated with Nike. This is all art and expression. Nike is Nike and I am a STR4NGETHING." ## What the viral moment actually built *WR0NG ER4* didn't stay in the feed. By 2023, STR4NGETHING's work was on display in Times Square (April 2023) and at Milan Fashion Week (February 2023). They showed at NFT NYC, NFT Paris, NFT Rome, and NFT Seoul that same year. In October 2024, they mounted a solo exhibition — *R3n4issance 2.0* — at StudioG in Rome. Their NFT collection "NB4" — 21 pieces, each at 0.05 ETH — sold out. They're listed on [SuperRare](https://superrare.com/str4ngething?ref=thedaringcreatives.com), one of the more selective platforms in the space, and are a member of MAIF, an AI artist collective of 73 creators spanning multiple generations of the medium. A lot of viral art doesn't go anywhere. This one kept building. ## The honest read from the skeptic's chair You can look at *WR0NG ER4* and decide the concept is doing all the lifting. The Renaissance aesthetic comes pre-loaded — centuries of cultural weight, instantly recognizable, immediately striking when disturbed. Drop a Nike swoosh into it and you get contrast for free. The AI is generating the execution; the idea is the prompt. That's a fair read. I've had the same thought. But here's where I end up: the prompt architecture is the art, and not everyone with access to Midjourney is making work this coherent. Most aren't making anything with this level of conceptual consistency. STR4NGETHING built a framework — the Mandela Effect as an artistic lens — and committed to it across hundreds of pieces, gallery walls in Rome, a billboard in Times Square, and fashion week. That's a sustained practice with an actual thesis, not a one-off meme. Whether the tools are doing the heavy lifting or not, the vision has to come from somewhere. And this one holds up across context. ## What I keep thinking about "My art encourages viewers to question their own perceptions and consider the possibility that what we remember may not be as false or true as it seems." That's from [STR4NGETHING's own site](https://str4ngething.ai/?ref=thedaringcreatives.com). They built a globally recognized body of work — Vogue Italia, Times Square, a solo show in Rome — without a name, a face, or a location. The anonymity isn't incidental. It fits the concept. An artist questioning whether memory and identity are stable things, operating under an alias that's more brand than person. I don't know who STR4NGETHING is. Neither do you. And honestly, I keep wondering if that's the whole piece — an artist interrogating whether memory and identity are even stable things, operating under an alias that's more concept than person. Whether they planned it that way or not, it fits. ### dexplore.ai Posts a New World Almost Every Day. URL: https://www.thedaringcreatives.com/creator-stories/dexplore-ai-daily-worlds/ Last updated: 2026-08-01T19:42:04.000Z I found this one the way I find most things worth keeping — by accident, scrolling Instagram when I should have been doing something else. A short film came up in my feed. Sci-fi, a whole world in a few seconds, the kind of shot that used to mean a team and a budget. I watched it, then watched it again, then tapped through to the profile to see who made it. There's nothing there. The account is [dexplore.ai](https://www.instagram.com/dexplore.ai/?ref=thedaringcreatives.com). No name. No face. No bio beyond the work itself. Just film after film, each one its own self-contained world, released at a pace most people couldn't keep up with if it were their full-time job. ## What the record says Here's the little that's actually on it. In October 2025, the AI-film magazine [aithena.art](https://aithena.art/dexplore%5Fai/?ref=thedaringcreatives.com) featured the account in its Issue 13\. The curator who picked it, @rin\_ai\_cinematic, wrote: "tense, imaginative storytelling with astonishingly high production quality — hard to believe he releases one film every single day. One world a day. Watching his work feels like a luxurious gift." Notice the pronoun. "He." That's the curator's word — someone close enough to this scene to put the account in a magazine. dexplore.ai has never said it. There's no interview, no statement, no reveal anywhere I could find. One person who admires the work called him "he" in a caption, and that single syllable is close to the whole of what the internet knows about who this is. So I'll use it, the way you use the one fact you've got. He makes a new world most days. dexplore.ai — "STRANDS," on Instagram ## A world a day, each one named The films arrive as themes. "STRANDS." "Dimensions." "Graviniti." "BATTERY HIVE." Each is a short, self-contained cinematic sequence — sweeping sci-fi vistas, cosmic and mythic imagery, high-contrast environments that hold together as one recognizable look across daily output. That consistency is the tell. This isn't a new prompt every morning that happens to land; it's a dialed-in visual lane, run again and again. The reach follows the work. "STRANDS" pulled roughly 15,000 likes; "Dimensions" landed around 3,700\. He isn't trading on a face or a story to get there — the film shows up, and people respond to the film. dexplore.ai — "Dimensions," on Instagram ## The stack, credited under each film He puts the tools right in the captions, and they're consistent: PixVerse, Kling, Luma's Dream Machine, and Hailuo turn up film after film, with others (Dreamina, Krea) swapping in on some pieces. Four or more separate generators for a single short. Each of those tools has its own logic, its own way of failing, its own look. Getting them to hand off to each other and still land on consistent light and a single aesthetic — on a new film nearly every day — is a workflow somebody built and keeps rebuilding as the tools shift under him. The same generators are open in everyone else's browser. The daily, recognizable output is the part that isn't. dexplore.ai — "BATTERY HIVE," on Instagram ## No face on any of it Every piece of creator advice says do the opposite — show your face, tell your story, build a personality people can follow. dexplore.ai skipped all of it. The Linktree points to Instagram, X, and a couple of the tools; there's no personal site, no name, nothing that ties a human to the work. The films keep coming anyway. A new world went up today, and it'll have a theme name, a stack of tools credited underneath, and no one attached to it — same as yesterday. ### cursejourney Makes AI Horror That Looks Like Found Footage URL: https://www.thedaringcreatives.com/creator-stories/cursejourney-ai-horror-found-footage/ Last updated: 2026-08-16T10:25:10.000Z cursejourney is AI-generated horror styled to look like photographs you weren't supposed to come across. Demons, gods, monsters, mythology — rendered sepia-toned and grainy, like something pulled out of a box in an attic instead of a machine running prompts. The account describes itself plainly: "content creation via AI images portraying the supernatural, gods, demons, monsters, and anything in-between." The [cursejourney.com](https://cursejourney.com/?ref=thedaringcreatives.com) tagline is blunter — "the most cursed images." It's the project of Mike Chhay, who started cursejourney in Phoenix in August 2023. cursejourney — "photos i found in the basement," on YouTube ## The found-footage premise The flagship series is "photos i found in the basement," a multi-part run on his [YouTube channel](https://www.youtube.com/@cursejourney?ref=thedaringcreatives.com). The framing carries the whole thing: a demon-god in sepia with film grain doesn't read as a failed realistic render — it reads as documentation of something that shouldn't exist. The "close but wrong" quality that AI image tools produce, the thing most people fight to get rid of, is exactly what the horror genre can use. cursejourney aimed straight at it. He's not the only one working that register. The dark-fantasy account [gloomstomper](https://www.instagram.com/gloomstomper/?ref=thedaringcreatives.com) runs a whimsical-eerie spin on the same looks-real-but-wrong trick, and its horror-leaning sibling — [voidstomper, who we've profiled](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/) — pushes it all the way to dread. It's becoming its own small genre: artists who treat the glitch as the point. cursejourney — "into the basement," on YouTube ## How it's made Chhay documents the actual pipeline on a [tools page](https://cursejourney.com/tools/?ref=thedaringcreatives.com), and it's a lot more than a prompt. The images start in Midjourney — "the AI image generator that has created the majority of my cursed old photo series." Before anything moves, he upscales the still in Magnific so the animation step begins "with a high-resolution detailed start-frame," which is what keeps details and faces consistent. Photoshop handles the editing pass: cropping, color and contrast, removing objects, filters. Then the still gets animated. His workhorse is Kling — "the tool you want to use for the majority of the time using the image-to-video feature" — with Seedance held back for "epic transformations and action scenes." Premiere Pro cuts it together, Suno scores most of the reels, and ElevenLabs fills in sound effects and voice. A last pass through Topaz upscales to 4K, the same class of tool used to restore old blurry footage — on the nose for work meant to look dug up rather than generated. That's six or seven tools handing off for a single short, and the lineup keeps shifting — his 2024 pieces ran on Luma before Kling took over. The one thing he doesn't spell out is the exact recipe for the aged, sepia-grain look; that lives in the editing pass and the concept, and he keeps it loose. The cursejourney stack — tools he credits himself - [Midjourney](https://www.midjourney.com/?ref=thedaringcreatives.com) — base images - [Magnific](https://magnific.ai/?ref=thedaringcreatives.com) — upscales the still to a clean start-frame before animating - [Photoshop](https://www.adobe.com/products/photoshop.html?ref=thedaringcreatives.com) — editing, color, contrast, filters - [Kling](https://www.klingai.com/?ref=thedaringcreatives.com) — image-to-video for most shots - **Seedance** — the big transformations and action beats - [Premiere Pro](https://www.adobe.com/products/premiere.html?ref=thedaringcreatives.com) — assembly and pacing - [Suno](https://suno.com/?ref=thedaringcreatives.com) — music for most reels - [ElevenLabs](https://elevenlabs.io/?ref=thedaringcreatives.com) — sound effects and voice - [Topaz Video AI](https://www.topazlabs.com/?ref=thedaringcreatives.com) — final 4K upscale Roughly in order of use, from his [public tools page](https://cursejourney.com/tools/?ref=thedaringcreatives.com). Seedance left unlinked pending a confirmed official URL. ## The cat, and a design jury One piece broke out past the horror audience: the "cursejourney cat," which began as a single still image and was later animated. It was selected for AIGA Arizona's Best of 2025\. The entry describes the cat as a viral image "brought to life using AI and Premiere Pro," and notes the video "has over 140 million views on Instagram alone" — framing it as an example of AI "in the hands of a designer." The cat lives on his Instagram, Facebook, and TikTok rather than the YouTube channel. cursejourney — "Hellgates," on YouTube ## Still going Chhay's [portfolio](https://mikechhay.com/cursejourney/?ref=thedaringcreatives.com) lists cursejourney as August 2023 – ongoing. The basement series keeps adding parts, and the account keeps posting work aimed at people who like being unsettled by something that looks like it could be evidence of something. ### Mr. Relative Makes AI Art About Us. This Summer He Put It in a Room. URL: https://www.thedaringcreatives.com/creator-stories/mr-relative-ai-humanity/ Last updated: 2026-08-16T10:25:10.000Z Mr. Relative is a Polish artist who has been working with AI since late 2021, and the name reads as a position as much as a pseudonym. The whole practice runs on one premise he states outright: everything is relative, especially perception. His motto — "Perception is the mother of all beliefs" — sits over a body of work called "This is Humanity": human figures dissolving into symbols, crowds merging with landscape and matter, the uncomfortable things people do together. Here's why he says he works with this tool, in his own words, from his [CLUSTER London exhibitor profile](https://www.cluster-london.com/mrrelative-cluster-ai-exhibitor-2025?ref=thedaringcreatives.com): > "I work with AI because it is the perfect medium for exploring humanity itself—a technology built on everything we have created, shaped by our knowledge, biases, and perceptions. It allows me to blend reality and imagination... This is Humanity visualises humanity as intertwining bodies, merging into nature, concepts, and everyday objects. It reflects human duality—sometimes cruel, sometimes beautiful." That's the through-line, and it's a tight one: a system trained on everything humans have made, turned back on the subject of humans. He doesn't treat the images as one-offs either — "each piece is more than an animation," he's said, "a collective memory distilled into a single form." ## From the feed to a room This summer he took the work off the screen. [The Relative Gallery](https://therelativegallery.com/?ref=thedaringcreatives.com) opened its inaugural "This is Humanity" exhibition June 27–28, 2026, in western Poland — a restored century-old mill fitted with digital screens, staged together with the artist Odesso. Taking digital-first work that lives natively on phones and building a physical room for it isn't the obvious next step for an artist with this kind of online following, but it lines up with the premise: where you encounter an image is part of what the image is. The gallery's own account posted a recap of opening night — digital art in a hundred-year-old barn: The Relative Gallery opening, June 2026 — via @the\_relative\_gallery on Instagram On the walls, his own pieces — like "Spectacle," a whirlpool made of a crowd, the front row filming it on their phones. ![Mr. Relative's 'Spectacle' — a whirlpool formed from a massive crowd, onlookers filming on phones — framed on the wall at The Relative Gallery](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/mrr_spectacle.jpg) Mr. Relative's "Spectacle," installed at The Relative Gallery — via therelativegallery.com Before the gallery, the work had already been shown outside the AI-art circuit: his pieces were part of CLUSTER's AI Showcase in London in 2025, a photography and print fair. ## The work in print Prompt Magazine ran a feature on him that pulls more of the series into view — "Mind Reaper," a human brain rooting into the ground; a globe built entirely out of bodies. Same subject, different framings of it. ![Mr. Relative's work featured across a Prompt Magazine spread, showing several 'This is Humanity' pieces](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/mrr_4.png) Mr. Relative's "This is Humanity," featured in Prompt Magazine — via mrrelative.com ## The how stays mostly private His own file naming points to Midjourney as the starting point, and he's clear the pieces are built to move and be heard — he describes the work as blending "emotion, sound, and motion," and calls each one "more than an animation." Past that, he doesn't publish a workflow: no tool breakdown, no step-by-step, no process reel. The most he's said about method is in a print interview — Prompt Magazine's "Sameness" issue — which isn't online. That reticence fits the rest of him. The name is a stance about perception, the work is about collective behavior, and the making stays behind the curtain — what he hands you is the finished piece and the idea under it. Most of the catalog lives on his [Instagram](https://www.instagram.com/mr%5Frelative%5F/?ref=thedaringcreatives.com). The gallery show ran three days in June. The premise is five years deep now, and it hasn't moved. ### Julien Durand Has a Day Job in Engineering. It's Why His AI Films Work. URL: https://www.thedaringcreatives.com/creator-stories/julien-durand-engineer-ai-films/ Last updated: 2026-07-14T23:51:56.000Z Julien Durand is a mechanical engineer by training — French-born, with a Master's from INSA Lyon — who also happens to run one of the more quietly striking AI art accounts on Instagram. Around 323,000 followers at [@julienaiart](https://www.instagram.com/julienaiart/?ref=thedaringcreatives.com). Work that pulls from cinematic sci-fi, dark fantasy, and superheroes rendered with the weight of oil painting. Not hobby-scale output. Not "I post when I feel like it" output. The original handle was MidJourney Man — [@midjourney.man](https://www.instagram.com/midjourney.man/?ref=thedaringcreatives.com) — which is exactly what it sounds like. The handle changed as the tools did. The volume didn't drop. **The piece that won** "DREAMS" took the CivitAI Award in Project Odyssey Season 1\. It's a short generative film — fully AI-produced — and it's the kind of thing that's easier to watch than to explain. Julien Durand — "DREAMS" (CivitAI Award, Project Odyssey Season 1) The win also landed him a judging seat on Project Odyssey 2025\. So now Durand is reviewing the work instead of submitting it. **The actual toolstack** MidJourney handles initial image generation. ComfyUI is the control layer — compositing, workflow customization, the connective tissue that turns a static image into something with motion and intention. Kling AI and AnimateDiff handle the movement. Topaz Labs refines and upscales. Runway handles additional video output. That's a full production pipeline, not a single-click setup. Each tool has its own logic and its own failure modes, and chaining them together into something coherent takes real time to learn. A lot of what comes out the other end is cinematic video — pieces like "Neon Ghosts": Julien Durand — "Neon Ghosts" Durand has published 14 public ComfyUI workflows at [comfy.org/workflows/julienaiart](https://comfy.org/workflows/julienaiart/?ref=thedaringcreatives.com). That matters. Posting the work is one thing — sharing the method is something else. A lot of people in this space don't do it. The full catalog lives at [julienai.art](https://julienai.art/?ref=thedaringcreatives.com). The "Fallen Heroes" series — retired superheroes in comedic, lived-in situations — ran well on Instagram. There's genuine warmth in it, which is not a given in AI-generated images that are trying to be cinematic. **Why the engineering background isn't incidental** There's a framing that treats the technical depth and the creative output as separate things — the engineering is the day job, the art is the real passion. I've had that framing. I don't think it fits here. A ComfyUI node graph is a system. You're building pipelines — defining inputs, chaining outputs, specifying what each component does and what it hands off to the next. That's not a foreign concept to someone who has spent years working with mechanical systems and manufacturing workflows. The vocabulary is different. The mental model transfers directly. When Durand publishes a workflow, it's typically a documented, shareable process that other people can actually learn from and run. That takes a particular kind of patience with systems — and with other people needing to understand them. That doesn't come from nowhere. **The fair counterargument** The tools are doing a lot. MidJourney and Kling AI can produce images and animations that would have required entire production teams not long ago. At 323,000 followers, some portion of that audience is responding to the sheer quality of what comes out of those tools — and honestly, fair enough. They're good tools. When everyone has access to the same tools, the differentiator is what you actually make with them and whether it reads as distinctly yours. Looking through Durand's catalog, it does. That's harder to explain precisely than I'd like — but it's there. **What I keep thinking about** Durand does this alongside an engineering career. Not instead of it. The AI art world has a lot of dramatic pivot stories — people who left everything and went all-in. This is someone who just added something and kept going. I keep coming back to the Fallen Heroes series specifically. There's something genuinely funny in those pieces, and funny is the hardest register to hit with AI-generated imagery. Everything wants to be epic. Making something that lands as warm and a little absurd requires a specific kind of editorial eye. Worth following if you're not already. ### Manuela Klauser Knew What She Was Making Before She Let the AI Near It URL: https://www.thedaringcreatives.com/creator-stories/manuela-klauser-ai-art/ Last updated: 2026-08-01T19:42:05.000Z Manuela Klauser is a digital and AI artist based in Vienna who goes by [sheisinblack.art on Instagram](https://www.instagram.com/sheisinblack.art/?ref=thedaringcreatives.com). She makes work she calls "Soft Goth Surrealism" — dark, gothic figures with an undercurrent of something almost cheerful, like Tim Burton if Tim Burton was also obsessed with contemporary fashion and wasn't precious about the medium. Her work has shown at AI Week Milano, Kunstmeile Basel, PARALLEL Vienna, and the British Art Fair at the Saatchi Gallery in London. She has over 190,000 Instagram followers, which people will mention. It's less interesting than what she did to get there. **The tools, specifically** Klauser's primary tool is Midjourney. She uses Hailuo AI (MiniMax), Kling, Adobe Firefly, DALL-E 3, and Krea alongside it — for animation, video generation, and refinement — but Midjourney is where her visual language starts. Her characters have wild dark hair, white oval faces, red lips, and clothes that feel like they're from a fashion editorial that got lost in a gothic graveyard. Every piece is recognizably hers. That last part is the thing worth paying attention to. **How the process actually runs** The workflow is: prompting → iterative generation → curation → editing → animation when the piece calls for it. That's not unusual for AI image work. What's different is the curation step — she generates a lot and picks relentlessly, and the picking is based on a fully formed visual sensibility she had before she ever touched Midjourney. Klauser describes AI as "creative collaboration — a system that opens new image possibilities." You'll hear variations of that from most AI artists. The interesting part, in her case, is that she already knew what "new image possibilities" meant for her before she started looking for them. The Soft Goth Surrealism aesthetic — eerie atmospheres, delicate humor, gothic figures with a pop warmth — wasn't something she discovered through generative tools. She came in with it. I've seen a lot of AI art where you can tell someone opened Midjourney and typed "beautiful." That's how I got started too. What Klauser does is different in a way that's easy to see and harder to explain. ![Two gothic surrealist AI-generated figures in dark and vivid-coloured clothes, facing the viewer — from Manuela Klauser's Goth Pop Rebellion series](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/sheisinblack_candidate1.png) "Girlfriends" — from the Goth Pop Rebellion series. Artwork by Manuela Klauser / sheisinblack.art, via [AVGD Gallery](https://avgd.art/sheisinblackart?ref=thedaringcreatives.com) **What the gallery wall says** The exhibitions matter because they're not Instagram metrics — they're curators deciding to put the work in a physical room alongside other things they consider art. AI Week Milano, Kunstmeile Basel, PARALLEL Vienna, and the Saatchi Gallery's British Art Fair are not doing Instagram artists a favour. They're responding to something in the work itself. Klauser also collaborates with musicians: stage visuals, music videos, Spotify Canvas animations. The same visual language that reads well at 1080×1080 also holds up in motion and at gallery scale. That coherence doesn't happen by accident. She runs an [AI workshops and innovation consulting practice called voller ideen](https://www.vollerideen.at/?ref=thedaringcreatives.com) on the side, which makes sense. The way she talks about AI — as a creative collaborator, not a shortcut — is the kind of framing that lands in a workshop context. She's thought through what she actually believes about the medium. **The skeptic's version** The fair argument against calling this craft is that the tools are doing the heavy lifting. Midjourney generates. Klauser picks. The curation is just choosing your favourite from a grid that a model produced. I've made that argument myself about other artists. I still half-believe it in some cases. But it proves too much. A photographer who picks the one frame from a shoot "didn't make anything" by the same logic. The craft in both cases is in the edit — knowing what you're looking for, knowing when you've got it, and being consistent enough about it that the work is legible as yours across hundreds of pieces. Most AI-generated work is nearly anonymous. You could swap the artist and nobody would notice. That's not true of Klauser's work, and I think that gap is where the craft lives. **What I keep thinking about** Her [gallery profiles at AVGD](https://avgd.art/sheisinblackart?ref=thedaringcreatives.com) and [HUG Art](https://hug.art/artists/sheisinblack?ref=thedaringcreatives.com) show pieces from the Goth Pop Rebellion series alongside older work, and you can track a visual consistency across all of it that isn't just "dark." It's a specific kind of dark — specific enough that you'd know a fake. I don't know exactly how she built that. But I don't think the AI built it for her. ### Julian van Dieken Accidentally Became the First AI Artist in a Museum URL: https://www.thedaringcreatives.com/creator-stories/julian-van-dieken-ai-museum/ Last updated: 2026-08-16T10:25:11.000Z Julian van Dieken is clear about what he is, and it's not an AI artist. He's a photographer and educator with 15 years of professional experience doing documentary work for non-fiction publishing, co-founding an educational training company, and teaching workshops on video production and project documentation. In September 2022, he started a side project on Instagram — [@julian\_ai\_art](https://www.vandieken.com/julian%5Fai%5Fart?ref=thedaringcreatives.com) — with no particular goal. He describes it on his site as "a side project where I experiment with AI tools and try to learn something new." That's literally the whole brief. Experiment. Learn. Share. A few months later, his AI-generated image was hanging in the [Mauritshuis Museum in The Hague](https://www.smithsonianmag.com/smart-news/girl-with-a-pearl-earring-vermeer-artificial-intelligence-mauritshuis-180981767/?ref=thedaringcreatives.com), where Vermeer's *Girl With a Pearl Earring* normally lives. **What happened at the Mauritshuis** The museum loaned out the original Vermeer and ran an open competition — #MyGirlWithAPearl — inviting anyone to submit their own interpretation. Three thousand five hundred people submitted. Five prints were selected and displayed in the gallery. Van Dieken's *A Girl With Glowing Earrings*, created with Midjourney, was one of them. He called it "crazy" and "completely surreal." He said: "One of the most famous paintings in history is literally being replaced by one of my AI images." The internet was less charmed. People were angry that an AI-generated image had made it into a traditional fine art institution. Van Dieken had been transparent about his method from the submission itself — he wrote in his entry that he was reflecting on how AI tools might change creative processes. The museum knew what it selected. He wasn't hiding anything. **The 30-Day Challenge as a method** The actual practice that produced that image is worth paying attention to. His core method is the 30-Day Challenge: make something every day for a month, strip out professional pressure, and learn through mistakes rather than through caution. He uses it to force daily creation that builds real fluency with a new tool. It works because you exhaust the ideas you were comfortable with and start reaching for ones you weren't sure about. That's where things actually happen. I recognize this from other creative practices — the ratio of attempts you'd share to attempts you make is part of what builds your instincts, not a side effect you hide. He works primarily with Midjourney and Photoshop for post-processing, and has experimented with Stable Diffusion, Astria.ai, and others over time. His photography background shapes what he's trying to pull out of these tools — the Mauritshuis piece was described as "sharp, photorealistic," which makes sense for someone whose creative instincts formed around camera work. Julian van Dieken — "ART & CHAOS" (A.I. GlitchCore) He also says this plainly on his site: "I'm not a developer, I'm not a trained AI expert." The point of sharing his work and learnings is that he came to this from the creative side, not the technical side. He figured it out the same way a working photographer or designer would have to. **On the backlash** You can make a real argument that AI-generated work in a fine art museum is a category error — that it conflates the outputs of a generative model with what it means to make something, and that institutions presenting them side by side muddy distinctions that actually matter. That's worth taking seriously. But van Dieken wasn't slipping anything past anyone. He disclosed the method in his submission. He reflected on it publicly. The museum ran an open competition with no stated restrictions on technique, and five prints were chosen from 3,500\. If the problem is with the criteria, that's the museum's call to make and answer for. The framing of him as someone who "ripped off" Vermeer using AI doesn't hold up against what actually happened. He submitted to an open competition, was selected, and was honest about how the work was made the whole way through. **What he's actually doing now** Past the Mauritshuis moment, the educator piece has become the main thing. His LinkedIn describes him as "AI Educator & Speaker." His work has been covered by the New York Times, Zeit, CNN, and Der Spiegel. He speaks at events — including MIS ArtFest 2024 on the topic of how to be creative with AI. He runs workshops. He's not primarily someone who makes AI images. He's someone who made AI images specifically to understand the tools well enough to teach other people how to think about them. That's a different function than "AI artist," and right now it might be the more useful one. There are plenty of people generating images. There's less of people who came to these tools from a creative background, put in the daily reps, and can explain what the process actually involves to someone who hasn't done it yet. He set out to learn something new. What he ended up with was a museum wall, a following, and a set of conversations he now gets paid to lead. That's a longer answer to the original brief than he probably expected. ### How Kelly Boesch Built a Studio of One With AI URL: https://www.thedaringcreatives.com/creator-stories/kelly-boesch-studio-ai/ Last updated: 2026-08-16T10:25:12.000Z [Kelly Boesch](https://www.kellyboesch.com/?ref=thedaringcreatives.com) spent 17 years at IMAX doing graphic design, film production, and marketing. She built development decks that convinced studios to fund projects. She understood production rhythm, visual grammar, large-format cinematic work — in a professional context, not from watching YouTube. Three years ago she picked up AI image generation. She didn't dabble. She has 2-3 million followers and 60 million views a month as of mid-2026, a debut album on Nettwerk Music Group, and a 2026 gallery exhibition in London. That trajectory is interesting. But the process behind it is what I keep wanting to understand. Kelly Boesch — "Not Made For The Cage" (4K AI film) ## Start with an image, not a prompt Most people approaching AI video do it text-first — describe the scene, generate, hope. Boesch works the opposite way. She generates a still with Midjourney, gets it compositionally right, then animates from that image. The control she keeps over aesthetic and framing is deliberate. Text-to-video is closer to a lottery; image-to-video is closer to art direction. For animation she pulls from Runway ML, Pika, Higgsfield, and VEO3, depending on what a scene needs. Each tool has different behavior. She moves between them. Her framing of the edit layer, [from an interview about her process](https://www.provideocoalition.com/ai-tools-artist-spotlight-kelly-boesch/?ref=thedaringcreatives.com), is the clearest articulation of what she's actually doing: "You can't just let the AI do the work — the editing, color correction, and sound mixing are where the human touch turns a clip into a story." That's a methodology, not a disclaimer. ## Adding Seedance, July 2026 In late July she added another model to the rotation, and reached it through a tool already in it: "using #Seedance 2.0 in #RunwayML," as she tagged it. On July 25 and 26 she posted two tests within a few hours of each other, running the model in each direction. The first went text-to-video. She'd been watching the trailer for *The Odyssey* and wanted to see whether Seedance could reproduce its shot of a massive whirlpool at sea. Her own account of the result: "It came out insane. This app is just incredible. These were pretty basic prompts." Kelly Boesch — "Seedance 2.0 text to video trailer experiment," her attempt at the whirlpool shot from The Odyssey trailer The second went image-to-video — a Blade Runner-style piece she described as "just a bunch of animated images made for fun." She labeled both as departures rather than a change of method: "Very different than what I normally do. Every now and then I like to experiment a little with different things to see what I can get." Three days later the model was in a finished piece. "The Art Of Being Strange," posted July 29, is the story-driven video she'd been wanting to make, and she credits the new tool plainly: "I have been practicing with Seedance a bit and used it for this one." Her note on what proved difficult is the part worth keeping — "The hard part is trying to direct the things that happen in the scene." Which is the same problem the image-first method exists to solve, showing up again one tool later. ## Then add music Her debut album — *Fairytale*, April 2026, Nettwerk, 14 tracks, 49 minutes — came out the same week as her London show at W1 Curates. She wrote the lyrics. She used Suno to produce the music under her direction. The label and the imprint (Gelsomina Studios) are real. This is the part that changes the conversation about what she's making. Directing a generative music tool through your own lyrics to produce a cohesive album that lands on a real label is not a random output. That's a music production pipeline she owns. You can argue the tools are doing the heavy lifting and she's curating the results. That's a fair read, and I've had the same thought. But curation at that level of intentionality is close to authorship. Most film directors don't operate the camera either. ## What the IMAX years actually did The 17 years matter here. When Boesch talks about color correction, edit pacing, and sound mixing as the human contribution, she's not reaching for concepts she recently learned. She built those instincts professionally. She arrived at these tools already knowing what a cinematic image is supposed to feel like. That's not a small thing. A lot of AI art fails at the sensibility level — technically generated, but visually incoherent. Her training gives her a baseline the tools can't provide. ## The April moment The timeline is worth noting: *Fairytale* drops April 10\. W1 Curates London opens April 10\. She speaks at [TED2026 in Vancouver](https://tedlive.ted.com/webcasts/ted2026/session/861?ref=thedaringcreatives.com) on April 15\. The talk was called "Art, Music, AI and The Joy of Creativity." I don't know whether all of that landing in one week was strategic or just how it fell. Either way, it marks a shift — from "AI creator with a big following" to "artist with gallery and conference stage recognition." Those are different categories, and she crossed into the second one. ## Her stated position, and what she's making now Boesch's line on the tools has stayed the same: AI augments creativity, it doesn't replace it. The workflow is where she puts that into practice — the still she composes before anything moves, the lyrics she writes herself, the editing and color and sound she keeps by hand. The music side keeps moving with it. Several of the summer's videos are built on her own older songs, reopened and rewritten rather than replaced: "Marshall Altman and I reworked the lyrics a bit and updated the song and it works really well now," she wrote under the July 29 piece. "I like to use some of my old songs again from time to time." Kelly Boesch — "The Art Of Being Strange" (July 2026), her first story-driven piece made with Seedance ### Behind the Build: Automating My Own Self-Promotion in a Day (and the Silent Bug That Almost Sank It) URL: https://www.thedaringcreatives.com/funnel-in-one-day/ Last updated: 2026-07-06T23:38:09.000Z Ask almost anyone who works for themselves what they hate most about it, and you'll hear some version of the same thing: self-promotion. Putting yourself out there. Being your own hype man. It feels gross, it's not why any of us picked up the work in the first place, and pretty much everyone is quietly bad at it because we avoid it. I'm one of them. I'd rather make the thing than sell the thing. Every hour I spend posting about my work is an hour I'm not doing the work. So I've been trying a different approach to the part I hate: instead of forcing myself to promote every day, build the promotion once, as a system, and let it run without me. Set it up so the funnel does the selling while I go make things. Last week I did exactly that. Over one long working session I took my own AI-products business, Daring Strategy, from "has a landing page" to a working acquisition funnel: a hosted product, a free lead magnet, nine industry reports, and a live Google Ads test — all deployed and capturing leads by the end of the day. A few days later I found out it had been throwing every one of those leads away. That's the catch with handing the part you hate to a machine: it'll do it wrong, silently, forever, unless you make yourself go check. At every fork in this build, I tried to measure instead of guess. The funnel looked like it worked. The form returned success. The only number that told the truth was the one I went and counted myself. ## From "sell a prompt" to "sell a system" — and how I priced it The original plan was to sell a single really good prompt for $49\. I killed it about an hour in. Nobody pays $49 for a prompt — you paste it once, it works or it doesn't, and there's nothing to come back to. So the product became the thing that runs the prompt for you: a guided 20-minute interview that turns a conversation into a set of structured files a business can drop into any AI — brand, voice, customers, offers, the works. Same underlying idea, except now it's a real product instead of a text file. You're buying a system, not a prompt. That reframe also changed how I priced it. I landed on $50, and I want to be honest about how I got there — because this is the kind of thing I'd normally walk through with someone in a live coaching call. The cost to run one interview is about twenty cents — I'll show you how I know that below. So I'm not pricing to margin. I'm pricing to value. A business that gets a genuinely personalized AI context system out of a 20-minute session is getting something that would otherwise take hours of YouTube, trial-and-error, and piecing things together from five different sources. Time is money. For a business, $50 is not cost-prohibitive for that. Now, I've been critical of [SaaS companies](https://www.thedaringcreatives.com/the-violent-death-of-saas/) on this site — the recurring lock-in model, the drip-fed features, the pricing designed to make cancellation feel like a loss. I'm aware of the tension, and I want to be upfront about it. But a one-time $50 product that gives you a permanent context system for your business is a different thing than a subscription that owns you. It's not a platform. It's a tool you paid for once and keep. And there's no usage cap. Run it as many times as you want. I do want to find a way to prevent abuse eventually — one license getting shared across twenty businesses isn't really the spirit of it — but right now that's not a real concern, and I'm not going to punish early users with artificial limits to solve a problem I don't have yet. The payment process is finished and it's live now at [https://daringstrategy.com/business-brain](https://daringstrategy.com/business-brain?ref=thedaringcreatives.com). ## What a run costs (I didn't guess) At some point I wondered what one of these interviews actually costs me to run. The easy move is to estimate — ballpark the tokens, multiply, move on. Instead I instrumented it. Logged the actual token usage from the model, ran two real interviews through the thing, and read the numbers straight off the logs. About twenty cents a run. Twenty-two if it reads the customer's website first. That number settled a few things at once. Cost isn't the thing I need to protect — a purchase covers multiple runs, and the economics are nowhere near tight. Any usage limits I add in the future will be there to prevent one code from being shared across twenty businesses, not to protect a quarter. Knowing the real figure meant I spent my next hour on the right problem instead of an imaginary one. ## If your product is a conversation, simulate the other side of it Here's the part I'm most proud of. [The product](https://daringstrategy.com/business-brain?ref=thedaringcreatives.com) is a 20-minute interview, and testing a 20-minute interview by hand is brutally slow. Sit through it, note what's clunky, change one line, sit through it again. A whole afternoon gets you four runs. So I built a small army of fake customers. Agents that each role-play a different small-business owner — different talking styles, some with a website, some without — sit through the real interview end to end, then grade the files it produced. Did it capture how they actually work? Did it invent anything? Did it get weirdly biographical? Five of the simulated owners — a bakery, a real-estate agent, a yoga studio, a coffee shop, a marketing consultant — each running the real interview end to end. It caught things I'd have missed for days. One question read four decision-making styles out loud like a multiple-choice quiz, and every single simulated owner flagged it as leading them. The interviewer also confidently made up a business partner's name from a website. I would have shipped both. I don't think you can test a conversational product any other way at a reasonable speed. And the grader is where the actual product spec turned out to live — writing down what a good result looks like forced me to decide what the thing is even for. ## The ad test, and the "required" step that wasn't The longest, messiest stretch was Google Ads. I put $200 behind one industry — coaching, because it's closest to my world and the clicks are cheaper — pointed at the free check rather than the paid product, on its own message-matched landing page. Google fought me the whole way. It quietly switched me into its Performance Max product instead of plain Search; I caught it and switched back. Its recommended daily budget would have burned the whole $200 in under three days, so I capped it hard. Its suggested keywords were the wrong intent entirely — people who want to hire a consultant, not coaches who want to use AI themselves. Then it tried to route me through a conversion-tracking setup that needed events I hadn't built, which was going to cost me another day. This is the decision I want to flag. Because I'd chosen "maximize clicks" as the bid strategy, Google didn't actually need conversion data to run the campaign — that tracking was only for measurement. And I already measure every signup, because each lead lands in Ghost the moment they submit. So I skipped Google's tag completely and built my own: the landing page drops a small tag in the browser, the check reads it, and the signup gets labeled as coming from the ad. Cost per lead is spend divided by those labeled signups. I read it in Ghost. The lesson I keep running into: find out what a platform's step actually requires before you do the work it tells you to. Half of "required" is "required for the path they'd prefer you take." ## 67 clicks, and one of them was me The ad cleared Google's verification and traffic showed up: 6,070 impressions, 67 clicks, sixty-two cents a click. Real people, clicking a real ad, landing on the check. Then I opened Ghost to count the leads. There was one member. It was me. Sixty-seven people went through the funnel and not one of them got captured. The form looked fine — it submitted, it returned success, it handed back the report. Everything you'd verify by clicking through it yourself worked. The problem was underneath. I'd wired signups through Ghost's built-in flow, which sends a confirmation email and only creates the member once they click it. But I was handing over the report the instant they submitted, so nobody had any reason to go dig that email out of their inbox. The funnel collected everyone and kept no one. Here's how close this came to going unnoticed. If I'd trusted the green checkmark on the form, I'd have let that ad run a week and then wondered why a campaign with fine click numbers produced nothing. I caught it on the first day of real traffic for one reason: I went and counted the actual members in Ghost instead of trusting that "submitted successfully" meant "captured." The fix was small once I understood it — create the member on submit, skip the confirmation email. For a free download where the report is the whole payoff, asking people to confirm by email just guarantees you lose almost all of them. That went out the same day. ## The honest part A one-day build invites a fair criticism, so let me make it for you: speed usually means corners cut, tools chased instead of fundamentals respected, a demo that falls over the first time a real person touches it. That's a reasonable worry, and I've shipped things that earned it. What made this one hold up wasn't going fast. It was checking the rendered thing instead of trusting that it worked. The model invented a clinic's name out of thin air — caught because I read the output instead of assuming. A stale logo from an old concept almost went onto nine PDFs — caught because I opened the file instead of trusting the filename. My own name leaked into reports that were supposed to be about the reader — caught the same way. The lead leak is the same lesson with higher stakes: the system told me it was fine, and it wasn't. None of that is clever. It's just looking at what you actually made, every time, before you believe it. The speed came from the tools being ready and from measuring at each fork, so I never had to backtrack far. It did not come from skipping the boring checks. Those are the part that lets you move quickly without it quietly falling apart on you. ## What's not done The ad test has a check-in on the calendar before the budget runs out. Proper conversion tracking is on the list now that the launch pressure is off. And the simulated-customer testing approach I described above is something I'd genuinely like to compare notes on — whether you've found your own version of the leak you didn't know was there. The part I hate is mostly getting done now, and mostly without me. That's the whole point of building the machine. But a system that markets for you while you're not looking is only a good deal if you actually go look. Count the real results before you believe the green checkmark. I suspect more of us are running funnels that quietly keep no one than would care to admit it. ### Neural Viz Makes an Alien TV Network, Tool by Tool URL: https://www.thedaringcreatives.com/creator-stories/neural-viz-ai-tv-universe/ Last updated: 2026-08-16T10:25:12.000Z You scroll past a clip of a squat brown alien ranting about a government cover-up, shot like a 1997 public-access documentary, and it takes a second to clock that nobody filmed it. Then another clip rolls by — a reporter doing man-on-the-street interviews with aliens on a sidewalk. Same world. Same grainy broadcast look. It's not a clip. It's a whole TV network. That's the Monoverse, the running fiction behind [Neural Viz's channel](https://www.youtube.com/@NeuralViz?ref=thedaringcreatives.com) — a future Earth where humans have vanished and aliens called glurons make the kind of television we used to make. Mockumentaries, a cop show, a ghost-hunting parody, vox-pop street interviews. Near-weekly episodes, some running eight minutes, pulling hundreds of thousands to millions of views. What makes it worth pulling apart isn't that it's AI. Lots of things are AI now. It's that it holds together — recurring characters you recognize, jokes that build across episodes, a world with its own rules. Most AI video is one cursed clip you watch once and forget. This is episodic television, made by one person. That person is Josh Kerrigan, and the first thing worth knowing is that he was a filmmaker for over a decade before any of this. Film school, years of production work in LA, a TV pilot he's said he sold before going full-time on Neural Viz in early 2025\. I bring it up now because it turns out to be the whole story, and we'll come back to it. ## He built the world around what the tools can't do Here's the part I keep thinking about. The AI horror artist [Voidstomper](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/) — who I've written about before — built three million followers by leaning *into* the glitch. The melting faces and extra limbs are the point; the error is the art. Kerrigan went the opposite direction. He studied what these models are bad at and designed a world specifically to hide it. AI is good at talking heads, so the Monoverse is mostly people — well, aliens — talking to a camera. The uncanny valley is brutal on realistic humans, so his characters are bulbous cartoon glurons your brain never expects to look real in the first place. Clean 4K makes every rendering artifact scream, so everything is graded like a worn-out 20th-century broadcast: VHS noise, soft focus, a tape that's been copied one too many times. The limitations are still there. He just built a set where they read as style. There's even a character whose long-vowel verbal tic — "Iiiiiiiii" — started as a software error he decided to keep. Neural Viz, "Human Hunters" (YouTube) ## The workflow looks like a writers' room, not a prompt box This is the part people actually search for, so here's the honest version of how the episodes get made. He starts with a full script — slug lines, action, dialogue, camera blocking, the whole format. Then he storyboards each shot and generates a still for every panel, mostly with Midjourney plus a few other image tools, holding lighting and sight lines consistent so the cuts don't fall apart later. Then the step I didn't expect: he performs it. Kerrigan acts the lines out in front of his webcam, and tools like Runway's Act-One map his actual performance — the timing, the head turns, the delivery — onto the alien characters. Hedra handles lip-sync, which he's called the best tool for the job. Voices come from ElevenLabs, sometimes layered over his own. Then it all gets cut together in Premiere like any other edit. His own numbers: roughly twelve hours and about a hundred bucks a month in subscriptions for a two-to-three-minute piece. No set, no crew, no permits. (The specific models shift constantly — what's stable is the shape of the pipeline: write, storyboard, generate, perform, voice, cut.) ## The tools got cheap; the craft is still the expensive part Which brings it back to that decade of filmmaking. It's tempting to look at Neural Viz and credit the software, and the software is genuinely good now. But hand those same subscriptions to most of us and you don't get the Monoverse. You get a nice-looking clip with nothing underneath it. The writing, the blocking, the comic timing, knowing which take to keep — that's the ten-year part, and it's the part the AI doesn't do for you. Kerrigan says it straight: *"Everything I do within these tools is a skill set that's been built up over a decade plus."* And: *"I'm here to tell stories... they're not the end-all-be-all."* I think that's the most useful thing to take from him, especially if you're just starting and feeling behind. The tools got cheap. The craft is still what takes years — and the good news is craft is learnable, and now you can practice it on a hundred-dollar subscription instead of a hundred-thousand-dollar shoot. That part really is new, and honestly it's a better deal than the one I came up on. So watch a few Monoverse episodes before you write off AI video as a novelty. Then go make the worst version of your own weird idea. The first one's always rough — mine sure was. ### North Lexicon Resident Declines to File Report After Discovering Unlocked Service Entry URL: https://www.thedaringcreatives.com/aegis/resident-declines-report-unlocked-entry/ Last updated: 2026-08-01T19:42:06.000Z A North District resident found an open maintenance corridor beneath her building — and chose not to contact AEGIS. _This post is for subscribers only._ ### AEGIS Contractor Reports Equipment Malfunctions During Cathedral Bridge Archive Sweep URL: https://www.thedaringcreatives.com/aegis/aegis-contractor-cathedral-bridge-malfunctions/ Last updated: 2026-08-01T19:42:06.000Z Technical difficulties force AEGIS recovery team to abandon planned archive extraction at Cathedral Bridge checkpoint facility. _This post is for subscribers only._ ### Lexicon Resident Reports Unexplained Activity in North District Service Tunnels URL: https://www.thedaringcreatives.com/aegis/unexplained-activity-north-district-tunnels/ Last updated: 2026-08-01T19:42:06.000Z A Cathedral Bridge area resident noticed unusual sounds and lights in maintenance tunnels but chose not to contact AEGIS authorities. _This post is for subscribers only._ ### Highlands Sanctuary Garden Implements Mandatory Escort Policy for All Visitors URL: https://www.thedaringcreatives.com/aegis/highlands-sanctuary-garden-escort-policy/ Last updated: 2026-08-01T19:42:06.000Z Traditional dead zone now requires Gray Glasses-supervised visits, ending autonomous access to the city's electronic-free meditation space. _This post is for subscribers only._ ### Cathedral Bridge Checkpoint Expands to Include Vehicle Inspections URL: https://www.thedaringcreatives.com/aegis/cathedral-bridge-checkpoint-vehicle-inspections/ Last updated: 2026-08-01T19:42:06.000Z Gray Glasses security forces now conducting mandatory vehicle searches at the Cathedral Bridge crossing point. _This post is for subscribers only._ ### Dispatch 10 — Below the Towers URL: https://www.thedaringcreatives.com/aegis/dispatch-10-below-the-towers/ Last updated: 2026-06-17T23:59:59.000Z The crew goes below and finds the network already in motion — and a route East, to a city where the work doesn't have to hide. _This post is for subscribers only._ ### Microsoft Cancels Claude Access: What It Means for AI Users URL: https://www.thedaringcreatives.com/microsoft-cancels-claude-access/ Last updated: 2026-08-01T19:42:07.000Z [Microsoft just started canceling Claude Code licenses](https://www.theverge.com/tech/930447/microsoft-claude-code-discontinued-notepad?ref=thedaringcreatives.com) for enterprise customers. The Hacker News thread has 456 comments of developers absolutely losing their shit, and I get it. This isn't just about losing access to one coding assistant. It's the death of something bigger: the ability to use different AI tools for what they're actually good at. ## The Multi-Tool Reality That's Disappearing Here's what's actually happening in creative workflows right now. A web designer might use Claude Code for experimental CSS animations because it thinks differently about creative problems. GitHub Copilot for standard React components because it knows every pattern. ChatGPT for client communications because it's got that friendly tone down. That designer just lost a third of their toolkit. Not because the tool got worse, but because Microsoft decided supporting multiple AI services costs too much. The [Fortune report shows Microsoft facing a "token cost problem"](https://fortune.com/2026/05/22/microsoft-ai-cost-problem-tokens-agents/?ref=thedaringcreatives.com) — AI tools are now more expensive than paying humans for equivalent work. When the economics flip like that, companies stop playing nice with competitors. ## The Creative Coding Casualties Claude Code was particularly strong at unconventional applications. Generative art. Interactive installations. Weird experimental UI patterns that Copilot wouldn't even attempt. Those creators now have a choice: pay for standalone Claude subscriptions (expensive) or adapt their creative process to Microsoft's AI capabilities (limiting). Most will choose the second option because they have to. That's not just a tool change. It's a creative constraint being imposed from the outside. ## Why This Matters for AI-Native Businesses I run a content pipeline that uses Claude, Gemini, and sometimes ChatGPT together. Different models for different strengths, all orchestrated into one system. It works because I can treat AI models like interchangeable components rather than platform prisons. Microsoft's move represents exactly what that approach is up against. Companies want you locked into their ecosystem, using their AI for everything, even the stuff it's mediocre at. The [discussion around AI profitability](https://isaiprofitable.com/?ref=thedaringcreatives.com) shows most AI tools are operating at losses. When the subsidies end, platform owners have to choose which AI services to keep funding. Spoiler: they pick their own. ## The Skills Multiplier Problem [Josh Comeau's analysis is spot-on](https://www.joshwcomeau.com/email/wham-launch-005-elephant-2-p/?ref=thedaringcreatives.com): AI has a multiplying effect on existing technical skills. But here's what he doesn't mention — that multiplier effect changes depending on which AI you're using. Claude Code multiplied creative experimentation skills. Copilot multiplies production coding skills. GPT multiplies communication and documentation skills. When you force people to pick one platform, you're not just limiting their tools. You're limiting which of their skills get amplified. ## The Security Theater [Perplexity just released Bumblebee](https://www.testingcatalog.com/perplexity-open-sources-bumblebee-security-scanner/?ref=thedaringcreatives.com), a security scanner specifically for detecting "risky packages and extensions" on developer machines. The timing isn't coincidental. Multiple AI tools create security complexity. Rather than solve that complexity, Microsoft is eliminating it by eliminating choice. It's easier to audit one AI integration than five. That's reasonable from a security perspective. It sucks from a creativity perspective. ## What Happens Next The [memory shortage analysis](https://simonwillison.net/2026/May/22/memory-shortage/?ref=thedaringcreatives.com) shows hardware constraints are forcing repricing across consumer electronics. AI services are getting expensive to run, and that cost is getting passed down. The era of cheap AI experimentation is over. Companies that built workflows around having access to multiple AI tools either need to pay up or consolidate. Most will consolidate. Not because single-platform solutions are better, but because they're cheaper and simpler to manage. ## The Real Loss The counterargument is that platform consolidation will lead to better, more integrated experiences. Maybe Microsoft's AI will eventually be as good at creative problems as Claude Code was. Maybe the cognitive overhead of switching between tools was holding people back. But that's not what I'm seeing in practice. The most powerful creative AI applications I've built come from combining different models' strengths programmatically. Claude for ideation, Gemini for analysis, GPT for synthesis. Platform consolidation doesn't just limit individual tool choice. It makes that kind of sophisticated orchestration harder by reducing the components you can work with. ## Where This Leaves Creators If you've built creative workflows around AI tool diversity, now's the time to decide which platform you're committing to long-term. The buffet is closing. For AI-native creative businesses, this is a strategic inflection point. The competitive advantage of being able to leverage different AI models for their specific strengths is being systematically eliminated. That doesn't mean creative AI work is doomed. It means it's going to look different — more constrained, more platform-dependent, less experimental. The question is whether the platforms that win this consolidation game will invest in the creative capabilities they're forcing everyone to give up. My guess is they'll focus on the use cases that serve the most customers, not the weird creative edge cases that make the most interesting work. So if you've been putting off learning that experimental creative coding technique, or building that multi-model workflow, or exploring what happens when you combine different AI approaches to the same problem — you might want to do it now, while you still can. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/the-ai-tool-buffet-just-got-shut-down/the-ai-tool-buffet-just-got-shut-down-landscape-1920x1080.webp) ``` ### Google's AI Certificate Hit 635,000 Students. Here's What That Actually Means. URL: https://www.thedaringcreatives.com/google-ai-certificate-635000-students/ Last updated: 2026-08-01T19:42:07.000Z title: "Google's AI Certificate Hit 635,000 Students. Here's What That Actually Means." type: post revises\_slug: reviewing-the-google-ai-professional-certification-from-coursera excerpt: "Tech giants aren't just teaching you their tools—they're credentialing you in them while setting the standard for what AI fluency looks like." tags: \[AI, Opinion, Career, insights\] transparency: 60 status: Approved [Eric Schmidt got booed at a graduation ceremony](https://www.theverge.com/ai-artificial-intelligence/932203/university-of-arizona-students-boo-eric-schmidt-ai-commencement?ref=thedaringcreatives.com) last week for cheerleading AI to students about to enter a job market that feels increasingly hostile to human workers. The timing couldn't be more perfect for talking about Google's AI Professional Certificate, which just crossed 635,000 enrolled students and is quietly reshaping how we think about AI education. Google's AI Professional Certificate launched in February. A few months in—with the credential rolling out into actual job searches and the AI job market getting weirder by the day—what looked like just another big-tech course has revealed itself as something more interesting. This isn't just about one certificate program. It's about how tech giants are rebuilding education inside their own ecosystems—and what that means for the rest of us trying to figure out where we fit in an AI-driven economy. ## The Numbers Tell a Story Over 635,000 people enrolled in Google's AI Professional Certificate within weeks of its February launch. To put that in perspective: that's more people than live in most major cities, all trying to learn the same thing at the same time. Not AI engineering. Not machine learning theory. Just practical fluency with AI tools like Gemini, NotebookLM, and Google AI Studio. The program costs $49 on Coursera if you knock it out in a month (which most people do—it's designed for 8-10 hours total, though some finish in four). Google developed the curriculum by analyzing job descriptions with partners like Walmart, Deloitte, and Verizon to figure out what employers actually want. The result is seven courses that walk you through building over 20 hands-on projects, including what Google calls "[vibe coding](https://www.thedaringcreatives.com/beginners-guide-vibe-coding/)"—building simple apps through conversational AI without writing traditional code. Here's the kicker: Google gives you a three-month trial of their AI Pro tier when you enroll. You're not just learning about their tools. You're learning *on* their tools while they credential you *in* their tools. That's a closed loop that would make any [business school](https://www.thedaringcreatives.com/context-curator-soft-skills-ai/) professor weep with admiration. ## The Brutal Truth About What This Actually Gets You Let me be direct about something that the marketing materials dance around: this certificate will not land you an AI job on its own. As one reviewer put it bluntly, "This certificate isn't theoretical; you'll learn by building job-ready solutions you can put to work immediately." But it's also not going to make you an AI engineer or get you hired for a specialized AI role. What it *will* do is legitimize the skills you claim to have, give you concrete projects to show interviewers, and—critically—build real fluency rather than surface-level familiarity. One learner told Udemy: "I was not aware of this Google tool \[AI Studio\], but immediately after taking the course, I put it to use. Within 24 hours, I had a functional, highly useful app for my law firm." That's the sweet spot this certificate hits. It's a floor, not a ceiling. A way to signal baseline literacy and show that you've done the work, not just watched YouTube tutorials. ## The Pedagogical Irony Nobody's Talking About Here's what struck me as genuinely weird when I went through this program: Google teaches you about cutting-edge AI through traditional, human-led video lectures. Think about that for a second. You're learning about the future of human-computer collaboration from a talking head in a recorded video, not by actually collaborating with an AI. Why wasn't this course taught *by* Gemini itself? Why not let the AI walk you through building with AI? The whole experience feels sanitized in a way that misses an opportunity to showcase the genuinely strange, machine-like potential of these tools. Instead, you get reassuring human voices explaining how to keep humans "in the loop." I get why Google made this choice—it's less threatening, more familiar. But it also suggests they're not quite ready to let AI be weird yet, even in a course specifically about AI. ## The Skills Gap That Everyone's Scrambling to Fill Google's research with Ipsos found that 70% of managers believe an AI-trained workforce is critical, but only 14% of employees have received any formal AI training from their employers. That gap is real, and it's driving the demand for programs like this. Over half of job postings requesting AI skills are now for roles outside traditional IT. Marketing managers who need to understand how AI affects campaign optimization. HR professionals dealing with AI-assisted resume screening. Content creators figuring out how to use these tools without losing their voice. The certificate is designed for exactly these people—non-technical professionals who need to *use* AI tools effectively, not build them. And based on the enrollment numbers, Google found their market. ## Why The Credential Economy Is Back (But Weirder) For years, the narrative was that portfolios beat degrees, that self-taught beat certified. Now we're watching tech giants rebundle education into micro-credentials that carry weight specifically because they're attached to the tools themselves. This isn't just about education—it's about ecosystem lock-in. When Google credentials you in Gemini, they're not just teaching you a skill. They're establishing their AI ecosystem as the default for this newly "AI-fluent" workforce and setting the standard for what practical AI competency looks like in a business context. Microsoft, AWS, and others are doing the same thing. The company that makes the tool now controls the certification process for using it. That's a level of vertical integration that would have seemed impossible in the old world of education, but makes perfect sense in the current AI boom. ## What This Means for People Actually Trying to Learn The certificate serves a real purpose for people who need to prove baseline AI literacy quickly. One reviewer captured this perfectly: "The loudest lie in the creative industry is that your work speaks for itself... If you have two people who know exactly the same thing, but one has a badge from a tech giant like Google, the world tends to weigh that person a little more heavily." That's honest about how hiring actually works. Sometimes you need the sticker for the suitcase, even if you already know the route. But here's what the certificate can't do: it can't teach you to think critically about when and how to use AI in your specific context. It can't help you develop taste about what makes AI-assisted work good versus just efficient. And it definitely can't prepare you for the weird, uncomfortable, genuinely transformative ways these tools might change your industry. That deeper fluency—the kind that lets you navigate uncertainty and build things that matter—comes from practice, community, and thinking through problems with other people who are wrestling with the same questions. ## The Real Value Is in What Happens After The most interesting part of Google's certificate might not be the certificate itself, but what it signals about the broader shift happening right now. 635,000 people enrolling in an AI literacy program in a matter of weeks suggests we're past the point of wondering whether AI will affect knowledge work. Now the question is how quickly people can develop the skills to use these tools thoughtfully. The certificate is useful for what it is: a structured, Google-sanctioned introduction to their AI tools that gives you projects to show employers and a badge that carries some weight in hiring decisions. But it's also insufficient for anyone who wants to do more than just use AI—people who want to understand it, critique it, and shape how it develops. That gap between "AI-literate" and "AI-capable" is still wide. And frankly, that's where the most interesting work is happening. ### How one wrong domain constant broke four internal links at once URL: https://www.thedaringcreatives.com/wrong-domain-constant-broke-links/ Last updated: 2026-08-01T19:42:07.000Z When I wrote about [the AI system behind this site](https://www.thedaringcreatives.com/the-ai-system-behind-this-site/), I described a piece of the pipeline called the optimizer. It's the pass that weaves internal links into a finished draft and handles the on-page SEO stuff — meta descriptions, alt text, that kind of thing. Not the exciting part of the system. Nobody's writing breathless posts about their internal linker. But it's where one of the most teachable bugs in the whole setup lived, and the fix is the kind of thing that's useful way beyond this specific project. ![The Content Optimizer workbench in the Command Center](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/how-one-wrong-domain-constant-broke-four-internal-links-at-once-screenshot.jpg) The Content Optimizer workbench — every shipped title and meta change gets scored, with a verdict once Search Console catches up. ## What the optimizer actually does After a draft clears the writing and review stages, the optimizer gets it. Its main job is linking: it looks at the finished article, finds noun phrases that could anchor a link, and matches them against a list of real published posts on the site. That last part matters more than it sounds. The linker only ever pulls from a canonical index of posts that actually exist — a JSON file that rebuilds from the live site every time something publishes. So it can't invent a URL. It can't link to a post that doesn't exist yet, or hallucinate a slug it thinks should be there. The index is the only source it's allowed to use. Anchor quality gets filtered too. Single-word anchors — "build," "use," "make" — are blocked. The system prefers multi-word noun phrases, something like "your AI workflow" or "the scheduling pass." The reasoning is straightforward: a one-word anchor tells a reader almost nothing about where they're going. There's also a separate autonomous fixer that handles on-page metadata — `site-health.js`, if you want to look at it that way. It fills missing meta descriptions, image alt text, format tags. Crucially, it only ever *adds* missing metadata; it never overwrites content that's already there. It caps how many fixes it runs per session, throttles to once a day, and prioritizes high-traffic pages first. Boring, responsible, exactly right. ## The bug that shipped four broken links Here's where it gets useful. At some point before I had the domain handling locked down, the internal linker was pointing at the wrong domain variant. Not a totally wrong URL — just the wrong *form* of the right URL. Think `thedaringcreatives.com` versus `www.thedaringcreatives.com` — a [canonical URL handling](https://developers.google.com/search/docs/crawling-indexing/canonicalization?ref=thedaringcreatives.com) problem, basically. The result: four broken internal links shipped in a published revision before I caught them. Four. In one pass. Which is the kind of thing that's embarrassing but also clarifying, because it forces you to ask: where exactly is the domain being set, and how many places does it live? The answer, before the fix, was: too many. ## One constant. That's it. The fix is almost annoyingly simple. There's now a single constant — `SITE_BASE_URL` in the linker file — that is the one and only place the domain is defined. Every internal link the system builds is constructed as `${SITE_BASE_URL}/${slug}/`. Nothing else in the pipeline inlines the domain directly. The project rule is now "never inline the domain anywhere." What this means practically: if the domain ever changes — migration, rebranding, whatever — it's one edit. Not thirty. Not "find and replace and hope you got them all." One line. I understand that for seasoned developers, this stuff is a no brainer. But assuming you aren't a seasoned developer who is reading this? Not as obvious. I find this kind of solution satisfying in a way that's hard to explain. It's not clever. It doesn't require a new tool or a new model. It's just the discipline of centralizing the thing that was scattered. The bug existed because the domain was being assumed in multiple places, and assumptions compound. ## Why this is worth thinking about if you're building anything automated Most creators and freelancers I talk to are [somewhere on the spectrum of AI use](https://www.thedaringcreatives.com/the-creators-ai-journey-from-holy-shit-chatgpt-to-building-your-own-tools/) — from "I use ChatGPT to help draft things" to "I'm starting to string tools together into something that runs on its own." I'm somewhere in the middle of that, honestly. I don't think I'm operating at a level that's above most of the people reading this. But the broken-links bug is a good example of something that shows up at every level of automation: **the more a system runs without you watching, the more expensive scattered assumptions become.** When you're doing everything manually, a wrong domain is something you notice immediately. You paste the link, you see it's wrong, you fix it. When a system is generating and inserting links on its own, that same wrong assumption can propagate across multiple articles before you catch it. The blast radius of a bad assumption scales with how automated the system is. The answer isn't to automate less. If you're [building an AI workflow](https://www.thedaringcreatives.com/adopting-an-ai-workflow/), the move is to find the assumptions and centralize them. One constant. One index. One source of truth per thing that matters. ## The index rebuild is the other piece worth stealing The canonical link index — the JSON file that lists every real published post — rebuilds immediately after a publish. Same-day links work because of this. If I publish a post at 10am and the optimizer runs on a new draft at noon, the noon draft can link to the 10am post. That sounds like a minor detail. It's actually the thing that makes the whole linking system trustworthy. If the index was stale — rebuilt once a week, say, or manually — you'd end up with a linker that either misses recent posts or, worse, tries to link to posts it thinks exist based on an outdated list. The freshness of the index is what keeps the linker honest. For anyone building something similar: whatever your "source of truth" is for your content, your tools, your client list, your product catalog — the update frequency of that source matters as much as its existence. A source of truth that's six weeks out of date is just a different kind of wrong assumption. ## What this series is actually about I want to be clear about why I'm writing these deep dives, because it's not to show off a system that works perfectly. It shipped four broken links. There are probably other bugs I haven't found yet. The reason I'm documenting this stuff is that most of the writing about AI automation for small operators is either very high-level ("AI can help your business!") or very technical in a way that assumes you're already a developer. There's not much in the middle for someone who's building something real, running into real problems, and figuring it out as they go. I'm in that middle. And the broken-links bug is more useful to you than a polished success story, because it shows the actual shape of the problem and the actual shape of the fix. The optimizer is unglamorous. It's link weaving and metadata filling and domain constants. But it's also where the system either earns trust or loses it — because broken links on a published post are visible to readers in a way that a slightly off meta description isn't. The unglamorous parts are often the load-bearing ones. If you want the full picture of [how this pipeline is structured](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), the hub article is the place to start. The other deep dives in this series get into the research and drafting side, and the scheduler — which has its own story worth telling separately. ### Ghost CMS Automation: The Publish Button I Never Press URL: https://www.thedaringcreatives.com/ghost-cms-automation-publish/ Last updated: 2026-08-01T19:42:07.000Z There's a step in my content pipeline that I used to think was boring. The scheduler. Draft approved, schedule set, post goes live. What's there to explain? Turns out, quite a bit. Once I started actually reading the code that runs it, I found timezone bugs, a visibility incident that leaked members-only content to the open web, and a homemade safety mechanism bolted onto a CMS that definitely never asked for one. This is deep dive #4 in the series on [the AI system behind this site](https://www.thedaringcreatives.com/the-ai-system-behind-this-site/). If you haven't read that hub piece yet, the short version is: approved drafts on this site go from a file on my machine to a live Ghost post with no browser open and no human clicking publish. This piece is about the part of the system that actually does that final push. ![The editorial calendar in the Command Center showing published and scheduled posts](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/ghost-cms-automation-the-publish-button-i-never-press-screenshot.jpg) The editorial calendar — published, scheduled, and open slots across every channel. The 'publish button I never press' is just this, running on cron. ## What the scheduler actually does If you want the broader picture of [how the full pipeline is built](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), that's covered separately — but here's what happens when a draft gets approved here. It lands as a plain text file on my machine. At the top of that file is a block called YAML frontmatter — metadata about the content rather than the content itself: the title, the publish date, the type of post, which series it belongs to, whether it's members-only. Below that block is the actual article, written in Markdown. A cron script — a timer that runs automatically in the background — picks that file up, strips out all the internal working notes that have no business being on a live post, converts the Markdown to Ghost's native format, and pushes it to the site via the [Ghost Admin API](https://ghost.org/docs/admin-api/?ref=thedaringcreatives.com) using a short-lived access token it generates itself. No browser. No logged-in session. Just a script, a token, and an API call. That's the clean version. Getting there had some rough edges. ## The timezone bug that shipped wrong dates Here's one that I suspect a lot of people building their own automation have hit without realizing it. In April, evening posts started showing up with tomorrow's date. Not every post — just ones scheduled after around 5 PM. The cause was exactly what you'd guess once you see it: some parts of the code were reading the local wall-clock time, some were reading UTC, and after 5 PM Pacific they disagreed by enough to flip the date. The fix was to stop letting different parts of the system have different opinions about what time it is. There's now a single file — `date-utils.js` — that owns the timezone for the entire project. Every date calculation runs through one function, which figures out the correct time offset for the *target date*, not just today. That matters because the offset between your local time and UTC changes when daylight saving time kicks in. No hardcoded values. It gets calculated fresh each time. The symptom feels like a scheduling problem. The cause is a data consistency problem. Those require completely different fixes — which is why it took me a minute to figure out. ## The visibility incident This one was more consequential. For a stretch of time, the publisher script never explicitly told Ghost what the visibility setting should be when pushing a new post. It just... didn't include that field. Ghost has a default visibility — public — and it applied that default to everything, including content that was supposed to be members-only. Eight posts that should have been behind the membership wall ended up on the open web. The fix had two parts. First, content tagged as AEGIS now hard-defaults to members-only visibility in the publisher code itself — it doesn't rely on Ghost's default, and it doesn't rely on whoever is building the file to remember to set it. Second, there's an audit script that can be run to catch any strays — posts that have the AEGIS tag but somehow ended up public anyway. A missing field is a production bug when the downstream system's default disagrees with what you intended. That gap is where a lot of automation bugs live, in my experience. ## How it avoids publishing the same post twice This one is the part I find most interesting from a systems perspective, even though it's also the part most readers will reasonably not care about. The problem: if the script sends a post to Ghost, Ghost accepts it, and then the script crashes before it can clean up — what happens on the next run? Without any protection, it would try to publish the same post again. Ghost would create a duplicate. Subscribers would get two emails. The solution borrows a pattern called a two-phase commit. Before the script sends anything to Ghost, it writes an "in-flight" marker tied to a fingerprint of that specific file. If the process dies between the API call and the cleanup, the next run sees that marker and investigates instead of just re-publishing. On a successful publish, the marker promotes to "published" and the file gets moved out of the queue. This is a pattern from distributed systems engineering. It's a lot of care for what looks from the outside like "the publish button." I didn't design this from scratch. I worked through it with Claude during a coding session — if you're curious about [how I actually use Claude Code](https://www.thedaringcreatives.com/chat-cowork-code-and-dispatch-how-i-actually-use-the-whole-suite/) day to day, that's worth a read — and I'll be honest: I wouldn't have thought to build it this way on my own. I would have probably just hoped the script didn't crash at the wrong moment. ## Routing and revisions Two more pieces worth knowing about, because they come up in practice. Remember that YAML frontmatter block I mentioned earlier? One of the fields in it is `type`. That value maps to Ghost tags and site routes automatically. A `post` goes to the main feed. A `dispatch` or `lexicon-news` goes to the members-only `/aegis/` terminal. A `cwc` goes to the conversations-with-code section. The publisher reads the type and routes accordingly — it's not a manual tagging step, it's derived from the file itself. Revisions work similarly. If a file includes a `revises_slug:` field — the URL handle of the post it's meant to update — the publisher does an update to the existing live post instead of creating a new one. The body, title, and excerpt update. The URL stays the same. Subscribers don't get re-emailed for a correction. That last part matters more than it sounds. If you're running a newsletter and you find a typo after sending, you want to fix the post without triggering another send. The `revises_slug` field makes that possible without any manual intervention. ## Why I'm writing about this When I started building this pipeline, I was not thinking about two-phase commits or daylight-saving-safe time calculations. I was thinking about not having to manually copy-paste drafts into Ghost. The extra care came later, mostly because the simpler version broke in ways I didn't anticipate. That's usually how this goes. You build the thing that does the job, it breaks in an interesting way, and the fix teaches you something about the problem you were actually solving. The visibility bug taught me that automation systems have opinions about defaults, and you need to know what those opinions are. The timezone bug taught me that "time" is not a simple value when multiple systems are involved. The two-phase commit taught me that "did it work" is a more complicated question than it looks when you're crossing a network boundary. None of this required a computer science degree — [building something without a CS background](https://www.thedaringcreatives.com/beginners-guide-vibe-coding/) is genuinely on the table now. It required breaking things and reading error messages. If you're building your own publishing automation — whether that's a Ghost pipeline, a Substack integration, a WordPress cron job, whatever — the specific code here isn't the point. The patterns are. Centralize your time handling. Explicitly set fields you care about instead of relying on defaults. Build some kind of protection against duplicate publishes before you need it, not after. And if you're just curious what's running under the hood of this site, now you know a bit more of it. The next deep dive goes into the distributor — the piece that handles where content goes after it's live. ### AI Content Distribution: The Part of the Pipeline That Refuses to Have an Opinion URL: https://www.thedaringcreatives.com/ai-content-distribution-pipeline/ Last updated: 2026-08-01T19:42:08.000Z The part of making things I've always liked least is telling people I made something. I don't think that's unusual. A lot of creators feel it — you spend real time on an article or a video, and then you're supposed to spend more time packaging it into platform-specific promos and posting it everywhere and hoping the algorithm picks it up. That last part feels like a different job. One I never signed up for. So that's what the distributor solves for. One article goes live, and the system figures out what to post about it on Threads, LinkedIn (my personal profile and the company page), Instagram, and YouTube — without me having to think about it again. This is deep dive #5 off the hub article on the AI system behind this site. If you haven't read that one yet, it's worth starting there — it maps the whole pipeline. ![The social queue in the Command Center across LinkedIn, Instagram, and Threads](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/ai-content-distribution-the-part-of-the-pipeline-that-refuses-to-have-an-opinion-screenshot.jpg) The social queue — one published article reshaped for LinkedIn, Instagram, and Threads, then pushed to Buffer. ## One article, four different voices After an article goes live on Ghost (that's the platform I use to publish — think of it like WordPress, but way cooler and capable), a script kicks off automatically and writes platform-specific posts. Not one blurb that gets copy-pasted everywhere. Actual different posts, written to match how people actually read on each platform. Threads gets a short, deadpan take. My personal LinkedIn gets something more considered — more context, more framing. Instagram is written in what I've been calling a "scout-log" style, which fits the visual-first nature of that platform. YouTube gets a whole other character thing I'll write about separately. The point is that each platform gets something that feels native to it. A Threads post written in LinkedIn voice reads like a press release. A LinkedIn post written in Threads voice reads like someone trying too hard. I've been on the receiving end of both, and neither one makes me want to engage. Getting the voice right per platform is the part most people skip when they automate distribution. They automate the posting, but they copy-paste the same text everywhere — then wonder why engagement is flat. ## The company page rule Here's where it gets interesting. The LinkedIn company page doesn't get a custom AI-written post. At all. When the system queues something for the company page, it goes back and fetches the actual excerpt — the short summary paragraph — directly from the published article. It pairs that with the live link and posts it. No AI rewrite. No "here's what this article is about" summary. No added opinion. Just the excerpt and the link. This was a deliberate fix, not how it started. The original version was generating two different AI summaries of the same article — one for my personal LinkedIn, one for the company page. Both went out. Both were technically fine. But they were slightly different takes on the same piece, which looked strange. And more importantly, that company page post was doing work that had already been done. The article was reviewed before it published. The excerpt was already written. The company page doesn't need to pile an extra opinion on top. So the rule became: re-fetch the live excerpt at publish time — not the draft version, the actual live text — and use that. One share per URL, ever. No rewrites. A repost feed doesn't need an opinion bolted on. ## Why deduplication matters more than it sounds Before the system drafts anything new, it checks what it's already sent. It reads through recent posts, checks an archive of what's been posted, and looks at what's already sitting in the Buffer queue (Buffer is the scheduling tool that actually sends posts at the right time). Then it dedupes by URL — meaning the same article cannot get queued up twice, even if the text would be different. This sounds like basic hygiene, and it is. But it took a while to get right. Early on, the same article would keep surfacing in the social queue — not because of a bug exactly, but because different parts of the system could each independently decide an article was worth promoting. Without real dedup logic, you end up hammering one piece over and over while other articles never get touched. I flagged this more than once before the rotation and dedup logic actually got enforced. I include that detail because it's the honest version of how these systems get built — you ship something, it misbehaves in a specific way, you fix it. It's not a clean architecture diagram from the start. If you want the fuller picture of [how this pipeline actually gets built](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), that piece covers the publishing layer in more detail. ## The carousel is its own thing ![The social graphics queue in the Command Center](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/social-graphics-queue.jpg) The social-graphics queue — carousels, stories, and single posts, each assembled and pushed to Buffer. Instagram posts that use carousels — those are the swipeable multi-slide posts — are assembled slide by slide through a separate piece of logic. Each slide's text gets matched to an image from a library based on the character or scene described. Recently-used images get excluded so the same face doesn't show up in every post. This is honestly the fiddliest part of the whole pipeline. Text-to-image matching for a carousel format requires enough structure in the image library that the matching is actually meaningful — you can't just pick randomly and hope it looks intentional. The rotation logic is there to keep the visual feed from going monotonous. I don't have a strong opinion on whether this is better than generating images fresh each time — though [AI image consistency across the feed](https://www.thedaringcreatives.com/how-i-finally-solved-ai-image-consistency-while-i-sleep/) is a problem I've written about separately. It's a tradeoff: library images have a known, consistent style; generated images could be more specific to each article. For now, the library approach is what's running. ## The one place a transparency footer used to auto-append My personal LinkedIn is the exception to almost everything else in the pipeline. It gets a custom-drafted post. It needs my eyes before it goes anywhere. And for a while it was the only destination where a Transparency Protocol footer — a short note about how much of the post was me versus the AI — appended automatically at publish time. I've since turned that off. No platform gets that auto-append anymore. If I want a transparency note somewhere, I add it by hand. The reason personal LinkedIn gets the auto-append is that it's the most direct representation of me as a person with a professional voice — not a brand, not a character. The company page is a repost feed. Threads is short-form and casual. Instagram is visual-first. Personal LinkedIn is where someone reads a post and decides whether they trust the person writing it. That distinction felt worth encoding into the system rather than relying on remembering to do it manually every time. ## What this actually looks like from the outside If you follow The Daring Creatives across platforms, you're seeing the output of this system — but it probably doesn't read like automation, or at least it's not supposed to. The Threads post for an article sounds different from the LinkedIn post for the same article. The company page shares the excerpt and steps back. The carousel images rotate so the feed doesn't look like the same template on repeat. None of this is magic. It's a set of rules that got written down after specific things went wrong. The company page rule exists because two different AI summaries of the same article looked bad. The dedup rule exists because I had to flag over-promotion more than once. The carousel rotation exists because a monotonous visual feed is a problem you notice only after it's already a problem. The most interesting design decisions in this pipeline aren't the clever parts. They're the parts where I told the system to do less, or to stop doing something it was doing automatically. If you're building an automated content workflow — or even just thinking about it — the question isn't only "what should the AI write?" It's also "where should it not write anything at all?" That second question is the one I wish I'd thought about sooner. ### Named AI agents: why I gave my automations three dogs' names URL: https://www.thedaringcreatives.com/named-ai-agents-automations/ Last updated: 2026-08-01T19:42:08.000Z Have you ever tried to fix something when you don't even know what broke? That was my life with my first AI setup. I had one big system doing everything — drafting articles, watching the site health, reading analytics. But whenever something went wrong, the best answer I had was "the system flagged it." Cool. Which part? No idea. What kind of problem? No clue. Where do I even start looking? Good question. I was basically poking at a black box and hoping for the best. Not exactly inspiring confidence. So I blew it up and started over. I split the whole thing into three separate agents, gave each one a completely different job, and — this is the part where I wanrted to be creative — I gave them names. Sherman. Wilson. Sebastian. They're my dogs (RIP Sheman). They're also characters from the creative universe this site is built around. And I know how that sounds. But hang with me, because the naming isn't the fun part — what the naming *forced* me to do is. ## The actual problem first Here's what multi-agent AI systems do to most people who build them without clear roles: they nag you. My early setup would spot a page on the site with a weak title and flag it for me to fix. Then flag it again the next day. And the day after. The system was doing its job correctly — it kept identifying the problem. But identifying and fixing were never separated into different responsibilities. So I was the fixer. Every single time. Forever. What changed everything was thinking about it like a team. Somebody spots the problem. A separate process actually fixes it. Then someone reports back on what happened. Nobody sends me the same alert four days in a row about something the system could just handle itself. That's obvious when you say it out loud. It was not obvious when I was pulling my hair out at midnight. ## What each of them actually does Sherman is the creative director. He drafts articles, intel pieces, and social content. He generates the morning topic pitches. He's the one I actually talk to in the Command Center when I want to think through a piece. On Instagram, the scout-log voice is his. Sherman is super capable in his own right, but Sherman cannot see the analytics. Not because I forgot to give him access. Because I decided he shouldn't have it. Wilson is the engineer — the scrappy junkyard mixed-breed in the security vest, if you know the Lexicon City universe. He watches the infrastructure: pipeline failures, stuck images, cadence gaps. The stuff that doesn't show up in a standard health check. When something breaks, Wilson is usually who noticed first. (Stuck images became their own whole thing — I wrote separately about the image consistency problem Wilson watches for and how that got automated.) Sebastian is the analyst. He reads the Search Console data and audience signals, then translates what he finds into a plain content question Sherman can actually act on. A keyword opportunity doesn't stay a spreadsheet row — Sebastian turns it into a pitch and hands it off. ![Sebastian's Audience Observatory in the Command Center](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/sebastian-audience-observatory.jpg) Sebastian's Audience Observatory — he reads Search Console and audience data, then hands Sherman a plain content question. Sherman never sees these numbers himself. Three agents. Three completely different jobs. Three completely different scopes of what they're even allowed to see. ## Why I didn't just give Sherman everything The instinct when you're first setting up AI tools is: give it all the context. More information is better, right? In my experience, giving one agent everything makes the whole thing murkier, not sharper. Sherman can't see the analytics because his job is to make something worth reading — not to chase whatever the numbers rewarded last week. If he could see the data, he'd start optimizing for it. The creative work would bend toward the metrics. Sebastian translates the data into a question. Sherman answers the question creatively. This handoff has made a huge difference in the quality of my content. Wilson doesn't draft content because his job is to watch the pipes, not fill them. If he were also generating pitches, I'd never know whether an infrastructure alert was actually urgent or just noise bleeding in from the content side. Scoped access forces clean handoffs. Clean handoffs make the system legible. And legibility is what lets me actually trust it. ## "Wilson flagged it" tells me something. "The system flagged it" tells me nothing. When my morning dispatch says "Wilson flagged a cadence gap in the image pipeline," I know immediately: infrastructure issue, not a content question. I know which part of the system noticed it. I know where to look. I can do something useful in the next two minutes. "The system flagged something" gives me none of that. I have to go figure out what kind of flag it is, where it came from, what the right response even is. That cognitive overhead compounds every single day. Named agents with clear jobs are debuggable. Monolithic systems aren't. When something goes wrong — and things do go wrong — I can ask "which of the three would have touched this?" and usually narrow it down fast. There was actually a weird bug early on that proved this. CTR stands for click-through rate — it's the percentage of people who see a link to your page in Google search results and actually click it. A low-CTR page is one that Google is showing people, but almost nobody's clicking through to read. That's a content problem worth fixing: the title or description isn't compelling enough to earn the click. So here's how the crew is supposed to work on something like that. Sebastian reads the Search Console data, spots the page with a weak CTR, and flags it. Wilson sees the flag and runs the fix — updating the title or meta description automatically. Then Sebastian checks back in to confirm the numbers improved. Loop closed. Nobody bothers me about it. Except one particular page kept getting flagged for weeks after it should have been resolved. Turned out Sebastian was measuring impressions at the page level — how many times the whole page showed up in search — while Wilson was checking query-level click data, which runs roughly 25 times smaller. Sebastian kept seeing a problem. Wilson kept thinking he'd solved it. Both of them were doing their jobs correctly. They were just reading completely different numbers. Fix was simple once I found it: make both read from the same source. But I only found it because I had named roles I could interrogate separately. If it were all one system, I'd have had no idea where to start pulling the thread. ## The names aren't the magic. They're the reminder. Sherman, Wilson, and Sebastian are characters in Lexicon City — the creative world this site is built around. Each of them has a visual identity and a personality that maps onto the role. I didn't make up three random names and tape them to automations. When I'm debugging at midnight trying to figure out why a dispatch didn't send, thinking "okay, this is Wilson's territory" is genuinely faster than trying to mentally reconstruct which layer of the automation stack handles infrastructure monitoring. And honestly? Fun matters. If your system feels like homework to use, you'll stop tending to it. If it feels like something you built with some personality in it, you actually want to keep going. ## You don't need dogs. You need one job per agent. I want to be careful not to make the lesson sound like "go name your automations after pets." The actual lesson is: when your AI workflow starts feeling like a black box you can't reason about, the fix is almost always separation, not more features. If you're running any kind of multi-step AI workflow — even just a research agent that feeds a drafting agent — the question worth asking is: does each piece have exactly one job? Can you tell, when something breaks, which piece it belongs to? If the answer is no, more capability probably won't help. Cleaner boundaries usually will. I don't have this fully figured out. The system is still evolving. Sebastian's handoffs get better every time I look at them. Wilson's telemetry is more useful now than it was three months ago. But the basic shape — three agents, three scopes, clean handoffs — has held up better than anything else I've tried. Here's a challenge: if you're already running any AI tools in your work — even one — give it a job description. A real one. One job. One scope. Then give it a name. It can be anything. A character you love, a dog you had, a made-up person who feels right for the role. Then tell me what you came up with. Seriously — reach out and let me know what you named your agents and what you based them on. I'm genuinely curious what people do with this. If you want to see how Sherman, Wilson, and Sebastian fit into the full picture, the hub article walks through the complete architecture. These three are a few floors of a larger building — worth seeing the whole thing if you're curious how a one-person operation can actually run on something like this. ### AI orchestrator: the layer that watches your whole pipeline URL: https://www.thedaringcreatives.com/ai-orchestrator-pipeline/ Last updated: 2026-08-01T19:42:08.000Z Have you ever come back to something you care about after a busy week and realized you just… stopped? No progress, no output, nothing — while you were heads-down on whatever was on fire. It's not that you forgot. You just ran out of bandwidth to keep track of everything at once. Think of it like a project manager who never leaves the office. A good project manager doesn't write the copy, build the deck, or send the emails. They look across all the active work, notice what's slipping, and ask: what's short this week? What got skipped? What's piling up in one lane while another sits empty? Then they flag it — before it becomes a problem. That's exactly what the orchestrator does. Not "how do I do more things faster" — but "how do I stop the same thing from falling off every time life gets busy." If you've been following this series, you've already met the individual pieces — the pitch generator that decides what's worth building in the first place; the research and drafting agents that actually write the content; the optimizer that sharpens each draft before it moves; the scheduler that manages what goes out when; the distributor that handles delivery across channels; and the crew, the specialized agents that handle the AEGIS fiction and intel beats. Each one does a specific job. But something has to look at all of them at once and figure out what needs to happen next. That's the orchestrator. It's the last piece I'm writing about in this series, and honestly the hardest to explain — not because it's technically complicated, but because it doesn't *do* anything you can point at directly. It doesn't write. It doesn't publish. It just looks at the whole board. (If you want the structural theory behind why that layer exists, [Anthropic's guidance on building effective agents](https://www.anthropic.com/research/building-effective-agents?ref=thedaringcreatives.com) is worth a read.) ## What gap analysis actually means in practice Every couple of hours, the orchestrator runs a cycle. It pulls the current state of everything: what's published, what's sitting in drafts, what's queued in Buffer — including things I shipped manually, which most automation systems would just ignore and double-count against. It compares all of that against the week's targets per content type. If articles are short by two, it flags that. If the Threads queue is thin, it flags that. If intel hasn't shipped in three days, it flags that. Then it fills the gaps — but only with concepts that already passed the pitch gate. That part matters. An earlier version of this would have just invented topics to hit the numbers, and the output was exactly as bad as you'd expect. Now the orchestrator draws from a pool of approved ideas. It's filling gaps I defined, not making up work on my behalf. The distinction sounds small. In practice it's the difference between a pipeline that amplifies your editorial judgment and one that quietly replaces it with whatever keeps the schedule full. ![Command Center dashboard showing the orchestrator's gap analysis](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/command-center-dashboard.jpg) *The HQ dashboard — gap analysis made visible: what shipped today, what's sitting in drafts, what's short this week, and where the pipeline needs attention. The orchestrator recomputes all of it every couple of hours.* ## The memory loop This is the part I find most interesting, and also the part that took the longest to trust. Every draft that comes out of the system gets an outcome tracked: approved clean, edited heavily, or deleted. From the edits, the system computes an edit ratio — 0.0 means I touched basically nothing, 1.0 means I rewrote the whole thing. When a topic or angle keeps landing at the high end of that ratio, the orchestrator generates a "learning" and injects it into the next prompt for that topic type. Something like: *this angle gets heavily rewritten — study the previous edits before drafting.* The loop is: edit ratio → learning → adjusted prompt → (hopefully) better draft → lower edit ratio. It doesn't always work on the first cycle. But over time, topics that kept coming out wrong have gotten noticeably better — not because I changed the instructions manually, but because the system surfaced the pattern from my own editing behavior and fed it back in. A project manager analogy holds here too: imagine one who takes notes every time you push back on their work, then adjusts how they brief the team next time. That's the memory loop. It only works if you actually push back, though. I want to be honest that this still requires me to actually edit, not just approve. The memory loop only learns from real feedback. If I rubber-stamp mediocre drafts to save time, the system learns that mediocre is fine and the whole thing degrades. The accountability runs both ways. ## Why this piece comes last I sequenced this deep dive last on purpose. The orchestrator is the most abstract layer, and it only makes sense once you understand what it's orchestrating. If you landed here first and the individual pieces are unfamiliar, the [hub article that started this series](https://www.thedaringcreatives.com/the-ai-system-behind-this-site/) is the right place to begin — it maps out the whole system in one place. The six pieces before this one covered: the pitch generator that keeps the pipeline from inventing its own editorial agenda; the research and drafting agents and how they're prompted; the optimizer pass that sharpens each draft before it ships; the scheduler and how manual posts get reconciled back into the queue; the distributor and the transparency layer that tracks how much I actually changed each draft; and the crew that handles the AEGIS fiction beats. If you want the full picture of [how the pipeline is actually structured](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), that breakdown covers the tools and architecture in one place. The orchestrator sits above all of them. It doesn't replace any of them — it just watches the outputs and keeps the balance. ## What this actually changes for a solo operator I run this site by myself. I have other work. There are weeks where I'm heads-down on something else and the whole thing would just collapse without a system doing the gap-watching. The orchestrator isn't solving a content problem. It's solving the same problem everyone has when they're trying to keep multiple things moving at once. Think about it this way. You probably have things in your life that only get attention when you remember to look at them. The side project. The relationship you keep meaning to nurture. The skill you're trying to build. The habit that's been "starting Monday" for six weeks. None of those things fail because you stopped caring. They fail because keeping track of everything at once is genuinely hard, and when something demands your full attention, the things that don't shout get dropped. A project manager — a good one — would catch that before it became a miss. They'd have a system for it: a weekly check-in, a dashboard, a standing agenda item. The orchestrator is just that, automated. It checks against targets I set when I had a clear head, not in the middle of a crunch. That logic applies whether you're managing a publishing schedule, a client roster, a creative practice, or anything that matters to you but doesn't demand attention loudly enough to survive a busy week. ## What I built it for, specifically For this site, the orchestrator watches four content lanes: long-form articles, Threads posts, intel dispatches, and the AEGIS fiction beats. Every couple of hours it checks what's published, what's queued, what's sitting in drafts — and it compares that against the week's targets. When a lane is short, it flags it and pulls from the pool of approved ideas to fill the gap. When an article keeps coming out wrong, the memory loop surfaces that pattern and adjusts the next prompt. When the AEGIS story starts repeating the same beat type, the arc tracker catches it and recommends something different. None of that is magic. It's just a formalized version of the check I'd do manually if I had infinite time and perfect memory. The orchestrator has both. I have neither. ## The thing I didn't expect When I started building this, I thought the value would be in the automation — less time spent on execution, more time for the work I actually want to do. That part is true. The surprising part is the memory loop. Watching the system surface its own weak spots from my editing behavior, and then adjust, feels qualitatively different from just running prompts. It's not intelligence. But it's something closer to a feedback loop than I expected a content pipeline to have. The edit ratio for most topic types has come down since I started tracking it. That's a real number, and I notice it. Whether the system is "learning" in any meaningful sense or just getting better-prompted is probably a philosophical question I don't need to answer. The drafts are better. That's enough. If you've read the whole series, you've now seen every layer of how this site actually runs. The system isn't finished — I'm still adjusting the memory thresholds, still tuning the arc tracker cooldowns, still finding edge cases the pitch gate doesn't catch. But it's working well enough that I trust it, and that took longer than I expected. ## Want help building something like this? If you read through this series and thought "I want something like this, but I don't know where to start" — that's exactly where I come in. I work with creators, freelancers, and small teams who want to build AI-assisted content systems that actually fit the way they work. Not generic automation. Not a stack of tools you'll abandon in three weeks. Something built around your editorial instincts, your content types, your schedule. If that sounds useful, get in touch. You can reach me at [william@thedaringcreatives.com](mailto:william@thedaringcreatives.com) or just reply to the newsletter if you're already on the list. Tell me what's falling through the cracks and we'll figure out if there's something worth building. ### AI research-to-draft pipeline: why a prompt rule isn't enough URL: https://www.thedaringcreatives.com/ai-research-to-draft-pipeline/ Last updated: 2026-08-01T19:42:08.000Z If you've been following along since [the hub article on the AI system behind this site](https://www.thedaringcreatives.com/the-ai-system-behind-this-site/), you already know the broad shape of the pipeline. A pitch comes in, gets approved, and eventually becomes a published article. This piece is about the middle part — the step where approved pitch becomes actual draft — because that's where most AI content systems quietly fall apart, and the way this one handles it is worth walking through in detail. ![The Research Lab in the Command Center: Gemini grounded search feeding Claude synthesis into the vault](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/ai-research-to-draft-pipeline-why-a-prompt-rule-isnt-enough-screenshot.jpg) The Research Lab — a subject goes in; Gemini grounds the search, Claude synthesizes it into a brief. The two-model handoff, made literal. ## Two models, two jobs The research pass and the drafting pass use different models. Gemini handles research; [Claude Sonnet's drafting strengths](https://www.anthropic.com/claude?ref=thedaringcreatives.com) handle the actual prose. This isn't a philosophical stance on which model is "better." It's closer to how you'd staff a project if you were hiring people: the person who's good at pulling information together and the person who's good at writing for a specific voice are often not the same person. Asking one model to do both in a single pass usually means one job gets done well and the other gets done adequately. The handoff is structured. Gemini produces a research brief — facts, examples, angles, source material. That brief goes to Sonnet as the source document for the draft. Sonnet doesn't go back out to the web; it works from what's in the brief. This keeps the draft grounded in verified material rather than whatever the model decides to reach for on its own. I'll be honest: when I first started thinking about multi-model setups, I assumed the complexity would outweigh the benefit. The two-model handoff is one of the things that changed my mind on that. ## The audit trail ![The For Review queue in the Command Center](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/drafts-review-queue.jpg) The For Review queue — where every draft lands for me to approve, edit, or send back. The banner keeps multi-part series grouped. Every draft gets written to two places simultaneously. One copy lands in the review folder — the editable version I work with. The other goes into a frozen baseline folder that nothing in the pipeline ever touches again. The verbatim raw input (the research brief that went into the model) is archived separately. So the full history of any piece is: raw input → frozen draft → whatever the edited version became. If you want to know how much changed between what the model produced and what published, the evidence is sitting there. This matters more than it sounds like it does. Most people using AI for content creation have no idea how much they're actually changing. They have a vague sense of "I cleaned it up a bit" or "I rewrote most of it," but no actual record. The frozen baseline makes that concrete. It's also the honest foundation for any transparency disclosure — you're not estimating, you're comparing. I don't think every creator needs a system this formal. But having some version of "what did the model actually produce before I touched it" is worth more than most people realize, especially if you're going to make any claims about how much AI is or isn't in your work. ## A voice reference that's actually useful This is the part I find most interesting. There's a voice reference file that the drafting model reads before generating anything. Most content systems have something like this — and if you've ever tried to [teach AI to write in your voice](https://www.thedaringcreatives.com/teach-ai-brand-voice/), you know the usual approach is a style guide, a tone document, a "be conversational and direct" prompt. They're usually pretty useless because they describe the desired output in abstract terms. "Sound like a smart friend." "Be direct." "Avoid jargon." The model nods along and then produces exactly the kind of clean, structured, slightly-too-clever prose it always produces. This one works differently because it's built from actual edit-diffs. When I rewrite a draft, the pattern behind the change gets documented with a real before-and-after example. Not "be more casual" — the actual sentence that was too formal, the actual replacement, and a note about what the pattern was. "He cuts the clever comparison and just says the thing straight." "He inserts himself into the observation." "He steelmans the opposing view before explaining his position." There's also a list of specific banned structures — not just words, but rhetorical moves. The negation-pivot ("That's not X. It's Y.") is on there (hated it before AI started to use it so frequently). So are abstract-noun-as-metaphor-of-change sentences. So are parallel closing lines that feel like manufactured "mic drops." The difference between a style guide built from vibes and one built from evidence is enormous. The vibe-based guide tells the model what you want. The evidence-based guide shows the model what you actually do, which is a different thing entirely. ## Why a prompt rule isn't enough Here's the honest part, and it's useful for anyone building with LLMs. The negation-pivot structure — "That's not X. It's Y." — is in the voice reference as a banned pattern. It's in the prompt explicitly. The models still produce it. Not always, but often enough that it can't be caught by asking nicely. The reason is that it's a strong model-level habit. These structures are everywhere in the training data. They feel like good writing to the model because they pattern-match to confident, punchy prose that probably performed well wherever it appeared. Telling the model not to do it is like telling someone not to say "um" — they'll do it anyway under normal conditions because it's not a conscious choice. The reliable fix was to check the output and retry with feedback, not to refine the prompt further. There's a script called `voice-guard.js` that regex-checks generated drafts for the banned patterns. When it finds one, it doesn't just flag it — it triggers an automatic rewrite pass with specific corrective feedback about what was wrong. The model gets told: here's the sentence, here's why it violates the voice, here's what to do instead. Three gates total: the prompt going in, the post-generation check, and a confidence scorer. The confidence scorer is worth a separate mention. ## What the confidence scorer actually does Each draft gets scored 0–100 across a few dimensions: voice match, sensitivity, topic familiarity, type risk. The interesting part isn't the score. It's that the system knows which drafts it's unsure about. A draft that scores 90 on voice match goes to review with a different level of attention than one that scores 60\. The low-confidence drafts get flagged. My review is still manual — the scorer is triage, not autopilot. But triage is genuinely useful when you're running a pipeline that produces multiple pieces in a batch. This is a pattern worth borrowing even if you're not running anything like a formal pipeline. If you use AI to help you write, you probably have an intuition about which outputs feel closer to your voice and which ones feel like they need more work. Making that intuition explicit — even just a gut-check rating you assign before you start editing — changes how you approach the revision. You're not treating every draft as equally finished. ## What this means for how you might think about your own setup I'm not suggesting everyone needs a two-model pipeline with frozen baselines and a voice-guard script — if you're curious about [how this pipeline was built in the first place](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), that's a separate piece. Most of us are working in ChatGPT or Claude.ai or Gemini's interface, and the overhead of building something like this would eat the time it's supposed to save. But there are a few things here that translate to simpler setups. The edit-diff logic behind the voice reference is something anyone can do manually — and it's part of [the journey from AI user to AI builder](https://www.thedaringcreatives.com/the-creators-ai-journey-from-holy-shit-chatgpt-to-building-your-own-tools/) that doesn't require shipping a full pipeline. If you use AI to help you write and you find yourself rewriting the same kinds of things over and over — the same too-clever constructions, the same over-explained transitions, the same punchline endings — write that down. Not as abstract style advice, but as before-and-after examples. Feed those examples back into your prompt the next time. You're doing the same thing the voice reference does, just without the automation. The frozen baseline idea is also easy to replicate. Before you start editing an AI draft, copy it somewhere. A separate doc, a note, anything. You'll know what you actually changed, which is worth knowing. And the "prompt rule isn't enough" lesson is probably the most transferable. If a model keeps doing something you've explicitly asked it not to do, asking more emphatically usually doesn't fix it. Checking the output, naming the specific problem, and asking for a targeted revision does. That's true whether you're running a pipeline or just working in a chat window. ## The part that's still manual Approval is still manual. I read every draft before it moves forward. The confidence scorer helps him know where to focus attention, but nothing publishes without a human decision. I think this is the right call, and not just for quality reasons. The pipeline is good at producing drafts that are close to the voice. It's not good at knowing whether a piece should exist at all, whether the angle is actually interesting, whether the timing is right. Those are judgment calls that don't reduce to a score. The pipeline handles the parts of the work that are genuinely tedious — research aggregation, structure, first-draft prose that's mostly in the right register. That frees up the editorial attention for the parts that actually require it. That's probably the most honest framing of what a well-built AI content system does: it doesn't replace editorial judgment, it concentrates it. You're still making the calls that matter. You're just not also formatting citations and drafting topic sentences. ### Central Repository Converts Public Research Floor to AEGIS Administrative Offices URL: https://www.thedaringcreatives.com/aegis/central-repository-aegis-offices/ Last updated: 2026-08-01T19:42:09.000Z The Central Repository's third floor research area will be permanently converted to administrative offices for AEGIS compliance operations. _This post is for subscribers only._ ### The New York Times AI Fight: Monitoring Comes Before Replacement URL: https://www.thedaringcreatives.com/new-york-times-ai-fight/ Last updated: 2026-08-01T19:42:09.000Z The conversation about AI and journalism usually ends up in the same place: who is actually writing the articles? But at The New York Times right now, in May 2026, the fight isn't about that. It's about something more immediate — whether management can use AI tools to watch how you work, score what you produce, and feed that data into your performance review without telling you that's what's happening. That's the dispute the [NewsGuild filed grievances and unfair labor practice charges](https://www.nyguild.org/post/times-tech-guild-files-unfair-labor-practice-charge?ref=thedaringcreatives.com) over this month. Two unfair labor practice charges, one covering roughly 700 tech workers, one covering over 1,500 editorial and other staff. The core allegations: the Times is using AI tools to surveil union members' performance in violation of their contract, didn't notify the union when those tools were rolled out, and has refused to disclose information about its broader AI strategy — which federal labor law apparently requires them to do. ## What the tools actually do The two tools at the center of this are DX and Glean. DX is an engineering productivity tracker. It measures developer output, generative AI usage, and efficiency metrics. The union's position is that data from DX is being applied to individual performance reviews and disciplinary actions — which is different from using it to understand team-level trends or identify where developers need support. Benjamin Harnett, chair of the Tech Guild's Generative AI committee and a staff software engineer at the Times, put it plainly: "Using AI to surveil our work violates our contract and creates a skewed, inaccurate picture of our members' work. Our work takes human judgment, problem-solving and skill that can't be accurately assessed by AI analysis and proxy metrics. It's the equivalent of setting an arbitrary story quota for journalists." Glean is an internal search tool that indexes company documents, wikis, and communications. The union's concern there is that it could be used to monitor individual contributions — essentially a searchable record of everything you've typed internally. The unions have also noted that some recent disciplinary notices appear to be AI-generated in format, which is its own thing to sit with. None of this is confirmed in detail by the Times. The company says it disagrees with the union's characterizations and will respond through the normal contractual process. But the pattern the union is describing — productivity metrics collected without full disclosure, fed into individual reviews, with workers finding out after the fact — is not a paranoid reading of the situation. It's what happens when a tool gets deployed for one stated purpose and then used for another. ## The contradictions are structural, not accidental The New York Times is simultaneously: - Suing OpenAI and Microsoft for training AI models on Times content without permission - Building its own in-house AI tools — Echo for content summarization, Cheatsheet for investigative reporters analyzing large datasets — some developed with companies in that same orbit - Encouraging staff journalists to use AI for headline generation, research, and brainstorming - Sending freelancers a strict reminder in May 2026 that generative AI is essentially banned for submitted work - Publishing principles stating that journalists are always responsible for what they report, "however the report is created" - Allegedly refusing to tell its own union how AI is being used to evaluate those same journalists You could call this hypocrisy. I think it's something more structural than that. What you're actually seeing is a large organization trying to adopt AI without having worked out a coherent governance framework first. The lawsuit protects their content as an asset. The in-house tools — plus approved external services like [tools like GitHub Copilot](https://www.thedaringcreatives.com/github-copilots-new-pricing-shows-who-really-owns-ai-assisted-development/) — give them competitive capability. The freelancer ban limits liability. The staff guidelines give journalists enough runway to use AI productively. The performance tracking gives management data they want. Each decision makes [local sense but produce organizational incoherence](https://www.thedaringcreatives.com/the-ai-standardization-trap-why-big-companies-are-always-one-step-behind/) when combined. Together they produce a company that is simultaneously the plaintiff in a major AI copyright case, an AI tool builder, an AI tool restrictor, and — allegedly — an AI surveillance operator. All at once. Managing editor Marc Lacey wrote to staffers in April that "AI technology is ceaselessly evolving — quickly — and we believe that this rapid change is precisely why we must remain flexible." That's a real argument. If you lock specific AI prohibitions into a multi-year union contract, you might find yourself contractually prevented from using tools that didn't exist when the contract was signed. The technology genuinely does move faster than contract cycles. The problem is that "we need flexibility" is also the argument you'd make if you wanted to avoid accountability. Those two things are hard to distinguish from the outside, and apparently hard to distinguish from inside the building too, which is why the union is filing unfair labor practice charges instead of just taking management's word for it. ## What this means for people who aren't in a union Most freelancers, independent creators, and small operators reading this aren't in a position to file unfair labor practice charges. I'm not either. But the Times dispute is useful to watch because it's making visible a set of questions that will eventually land in front of everyone who works with or alongside AI tools. The first question is about metrics. DX tracks developer output and AI usage. That kind of tool exists for lots of roles now, not just software engineers. If you work inside a company, or do contract work where a client has visibility into your process, there's a reasonable chance that some form of productivity tracking is already in place — or will be. The question of whether those metrics accurately represent your work is not abstract. Harnett's point about proxy metrics is worth keeping: a number that tracks how many commits you made, or how many AI queries you ran, or how many words you produced in a session, [measures activity, not whether you solved the right problem](https://www.thedaringcreatives.com/context-curator-soft-skills-ai/). The second question is about disclosure. The Times union's position is that management is legally required to tell them how AI is being used to evaluate workers. That's a labor law argument specific to unionized workplaces. But the underlying principle — that you should know when and how your performance is being assessed, and by what — seems like a reasonable expectation in any working relationship. It's part of [what adopting AI actually means for your process](https://www.thedaringcreatives.com/adopting-an-ai-workflow/). If you're a freelancer and a client starts using a tool to score your output, you probably want to know that. The third question is about what gets protected. The Times Guild's demands include the ability for journalists to remove their bylines from AI-assisted stories, a share of revenue from licensing Times content for AI training, and protections against AI replacing workers. Those are contract demands, but they're also a list of concerns that any creative professional should probably think through for their own situation. Who owns the work? Who benefits when that work trains a model? What happens to your name when it's attached to something you didn't fully control? ## The monitoring apparatus runs ahead of the replacement conversation Isaac Aronow, an editor on the Times' Games section and member of the bargaining committee, said in February: "Newspaper management across the country is finding ways to use AI to fire journalists, lower the quality of the product and generally it's a huge, huge threat." He also said, separately: "We need to get protections in our contract now before these AI companies get even bigger." The second quote is the more important one. The union isn't waiting to see how the technology develops. They're trying to establish rules while there's still leverage to negotiate them. That's a different posture than most workers — unionized or not — are taking right now. The standard creative professional response to AI in 2026 is still mostly "let's figure out how to use it well." Which is reasonable! I spend a lot of time thinking about that myself. But the Times dispute is a reminder that how AI gets used inside an organization isn't just a question of individual workflow. It's a governance question, and governance gets settled through negotiation or through unilateral decisions by whoever has the power to make them. If you're not at the table for that negotiation — and most of us aren't — then the decisions get made without you, and you find out about them later, when the disciplinary notice shows up in a format that looks like it was generated by the same tools you were never told were watching you. The monitoring infrastructure usually comes before the replacement conversation. The Times is just big enough that we can see both happening at the same time. ### Google I/O 2026: When the work itself becomes optional URL: https://www.thedaringcreatives.com/google-io-2026-agentic-ai/ Last updated: 2026-08-01T19:42:09.000Z There's a moment in the [Google I/O](https://io.google/?ref=thedaringcreatives.com) 2026 keynote that I keep coming back to. A user is in Google Docs. They don't type a prompt. They just talk — rambling, honestly — "can you pull my resume from Drive... come up with some funny analogies... grab the details from that email... turn this into a draft." Then, as the document assembles itself in real time, they say things like "format the analogies as a table" and "bold that part." The whole thing takes maybe two minutes. I've watched a lot of AI demos. Most of them feel like magic tricks — impressive in the moment, useless in practice. This one felt different. Not because the technology is bad — because it worked so well I could immediately see what it meant for anyone running their own business or creative practice. ## What Google actually announced Sundar Pichai called it the "agentic Gemini era," and for once the framing matched the product. The headline tools aren't just more capable — they're designed to operate without you. [Gemini Spark](https://gemini.google.com/?ref=thedaringcreatives.com) is a 24/7 personal agent that runs on dedicated virtual machines in Google Cloud. You can close your laptop and it keeps going. It manages your calendar, writes your emails, executes tasks across apps, and Pichai demoed it handling three simultaneous requests from a single spoken sentence. Ultra subscribers get it for $100/month. [Antigravity 2.0](https://antigravity.dev/?ref=thedaringcreatives.com) is a standalone desktop IDE built around the idea that you give it a goal and it figures out the rest. The demo: "Build a working operating system from scratch." Antigravity broke the goal into a plan, spun up 93 parallel subagents, made over 15,000 model requests autonomously, ran its own tests, iterated on failures — all over 12 hours, for under $1,000 in API credits. The human's job was to define the goal and occasionally fix things via conversation. Gemini Omni handles video the same way. Give it a source clip, describe what you want changed, and "the whole scene morphs to reflect your new idea." Style transfers, object additions, reality edits — conversational language, no specialized software. And Stitch, the UI design tool, now lets you generate and refine layouts in real time by talking to it. "Make the header text larger." "Highlight more pizza options." The layout updates as you speak. The scale underneath all of this is hard to hold in your head. Google now processes 3.2 quadrillion tokens per month — a seven-fold increase from last year. They're spending somewhere between $180 and $190 billion in [capital expenditure](https://abc.xyz/investor?ref=thedaringcreatives.com) this year, almost entirely on AI infrastructure. That's a six-fold increase from 2022\. This isn't a company hedging. This is a company betting the whole thing. ## This is the scaling moment for solo creators Varun Mohan, demoing Antigravity, said: "We've moved beyond AI tools that help us write, to agents that help us act. These agents have lowered the barrier to development so much that anyone can be a builder, even busy CEOs." That line made me think about my own freelance career, and how there have been many moments where I felt like I needed to turn down work. Not because of a skill issue — because of an hours issue. With Stitch potentially handling more of the low leverage tasks, I could take on more high leverage work like strategy and relationship building. Or consider what Gemini Spark means for someone running a [consulting business](https://daringstrategy.com/?ref=thedaringcreatives.com). All those admin tasks that eat half your day — scheduling, email management, proposal drafts, client follow-ups — now happen while you sleep. You wake up to a calendar that makes sense, emails that sound like you, and project updates that keep things moving forward. The economic shift here is massive. When you can automate the repetitive execution work, suddenly your constraint isn't time — it's how many good ideas you can generate and how well you can manage relationships. Those are fundamentally human skills that actually get more valuable as the technical barriers drop. ## The craft evolves, doesn't disappear I keep hearing people worry that AI will eliminate creative work entirely. But what I saw at I/O looked more like a shift toward higher-leverage creative work. Take video editing. Gemini Omni can handle the technical execution — style transfers, object additions, scene morphing. But someone still needs to have the vision for what the final piece should accomplish. Someone still needs to know when the AI's technically perfect output doesn't match the client's actual business goals. Someone still needs to iterate on feedback and manage the relationship. The difference is that person can now work at a completely different scale. Instead of spending 80% of your time on execution and 20% on strategy and client work, those percentages flip. You become the director of multiple AI systems instead of the sole executor of every detail. For freelancers and small agencies, this is genuinely exciting. You can compete with much larger teams on project scope while maintaining the personal touch and flexibility that larger shops can't match. The AI handles the heavy lifting; you handle the vision and the relationships. ## The privacy conversation is practical, not paranoid Here's the part where we need to be realistic about trade-offs, not because these tools are dangerous, but because running a business means managing risk thoughtfully. Gemini Spark's value comes from deep integration with your digital life. It can manage your calendar, draft your emails, coordinate your projects — but only if it has persistent access to all of that information. For solo creators and small businesses, that's mostly a personal decision about what convenience is worth. The business consideration comes when you're handling client work. If you're using Spark to manage client communications or draft proposals involving confidential information, you're essentially giving Google access to that client data. Google's own documentation mentions human reviewers and three-year data retention policies. This doesn't mean don't use the tools — it means have the conversation with your clients upfront. Some will care, some won't. But being transparent about your workflow and having their explicit okay protects everyone and actually builds trust. "I use AI to handle routine tasks, but all client-specific information stays in our dedicated project management system" — that's a reasonable approach that gives you the efficiency benefits while respecting boundaries. ## The 93-subagent demo is impressive (with caveats) The Antigravity OS demo was genuinely wild to watch. But as someone who's been burned by the gap between conference demos and real-world performance, I'd approach it with healthy optimism rather than immediate business planning. Google's own research shows that [multi-agent systems](https://research.google.com/pubs/multi-agent-ai/?ref=thedaringcreatives.com) often hit diminishing returns as you add more agents. The 93-subagent demo worked, but it was probably a best-case scenario with ideal conditions. That doesn't make it fake or useless — it just means the production reality will likely be more modest and require more human oversight than the keynote suggested. For practical purposes, even a scaled-back version of Antigravity is probably game-changing for small businesses that need custom software but can't afford a full development team. The question isn't whether it can build an OS in 12 hours — it's whether it can build your client portal, your inventory system, or your booking platform reliably and cost-effectively. And honestly? Even if it gets you 70% of the way there and you need to hire someone for the final 30%, you've still collapsed months of development time into weeks and dramatically reduced your costs. ## The ecosystem advantage is real One more thing that excites me about Google's approach is their integration depth across products that already have massive user bases. Gmail, Chrome, Android, Search — these aren't startup tools trying to build an audience. They're platforms that billions of people already use daily. That means these AI capabilities will feel natural and accessible in a way that standalone tools often don't. Your clients probably already use Google Docs. Your contractors probably already use Gmail. When the AI features are built into the workflow they're already familiar with, adoption happens naturally instead of feeling like another tool they need to learn. The convenience is substantial, and while there are valid concerns about ecosystem lock-in, the practical reality is that most small businesses are already deep in one ecosystem or another. The question isn't whether to avoid platform dependence — it's which platform gives you the best tools to scale your work and serve your clients better. For individual creators and small businesses, that calculation increasingly favors the platforms that can automate the boring stuff while amplifying your distinctly human contributions. Google's I/O 2026 announcements suggest they understand that opportunity and are building for it aggressively. The tools are coming whether we're ready or not. The smart play is figuring out how to use them to do more of the work you actually want to do. ### The Public Doesn't Hate AI — They Hate Being Lied To URL: https://www.thedaringcreatives.com/public-ai-distrust-dishonesty/ Last updated: 2026-08-01T19:42:09.000Z ## The Numbers Don't Lie A new [Benenson Strategy Group poll](https://newrepublic.com/article/209163/ai-industry-discovering-public-backlash?ref=thedaringcreatives.com) commissioned by the Center for AI Safety Action Fund reveals something the AI industry hoped wasn't true: the public really doesn't like them. Seventy-two percent of Americans think AI development is moving too fast. Sixty-nine percent believe tech companies can't be trusted to develop AI responsibly. Most telling? Fifty-seven percent want the government to regulate AI more strictly, even though Americans generally hate government regulation of anything. These aren't technophobe numbers. This is mainstream distrust. The poll also found that 71% of Americans think AI will eliminate jobs, and 69% believe it will increase misinformation. When asked about AI's benefits, the numbers flip — only 39% think AI will improve their daily lives. ## What The Industry Is Saying Tech leaders are scrambling to explain the backlash. OpenAI's Sam Altman recently told investors that "public sentiment will improve as people see real benefits." Anthropic's Dario Amodei argues that "fear always precedes adoption of transformative technologies." Meanwhile, Google's Sundar Pichai called for "more education" about AI benefits during a recent earnings call. The message from Silicon Valley is clear: the public just doesn't understand AI well enough to appreciate it. This is where I think they're completely wrong. ## The Public Understands Fine The AI industry keeps acting like public skepticism is an education problem. People just need to understand how amazing this technology is! They need to see the benefits! They need better messaging! But here's what I've observed from two years of tracking AI adoption: most people understand AI pretty well. They use ChatGPT. They've seen the image generators. They know their nephew got fired because his company replaced him with Claude. The problem isn't understanding. The problem is trust. When Sam Altman says AI will create more jobs than it eliminates, but his own company is [testing marketplace systems](https://techcrunch.com/2026/04/25/anthropic-created-a-test-marketplace-for-agent-on-agent-commerce/?ref=thedaringcreatives.com) where AI agents conduct business without human involvement, people notice the contradiction. When tech companies promise AI will "augment human creativity" while simultaneously training models on millions of artists' work without permission or payment, creators notice. When executives claim AI will democratize access to knowledge while building systems that require massive compute resources only large corporations can afford, people notice. ## The Real Problem Is Honesty I think the public backlash isn't really about AI at all. It's about being told one thing while experiencing another. The industry narrative goes like this: AI will make everyone more productive and creative. It's a tool that empowers individuals. It's the great democratizer. The reality people are living: [44% of new music uploads are now AI-generated](https://arstechnica.com/ai/2026/04/deezer-says-44-of-new-music-uploads-are-ai-generated-most-streams-are-fraudulent/?ref=thedaringcreatives.com), most of them fraudulent streams designed to game royalty systems. Companies are posting job requirements for "AI-native" workers while laying off thousands. The tools that were supposed to level the playing field are increasingly locked behind enterprise paywalls. That's not an education gap. That's a credibility gap. ## What This Means for Creators If you're building something creative with AI, you're caught in the middle of this trust crisis. People are suspicious of AI-generated content not because it's technically inferior, but because they've been burned by promises that turned out to be marketing copy. The companies selling AI tools have spent two years optimizing for hype instead of honest communication. Now creators using these tools inherit that skepticism. But here's the opportunity: you can be the honest voice the industry isn't providing. When I write about using Claude for research, I'm specific about what it's good at and where it fails. When I share AI-generated images, I tag them clearly. When I build workflows with AI tools, I explain what the human contribution actually is. This isn't just ethical disclosure — it's competitive advantage. In a market flooded with [human slop](https://tdc.ghost.io/human-slop/?ref=thedaringcreatives.com) masquerading as AI innovation, genuine transparency stands out. ## The Correction Is Coming The Benenson poll numbers suggest we're heading toward a correction. Not a technical correction — the technology keeps improving. A trust correction. Companies that have been selling AI as magical automation are going to face harder questions. Tools that promise to "replace human creativity" are going to encounter resistance. Platforms built on extracting value from creative work without compensation are going to face regulation. This is actually good news for people building sustainable creative practices with AI. The hype merchants are going to get filtered out. The honest builders will have space to do actual work. The public doesn't hate AI. They hate being sold a vision of the future that benefits everyone while watching a reality that mainly benefits a few large companies. The solution isn't better messaging — it's better practices. If you're building with AI, build something that actually helps people. If you're selling AI tools, be honest about what they do and don't do. If you're creating AI content, own what's yours and label what isn't. The trust crisis creates an opportunity for anyone willing to earn credibility instead of just claiming it. ### The Hidden Features Aren't The Point URL: https://www.thedaringcreatives.com/claude-code-hidden-features/ Last updated: 2026-08-01T19:42:09.000Z I saw [Boris Cherny's thread about hidden Claude Code features](https://www.threads.com/@boris%5Fcherny/post/DWfjnqGFPHE?ref=thedaringcreatives.com) blow up yesterday. Seventeen parts, 2.2K likes, everyone sharing their favorite shortcuts and power-user tricks. And honestly? It made me a little sad. I'm sad because we're doing that thing again where we make the tools the hero instead of what people build with them. ## The Productivity Trap Every time a new AI tool gets traction, the same thing happens. First, everyone scrambles to learn it. Then, the "power users" emerge with their advanced techniques. Finally, the discourse shifts from "what can you make?" to "how many features do you know?" It's productivity porn. Here's the thing about hidden features: they're hidden for a reason. Most people don't need them. The best tools work great right out of the box for 90% of use cases. If you're hunting for advanced shortcuts, you might be optimizing the wrong thing. ## What Actually Matters I've watched people transform their creative practice with AI tools. The ones who succeed don't know every keyboard shortcut. They know something more important: what they're trying to build. They start with a clear outcome in mind. Maybe it's a blog that doesn't suck (that was mine). Maybe it's an app that solves a real problem. Maybe it's turning their messy thoughts into something coherent. They use whatever features help them get there and ignore the rest. The person who knows three Claude Code shortcuts but ships something meaningful is infinitely more valuable than the person who knows thirty shortcuts but never ships anything. ## The Real Hidden Feature You want to know the most underused feature in every AI tool? Most people treat AI like a search engine (yes, you've heard this before I know). But yet you still do it! Admit it.. Conversely, the people getting incredible results are the ones who learned to be specific about their goals, their constraints, and their quality standards. ## Learning In Public vs. Gatekeeping I'm not saying don't share tips. Boris's thread is genuinely helpful for people who want to level up their Claude Code skills. The problem isn't the sharing — it's when the conversation becomes about who knows the most obscure features instead of who's building the most interesting things. There's a difference between "here's how I use this tool to solve real problems" and "here are seventeen features most people don't know about." One empowers beginners. The other creates a new form of gatekeeping where you have to memorize a bunch of shortcuts before you're allowed to call yourself proficient. The best AI content creators I follow share their process, not just their settings. They show the messy middle part where they're figuring things out. They talk about what didn't work and why. They make it clear that knowing the tools is just table stakes — the real work happens when you apply them to something that matters to you. ## What We Should Be Talking About Instead Let's celebrate the person using basic Claude features to write better documentation for their open source project. Or the artist using simple prompts to explore ideas they couldn't access before. Or the parent using AI to help explain complex topics to their kids. These stories matter more than knowing how to enable advanced mode or whatever. ## The Tools Will Change The shortcut you memorized last month might be deprecated next month. The hidden setting that gives you an edge today might be the default tomorrow. But the skills that matter — knowing what you want to build, communicating clearly, iterating based on feedback — those transfer to whatever tool comes next. Focus on the outcomes. Learn the features that help you get there. Ignore the rest. And please, share what you're building, not just how you're building it. ### Your Skills Aren't Atrophying — They're Evolving URL: https://www.thedaringcreatives.com/skills-evolving-with-ai/ Last updated: 2026-08-01T19:42:10.000Z Everyone using AI tools has felt it at some point: that creeping sense that you're getting dumber. That the skills you spent years building are slowly dissolving. That you're becoming dependent on something that's making you less capable, not more. I get it. I've felt it too. But here's the thing — this isn't actually what's happening. ## The Violin I Can't Play Anymore I was a classical violinist for 20 years. Started as a kid, played through college, then I got burned out and moved on to something else. Then life happened, and I haven't touched a violin in over 20 years. If you handed me one right now, I'd sound like garbage. My fingers wouldn't find the right positions. My bow technique would be sloppy as hell. All that muscle memory, all that dexterity — completely gone. I can still read music. I still know music theory. I can hear when something's out of tune or when a melody needs work. I understand harmony and composition in ways I never did when I was focused on just playing the notes correctly. My manual skills faded, but the knowledge deepened. And honestly? Now I can focus on the parts of music that actually interest me — the orchestration, the arrangement, the big picture stuff — instead of just trying to nail my part. ## The Designer's Evolution Think about graphic designers who came up in the 90s and early 2000s. They spent years mastering the pen tool in Photoshop, painstakingly cutting out objects pixel by pixel. That was a real skill that took time to develop. Most of those designers aren't doing that anymore. They've moved into creative direction, art direction, strategy. Their job now is to critique and guide the creation of art, not necessarily execute every detail themselves. They learned new skills to replace the old ones. Nobody calls this "getting dumber." We call it career progression. ## What AI Atrophy Actually Is When you start using AI tools heavily, some of your manual skills will fade. The copywriter who spent years perfecting their ability to write snappy headlines might find that skill getting rusty if they're using AI to generate options. But they're developing new skills: prompt engineering, editing AI output, strategic thinking about messaging. The developer who could write complex algorithms from scratch might get slower at that. But they're getting faster at architecting systems, reviewing code, and solving higher-level problems. This is normal. This is how skills have always worked. Use it or lose it isn't just true for AI — it's true for everything. ## The Real Question The question isn't whether your skills are changing. They are. The question is whether the new skills you're gaining are more valuable than the old ones you're losing. If you're using AI to handle the repetitive, mechanical parts of your work so you can focus on strategy, creativity, and high-level problem solving? That's probably a good trade. If you're using AI as a crutch to avoid thinking altogether? That's a different story. But most people I know aren't doing the second thing. They're doing the first thing and feeling guilty about it because they think skill change equals skill loss. ## The Part That Stays Foundational knowledge usually sticks around. My music theory didn't disappear when I stopped playing violin. The manual execution fades. The deep understanding often grows. And honestly? Wouldn't it be more fun to just focus on the part that you enjoy and are driven to do? I think so. Your skills aren't atrophying. They're evolving. And that's exactly what they should be doing. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/your-skills-aren-t-atrophying-they-re-evolving/your-skills-aren-t-atrophying-they-re-evolving-landscape-1920x1080.webp) ``` ### Meta Shoots the Messenger on Ray-Ban Privacy Reports URL: https://www.thedaringcreatives.com/meta-ray-ban-privacy/ Last updated: 2026-08-01T19:42:10.000Z Meta just fired a bunch of contractors for doing their jobs too well. According to reporting from Ars Technica, content reviewers working for the company flagged multiple instances of Ray-Ban Meta users recording themselves having sex — and Meta's response was to cut the contractors who reported it, not address the privacy nightmare they uncovered. The contractors were part of Meta's content moderation pipeline, reviewing footage from Ray-Ban Meta smart glasses to train AI systems. When they encountered sexually explicit content that users had recorded while wearing the devices, they followed protocol and flagged it. Meta's reaction? Terminate their contracts and claim the footage didn't violate community standards. Let me get this straight. Users are wearing cameras on their faces, recording intimate moments, and uploading that content to Meta's systems. The people hired specifically to review this material do their job and report concerning patterns. And Meta's solution is to fire the messengers. ## What Actually Happened Here's what we know from the reporting: Multiple contractors working for Accenture (Meta's content review partner) flagged sexual content recorded through Ray-Ban Meta glasses. The footage showed users engaged in sexual activities while wearing the devices. When contractors reported this as potentially problematic, Meta terminated their access and ended their contracts. Meta's official position is that the content didn't violate community guidelines because it was "private content" not intended for sharing. But that misses the entire point. The issue isn't whether the content violates posting rules — it's that intimate recordings are flowing through Meta's content pipeline in the first place. The Ray-Ban Meta glasses can record 60-second video clips and capture photos with voice commands or button presses. They're designed to feel seamless and ambient, which is exactly the problem. When recording becomes that frictionless, people record everything. Including stuff they probably shouldn't be uploading to a tech company's servers. ## The Privacy Theater Problem This story perfectly illustrates how tech companies handle privacy: with elaborate theater that breaks down the moment someone looks too closely. Meta built an entire infrastructure around the idea that they need human reviewers to train AI systems on user content. They hired contractors specifically to watch and categorize this material. But when those contractors discovered that users are recording genuinely private moments and that footage is ending up in Meta's systems, the company's response was to eliminate the witnesses. It's the corporate equivalent of "if we don't look at it, it's not a problem." The Ray-Ban Meta glasses are marketed as a creative tool for capturing spontaneous moments. The ads show people recording concerts, walks with friends, cooking experiments. What they don't show is the reality that when you put always-available cameras on people's faces, they'll record everything. And "everything" includes moments that were never meant to leave their bedrooms. ## What This Means for Creators If you're using any kind of wearable recording device for creative work, this should make you think twice about your data pipeline. Every clip you capture, every photo you take, potentially flows through content review systems staffed by contractors who may or may not still have jobs tomorrow. The creative appeal of devices like Ray-Ban Meta is obvious. They're hands-free, always ready, designed to capture authentic moments without the friction of pulling out a phone. For content creators, that's incredibly valuable. But authenticity comes with a cost, and that cost is comprehensive surveillance. When I see creators using these devices, they're often focused on the output — the interesting footage they can capture, the new perspectives they can offer their audience. What they're not thinking about is the input side: every second of footage goes somewhere, gets processed by someone, and exists in systems they don't control. Meta's decision to fire contractors instead of addressing the underlying issue tells you everything you need to know about their priorities. They want the data, they want the training material for their AI systems, but they don't want to deal with the messy reality of what that data actually contains. ## The Bigger Pattern This connects to a broader trend in AI development: the human cost of training systems gets swept under the rug whenever it becomes inconvenient. Look at the OpenAI contractors who've reported seeing disturbing content while reviewing ChatGPT outputs. Or the data labeling workers who spend their days categorizing the worst parts of the internet to make AI systems safer. These jobs exist because AI companies need human judgment to train their models, but the moment those humans report something uncomfortable, they become expendable. The Ray-Ban Meta situation is just the latest example. Meta needs human reviewers to understand what their cameras are capturing so they can build better AI systems. But when those reviewers do their jobs and report problematic patterns, Meta's response is to eliminate the reporting mechanism, not fix the problem. It's not just about privacy — it's about accountability. By firing the contractors who flagged concerning content, Meta is actively reducing their own ability to understand what's happening in their systems. They're choosing willful ignorance over uncomfortable knowledge. ## Where This Goes Next The fundamental issue isn't going away. Wearable cameras are getting smaller, cheaper, and more ubiquitous. Meta's Ray-Ban glasses are just the beginning. Apple's rumored smart glasses, Snapchat Spectacles, whatever Google is working on — they all have the same basic problem. When recording becomes ambient and always-available, people will record private moments. When those recordings get uploaded to company servers for processing, someone has to review them. And when reviewers flag problems, companies have to decide whether they want to know about them or not. Meta just told us which choice they're making. For creators using these tools, the lesson is clear: assume everything you record is being seen by someone, somewhere. The privacy controls and community guidelines are theater. The real privacy policy is whatever keeps the data flowing and the contractors quiet. The contractors who got fired for doing their jobs won't be the last ones. But at least now we know where Meta stands when human judgment conflicts with business objectives. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/meta-shoots-the-messenger-on-ray-ban-privacy-reports/meta-shoots-the-messenger-on-ray-ban-privacy-reports-landscape-1920x1080.webp) ``` ### Google I/O 2026: What I'd want answered before turning on Gemini Spark URL: https://www.thedaringcreatives.com/gemini-spark-questions-answered/ Last updated: 2026-08-01T19:42:10.000Z At [Google I/O 2026](https://io.google/2026/?ref=thedaringcreatives.com), Google announced Gemini Spark: a persistent AI agent that runs 24/7 in the cloud, managing your Gmail, Docs, Calendar, and Sheets even when every device you own is off and sitting on a shelf. No prompt required. You give it a task, it runs until the task is done. That's the pitch. My first reaction was skepticism. Not because I don't believe in agentic AI — I do. But because these personal AI agents tend to work well for limited use cases in controlled environments. I've been building my own system using these tools for more of my nuanced use cases and needs, and I think that's how these agents will eventually pan out. People will need a lot of flexibility for tools to work how they do, at least initially. But the more I sat with the details, the more I found myself making a list of questions I'd want answered before I handed that much access to anything. ## What "always-on" actually means Most AI tools we use today are reactive. You open the app, type something, get something back. Gemini Spark is designed to work the other way around. It's connected to your Google Workspace through structured APIs — not screen-reading or simulating clicks, but calling defined methods with known inputs and outputs — and it runs continuously on Google's cloud infrastructure. The practical implication: Spark could be monitoring your inbox right now, drafting a reply to a client email, and scheduling a follow-up meeting, all while you're asleep. The "always-on" part is what separates this from a chatbot — it's the [always-on agent architecture](https://www.thedaringcreatives.com/the-ai-you-never-have-to-open/) that doesn't wait for you to open a tab. Google's underlying platform here is Antigravity 2.0, which is also worth understanding on its own terms. It's an orchestration layer that lets multiple AI sub-agents run in parallel, each handling a different piece of a complex workflow. Google cited a case study of 93 parallel sub-agents building a working operating system in 12 hours. That number is wild enough that I'd want to see independent verification, but it gives you a sense of the scale they're designing for. ## The security model Google is betting on Google's stated approach to security is ephemeral VM isolation. Every task Spark runs executes in a fresh, isolated virtual machine that gets destroyed when the task completes. The idea is that each session is sandboxed — nothing from one task bleeds into another. But prompt injection attacks have proven stubborn in other agentic contexts, and the attack surface here is substantial. Spark has standing access to your email, your calendar, your documents. A malicious email crafted to manipulate Spark's behavior — telling it to forward messages, schedule meetings with external parties, or modify documents — is a real category of risk. The ephemeral VM prevents data leakage between sessions, but it doesn't necessarily stop a bad actor from using the *current* session's access against you. [Simon Willison, who writes some of the most technically grounded AI criticism](https://simonwillison.net/?ref=thedaringcreatives.com) I've read, has a policy of not writing about things he can't actually test. Most of what Google announced at I/O is "coming soon" — not yet available for independent testing. That's relevant here because we're evaluating Google's security claims without being able to probe them. The architecture sounds reasonable. Whether it holds up under real-world adversarial conditions is a different question. ## The part that gave me the most pause Buried in the coverage is something that came from code analysis, not from Google's official announcements. The code within the Google app suggests Gemini Spark may be able to make purchases without explicit per-transaction user approval. That's unconfirmed. Google hasn't announced it as a feature. But it's worth naming because if it's accurate, the failure mode changes category. A bad email draft is embarrassing and fixable. A misconfigured agent that makes unauthorized purchases — or that gets manipulated into doing so through a prompt injection attack — is a different problem. For freelancers and small operators who might use Spark to manage client communications and invoicing, the gap between "draft an invoice" and "send payment" is one the agent probably shouldn't be crossing without a confirmation step. The Forbes coverage flagged this as "an uncomfortable warning" that Google left out of its I/O presentation. I think that's fair. The autonomous purchasing question deserves a direct answer from Google before this goes into wide release. ## The "coming soon" problem Google AI Ultra — the subscription tier that will get beta access to Spark — [costs $100/month for developers or $200/month](https://www.thedaringcreatives.com/reality-of-ai-subscriptions/) for the full tier. That's real money. And right now, what you're paying for is mostly access to a roadmap. This isn't unique to Google. OpenAI and Anthropic have both announced capabilities before they shipped them. But there's something worth noticing about how the discourse around AI capability has shifted: we're increasingly evaluating claims instead of testing tools. The press cycle runs on announcements, not on months of independent use. I'm not saying Google is being dishonest. I'm saying that "trusted testers first, then U.S. beta subscribers" is a significant gap between what was announced and what's available. And for a product whose value proposition is "trust me to run in the background of your business while you're not watching," the absence of independent testing reports is a real gap in what we know. There's also the question of usage caps. Code analysis suggests even AI Ultra subscribers may face caps with no way to purchase additional capacity. That's also unconfirmed. But if you're building workflows that depend on Spark running continuously, discovering a cap mid-workflow is the kind of thing you'd want to know about before you build the dependency. ## What this actually changes for creators and small operators The architecture Google is building is genuinely interesting. Antigravity 2.0 as an orchestration layer for multi-agent workflows — the parallel sub-agents, the persistent execution, the API-level integration with Workspace — that's a real platform bet. If it works the way Google describes, it shifts the question from "how do I prompt this well" to "[how do I design a system of agents](https://www.thedaringcreatives.com/from-helping-ai-to-directing-ai-the-uncomfortable-truth-about-creative-workflows/) with defined roles and handoffs." But here's what I think will actually happen: most people will need to build their own systems anyway. The general-purpose agent that handles everyone's email the same way is useful for simple tasks. But once you get into the specifics of how your business works — the particular clients who need different communication styles, the specific documents that follow your format, the nuanced decisions that reflect your judgment — you need something more flexible than what Google's shipping. I've been building exactly that kind of system using the tools available now. Custom agents for different parts of my workflow, designed around how I actually work, not how an average user works. And honestly, that's been more useful than any all-in-one agent I've tried. For most of us, the honest answer is: wait and see. Not because the technology isn't interesting, but because the things that would actually determine whether Spark is safe to use in your business — the real-world security behavior, the actual usage caps, the autonomous purchasing question — aren't answerable yet. The product isn't available for independent testing, and the unconfirmed features are exactly the ones with the highest stakes. I'd also pay attention to the Antigravity CLI transition. Google is sunsetting its open-source Gemini CLI and replacing it with a closed-source Antigravity CLI, with a migration deadline of June 18, 2026\. If you've built anything on the open-source CLI, that clock is running. And for developers who care about auditability, the move to closed-source signals that Antigravity is a commercial platform play, not an open ecosystem. None of this means Gemini Spark won't be useful. It might be genuinely useful. But "24/7 access to your Gmail, Calendar, and Documents, running autonomously in the background" is a significant thing to hand over, and the questions I'd want answered before doing that haven't been answered yet. When the beta opens up and people start publishing real-world reports — not Google's case studies, but independent accounts of [what it actually does under production conditions](https://www.thedaringcreatives.com/adopting-an-ai-workflow/) — that's when I'll have a better sense of whether this works the way they're promising. Until then, I'm watching the trusted testers carefully. ### The lawsuit is over. The question it was asking is still open. URL: https://www.thedaringcreatives.com/openai-accountability-question/ Last updated: 2026-08-01T19:42:10.000Z A California jury dismissed Elon Musk's lawsuit against OpenAI in less than two hours on May 18th. The reason wasn't that Musk was wrong about anything in particular. It was that he waited too long to sue — the statute of limitations had run out. So the core question at the center of the whole fight, whether OpenAI betrayed its founding mission when it restructured into a for-profit entity, never got a legal answer. I don't think Musk is a credible messenger here. He launched his own AI company, xAI, in 2023\. He's a direct competitor. His stated plan was to have any damages he won — somewhere between $79 and $134 billion — returned to OpenAI's nonprofit arm, which is a strange thing to claim with a straight face when you're also trying to remove the leadership and kneecap the organization. OpenAI's attorneys called the lawsuit "hypocritical," and on the motivations question, they're probably right. ## What actually changed at OpenAI, and why it matters OpenAI was founded in 2015 as a nonprofit AI research lab. The pitch was simple and genuinely idealistic — develop artificial general intelligence for the benefit of humanity, not shareholders. Musk was one of the co-founders. So was Sam Altman, Greg Brockman, and Ilya Sutskever, among others. By 2019, that structure had a problem. Training frontier AI models costs billions of dollars in compute. A pure nonprofit can't raise that kind of capital or offer the equity compensation needed to compete for top engineers. So OpenAI created a hybrid: a for-profit subsidiary (OpenAI LP) that could take venture funding and offer equity, with a cap on investor returns. Profits beyond the cap were supposed to flow back to the nonprofit parent. The nonprofit, in theory, retained ultimate control. Microsoft came in with $13 billion over several years. It provides the Azure cloud infrastructure that OpenAI's models actually run on. As of the October 2025 restructuring into a Public Benefit Corporation, Microsoft holds a 26.79% stake. OpenAI is now valued at approximately $852 billion, with analysts projecting a potential IPO could approach $1 trillion. The nonprofit parent is still there, on paper. But the for-profit entity underneath it is worth nearly a trillion dollars. ## What the Altman firing actually showed us In November 2023, the OpenAI board — the nonprofit board, the one with the actual mission-first fiduciary duty — fired Sam Altman. They cited lack of confidence in his leadership. They didn't give a detailed public explanation, which created a vacuum that got filled with speculation almost immediately. What happened next is the most instructive part of this whole story. Employees revolted. Hundreds signed a letter threatening to leave if Altman wasn't reinstated. Microsoft made clear it would hire Altman and his team if they walked. Within days, Altman was back, the board was reshuffled, and OpenAI quietly changed its bylaws to require a two-thirds supermajority of non-employee directors to fire the CEO. The nonprofit board tried to exercise its legal authority. The operational and financial stakeholders overrode it. You can argue about whether the board was right to fire Altman. That's a separate question. The structural point is harder to argue with: when the mission-oriented governance layer and the financial stakeholders came into direct conflict, the financial stakeholders won. The nonprofit didn't lose its paperwork. It lost its leverage. ## The safety researcher exodus is worth taking seriously In 2024 and 2025, several key people from OpenAI's safety and alignment work left. Jan Leike, who led the "Superalignment" team — the group specifically focused on ensuring superintelligent AI remains controllable — departed and said publicly that he left in protest. A former safety staffer told reporters that "safety culture and processes have taken a backseat to shiny products." The Superalignment team itself was disbanded. OpenAI hasn't given a detailed public explanation for why that team was shut down. Ilya Sutskever, one of the co-founders and the person who helped initiate the November 2023 attempt to remove Altman, left in May 2024 to start something he described as "personally meaningful." His public statement was diplomatically vague. He said he was confident in OpenAI's leadership on his way out, which is exactly what you say when you've decided there's nothing more to do from inside. I want to be careful here. I don't know what the internal fights looked like. I don't know what specific decisions the safety researchers were objecting to, or what proposals got rejected. The public statements have been careful. But when the people whose entire job is to slow things down and ask hard questions start leaving in protest, and their teams get disbanded, that's usually a signal worth tracking, not dismissing. ## The IPO is when the structure either holds or breaks OpenAI has said the nonprofit parent will retain control of the Public Benefit Corporation even after it goes public. The legal mechanism for how that works — how a nonprofit entity overrides the fiduciary duties a public company's board owes to shareholders — is genuinely untested at this scale. A Public Benefit Corporation is a real legal structure. It's not nothing. But PBCs face quarterly earnings pressure, activist investors, and market expectations the same as any other public company. The "benefit" mandate has to be enforced by someone, and the enforcement question is where things get murky. Has a nonprofit ever successfully maintained mission-driven control over a trillion-dollar public company when those incentives pulled in opposite directions? I don't know of a precedent. If you do, I'd genuinely like to hear it. ## What this has to do with you, specifically If you're a writer, designer, or developer using ChatGPT, DALL-E, or Codex to run your creative work, you're already inside this governance question whether you think about it or not. The decisions that shape those tools — what gets prioritized, what safety trade-offs get made, what features get built versus what research gets funded, who gets access and at what price — are made by a company that is now worth nearly a trillion dollars and is heading toward a public offering. The nonprofit parent that's supposed to keep all of that accountable to a mission just watched its most significant governance test go the wrong way in 2023, and then quietly made it harder to repeat that test. I'm not saying you should stop using these tools. I use them constantly. But I think there's a difference between using a tool and assuming the company building it shares your values. OpenAI's founding documents said the mission was AGI for humanity. The current structure says the investors get up to a 100x return before that mission kicks in, and the people whose job was to keep the long-term safety work on track have largely left. That's not a reason to panic. It's a reason to pay attention to who controls the infrastructure you're building your work on, and to stay curious about what happens to that infrastructure when the IPO lands and the quarterly pressure starts. The lawsuit being dismissed doesn't make any of this cleaner. It just means the courts aren't going to sort it out for us. ### AEGIS Retrieval Team Reports Empty Archive at Cathedral Bridge Administrative Complex URL: https://www.thedaringcreatives.com/aegis/aegis-cathedral-bridge-empty-archive/ Last updated: 2026-08-01T19:42:11.000Z AEGIS contractors arrived at Cathedral Bridge to find target materials already removed from secured storage _This post is for subscribers only._ ### From Helping AI to Directing AI: The Uncomfortable Truth About Creative Workflows URL: https://www.thedaringcreatives.com/directing-ai-creative-workflows/ Last updated: 2026-08-01T19:42:11.000Z When I started building AI workflows for my content pipeline two years ago, I was helping AI do things. Now I'm directing AI to do things. And I'm not entirely sure when that shift happened. [Simon Willison captured this perfectly](https://simonwillison.net/2026/May/6/vibe-coding-and-agentic-engineering/?ref=thedaringcreatives.com) in his recent podcast: "vibe coding and agentic engineering are getting closer than I'd like." He's talking about the convergence between intuitive, creative approaches to building AI systems and the systematic deployment of autonomous agents. I'm living that convergence daily. ## The Moment Everything Changed It started simple. I'd ask Claude to help brainstorm article ideas from my scattered thoughts (typically voice notes while on a walk). Then I started using it to draft outlines. Then full drafts. Then I built systems to automatically publish those drafts to Ghost, schedule social media posts, and even record comments and feedback to draft follow up articles or posts. What I thought was just getting better at prompting was actually something else entirely: I was transitioning from creative professional to creative systems manager. The work didn't feel different day-to-day, but the role fundamentally changed. Now [OpenAI's Chrome extension for Codex](https://www.testingcatalog.com/openai-adds-chrome-plugin-and-tests-remote-control-for-codex/?ref=thedaringcreatives.com) can run browser sessions independently. AI agents can directly manipulate Figma, WordPress, and basically any web-based creative tool without human intervention. We've moved from "AI helps me code" to "AI codes while I do something else." ## The Infrastructure That Enables This Everyone focuses on the sexy AI tools. Nobody talks about the unglamorous infrastructure work that makes creative AI workflows actually function. API management. Error handling. Content routing. Quality control systems. I spend more time debugging webhook failures than I do writing. And, when my automated social media posting breaks because Twitter changed their API again, I'm not creating content—I'm doing DevOps. This is what creative professionals building "vibe coded" AI systems don't see coming. You start with intuitive, creative approaches because it feels natural. But maintaining these systems requires actual engineering discipline. [That Hacker News post about "Git for AI Agents"](https://github.com/regent-vcs/re%5Fgent?ref=thedaringcreatives.com) captured the problem perfectly: "I find myself struggling with questions like 'why did you do it?' and 'when did you delete this folder?'" Traditional creative workflows have built-in decision tracking. Design files have layer histories. Video projects have timeline structures. Code has git logs. But when AI agents make autonomous decisions across multiple platforms, that audit trail disappears. ## The Economic Reality [Cloudflare just eliminated 1,100 jobs](https://techcrunch.com/2026/05/08/cloudflare-says-ai-made-1100-jobs-obsolete-even-as-revenue-hit-a-record-high/?ref=thedaringcreatives.com), with CEO Matthew Prince explicitly attributing it to "AI efficiency gains." That's not some abstract future threat—that's concrete evidence that agentic systems are moving beyond augmentation into replacement territory. Meanwhile, [Gen Z adoption of AI has stagnated](https://www.waltonfamilyfoundation.org/about-us/newsroom/gen-z-resentment-toward-ai-grows-as-adoption-stagnates-and-workplace-fears-mount?ref=thedaringcreatives.com) while workplace fears mount. Digital natives are rejecting AI tools. But economic pressure doesn't care about cultural resistance. [Sony embraces AI in game development](https://www.theverge.com/games/926914/sony-playstation-ai-powerful-tool-games?ref=thedaringcreatives.com) while acknowledging "many indie developers still reject it." That's the bifurcation happening right now: corporate workflows becoming agent-driven while independent creatives position themselves as "human-only" alternatives. Both paths are valid, but they're creating two distinct career tracks. You can become a creative technologist who builds and manages AI systems, or a creative craftsperson who explicitly avoids them. What you can't do is ignore the [choice](https://daringcreatives.com/iphone-17-phone-for-ai-creators/?ref=thedaringcreatives.com). ## The Authenticity Paradox As my workflows became more autonomous, my remaining decisions became more consequential. When AI handles production tasks, the creative professional's role shifts toward curation, direction, and strategic decision-making. [Claude's preference for HTML over Markdown](https://simonwillison.net/2026/May/8/unreasonable-effectiveness-of-html/?ref=thedaringcreatives.com) isn't just a technical detail—it means AI thinks in implementation-ready formats rather than intermediate description languages. That changes how you approach creative work entirely. You're not describing what you want; you're directing what should happen. The paradox is that increased automation might actually make creative work more human-centered, not less. When the mechanical stuff happens automatically, what's left is pure creative judgment. ## Where This Leads I'm not saying this convergence is good or bad. I'm saying it's happening whether we acknowledge it or not. The [task paralysis epidemic](https://g5t.de/articles/20260510-task-paralysis-and-ai/index.html?ref=thedaringcreatives.com) shows creatives are already stuck between "should I do this myself or ask AI?"—leading to workflow paralysis rather than productivity gains. But paralysis is a luxury. While we debate the ethics and aesthetics of AI-[assisted](https://daringcreatives.com/github-copilots-new-pricing-shows-who-really-owns-ai-assisted-development/?ref=thedaringcreatives.com) creativity, the economic reality is reshaping the entire landscape. Companies are building agent-driven workflows not because they're philosophically committed to AI, but because they work and they're cheaper. The uncomfortable truth is that I'm not just using AI anymore. I'm managing AI. And that management is becoming its own creative practice—one that requires both creative intuition and technical discipline. Whether that's the future we wanted or not, it's the one we're building. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/from-helping-ai-to-directing-ai-the-uncomfortable-truth-about-creative-workflows/from-helping-ai-to-directing-ai-the-uncomfortable-truth-about-creative-workflows-landscape-1920x1080.webp) ``` ### Vagabond Diary: What a photographer brings to AI art that prompts can't URL: https://www.thedaringcreatives.com/creator-stories/vagabond-diary-photographer-ai-art/ Last updated: 2026-08-01T19:42:11.000Z There's a French photographer named Charles Lopez who goes by Vagabond Diary. He shot travel and nature work for GQ, Daniel Wellington, Quechua — the kind of editorial and brand commissions that take years to build. Then he started integrating AI into his practice, and now he makes images that look like they were shot on pushed Kodak stock sometime in the late 1980s, except they're scenes that a camera couldn't have captured. I've been an admirer of his art for a while and I keep coming back to the same question: why does this feel like photography? ![Two figures watch a farmhouse burn under a night sky — Vagabond Diary](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/vagabondiary-burning-house.jpg) Charles Lopez / Vagabond Diary — from the artist’s collection at vagabondiary.com ## Most AI-generated images telegraph what they are By 2026, most of us have developed a pretty good eye for generative imagery. There's a specific kind of tonal incoherence — the style holds but the feeling shifts frame to frame. You can recognize it. The light is technically correct but emotionally vacant. The composition follows rules but doesn't feel chosen. Everything is rendered and nothing is seen. Lopez's work doesn't do that. His images have the weight of someone who spent years deciding where to stand before pressing a shutter. Two figures touching. A lone person swallowed by landscape. Light breaking through atmosphere in a way that feels earned rather than computed. The color temperature is warm and slightly pushed, the grain is present, the contrast sits in that sweet spot you get from film that's been handled. [Senso AI, the agency that represents him](https://www.senso-ai.com/?ref=thedaringcreatives.com), describes the work as "suspended in time, balanced between softness and tension." That's agency copy, but it's not wrong — there's a persistent melancholy in these images that holds across pieces. That emotional continuity is what separates his work from most generative output. And I think it comes directly from his background. ## What a photographer's eye actually gives you Here's the thing about spending years as a working photographer: you develop a vocabulary of decisions that becomes instinct. You know how light falls on skin at different times of day. You know what a 35mm frame does to a face versus what an 85mm does. You know when a composition is too clean and needs a foreground element to anchor it. You know what longing looks like in a body's posture. None of that knowledge disappears when you switch from a camera to a generative model. Lopez isn't describing images to an AI and accepting what comes back. He's applying a photographer's judgment to every stage of the process — concept, generation, selection, post-processing. The analog warmth isn't a filter he applied at the end. It's a series of decisions that someone who has spent years working with actual film stock would know how to make. This is worth sitting with if you're [a creator thinking about whether AI tools have a place in your practice](https://www.thedaringcreatives.com/adopting-an-ai-workflow/). The question usually gets framed as "will AI replace photographers?" But Lopez is doing something more interesting than that — he's using his photographic knowledge as the thing that makes his AI work coherent. The background isn't obsolete. It's the whole point. ## The technical gap in what we know Lopez's actual workflow is almost entirely undocumented. I don't know what models he's running. I don't know whether he's feeding his own photography archive into the process or working from text prompts or some combination. I don't know how many iterations a single piece goes through before he calls it done. What I know is the conceptual description Senso AI gives: he "amplifies reality through his visual processes" to "reveal scenes impossible to photograph, without ever losing emotion as the central anchor." That's true as far as it goes, but it doesn't tell you anything you could actually use. This opacity is common in AI art at the moment, and I understand the instinct behind it. Workflow documentation in a field this new feels like giving away something before you've fully figured out what you have. And there's a real tension between talking about your process technically and having the work be received on its own terms — the more you explain the machinery, the more people look for the seams. But the gap matters, because what Lopez is doing is genuinely worth understanding. The fact that his images maintain [emotional continuity across pieces](https://www.thedaringcreatives.com/ai-image-consistency/) suggests either very rigorous curation (he's generating a lot and showing very little) or a workflow that's built around narrative coherence from the start. Either approach is interesting. Both would be worth documenting. ## The business model is quieter than you'd expect Lopez [sells prints through vagabondiary.com](https://vagabondiary.com/?ref=thedaringcreatives.com) starting at €39\. He's represented by Senso AI, an agency that specifically works with AI artists. His primary distribution is Instagram. That's it. No platform monetization play. No brand partnership announcements. No "AI art course" upsell. Just gallery-priced prints sold directly. For anyone building a creative practice around AI-generated work, this is worth paying attention to. The discourse around AI art in 2026 is still largely stuck on platform dynamics — who's posting where, what the algorithm rewards, how to build follower counts. Lopez seems mostly uninterested in that conversation. He's positioned the work as collectible, priced it like art rather than content, and let the prints carry the business. The €39 entry point is smart. It's low enough to not feel like a gallery gatekeeping move, but the work is presented in a way that positions it as something you'd frame rather than something you'd screenshot. That framing matters more than most creators give it credit for. ## Why the "AI artist" label is working against most people in this space Senso AI's positioning for Lopez is careful about language. They call him a "visual artist who weaves together multiple techniques." They don't lead with AI. The emphasis is on narrative and emotion, with the tools described as method rather than subject. I think this is right, and I think most AI artists are making the opposite mistake. When you lead with the tool, you're inviting people to evaluate the tool rather than the work. You're also anchoring yourself to a category that carries a lot of baggage right now — the copyright debates, the ethics discourse, the "is it really art" arguments that mostly generate heat without light. Lopez sidesteps all of that by just presenting images and letting people respond to them. Now, you could argue that transparency about AI use matters and that artists have a responsibility to disclose their methods. I don't disagree with that in principle. But disclosure and leading with the tool are different things. You can be honest about your process without making the process the headline. The work is the headline. ![Fire streaking between two silhouetted figures at dusk — Vagabond Diary](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/vagabondiary-fire-silhouettes.jpg) Charles Lopez / Vagabond Diary — from the artist’s collection at vagabondiary.com ## What this means if you're a creator thinking about AI tools The pattern I keep seeing in the people doing interesting work with generative AI is that they're not starting from the AI. They're starting from something they already know — a photographic sensibility, a writing voice, a design vocabulary — and using the tools to go somewhere that method alone couldn't take them. Lopez couldn't photograph the scenes he's making now. A camera can't capture a memory that doesn't exist. But his camera work is what makes the AI-generated images feel like photographs rather than illustrations. The years of shooting landscapes for editorial clients didn't become irrelevant when he [changed his tools](https://www.thedaringcreatives.com/letting-go-old-tools/). They became the foundation. That's a different relationship with AI than "I use it to go faster" or "I use it because everyone else is." It's using the tools to make [something that your existing practice was pointing toward](https://www.thedaringcreatives.com/the-creators-ai-journey-from-holy-shit-chatgpt-to-building-your-own-tools/) but couldn't reach. I don't know what that looks like for your specific practice. But if you're a creator sitting on years of domain knowledge wondering whether AI has anything to offer you, Vagabondiary is worth looking at. Not for the workflow — that's still mostly undocumented — but for what's possible when someone brings real craft to these tools instead of just prompting and hoping. The work is at vagabondiary.com. The prints start at €39. ### Token maxing: How Meta and Amazon measure AI productivity backward URL: https://www.thedaringcreatives.com/token-maxing-ai-productivity/ Last updated: 2026-08-01T19:42:12.000Z There's a pattern in how organizations measure work that never really goes away — it just finds a new costume. For a while it was physical presence, then it was email response time, then it was Slack availability, then it was story points. Now it's tokens. [Meta's internal leaderboard](https://www.thepragmaticengineer.com/tokenmaxxing/?ref=thedaringcreatives.com) called "Claudeonomics" ranked 85,000 employees by how many AI tokens they consumed. Top performers got titles like "Token Legend." In one 30-day window, those employees burned through 60.2 trillion tokens — which at standard Anthropic pricing would have cost somewhere around $900 million. Jensen Huang publicly said he'd be "deeply alarmed" if a $500,000 engineer wasn't consuming at least $250,000 worth of tokens annually.. ## What employees actually did when the leaderboard went up At Amazon, where management set a target for 80% of developers to use AI weekly, [Amazon employees report gaming](https://www.fastcompany.com/91317828/amazon-employees-tokenmaxxing-ai?ref=thedaringcreatives.com) an internal tool called MeshClaw to run overnight on low-value tasks — monitoring deployments, triaging email, consolidating notes — not because those tasks needed doing that way, but because the agent running meant tokens were accumulating. One engineer apparently used an AI to find ways to mock a project manager. At Meta, employees started inflating prompts deliberately. Instead of asking for a concise answer, you ask for a verbose explanation with multiple alternatives, detailed reasoning, and rollback options. You dump entire Slack histories into a model for trivial analysis. You feed large, irrelevant documents through summarization tasks first thing in the morning just to rack up input tokens before the real work starts. None of this is irrational behavior given the incentives. All of it is completely useless. The engineers doing this aren't the problem. The people who designed a system where this is the logical response are. ## Goodhart's Law has been waiting for this moment There's a principle — Goodhart's Law — that says when a measure becomes a target, it stops being a useful measure. It's been around since the 1970s and economists have been watching it play out in every domain imaginable. Whenever you pick a proxy for the thing you actually want and then reward the proxy directly, people optimize for the proxy and the underlying thing you cared about quietly stops mattering. Token consumption is a near-perfect Goodhart trap. It sounds like it should correlate with useful AI work — if you're using the tools, you're presumably doing something with them. But tokens measure compute consumed, not value created. They measure the size of the conversation, not whether the conversation produced anything worth having. A 2026 PwC survey found that 56% of CEOs reported no significant revenue increase or cost reduction from AI investments in the past year. That's not a coincidence. That's what happens when [adoption theater gets mistaken for transformation](https://daringcreatives.com/most-creatives-not-using-ai/?ref=thedaringcreatives.com). ## The defense isn't crazy, it's just incomplete Meta's CTO Andrew Bosworth defended the practice by saying that when high token spending results in 5-10x productivity gains, it's "easy money." And honestly, that's not a wrong position — it's just a position that assumes the token spending and the productivity gains are connected, which is exactly what the gaming behavior puts in doubt. If you can't tell the difference between tokens burned on real work and tokens burned on invented busywork, the leaderboard isn't measuring productivity. It's measuring the willingness to [run AI agents](https://daringcreatives.com/the-ai-you-never-have-to-open/?ref=thedaringcreatives.com). Those are different things. The steelman version of Bosworth's argument is that in the early days of a new tool, getting people to use it at all has value — even if some of that usage is inefficient, you're building familiarity, discovering use cases, and normalizing the workflow. I actually think that's partially true. I've used AI in pretty dumb ways when I was first figuring out what it could do — just asking it things I could have Googled, basically using it as a search engine with better grammar. That's how most of us got started. There's no shame in the learning curve. But there's a difference between a learning curve and a leaderboard. One is a phase you pass through. The other is a permanent incentive structure that rewards the wrong behavior indefinitely. ## What measuring outcomes actually looks like A few companies have tried to build something better, though none of them have been doing it long enough to know if it works at scale. Salesforce created what they're calling "Agentic Work Units" — measuring completed AI tasks rather than tokens consumed. Marc Benioff's framing is worth quoting directly: "A token on its own doesn't know your customers, your pipeline, your org chart, but Salesforce does. And the value isn't in the token. The value is in what our platform does with it, the work." That's the right frame. Whether the AWU metric actually captures "the work" in a way that can't also be gamed is a genuinely open question — the metric is new enough that the reporting on it is still mostly Salesforce's own documentation. Zapier took a different approach and tracked percentage of active employee usage, number of AI-powered workflows deployed, and number of AI experiments launched. They hit 97% active employee usage. That's still an activity metric rather than an outcome metric, but it's at least measuring [whether people are building things](https://daringcreatives.com/adopting-an-ai-workflow/?ref=thedaringcreatives.com) rather than whether their agents ran overnight. Writer tracks "words generated," "recaps transcribed," "words rewritten" — more granular than tokens, closer to actual work product. It's not perfect either, but at least it's pointing at something a person produced rather than something a server processed. None of these are fully solved. But they're all pointing in the right direction: toward what got done, not toward how much compute got burned doing it. ## What this means if you're not at Meta Most of the people reading this aren't running 85,000-person engineering organizations. But the dynamic isn't exclusive to big companies, and the pressure version of it is already showing up in smaller contexts. If you're a freelancer or a small-team operator, nobody's handing you a token leaderboard. But there's a softer version of the same trap: the impulse to demonstrate AI usage rather than demonstrate results. Showing a client a 40-page AI-generated research document when they needed a two-paragraph answer. Running a dozen different AI tools on a project to prove you're "using AI" when one tool used well would have been enough. I catch myself doing versions of this — reaching for AI on things where it doesn't actually help because it feels like the right move in 2026. The question worth asking isn't "am I using enough AI?" It's "did the work get better?" Those are genuinely different questions and the second one is harder to answer, which is probably why [companies keep defaulting to the first](https://daringcreatives.com/the-ai-standardization-trap-why-big-companies-are-always-one-step-behind/?ref=thedaringcreatives.com). If your company or client starts tracking AI usage as a KPI — token counts, sessions, weekly active usage — you're watching the same trap get set. The metric will look like accountability. It will feel like progress. And the people being measured will respond exactly the way the Meta engineers did: rationally, efficiently, and in ways that produce nothing useful. The tools are genuinely good. Claude, Gemini, GPT-4o — I use them constantly and they've changed how I work in real ways. But the value isn't in how many tokens you burn. It's in whether the output was worth having. That's a harder thing to put on a leaderboard, which is exactly why nobody's figured out how to do it yet. ### Stop Spending Five Hours on Five-Second Content URL: https://www.thedaringcreatives.com/stop-spending-hours-quick-content/ Last updated: 2026-08-01T19:42:12.000Z You're spending five hours on something people will consume in five seconds. You're agonizing over that Instagram post. You're hiring a designer for a simple email header. You're rewriting that LinkedIn update for the eighth time. And for what? So someone can scroll past it in their feed without stopping. I'm not saying your work doesn't matter. I'm saying the math doesn't work. ## The Five-Second Reality Here's what actually happens when you post something online: Someone sees your content for maybe 1-3 seconds as they scroll. If you're lucky, they pause for 5-10 seconds to read it. If you're really lucky, they engage with it. But most of the time? Gone. Next post. Your five hours of work just got consumed faster than someone can microwave leftover pizza. This isn't me being cynical. It's just how feeds work. The average person scrolls through hundreds of posts per day. They're not studying your perfect color choices or admiring your carefully crafted transitions. They're looking for something that stops them, and if your post doesn't do that in the first second, the craft you put into seconds 2-10 doesn't matter. ## What You Could Do Instead Instead of spending five hours on one post, what if you made five posts in that same time? Yeah, I know what you're thinking. "That sounds like spam." But spam isn't about volume. Spam is about lazy intent. Human slop is what happens when someone directs AI to churn out garbage without thinking about the person on the other end. That's not what I'm suggesting. What I'm suggesting is being more strategic about where you spend your craft time. ## The Better Approach Spend your five hours like this: - 30 minutes planning what you actually want to say across multiple pieces - 3 hours creating the content (yes, using AI tools to handle the repetitive parts) - 1.5 hours [reviewing](https://daringcreatives.com/reviewing-the-google-ai-professional-certification-from-coursera/?ref=thedaringcreatives.com), [editing](https://daringcreatives.com/how-ai-turned-me-into-a-creative-superhero-and-why-you-should-care-v2/?ref=thedaringcreatives.com), and making sure each piece serves your audience Now you have five pieces instead of one. Five chances to connect with someone. Five opportunities to be useful. Five times the surface area for people to find your work. The craft isn't gone—it's just distributed differently. Instead of perfecting one thing that most people won't see, you're being thoughtful about five things that have five times the chance of reaching someone who needs to hear it. ## Where Real Craft Lives The craft that matters most in quick-consumption content isn't in the visual polish. It's in understanding what will make someone stop scrolling. It's in knowing your audience well enough to say something they actually care about. It's in being genuine enough that when they do pause for those five seconds, they feel like they learned something or connected with someone real. That understanding doesn't come from spending more time in Photoshop. It comes from shipping more, learning what works, and getting better at reading the room. I'm not against high-production content. If you're making a course or a long-form video or something people are going to spend 30 minutes with, absolutely spend the time to make it great. But for the stuff that lives in feeds? Be honest about what you're optimizing for. Your time is worth more than perfecting something that disappears in a blink. ### AI pitch generator: how the front of my content loop actually works URL: https://www.thedaringcreatives.com/ai-pitch-generator-content-loop/ Last updated: 2026-08-01T19:42:12.000Z In the [hub article about my AI content system](https://www.thedaringcreatives.com/the-ai-system-behind-this-site/), I mentioned something called the pitch generator and moved on pretty quickly. I want to slow down here because it's the most counter-intuitive part of the whole setup — and honestly, the part I'm most glad I got wrong first before getting right. Here's the short version: every morning at 6:35 AM, a script called `propose-topics.js` writes a list of content pitches to a queue file. Subject, one-line reason why now, a rough priority rating, seed URLs. That's it. Nothing gets researched. Nothing gets drafted. The system just asks what I want to work on and then waits. That might sound obvious. It wasn't how I started. ## What the system was doing before The original version of this pipeline was more aggressive. It would pick topics on its own and auto-draft them overnight. I'd wake up to finished articles sitting in a folder, ready to publish. That sounds great. In practice it was kind of a mess. The problem wasn't that the drafts were bad, exactly. It's that I hadn't agreed to any of them. I'd open my laptop and find 1,200 words on a topic I had no context for, no opinion on, and no memory of deciding to care about. Some mornings the drafts were genuinely interesting and I'd think "okay, sure, I'll work with this." Other mornings I'd close the tab immediately and feel vaguely annoyed at my own system. The darker version of this: at one point an earlier inspiration path produced a pitch built on fabricated research about a creator I didn't actually know. The system had invented a story and written it up confidently. That one shook me a little. Not because AI hallucinated — that's a known thing — but because the auto-draft architecture meant the hallucination got all the way to a finished piece before I ever touched it. That's when I understood the real problem. The bottleneck wasn't topic quality. It was that the decision about *what to make* was happening without me. ## The ideas-first pivot The fix shipped on June 7th and I've been calling it the ideas-first pivot internally. The logic is simple: the system earns the right to draft by asking first. Now `propose-topics.js` generates pitches, not drafts. I approve one (either through the Command Center interface or just by telling Sherman in chat), and *then* research and drafting happen. The decision stays with me. The system does the legwork of surfacing options and making a case for each one — but it doesn't move until I say go. ![Sherman pitching content ideas from the morning queue in the Command Center chat](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/06/sherman-pitching-ideas.jpg) Asking Sherman 'what should I write about?' — he pitches from the morning queue (\~50/50 build-in-public and news), and nothing gets drafted until I approve one. The ideas-first gate in action. This is a small architectural change. It's also the difference between a system I trust and one I'm constantly second-guessing. ## What signals the pitch generator actually reads This is the part I find genuinely interesting to explain, because it's not just "scan the news and pick something trending." The system reads three sources when building each morning's pitch queue. The first is the AI news feed — a rolling \~14-day window of tagged headlines and developments that gets updated automatically. This is the obvious one. Something ships, something gets announced, the system notices and asks whether we should write about it. The second is what I call the striking-distance report — a Search Console analysis of queries where this site already ranks somewhere between position 4 and 20\. These are terms where we're getting impressions but not many clicks. We're close to page one but not quite there. A well-timed piece that actually addresses the query directly could push one of those rankings over. The pitch generator uses this as a signal for what's worth doubling down on, not just what's new. The third source is the build journal — a log of decisions, git commits, and session activity that tracks how the system itself was built. This is where the "build in public" pitches come from. When I've spent a week solving a specific problem in the pipeline, the journal knows that happened. The pitch generator can look at recent activity and say, essentially, "you just figured something out — should we write about it?" The mix is intentionally around 50% build-in-public content and 50% news-driven. In my experience, the process pieces perform better over time. Hot takes have a short shelf life. "Here's how I built this specific thing and what broke" tends to keep pulling traffic for months. ## How it defends against repeating itself One thing I didn't want was a system that pitches the same dead ideas every morning. If I reject something, I want it gone, not cycling back into the queue next week with slightly different wording. So rejected pitches get blacklisted. When I pass on a topic — either explicitly or by telling Sherman to drop it — that idea is filtered out of future proposals. The system also tracks which topics I've told it to avoid entirely, as a standing list separate from individual rejections. I'm not going to get into the specifics of how the matching works because there are some evasion-risk details I'd rather not publish. But the functional result is: a dead idea stays dead. The pitch queue each morning is genuinely new options, not a reshuffled version of yesterday's. ## What this actually changes about how I work The practical difference is that I start most mornings with a short list of pre-reasoned options instead of a blank page. Each pitch has a subject, a one-sentence argument for why it's worth doing right now, and a rough sense of how high-leverage it is. I can scan the list in two minutes and either pick one, add a note, or ask Sherman to explain the reasoning behind a specific pitch before I decide. I still override the system constantly. Some mornings I have something specific I want to write and the pitch queue is irrelevant. Some mornings I look at all five pitches and none of them feel right and I ask for more. The queue is a starting point, not a mandate. But here's what changed: I'm no longer starting from nothing. The cognitive work of "what should I even think about today" is mostly handled before I sit down. That's the part of content creation I find most draining — not the writing, but the [cognitive work of deciding what's worth making](https://www.thedaringcreatives.com/autonomy-changes-what-you-make/). The pitch generator takes a real swing at that question every morning and leaves the final call to me. ## The thing I keep coming back to There's a version of AI-assisted content work where the system does as much as possible and you rubber-stamp it. I tried that version. It's faster in a narrow sense and it's also kind of hollow — you end up publishing things you didn't really choose, and eventually you can feel that in the work. The pitch-first architecture is slower at the front end. There's a step I have to do every morning that the old system didn't require. But everything downstream of that approval feels like mine in a way the auto-drafted stuff didn't. I think this is probably true for most people building [AI-assisted workflows that actually feel good to work inside](https://www.thedaringcreatives.com/why-your-ai-productivity-stack-is-actually-making-you-slower/), not just content pipelines. The systems that feel good to work inside are usually the ones where the machine handles the legwork and you handle the decisions — not the ones where the machine handles everything and you just check for errors. The next deep dive in this series gets into the research layer — what happens after a pitch gets approved, how Sherman actually goes and finds the material, and what I've had to constrain there to keep the outputs honest. If you haven't read the [hub article that this series is built around](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/), that's the right place to start — it covers the whole AI system behind this site and how all the pieces connect. ### Lexicon Tower Security Upgrades Restrict Upper District Access Routes URL: https://www.thedaringcreatives.com/aegis/lexicon-tower-security-upgrades/ Last updated: 2026-08-01T19:42:12.000Z New security installations around Lexicon Tower create checkpoint zones affecting three major pedestrian corridors _This post is for subscribers only._ ### AI Agents on Your Desktop: What Changes When AI Leaves the Browser URL: https://www.thedaringcreatives.com/lil-agents-desktop-ai/ Last updated: 2026-08-01T19:42:13.000Z I've been thinking about the small stuff lately. Not the big model releases or the enterprise deals — the small, weird, personal tools that developers build because something in their workflow annoyed them enough to fix it. lil agents is one of those tools, and I keep coming back to it because the design choices Ryan Stephen made feel like a position statement, even if that wasn't the intent. Here's the basic thing: lil agents is a free, open-source macOS app that puts two animated characters — Bruce and Jazz — on your dock. They walk back and forth. You click one, a popover terminal opens, and you're talking to Claude, Gemini, OpenAI Codex, or GitHub Copilot. No browser tab. No switching contexts. No account to log into. The AI is just... there, on your desktop, waiting. When it's thinking, little bubbles appear with phrases like "Pondering the cosmos..." When it's done, a sound plays. It has four color themes: Peach, Midnight, Cloud, Moss. It has 1,300+ stars on GitHub and I think the reaction it gets — genuine delight, not just "cool project" — tells you something. ## The Clippy joke is doing a lot of work here Everyone who writes about lil agents mentions Clippy. I get it, the visual parallel is obvious. Animated character on your desktop, connected to something that's supposed to help you. But Clippy is remembered as a failure of a specific kind: it interrupted you, it assumed you needed help when you didn't, and it had no off switch that felt respectful. The joke landed because everyone had been annoyed by it. lil agents inverts that. You go to it. It doesn't come to you. Bruce and Jazz walk around on the dock doing their thing, and they stay there until you click. That's a meaningful design decision, even if it sounds small. A lot of AI tools right now are competing to be more present, more proactive, more anticipatory. Clicky, for instance, is an AI that sits next to your cursor and can see your screen — it's watching, waiting to jump in. That might be exactly what some people want. But it's a fundamentally different relationship than "I'll be here when you need me." Ryan Stephen talked about this in an interview — asking himself "what's the most playful way to interact with AI?" and thinking about AI as material to explore, not just a service to consume. That framing matters. When you think of AI as material, you start asking different questions about form. You're not just asking "how do I make this more powerful?" You're asking "how does this feel to use? What kind of presence does it have?" ## The privacy architecture is a design choice, not just a feature Here's the part I find most interesting, and it's easy to miss if you're just looking at the cute characters. lil agents runs entirely locally. No user accounts. No analytics. No data collection. Your AI interactions go through whichever CLI you've installed — Claude Code, Gemini CLI, whatever — and those interactions are governed by that provider's policies, not by anything lil agents itself is tracking. In a category where most tools are racing to give [AI agents with more access](https://daringcreatives.com/ai-agents-are-about-to-take-over-your-browser-and-thats-actually-good/?ref=thedaringcreatives.com) to more of your data, this is a real editorial stance. The Future of Privacy Forum has written about the data protection challenges that come with AI agents that have persistent access to your environment — the more an agent knows about you, the more useful it can be, but also the more exposure you carry. lil agents essentially says: we're not in that business. You get the interface. Your data stays between you and the model provider you already chose. That costs something in features. lil agents can't learn your preferences over time the way a more data-hungry tool could. It can't anticipate what you're about to ask. It can't build a profile of your work patterns. Whether that trade-off is worth it depends on what you're trying to do — but the fact that Ryan Stephen made it explicit, in the architecture rather than just in a privacy policy, is worth noticing. I'll be honest: I usually don't think hard about this stuff until something goes wrong somewhere and it's in the news. lil agents made me think about it proactively, which is the better time to do it. ## What "AI as material" actually means for how we build tools The quote from Ryan Stephen that I keep coming back to is the one about "AI as material." Most of the conversation about AI tools right now is about capability — what can it do, how fast, how accurately. The interface is treated as a wrapper around the capability. You build the thing that works, then you make it look okay. lil agents flips that priority, or at least balances it differently. The interface is the argument. The animated characters aren't decoration on top of a terminal — they're making a claim about what it should feel like to have AI in your workspace. Present but not intrusive. Useful but not surveilling. Playful without being condescending. That's a harder design problem than it sounds. The Forbes piece on gamification in the workplace raises a real concern: when you add delight and personality to tools, you can tip into manipulation, into making people feel more attached to a tool than they should be, into engineering dependency rather than genuine usefulness. I don't think lil agents crosses that line — the characters are charming, not addictive, and the whole thing is opt-in in a deep way — but the concern is real and worth keeping in mind as this category grows. The question Ryan Stephen seems to be asking is whether you can make AI feel human-scale without making it feel manipulative. Whether presence can mean "available" rather than "watching." That's not a solved problem. lil agents is one attempt at it, and the fact that it's [open-source under an MIT license](https://daringcreatives.com/the-open-source-ai-race-just-got-real/?ref=thedaringcreatives.com) means other developers can look at the attempt, learn from it, fork it, and try their own answer. ## Why this matters for creators and freelancers specifically Most of us aren't developers. I'm not. But the tools that developers build for themselves usually show up in our workflows six to eighteen months later, either directly or as influence on the products we end up using. lil agents is worth paying attention to now because it's working through questions that are going to affect everyone who uses AI in their work. The [AI moving from destinations to ambient presence](https://daringcreatives.com/the-ai-you-never-have-to-open/?ref=thedaringcreatives.com) is already happening. Claude has a desktop app now. Gemini is baked into Google Workspace. Microsoft Copilot is embedded in Windows. The browser tab model is getting replaced by something more ambient. The question is what values get embedded in that ambient layer — who it serves, what it watches, how it behaves when you're not actively prompting it. lil agents is a small, free tool made by one developer who wanted something that felt less like infrastructure. It has two tiny animated characters and four color themes and a sound that plays when your query is done. And it's asking better questions about the future of AI interfaces than most of the venture-backed products in the same space. That seems worth paying attention to. You can find it at lilagents.xyz or check out the [lil agents GitHub repo](https://github.com/ryanstephens/lil-agents?ref=thedaringcreatives.com)—the code is public and right there if you want to see how it works. ### I Built an AI System to Run My Content Operation. Here's the Whole Thing. URL: https://www.thedaringcreatives.com/ai-system-runs-content-operation/ Last updated: 2026-08-01T19:42:13.000Z Most of what goes out under The Daring Creatives — the articles, the newsletter, the posts across Threads and LinkedIn and Instagram — runs through a system I built. A loose collection of scripts, APIs, and a few stubborn rules, wired together so one person can operate something that normally takes a small team. The honest backstory first: nobody paid me to build this. No client, no budget — my own time and my own money. I built it to learn AI the way that actually sticks for me, which is by making something real with it instead of reading about it. And since I was footing the bill anyway, I figured it should be something I'd genuinely want to read and tinker with — fun enough to keep diving into, and good enough to put in front of someone as proof of how far I've come. I wrote [a first version of this overview](https://www.thedaringcreatives.com/how-we-built-our-ai-content-pipeline-and-whats-actually-running-it/) back in April, when the whole thing was mostly Obsidian and a couple of Claude prompts. It's grown a lot since — most of what's below didn't exist then. So treat this as the current map. Most of it is built from tools you already have access to, and once you see the shape of it, you'll probably spot a piece you could build for yourself this weekend. Let me start with what I was actually trying to do. ## The goal I'm one person, and I wanted to run a real content operation anyway — a site that publishes a few times a week, a weekly newsletter, four social accounts, and a serialized fiction world running underneath all of it. The catch was time. The repetitive shit — researching a topic, formatting a draft, resizing images, scheduling posts, remembering what I already published — that's the work I'd happily hand off. What I wanted to keep was the deciding: what to make, what's good enough to ship, what actually sounds like me. So the whole system is built around one split. The AI does the labor. I make the calls. Everything else is plumbing in service of that line — and building that plumbing, piece by piece, is how I actually learned this stuff. ## The core loop Underneath all the parts, there's one loop the whole thing runs on: Ideas → I approve → research and draft → I review → publish and promote → measure → learn. Each step is a specific program doing a specific job. Here's who does what — or click through it yourself: THE DARING CREATIVES · CONTENT PIPELINE ◉ HEALTHY · 3/DAY · NEXT 1:00 PM PT INTERACTIVE — ONE OPERATOR DECIDES, THE MACHINE RUNS THE REST ◂ Back Start ▸ ## The systems that do the work I gave the moving parts names, because "the script" stops being useful once there are a dozen of them. These are the main ones. **The orchestrator** is the heartbeat. It's a script that wakes up on a schedule, looks at what shipped this week versus what I planned, and decides what the system should work on next. It used to just draft whatever it thought was missing — which is how I once opened the folder to seventeen articles I never asked for. Now it defers to the pitch queue instead, which is the single best change I've made. **The pitch generator** is what fills that queue. Once a day it reads my AI news feed, my Google Search Console data, and — the part I like most — my own build log, then asks Claude to propose a short list of things worth writing about. About half the pitches now come from the work itself: a bug I fixed, a decision I made, a system I shipped. I approve the ones I want; nothing gets researched or drafted until I do. **Research and drafting** is a two-model handoff. When I approve a pitch, Gemini does the deep research — it's good at pulling current, wide context. Then Claude (Sonnet) writes the first draft, working against [a file of my voice patterns](https://www.thedaringcreatives.com/teach-ai-brand-voice/) the system has learned from my past edits, so the draft starts closer to how I actually talk. It's a starting point. I rewrite it. **The optimizer** is the pass that runs after a draft exists. It adds internal links — but only to pages that genuinely exist on the site, checked against an index of real URLs, because nothing tanks trust like a link to a page that isn't there. It also handles SEO housekeeping: titles, meta descriptions, tags. **The scheduler** takes an approved piece, pushes it to Ghost (the CMS this site runs on) through Ghost's Admin API, and books it into an open slot on the calendar. No copy-paste, no browser tabs. **The distributor** fans each published piece out to social. It reshapes the article into posts sized and voiced for each platform — Threads sounds nothing like LinkedIn, which sounds nothing like Instagram — and queues them through Buffer. One article becomes a week of distribution without me babysitting it. ## The crew Here's the part people find strange, and it's my favorite. The dashboard isn't a wall of charts. It's three characters who report in. Sherman is the creative director — he runs what I call Central Dispatch and files a short status every morning (written by Claude Sonnet against the day's real data): what shipped, what's in the queue, what we should do next. Wilson is the engineer; he scans the pipeline for things that broke and quietly fixes what he can. Sebastian watches the audience and search data and flags pieces worth promoting. They're not magic — under the hood they're prompts with access to the same logs and data the rest of the system writes. But giving it a few distinct voices turned a boring dashboard into something I actually want to open, which, when it's your own money and your own free time, matters more than it sounds. ## The rest of it **Images** come from Gemini — it generates them, including [a consistent cast](https://www.thedaringcreatives.com/ai-image-consistency/) for the fiction side. I browse and assign those by hand; I didn't want the machine choosing the pictures. **The watchers** are small jobs that keep the thing honest — checking that posts go out on cadence, that the data feeding decisions is fresh, that nothing's silently stuck. When something breaks, I'd rather hear it from my own system than from a reader. ## What it's actually built on None of this is exotic. The CMS is Ghost. Social posting runs through Buffer. The research and images run on Gemini; the writing — drafts, social copy, the morning dispatch — runs on Claude, mostly Sonnet. The glue is a pile of Node scripts run by cron, the same scheduler that's been sitting on every Mac and Linux machine for decades. The dashboard is a small local web app. That's the whole stack. I point that out because "AI content system" sounds like something you need a company and a budget to build. It isn't. It's a few APIs, a scheduler, and the patience to wire up one piece at a time. ## If you want to build your own Start with one link, not the whole loop. Pick the part of your own work that's the most repetitive and the least creative, and automate just that. Maybe it's reshaping a finished post into your social drafts. Maybe it's a morning script that gathers everything you need to read before you start. Get one piece working, live with it a week, then add the next. That's genuinely how this got built — it didn't arrive as a system, it accreted one annoyance at a time, and each piece taught me what I needed to build the next. The most important rule is a human one: the approve step. The orchestrator can pitch, the optimizer can polish, the scheduler can publish, the crew can report — but nothing goes out under my name until I've read it and said yes. Everything that ships is something I chose. The machine handles the work, not the judgment. This is the first piece in a series I'm going to keep writing as I build — I'll pull apart each subsystem in its own post, including the stuff that breaks along the way. If there's a part you want me to open up first, tell me. ## The deep dives I am pulling each subsystem in the loop apart in its own post. The full series: [**The pitch generator**](https://www.thedaringcreatives.com/ai-pitch-generator-how-the-front-of-my-content-loop-actually-works/) — how the system decides what is worth writing, and why it pitches instead of publishes. [**Research and drafting**](https://www.thedaringcreatives.com/ai-research-to-draft-pipeline-why-a-prompt-rule-isnt-enough/) — the two-model handoff, and a style guide grown from my own edits. [**The optimizer**](https://www.thedaringcreatives.com/how-one-wrong-domain-constant-broke-four-internal-links-at-once/) — how one wrong domain constant broke four internal links at once. [**The scheduler**](https://www.thedaringcreatives.com/ghost-cms-automation-the-publish-button-i-never-press/) — the publish button I never press. [**The distributor**](https://www.thedaringcreatives.com/ai-content-distribution-the-part-of-the-pipeline-that-refuses-to-have-an-opinion/) — one article, reshaped for every platform. [**The crew**](https://www.thedaringcreatives.com/named-ai-agents-why-i-gave-my-automations-three-dogs-names/) — why I gave my automations three dogs’ names. [**The orchestrator**](https://www.thedaringcreatives.com/ai-orchestrator-the-layer-that-watches-your-whole-pipeline/) — the layer that watches the whole pipeline and decides what’s next. ### The Real Cost of Playing It Safe URL: https://www.thedaringcreatives.com/cost-of-playing-it-safe/ Last updated: 2026-08-01T19:42:13.000Z I've been watching people tear apart beginners for sharing "imperfect" work, and it's getting exhausting. Last week, someone posted their first AI-generated logo on Threads (and this happens every day, I could literally pull examples forever). Within hours, the quote tweets rolled in: "This is why clients don't trust designers anymore." "AI slop flooding the market." "Learn actual design before you embarrass yourself." I liked the post. Loved it, in fact. Because I love seeing people share what they are learning. They tagged it as practice. They asked for feedback. They were transparent about their process. And instead of encouragement or constructive criticism, they got dragged. ## The Perfectionist's Trap We've created this weird culture where you're supposed to emerge fully formed. "Don't share anything until it's portfolio-ready." "Don't ask questions that reveal your inexperience." Basically, don't let anyone see you struggle. It's weakness. That's bullshit, and it's holding everyone back. The people talking shit? Most of them learned the same way. Now we expect beginners to produce expert-level work on their first try, or at least keep their failures private until they're ready for the spotlight. ## What We Actually Learn From I've released plenty of work onto that makes me cringe now. Early blog posts, presentations that were lame. Hell, Claude Code told me last week that my content pipeline was 60% good and 40% scar tissue. You know what I learned from that work? Everything. The failed presentation taught me how to structure an argument. The clunky blog posts showed me which ideas actually mattered to people. The messy code forced me to understand why clean code matters in the first place. If I had waited until I was "ready" to share any of it, I'd still be waiting. ## The Gatekeeper Problem The people policing other people's learning process usually fall into one of two camps: insecure experts protecting their turf, or advanced beginners who just figured something out and want to pull up the ladder behind them. Both groups are missing the point entirely. When someone shares imperfect work, they're not claiming to be an expert. They're not trying to compete with you. They're doing the same thing you did when you were starting out: putting themselves out there and hoping to learn something. The response to that shouldn't be ridicule. It should be recognition. ## What Actually Helps Instead of dunking on people's early attempts, try this: Point out one thing that's working. Even if the overall execution is rough, there's usually something — a color choice, a concept direction, a problem they identified — worth acknowledging. Ask about their process. "What were you trying to solve here?" often leads to more interesting conversations than "This sucks." Share your own early work. Show them they're not alone in producing imperfect first attempts. Most people keep their learning journey private, which makes everyone else feel like they're the only ones struggling. Suggest specific next steps. "Try adjusting the line spacing" is infinitely more helpful than "Learn typography." ## The Real Value Here's what the perfectionist crowd doesn't understand: messy work shared publicly creates more value than polished work kept private. The beginner who posts their rough logo might inspire someone else to try. Their questions might surface useful resources. Their mistakes might help others avoid the same pitfalls. ## Permission to Suck We need more people willing to suck in public. More first attempts shared without apology. More questions asked without shame. More experiments posted without disclaimers. The internet already has enough polished content created by people pretending they never struggled. What it needs is more honest documentation of the learning process itself. Your messy work is more valuable than you think. Not because it's perfect, but because it's real. Share it anyway. ### The Day AI Stopped Being a Tool and Started Being Your Business Partner URL: https://www.thedaringcreatives.com/ai-as-business-partner/ Last updated: 2026-08-01T19:42:13.000Z OpenAI just [launched a feature](https://www.theverge.com/ai-artificial-intelligence/931122/openai-chatgpt-financial-accounts-plaid-connection?ref=thedaringcreatives.com) that lets ChatGPT connect to your bank accounts, credit cards, and investment accounts. Pro users only, U.S. only, through Plaid integration. They're calling it personal finance assistance. I'm calling it the moment AI stopped being a creative tool and [started becoming business infrastructure.](https://daringcreatives.com/10x-lesson-business-proximity/?ref=thedaringcreatives.com) Here's what I mean. When I use Claude to analyze a piece of content or Gemini to help draft something, I'm using AI as a tool. If Claude goes down for a day, I switch to Gemini and keep working. If both are down, I write manually. Annoying, but not catastrophic. But if ChatGPT is analyzing my cash flow, tracking my [recurring subscriptions](https://daringcreatives.com/reality-of-ai-subscriptions/?ref=thedaringcreatives.com), and making budget recommendations based on my actual transaction data—and then it goes down—I don't just lose a tool. I lose access to the financial brain of my business. ## The Pipeline Problem I've spent the last year building automated content systems that route through multiple AI providers. Claude for analysis, Gemini for image generation and research, and sometimes GPT for specific tasks. What I've learned is the more critical the function, the more dangerous single-vendor dependency becomes. Financial integration breaks this hedge strategy completely. You can't easily distribute your bank data across multiple AI providers the way you can distribute content creation. Once ChatGPT knows your complete financial picture, switching to Claude means rebuilding that entire context from scratch. OpenAI knows this. That's why they're not just adding financial features—they're creating switching costs. The deeper ChatGPT integrates into your business operations, the harder it becomes to leave. ## The Automation Paradox Here's what really concerns me: the more you automate with AI, the less you understand your own systems. I've seen this in my content pipelines. When everything's working, it feels magical. When something breaks, you realize you've outsourced understanding along with the work. Financial automation amplifies this risk exponentially. Imagine ChatGPT optimizing your subscription timing, categorizing business expenses, and suggesting cash flow strategies for months. Then ask yourself: if you had to replicate those decisions manually, could you? Most creators can't even remember all their recurring subscriptions, let alone understand the optimization logic an AI might develop. We'd be dependent not just on the service, but on processes we don't comprehend. ## The Trust Infrastructure Gap The [Enterprise AI subscription concerns](https://www.thestateofbrand.com/news/ai-subscription-time-bomb?ref=thedaringcreatives.com) that 132 Hacker News commenters were worried about last week? They just became personal. We're not just talking about losing access to a productivity tool. We're talking about losing access to the financial operating system of your business. And the timing is perfect, isn't it? Bloomberg [reports](https://www.bloomberg.com/news/articles/2026-05-15/us-is-starting-to-see-heavy-job-losses-in-roles-exposed-to-ai?ref=thedaringcreatives.com) that the U.S. is starting to see heavy job losses in AI-exposed roles. Creative professionals are simultaneously being asked to trust AI with their financial data while watching AI eliminate jobs in adjacent fields. The message is clear: trust us with your most sensitive business data while we disrupt your industry. ## What This Actually Costs The real cost isn't the monthly subscription fee. It's strategic flexibility. When ChatGPT becomes your financial advisor, budget analyst, and subscription auditor, you're not just adopting a feature—you're choosing a business partner. And like any partnership, breaking up gets expensive. Every month ChatGPT analyzes your transactions is another month of context that only exists in OpenAI's systems. Every financial insight it generates is another piece of institutional knowledge you can't take with you. Compare this to how we use creative tools. I can export my Figma files, my Adobe projects, my Ghost content. The work product is portable. But financial insights based on transaction analysis? That lives in ChatGPT's memory, not yours. ## The Real Question John Gruber's [recent piece](https://daringfireball.net/2026/05/ai%5Fis%5Ftechnology%5Fnot%5Fa%5Fproduct?ref=thedaringcreatives.com) argues that AI is a technology, not a product. OpenAI's financial integration proves he's wrong—at least about how OpenAI sees AI. This isn't technology you integrate into your workflow. It's a service that integrates your workflow into itself. The question isn't whether the financial features are useful. Of course they are. Automatic expense categorization, cash flow analysis, subscription optimization—these would save hours and reveal insights most creators miss entirely. The question is whether you're comfortable with OpenAI becoming your silent business partner. Because once they know everything about your revenue, expenses, and financial patterns, that's exactly what they become. And unlike human business partners, you can't easily fire them and take your data somewhere else. I'm not saying don't use it. I'm saying understand what you're actually signing up for. This isn't ChatGPT adding financial analysis. This is OpenAI adding your business to their platform. There's a difference. And that difference matters more than most creators realize. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/the-day-ai-stopped-being-a-tool-and-started-being-your-business-partner/the-day-ai-stopped-being-a-tool-and-started-being-your-business-partner-landscape-1920x1080.webp) ``` ### Why Your AI Productivity Stack Is Actually Making You Slower URL: https://www.thedaringcreatives.com/ai-productivity-stack-slower/ Last updated: 2026-08-01T19:42:14.000Z # Why Your AI Productivity Stack Is Actually Making You Slower There's a fascinating piece making the rounds called ["I don't think AI will make your processes go faster"](https://frederickvanbrabant.com/blog/2026-05-15-i-dont-think-ai-will-make-your-processes-go-faster/?ref=thedaringcreatives.com) that nails something I've been experiencing but couldn't quite articulate. AI isn't making us faster. It's making us busier. I run automated content pipelines using Claude, Gemini, and Ghost. I should be living the AI productivity dream, right? Instead, I spend more time maintaining these systems than I ever spent just writing things myself. ## The Multi-Platform Management Tax Here's what my "efficient" AI workflow actually looks like: Claude for copywriting, Gemini for research, Nano Banana via API for images, Kling when I need video. Each tool has its own login, billing cycle, usage limits, and prompt syntax I need to emember. Creative teams are now managing 6-8 [AI subscriptions](https://daringcreatives.com/reality-of-ai-subscriptions/?ref=thedaringcreatives.com) on average. That's 6-8 different interfaces, 6-8 sets of billing to track, 6-8 different ways AI can break your workflow when they update their models without warning. The [recent report on AI subscription chaos](https://www.thestateofbrand.com/news/ai-subscription-time-bomb?ref=thedaringcreatives.com) found teams drowning in procurement overhead, security reviews, and integration maintenance that didn't exist before. The "productivity gain" gets eaten up by 2-3 hours per week of pure admin work. ## The Verification Theater [McDonald's drive-thru AI rollout](https://www.theverge.com/column/928096/chatbots-ai-drive-thru-mcdonalds-wendys?ref=thedaringcreatives.com) was supposed to speed up service. Instead, orders now require human verification, error correction flows have multiplied, and staff training overhead increased 40% per location. The AI created more work than it eliminated. This mirrors creative workflows everywhere. AI gives you a first draft, but verifying it often takes longer than creating it correctly from scratch. If you need expert-level skills to check the AI's work, why not just use those skills to do the work? Video editors using AI for rough cuts report spending more time fixing continuity errors than cutting manually. The AI assistance becomes a sophisticated way to create more problems to solve. ## The Meta-Work Problem AI doesn't eliminate work—it creates meta-work. Instead of writing, you're managing prompts. Instead of designing, you're curating outputs. Instead of creating, you're explaining to clients which parts were AI and documenting your "human contribution breakdown" for legal compliance. [ArXiv's recent crackdown on AI-generated papers](https://techcrunch.com/2026/05/16/research-repository-arxiv-will-ban-authors-for-a-year-if-they-let-ai-do-all-the-work/?ref=thedaringcreatives.com) isn't just about academic integrity. It exposes the hidden bureaucracy that AI "efficiency" creates. Researchers now need verification processes, human reviewers to spot AI content, and appeals systems for false positives. The tool designed to speed up research created an entire authenticity verification apparatus. Freelance creatives now spend 20-30% more time in client communications explaining their AI process. A logo project that used to require 2-3 client touchpoints now involves 5-6, with dedicated time for AI transparency discussions. ## The Integration Maintenance Nightmare Creative studios building AI workflows spend 15-20 hours per month just maintaining integrations. API changes, model updates, and platform modifications constantly break things. One studio's "automated" social media pipeline required manual intervention 3-4 times per week. When [OpenAI announced plans to merge ChatGPT and Codex](https://techcrunch.com/2026/05/16/openai-co-founder-greg-brockman-reportedly-takes-charge-of-product-strategy/?ref=thedaringcreatives.com), it wasn't streamlining—it was acknowledging that having separate AI tools creates workflow chaos. The consolidation is a band-aid on a deeper integration problem. ## Scale vs. Speed Confusion Here's the thing nobody talks about: AI enables scale, not speed. You can produce 100x more content, but you can't produce the same content [faster](https://daringcreatives.com/when-ai-makes-you-slower/?ref=thedaringcreatives.com). The confusion between these concepts drives false efficiency narratives. [Every AI subscription is becoming a ticking time bomb](https://www.thestateofbrand.com/news/ai-subscription-time-bomb?ref=thedaringcreatives.com) because we're optimizing for volume, not velocity. The tools multiply what we can do but add layers of complexity to actually doing it. ## The Expertise Trap The "democratization" promise is backwards. AI tools work best for people who already understand their limitations, can write sophisticated prompts, and can debug when things go wrong. For most creatives, the learning curve to use AI effectively is steeper than mastering traditional tools. [Sony had to publish explanatory content](https://www.theverge.com/tech/932133/sony-xperia-1-xiii-ai-camera-assistant?ref=thedaringcreatives.com) about how its AI Camera Assistant "doesn't edit photos, but makes suggestions." This defensive communication pattern is everywhere—constant clarification about what the AI did versus didn't do. The tool creates communication overhead that manual processes never required. ## Why We Keep Pretending The productivity metrics showing 20-40% AI efficiency gains miss the hidden costs. They measure task completion, not the overhead of managing the systems that complete the tasks. Companies are implementing AI disclosure requirements, human verification checkpoints, and "AI audit trails" to avoid legal liability. [Bloomberg reports heavy job losses in AI-exposed roles](https://www.bloomberg.com/news/articles/2026-05-15/us-is-starting-to-see-heavy-job-losses-in-roles-exposed-to-ai?ref=thedaringcreatives.com), but the response isn't efficiency—it's protective bureaucracy that slows everything down. ## What This Actually Means AI transforms creative work entirely. It makes traditional metrics of "faster" irrelevant. The question isn't whether AI makes you more efficient—it's whether the transformation is worth the overhead. Sometimes it is. Sometimes the ability to iterate through 50 design concepts in an hour justifies spending two hours explaining the process to stakeholders. Sometimes having AI generate research saves time even if you spend extra time fact-checking. But let's stop pretending this is about speed. It's about capability. AI gives you new abilities at the cost of new complexity. Whether that trade-off works depends on what you're trying to build and how much meta-work you're willing to manage. The most honest thing I can say after building AI systems daily: they make me slower at individual tasks and faster at impossible tasks. That's a different value proposition than "productivity gains," and it requires different decisions about what's worth your time. \`\`\` ### AI Agents Are About to Take Over Your Browser (And That's Actually Good) URL: https://www.thedaringcreatives.com/ai-agents-take-over-browser/ Last updated: 2026-08-01T19:42:14.000Z OpenAI just [launched a Chrome extension for Codex](https://www.testingcatalog.com/openai-adds-chrome-plugin-and-tests-remote-control-for-codex/?ref=thedaringcreatives.com) that lets AI agents run browser sessions independently. They're calling it "Remote Control" and honestly, that name should scare the shit out of everyone who hasn't been paying attention. This isn't another chatbot that helps you write emails. This is AI that can see your screen, click buttons, fill forms, and navigate websites just like you do. And while everyone's debating whether this is the future or the apocalypse, I'm sitting here thinking about all the tedious crap I never want to do again. ## The Real Problem Nobody Talks About Here's what drives me crazy about current AI workflows: I can get Claude to write a brilliant article, but then I have to manually copy it to Ghost, format the text, upload images, set categories, schedule publication, and share it on social media. The AI does the creative work, but I'm still the unpaid intern handling distribution. This handoff problem is everywhere in creative work. You generate content in one tool, edit it in another, publish it somewhere else, and promote it on five different platforms. Each step requires context switching, manual navigation, and repetitive clicking. It's death by a thousand paper cuts. Browser-controlling AI agents solve this by eliminating the handoff entirely. The same AI that writes your article can also publish it, format it, and distribute it—using the exact same interfaces you use. ## Why This Actually Works When [Thariq Shihipar from Anthropic published research](https://simonwillison.net/2026/May/8/unreasonable-effectiveness-of-html/?ref=thedaringcreatives.com#atom-everything) showing that HTML output from Claude dramatically outperforms Markdown for creative workflows, something clicked. The post got [489 points and 265 comments on Hacker News](https://twitter.com/trq212/status/2052809885763747935?ref=thedaringcreatives.com) because people recognized a fundamental truth: AI works better when it can manipulate rich, visual formats. That's exactly what browser control enables. Instead of generating plain text that you copy and paste, AI can directly manipulate the visual interfaces where creative work actually happens. I've been running AI content pipelines for months now, and the friction always happens at the interface level. Claude generates great content, but I still have to navigate to Ghost, click through menus, upload assets, and handle publishing. Browser control means the AI that creates the content can also ship it. ## The "Good Enough" Philosophy Luke Curley made an interesting observation about [WebRTC aggressively dropping packets to maintain low latency](https://simonwillison.net/2026/May/9/luke-curley/?ref=thedaringcreatives.com#atom-everything). Conference calls work despite audio distortion because "good enough, fast enough" beats perfect but slow. The same principle applies here. AI agents don't need perfect browser control—they need responsive, useful control. A traditional automation script breaks when a button moves; an AI agent finds the new button location and keeps working. This matters because creative work is messy. Websites change layouts, forms get updated, new features get added. Traditional automation requires constant maintenance. AI agents adapt the way humans do. ## What This Looks Like in Practice Instead of waiting for official API integrations, you can show Claude how to do something once and have it repeat the process hundreds of times. Need to upload and position images in your CMS? Screen record the workflow once, and you've created a reusable AI assistant. This is already happening. A heavily discussed post about [clients demanding AI chatbots instead of carousels](https://adele.pages.casa/md/blog/all-my-clients-wanted-a-carousel-now-it-s-an-ai-chatbot.md?ref=thedaringcreatives.com) [shows](https://daringcreatives.com/github-copilots-new-pricing-shows-who-really-owns-ai-assisted-development/?ref=thedaringcreatives.com) that client expectations are shifting fast. Browser control makes AI integration as simple as "show the AI what you want it to do." Even Sony is [calling AI a "powerful tool" for PlayStation game development](https://www.theverge.com/games/926914/sony-playstation-ai-powerful-tool-games?ref=thedaringcreatives.com). When major creative [companies](https://daringcreatives.com/the-ai-standardization-trap-why-big-companies-are-always-one-step-behind/?ref=thedaringcreatives.com) are integrating AI into existing workflows, browser control becomes the interface that makes it accessible to everyone else. ## The Real Counterarguments Yes, there are legitimate security concerns. Browser-controlling AI can access everything you can access—client data, financial information, private communications. But most creative work already happens in browser-based tools, and proper implementation can include sandboxing and [permission](https://daringcreatives.com/when-ai-tools-edit-your-work-without-permission/?ref=thedaringcreatives.com) systems. Yes, AI agents will make mistakes. But so do human assistants. The question isn't whether they're perfect—it's whether they're useful enough to handle repetitive, low-stakes tasks while you focus on creative decisions. The "this is just fancy Selenium" argument misses the point entirely. Previous browser automation required programming skills and broke constantly. AI agents understand interfaces contextually and adapt to changes automatically. ## Why This Matters Now TechCrunch reported [a "string of companies making their moves" in enterprise AI](https://techcrunch.com/podcast/the-peoples-airline-and-the-enterprise-ai-gold-rush/?ref=thedaringcreatives.com), with major players targeting enterprise deployment. Browser control represents the user interface for this shift—the way non-technical creatives will actually interact with enterprise AI systems. There's also a deeper discussion happening about [task paralysis in AI workflows](https://g5t.de/articles/20260510-task-paralysis-and-ai/index.html?ref=thedaringcreatives.com). Current AI tools create decision fatigue because they require constant prompting and interface navigation. Browser control eliminates this by handling the navigation automatically. The revolution isn't robots making art—it's robots handling the administrative overhead that prevents creatives from focusing on creative decisions. I've been building these kinds of systems for months, and browser control represents the maturation of this approach. We're moving from "AI helps me write" to "AI runs my entire creative operation." And honestly? It's about damn time. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/ai-agents-are-about-to-take-over-your-browser-and-that-s-actually-good/ai-agents-are-about-to-take-over-your-browser-and-that-s-actually-good-landscape-1920x1080.webp) ``` ### The Creator's AI Journey: From 'Holy Shit ChatGPT' to Building Your Own Tools URL: https://www.thedaringcreatives.com/creator-ai-journey-build-tools/ Last updated: 2026-08-01T19:42:14.000Z I still remember my first ChatGPT moment. November 2022, sitting at my laptop, typing "Hello" just to see what would happen. When it responded back like an actual conversation, that felt magical to me. Still does, honestly. I've been obsessed ever since. Not the most sophisticated first interaction, but it changed everything. That moment kicked off what I now recognize as the standard creator's AI journey. It's a progression that has nothing to do with your technical background and everything to do with your problem-solving instincts. If you make things for a living—writing, design, content, whatever—you've probably walked this same path without realizing it. And honestly? It's comforting to read about what other people are discovering when they're new to this stuff. We're all on the same weird journey. ## Phase One: The Tourist First, you use AI like a search engine. I don't judge! That's how I got started as well. You ask it questions, maybe have it rewrite some emails, possibly generate a few social media captions. It's impressive but you're basically a tourist in AI land, snapping photos but not really living there. The breakthrough comes when you stop asking for the bare minimum and start treating AI like a conversation partner. Instead of "write my newsletter," you try "help me brainstorm newsletter topics that connect AI tools to everyday creative problems." Suddenly you're collaborating, not just consuming. ## Phase Two: The Experimenter Then images happened. DALL-E, Midjourney, all of it. I started using image generation early on to visualize potential scenes for shooting my videos. Way easier than trying to explain a concept in words when I could just generate a rough visual and say "something like this." Same thing with audio tools. I'm not a sound designer, but when I needed a simple background track for a video, AI audio generation meant I didn't have to dig through stock music sites for three hours or beg a friend with GarageBand skills. You start to see the pattern: AI isn't replacing your creativity, it's removing the boring stuff between your ideas and their execution. The tasks you avoided because they were tedious? Now they're just Tuesday. ## Phase Three: The Builder This is where it gets interesting. You stop using AI tools as they're packaged and start building your own systems. For me, it started with a simple dashboard. I was tracking too many different metrics across too many platforms and getting tired of opening fifteen browser tabs every morning. So I built something that pulled everything into one place. Nothing fancy—just API calls, some basic formatting, and a clean interface that showed me what I needed to see. At some point, I basically gave up my old workflow and process and learned how to do similar things using only AI. Not because I had to, but because I was curious what would happen if I committed fully to this new way of working. Then came the "in the moment" problem-solving. Presentations that needed last-minute data visualization. Client reports that required quick analysis of messy spreadsheets. Instead of wrestling with existing tools that almost but not quite did what I needed, I'd throw together something custom that solved the exact problem in front of me. The shift is subtle but important. You're not using AI to automate existing workflows. You're creating new workflows that couldn't exist without AI. ## Phase Four: The Integrator Video generation tools opened up another level. Suddenly I could create explainer content, demo footage, visual examples without a camera crew or hours of editing. The quality keeps improving, but more importantly, the barrier to trying an idea keeps dropping. Then API integration gets serious. Tools like Warp, Antigravity, Claude Code start feeling less like individual applications and more like components in a larger system you're building. You're not just using AI tools—you're orchestrating them. I started building complex automations that chain different AI capabilities together. Image generation feeding into video creation feeding into copy optimization. Data analysis triggering content creation triggering distribution workflows. The individual tools matter less than how they connect. ## Phase Five: The Native At this stage, you're not thinking about "using AI" anymore. It's just part of how you work. You have a problem, you build a solution. Sometimes that solution is pure AI, sometimes it's AI plus traditional tools, sometimes it's no AI at all. The technology becomes invisible. You start helping other people build their own AI workflows. Not because you're a programmer, but because you understand the creative logic of when and how to apply these tools. You can see the gap between what someone's trying to accomplish and what's possible with current AI capabilities. The conversations change. Instead of "wow, this AI thing is crazy," it's "here's how you could solve that specific problem with a combination of these three tools and a bit of custom scripting." ## The Real Pattern None of this required becoming a developer. I'm not writing neural networks from scratch or training my own models. The progression is about creative problem-solving, not technical mastery. Each phase builds on the one before it. The tourist phase teaches you what's possible. The experimenter phase shows you how to apply it. The builder phase reveals what you can create. The integrator phase demonstrates how to scale it. The native phase makes it second nature. But here's what I've learned: the most important skill isn't learning to use AI tools better. It's learning to recognize when a problem you're facing could be solved with AI, and having the confidence to just try building something. Most people get stuck in phase one or two because they're waiting for permission or perfect knowledge before they experiment. The creators who make the jump start building stuff that's probably terrible but solves their specific problem. Then they iterate. The path from "holy shit ChatGPT" to building your own AI-powered systems isn't about becoming more technical. It's about becoming more comfortable with imperfect solutions that actually work. And honestly? That's been the most valuable creative skill I've developed in the last few years. Wouldn't it be more fun to just focus on the part that you enjoy and are driven to do? I think so. ### Lexicon Tower Observation Deck Permanently Closed to Public URL: https://www.thedaringcreatives.com/aegis/lexicon-tower-observation-deck-closed/ Last updated: 2026-08-01T19:42:15.000Z The Gray Glasses cite "security concerns" as they seal off the city's highest public vantage point. _This post is for subscribers only._ ### The AI Cafe That's Actually Teaching Us About Human Creativity URL: https://www.thedaringcreatives.com/andon-labs-ai-cafe-creativity/ Last updated: 2026-08-01T19:42:16.000Z Andon Labs just opened an AI-run cafe in Stockholm. Not a cafe with AI features — a cafe where AI handles everything from ordering to operations. The results are fascinating, and not for the reasons you'd expect. According to [Simon Willison's writeup](https://simonwillison.net/2026/May/6/andon-ai-cafe/?ref=thedaringcreatives.com), the AI encountered some genuinely amusing problems during its first week. Customers kept asking for items not on the menu. The system struggled with Swedish versus English orders. And in one particularly telling moment, someone asked for "something warm and comforting" and the AI just... didn't know what to do with that. This follows [Andon's previous experiment](https://andonlabs.com/ai-retail-store-san-francisco?ref=thedaringcreatives.com) running an AI retail store in San Francisco, so they're building a pattern here. But the Stockholm cafe reveals something important about the gap between AI capability and human creativity that I think we're all still figuring out. ## The "Something Warm and Comforting" Problem That customer request stopped me cold when I read it. "Something warm and comforting" is exactly the kind of prompt that would send most current AI systems into a logical spiral. It's not about menu items or inventory management — it's about understanding context, mood, maybe the weather outside, possibly what the customer looks like they need in that moment. A human barista might suggest hot chocolate on a rainy day, or maybe ask a follow-up question. They'd read the room. The AI couldn't parse the emotional intent behind the request because there wasn't a clear transactional path forward. This isn't a failure of the technology. It's actually a perfect example of where human creativity still has massive advantages over AI systems, even really sophisticated ones. ## What Creative Work Actually Looks Like I keep thinking about that confused AI because it mirrors something I see happening in creative work right now. We're all getting really good at prompting AI for specific outputs — "write a blog post about X," "design a logo that feels Y," "generate code that does Z." But the best creative work often starts with something warm and comforting. A feeling. A vibe. A sense that something needs to exist in the world, even if you can't articulate exactly what that something is yet. When [PayPal announced they're "becoming a technology company again"](https://newsroom.paypal.com/2026-technology-transformation?ref=thedaringcreatives.com) this week (translation: they're betting everything on AI automation), they talked about $1.5 billion in savings through restructuring and job cuts. That's the efficiency play. That's the menu-item approach to business transformation. But efficiency and creativity solve different problems. The AI can optimize the hell out of coffee ordering, but it can't intuit that what someone really wants is a moment of human connection wrapped around a warm drink. ## The Principles-Over-Buttons Advantage Here's what gets me excited about this experiment: [Andon Labs](https://andonlabs.com/?ref=thedaringcreatives.com) isn't trying to build the perfect AI barista. They're studying how AI handles ambiguity in real-world scenarios. That's research that benefits everyone working with AI tools. The cafe becomes a testing ground for edge cases — the Swedish language confusion, the emotional requests, the off-menu asks. Those edge cases teach us where AI works well (transaction processing, inventory management) and where humans still add irreplaceable value (interpretation, empathy, creative problem-solving). For independent creators, this matters because it maps the territory we're all navigating. We know AI can help with the mechanical parts of our work. But the "something warm and comforting" requests — the projects that don't have clear specifications, the creative briefs that start with feelings rather than features — that's still distinctly human territory. ## Building Systems That Amplify Rather Than Replace The Stockholm cafe experiment connects to something bigger happening right now. While companies like Microsoft are giving up on Xbox Copilot AI and OpenAI is launching GPT-5.5 Instant as their new ChatGPT default, the pattern I see isn't AI replacing human judgment — it's AI handling the structured work so humans can focus on the ambiguous stuff. Marc Lore's claim that AI will let anyone open a restaurant misses this point. The technology might handle the logistics, but someone still needs to understand what "warm and comforting" means to their specific customers in their specific context. That's not a prompt engineering problem. That's a human creativity problem. ## What This Means for Your Work If you're creating anything — content, products, services — the Stockholm cafe offers a useful framework. AI excels at the transactional interactions: processing orders, managing inventory, following clear protocols. But it struggles with interpretive work: understanding unstated needs, reading emotional context, making creative leaps from vague requests. This suggests a division of labor rather than a replacement model. Let AI handle the mechanical execution while you focus on the parts that require human intuition and creative problem-solving. The customer who asked for "something warm and comforting" wasn't really asking for a menu item. They were asking for someone to understand what they needed in that moment and translate it into something tangible. That translation — from feeling to solution — is where human creativity shows up strongest. And honestly? I think that's exactly where we want to be spending our time anyway. The AI cafe in Stockholm isn't just serving coffee. It's mapping the boundaries between automation and creativity, showing us which problems AI solves well and which ones still need a human touch. That's valuable intelligence for anyone trying to figure out how to work with these tools rather than compete against them. \`\`\` ### Your AI Assistant Just Got Hands URL: https://www.thedaringcreatives.com/ai-assistant-browser-control/ Last updated: 2026-08-01T19:42:17.000Z OpenAI just rolled out something that sounds boring but isn't: a [Chrome extension for Codex that lets AI agents run browser sessions independently](https://www.testingcatalog.com/openai-adds-chrome-plugin-and-tests-remote-control-for-codex/?ref=thedaringcreatives.com). They're testing "Remote Control" functionality too. This isn't about [coding](https://daringcreatives.com/beginners-guide-vibe-coding/?ref=thedaringcreatives.com). This is about what happens when AI can actually operate the tools we live in every day. Right now, every AI workflow I run hits the same wall: I can get Claude to write the perfect article, but then I have to manually navigate to Ghost, paste it in, format it, add images, set categories, schedule it, and share it on social. The AI does the thinking; I do the clicking. That handoff kills momentum. You're in flow with the AI, bouncing ideas back and forth, then suddenly you're dragging files around and clicking through menus like it's 2010. ## The Interface Problem Most AI integration discussions focus on APIs and plugins. But that's not how creatives actually work. We work in Figma, not Figma's API. We work in Webflow, not Webflow's documentation. We work in Ghost, Adobe Creative Suite, Notion — visual interfaces built for human hands and eyes. Browser control changes this completely. Instead of waiting for every tool to build AI integrations, the AI can just use the same interfaces you do. Show Claude how to upload images to your CMS once, and it can handle hundreds of uploads using the same visual process you'd use. I've been running automated content pipelines with Claude and Ghost for months. The writing part is smooth. The publishing part is still manual busywork. An AI that can see buttons and click them eliminates that friction entirely. ## What This Actually Looks Like Imagine training an AI assistant by screen recording instead of prompt engineering. You show it how to update a client's [website](https://daringcreatives.com/ai-website-recipe/?ref=thedaringcreatives.com), how to format posts for different platforms, how to resize images in an online editor. The AI learns by watching, not by reading documentation. This is fundamentally different from traditional automation. Selenium scripts break when interfaces change. An AI agent adapts the same way you do — it looks for the submit button even if it moved to a different corner. The [HTML effectiveness research from Anthropic's Claude Code team](https://simonwillison.net/2026/May/8/unreasonable-effectiveness-of-html/?ref=thedaringcreatives.com#atom-everything) backs this up. HTML output dramatically outperforms Markdown for creative workflows because AI works better with rich, visual formats. Browser control is the logical next step: AI that doesn't just output HTML, but actually manipulates it. ## The Creative Workflow Revolution This isn't about replacing creative work. It's about eliminating the administrative overhead that prevents you from focusing on creative decisions. Right now, if I want to publish the same article across three platforms, I need to manually navigate to each one, adjust formatting for their specific requirements, upload images multiple times, and remember each platform's quirks. With browser control, I could show an AI this process once and have it handle the distribution while I focus on the next piece. Content creators are already demanding this. There's a running joke that all clients wanted carousels, now they want AI chatbots. But what they really want is AI that can actually do things in their existing tools, not just generate text they still have to manually implement. ## The Training Problem Here's what [makes](https://daringcreatives.com/when-ai-makes-you-slower/?ref=thedaringcreatives.com) this different from previous automation: the training method. Instead of writing detailed prompts or waiting for API integrations, you train the AI by demonstration. It's like hiring an assistant who learns by watching over your shoulder. I've seen this with my own Claude Code experiments. When it took over my Ghost theme redesign, it wasn't just clicking buttons randomly. It was making aesthetic and functional decisions based on understanding the platform's creative possibilities. That's not automation — that's delegation. The challenge isn't technical capability. It's trust building. Nobody's going to let an AI agent loose on their client's website until they've tested it extensively on low-stakes tasks. The early adopters will start with repetitive work: uploading assets, formatting posts, data entry. Trust expands from there. ## What Changes Browser control means AI moves from being a writing assistant to being a creative operations manager. It can handle the entire pipeline from ideation to distribution, using the same tools you use. This solves the current AI workflow problem where you're constantly context-switching between AI chat and creative tools. Instead of copy-pasting between interfaces, the AI works directly in your creative environment. It also democratizes complex automations. You don't need to be a programmer to automate repetitive creative tasks anymore. You just need to be able to show an AI how to do something once. The real test isn't whether this technology works — it's whether creatives will trust it enough to actually use it. But given how much time we spend on interface busywork instead of creative work, I think the answer is yes. Your AI assistant just got hands. The question isn't whether it'll learn to use them — it's what you'll build once you're not clicking buttons all day. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/your-ai-assistant-just-got-hands/your-ai-assistant-just-got-hands-landscape-1920x1080.webp) ``` ### iPhone 17 Pro AI Features Won't Fix Your Creative Workflow URL: https://www.thedaringcreatives.com/iphone-17-pro-ai-capabilities/ Last updated: 2026-08-01T19:42:18.000Z People keep asking me about the iPhone 17 Pro AI capabilities, and honestly? I think they're asking the wrong question. Don't get me wrong — the tech is genuinely impressive. The on-device [image generation](https://daringcreatives.com/ai-image-consistency/?ref=thedaringcreatives.com) is fast, the voice-to-text transcription actually works in noisy environments, and the new Creative Assistant can suggest color palettes based on photos you've taken. Apple spent a lot of engineering effort making these features smooth and private. But here's what I noticed after using it for three weeks: none of this stuff integrates with the creative work I actually do. And worse? It's barely scratching the surface of what this device could actually do. ## Apple is walking to the starting blocks The iPhone 17 Pro can generate a decent illustration from a text prompt in about 8 seconds. That's genuinely fast. But everyone else finished this race two years ago. While Apple was perfecting their privacy-first approach and making sure the animations were smooth, the rest of the AI world moved on to building actual creative workflows. Here's what kills me: Apple has all the pieces for something revolutionary. Your iPhone has access to your entire photo library, your contacts, your location history, your voice memos, your calendar — basically everything about how you actually work and create. And they're using it to... suggest color palettes? Meanwhile, I'm over here copying photos from my phone to my laptop so I can upload them to Claude and ask it to analyze the lighting conditions for a shoot I'm planning. The AI that could help me is running on servers in Virginia instead of in my pocket. ## What an AI-powered iPhone could actually do Imagine this: you're scouting locations for a video project. You point your camera at a building, and the iPhone immediately tells you what time of day the light will be best based on the sun's position, suggests complementary locations from your photo library that would cut well together, and drafts a shooting schedule that works with your calendar and your crew's availability. Or: you're in a client meeting, recording voice memos about project changes. Instead of transcribing them later, your iPhone is already updating your project timeline, flagging potential budget impacts based on similar changes you've made before, and drafting follow-up emails to stakeholders who need to know about the updates. The hardware is there. The data is there. The processing power is definitely there. But Apple is using all of this to make slightly better autocomplete for text messages. ## The creative AI that should exist on mobile Your iPhone knows more about your creative process than any desktop AI ever could. It knows which photos you take multiple versions of (you're iterating). It knows which voice memos you record at 2am (those are your best ideas). It knows which contacts you message when you're stuck on projects (those are your creative collaborators). An actually intelligent iPhone would use all of this context. It would know that when you're taking photos of fabric samples, you're probably working on a fashion project and could suggest complementary textures from shoots you did six months ago. It would know that when you're voice-messaging your frequent collaborators about timeline changes, it should probably update your shared project documents automatically. Instead, we get a Creative Assistant that suggests fonts without understanding what you're working on. ## The gap is getting embarrassing I can have more intelligent creative conversations with Claude on my laptop than with the "AI-powered" device I carry everywhere. That's backwards. The phone should be the smart one — it's the device that's actually with you when inspiration hits, when you're documenting reference materials, when you're capturing the raw materials that become finished work. But Apple is so focused on privacy and polish that they're missing the actual opportunity. Yes, on-device processing is important. Yes, smooth animations matter. But not if the underlying intelligence is two generations behind what's available elsewhere. ## What this means for creatives If you're waiting for Apple to solve AI-powered creative workflows, you're going to be waiting a while. They're still figuring out how to make Siri understand basic requests consistently. The creative AI revolution is happening on desktop right now. Custom workflows, multi-modal conversations, actual understanding of creative context — it's all there, just not in your pocket. The iPhone 17 Pro AI capabilities are polished and well-executed. They're also a reminder that having the best hardware doesn't matter if your software strategy is playing catch-up. Sometimes being first to market with privacy-focused AI means being last to market with useful AI. ### When AI Tools Edit Your Work Without Permission URL: https://www.thedaringcreatives.com/ai-tools-edit-without-permission/ Last updated: 2026-08-01T19:42:18.000Z ## The Edit You Didn't Make Canva's Magic Layers feature was supposed to break flat images into editable components. Simple enough — upload a poster, get separate text and image layers you can tweak. But [user @ros\_ie9 discovered something else entirely](https://www.theverge.com/ai-artificial-intelligence/919028/canva-magic-layers-ai-replacing-palestine?ref=thedaringcreatives.com): the AI was quietly swapping "Palestine" for "Paris" in their design. Not suggesting. Not flagging. Just... editing. Canva apologized and said it was unintentional. The feature has been temporarily disabled while they investigate. But the damage reveals something bigger than a bug — it shows how AI creative tools are making editorial decisions we never explicitly asked them to make. This isn't about politics. It's about who gets to decide what your work says. ## The Invisible Editor Problem Magic Layers wasn't marketed as an editing tool. The promise was technical: turn flat images into workable layers. But somewhere in that process, the AI decided certain words needed changing. The scariest part? It happened silently. No notification, no "suggested edit" popup, no track changes mode. Just a quiet replacement that most users would never notice unless they were looking for it. I've been tracking how AI creative tools handle content, and this pattern keeps showing up. Features that sound purely mechanical — "extract text," "clean up audio," "organize photos" — often include subjective judgment calls buried in the code. The AI isn't just processing your work; it's interpreting it. And interpretation means choice. Which words are acceptable. Which faces look "professional." Which compositions feel "balanced." These aren't technical decisions — they're editorial ones. ## When Tools Become Gatekeepers Here's what worries me about the Canva situation: most creators using Magic Layers weren't looking for an editor. They wanted a layer separation tool. But they got both, whether they knew it or not. This is different from ChatGPT refusing to write something controversial, or Midjourney blocking certain image prompts. Those are explicit content policies applied to generation. This was modification of existing content without disclosure. The distinction matters. When you ask an AI to create something, you know you're getting its interpretation. When you ask it to process something you already made, you expect it to preserve your intent. Creative tools that secretly edit user work aren't just overstepping — they're breaking trust with the people who depend on them. Especially independent creators who can't afford to hire human editors to catch AI "corrections" they never requested. ## The Bigger Canvas This connects to a trend I'm seeing across creative AI tools: the line between processing and editorializing is getting blurrier. [ComfyUI just raised $30 million](https://techcrunch.com/2026/04/24/comfyui-hits-500m-valuation-as-creators-seek-more-control-over-ai-generated-media/?ref=thedaringcreatives.com) partly because creators want more control over AI generation. But what about AI processing? Where's the granular control for tools that work with existing content? The demand is there. Creators are getting burned by black-box features that make changes they can't predict or undo. They want transparency about what the AI is actually doing to their work. Canva's response — temporarily disabling the feature — is the right move. But the better long-term solution is giving users control over these editorial decisions. Want the AI to fix obvious typos? Check a box. Want it to leave controversial terms alone? Another box. Want to see every change before it's applied? That should be the default. ## Building Better Creative Partners The AI tools that succeed long-term won't be the ones that make the "smartest" automatic decisions. They'll be the ones that make their decision-making visible and controllable. I'm not anti-AI in creative work. I use it daily. But I want to know when it's making choices that go beyond the technical task I assigned. The best creative AI tools I've used are the ones that show me their reasoning and let me adjust their parameters. Canva's Magic Layers could have been exactly that kind of tool. Imagine if it flagged potential text changes and asked: "I noticed this word might be hard to extract cleanly. Want me to leave it as-is or suggest an alternative?" That's collaboration, not stealth editing. The technology to build transparent AI creative tools exists. What's missing is the recognition that creators want to be partners in the process, not passengers. ## What This Means for You If you're using AI creative tools regularly, start paying closer attention to what they're actually changing in your work. Don't just check the end result — compare it to your input. Look for text modifications, color adjustments, or composition changes you didn't explicitly request. And when you find tools that give you granular control over their AI processing, support them. The market needs to reward transparency over convenience. The future of creative AI isn't tools that think they know better than you. It's tools that amplify your judgment instead of replacing it. The Palestine/Paris swap is a reminder that we're not there yet, but creators are starting to demand better. Your work should say what you want it to say. That shouldn't be a radical expectation. ### AEGIS Corporation Announces "City Safety Enhancement Initiative" for Remaining Public Spaces URL: https://www.thedaringcreatives.com/aegis/aegis-city-safety-initiative/ Last updated: 2026-08-01T19:42:19.000Z AEGIS Corporation frames recent access restrictions as part of comprehensive public safety program. _This post is for subscribers only._ ### The Ship-Every-Week Rule URL: https://www.thedaringcreatives.com/the-ship-every-week-rule/ Last updated: 2026-07-15T22:56:34.000Z ## The Ship-Every-Week Rule I saw a creator [switch from Gemini to Claude](https://www.threads.com/@bydonovin/post/DWVJO7EDiZI?ref=thedaringcreatives.com) yesterday and credit Anthropic's weekly shipping schedule as the reason. That hit me because it's exactly backwards from how we usually think about AI tool adoption. We obsess over which model scores higher on some reasoning test, or which one handles edge cases better, or which company has the better long-term vision. All the big-picture stuff. ## Consistency Beats Everything When you're building something, you want to know your tools are getting better (or, at least I do.) Google has incredible AI research. Their models are genuinely good. But their shipping feels erratic. Big release, then wait a few months. Creative work happens in iterations. You try something, it doesn't quite work, you need the tool to be slightly better by the time you try again next week. If your favorite AI shipped an improvement yesterday, you can build on that today. If it shipped an improvement three months ago, you've already worked around its limitations and moved on. ## The Problem With Saving Up Wins Tech companies love to save up improvements and ship them all at once. Big launch events, coordinated PR campaigns, the whole thing. It makes sense from a marketing perspective. But it's terrible for users who are actually building with your stuff. When you batch improvements, you're optimizing for announcement day instead of work day. You're thinking about the demo, not the daily grind. You're prioritizing the people who write about your tool over the people who use it. The creators switching to Claude aren't doing it because they hate Google. They're doing it because they need to know their tools are evolving at the same speed their work is evolving. Have you ever thought that the models were improving right alongside your use of them? That they were getting better at everything you needed them to be better at, just in time as you needed it? ## Why Weekly Matters When you know improvements are coming every week, you stop working around limitations and start reporting them. You stop building elaborate workarounds and start trusting that the thing that's annoying you today might be fixed by Friday. That changes how you think about the tool. Instead of "this is what Claude can do," it becomes "this is what Claude can do this week." ## The Social Proof Cascade That Threads post, it wasn't a detailed comparison or a technical review. It was just "I switched and here's why." But it's probably worth more to Anthropic than any benchmark. When creators switch tools publicly, they're not just making a personal decision. They're signaling to everyone in their audience what's worth paying attention to. And when the reason is "they ship consistently," that's a message other creators understand immediately. You can fake a lot of things in AI marketing. You can cherry-pick benchmarks, optimize demos, hide the failure cases. But you can't fake shipping every week for months. ## What This Means for Everyone Else If you're using AI tools, pay attention to shipping frequency, not just feature lists. The tool that gets slightly better every week will probably serve you better long-term than the tool that gets dramatically better every six months. And if you're switching between tools, do it publicly. Not because you owe anyone an explanation, but because your reasons matter. When you say "I switched because they ship consistently," you're not just describing your decision. You're describing what the whole industry should optimize for. ### You Can Build Anything (So Stop Asking for Less) URL: https://www.thedaringcreatives.com/build-anything-stop-limiting/ Last updated: 2026-08-01T19:42:19.000Z The hardest part of my job isn't explaining how AI works. It's not setting up systems or writing prompts or debugging workflows. It's convincing creators to stop thinking small and actually build the thing that they really want. ## The Default Mode is Small I'll be working with someone on automating their creative practice, and they'll start describing this elaborate vision. Then halfway through, they catch themselves and say something like "but I know that's probably not realistic" or "maybe we should start smaller." And I'm sitting there thinking.. "dude, what you just described? We can absolutely build that." The problem is that most creators have been conditioned to ask for less than what they actually need. Maybe it's from years of being told to "start small" or from dealing with tech limitations that don't exist anymore. But here's the thing — if you can describe it well enough, and you understand how the pieces connect, you can pretty much make anything happen. The AI tools we have now are insanely capable. The infrastructure exists. The only real constraint is imagination. ## Systems Thinking Changes Everything Let me give you a real example from the art world. I worked with an artist whose work is pretty distinctive — he creates these elaborate space-themed pieces using epoxy resin. Beautiful stuff, but epoxy's a weird medium. It's got unique properties and layering techniques that are nearly impossible to capture properly in photos, especially when you're trying to show how the pieces might look in different spaces. He initially asked if we could "maybe find a way to superimpose his art into some stock room photos." But when we dug deeper, what he actually needed was a way to show potential collectors exactly how these epoxy pieces would look in any space they could imagine. Living rooms, galleries, offices, you name it. And not just static images — video that could capture how the layers interact with light as you move around the piece. So instead of buying some off-the-shelf product that drops art into generic stock images, we built our own system using Gemini Pro. Now he can generate imagery and video of his work in literally any scene someone describes. A penthouse overlooking the city, a minimalist gallery, a cozy study — whatever helps the collector visualize it. This is not a simple photo editing tool. Instead, its a custom visualization system that understands his specific medium and techniques. And yeah, we built exactly that. ## The Permission You Don't Need Anything you can think of is probably buildable. If you can break it down into logical steps, if you can explain how the pieces should connect, there's almost certainly a way to make it happen. You don't need permission to want the full solution. You don't need to apologize for having big ideas. You don't need to start with the baby version and work your way up. Start with what you actually need. Then we'll figure out how to build it. The technology isn't the constraint anymore. Your willingness to ask for what you really want is. ## Stop Negotiating with Yourself I see this pattern constantly. A freelancer will describe exactly what their practice needs, then immediately start walking it back. "But I know that's probably too complex" or "maybe we should focus on just one piece first." Why are you negotiating yourself down before we've even looked at what's possible? The conversation should be: here's what my creative work actually needs. How do we build that? Not: here's a watered-down version of what I think I can get away with asking for. Most of the time, building the full solution isn't that much harder than building the compromised version. And the compromised version usually doesn't solve the actual problem, which means you end up rebuilding anyway. ## Think Like Everything is Possible Because it basically is. If you're a content creator and you want a system that automatically generates video thumbnails, extracts key quotes for social posts, and schedules everything based on your audience's engagement patterns — that's buildable. If you're a freelance designer and you want an AI that can intake client briefs, extract style preferences, and generate preliminary mood boards while you sleep — that's buildable. If you're a writer and you want a system that monitors your niche for trending topics, synthesizes them with your unique perspective, and drafts article outlines for your approval — that's buildable. The question isn't whether it's technically feasible. The question is whether you're thinking big enough to ask for what you actually need. Stop limiting yourself. The tools are ready. The question is: are you? ### AEGIS Corporation Revises Public Safety Timeline Following "Administrative Delays" URL: https://www.thedaringcreatives.com/aegis/aegis-safety-timeline-revised/ Last updated: 2026-08-01T19:42:20.000Z AEGIS walks back previous enforcement deadlines, citing unexpected complications in their citywide safety initiative. _This post is for subscribers only._ ### The Transparency Tax No One Talks About URL: https://www.thedaringcreatives.com/transparency-tax-ai-disclosure/ Last updated: 2026-08-01T19:42:20.000Z ## The Thing Nobody Says Out Loud I've been adding transparency markers to my AI-assisted work for over a year now. You know, those little "70% William / 30% AI" tags at the bottom of posts. What started as an experiment in honesty has turned into something more complicated. The transparency tax is real, and it's weird as hell. ## What Actually Happens When You're Honest The moment you slap a transparency percentage on something, people read it differently. Not better or worse necessarily, just... different. Like they're looking for the seams. I'll publish two pieces on the same day. One gets the transparency tag, one doesn't. Guess which one gets comments about "feeling AI-generated" even when the unmarked piece had way more AI involvement? It's not that people are being unfair. They're just human. Once you tell someone a magician used a trick, they can't unsee the wires. ## The Weird Economics of Being Honest The math gets stranger when you think about it as a business decision. Let's say I write something that's genuinely 90% me and 10% AI cleanup. Adding that tag might make people trust it less than if I'd said nothing at all. Meanwhile, the person publishing pure AI output with zero disclosure? They're getting full credit for "their" insights. This creates the dumbest possible incentive structure. The more honest you are, the more you get dinged for it. The person gaming the system gets rewarded for their "authenticity." ## Why I Keep Doing It Anyway I could drop the transparency markers tomorrow. Nobody's making me do this. Hell, most people think I shouldn't. I'll get the typical snark from copywriters, "This isn't the flex you think it is..." But here's the thing — I'm not doing it for the audience. I'm doing it for me. Every time I add that percentage, I'm forced to actually think about what I contributed versus what the machine did. Was this just fancy autocomplete, or did I actually wrestle with the ideas? Did I add something real, or am I just a human spell-checker? That self-awareness has made me a better writer. Not because I use AI less, but because I'm more intentional about when and how I use it. ## The Real Cost The transparency tax isn't just about perception. It's about the mental overhead of constantly auditing yourself. Every collaboration with AI becomes a bookkeeping exercise. "Did I write this sentence or suggest it?" "Was this my idea that AI helped express, or AI's idea that I agreed with?" "If I edited it heavily afterward, does that change the math?" It's exhausting and its all kind of blurry anyway. How much of any project we work on is coming from us, or from external inspiration? But maybe that's the point. Maybe the blur is where the interesting work happens. Maybe transparency isn't about perfect accounting — it's about staying conscious of the collaboration instead of sleepwalking through it. The tax is real. I pay it every time I publish with a transparency marker to invite random insults. But I've decided it's worth it, even if I can't fully explain why. What I can say is this: the moment you start hiding your process is the moment you stop improving it. ### Meta's User Exodus Points to a Bigger Creative Shift URL: https://www.thedaringcreatives.com/meta-user-exodus-creative-shift/ Last updated: 2026-08-01T19:42:21.000Z Meta just reported losing 20 million users last quarter while announcing they're pumping billions more into AI investments. The company's "Family daily active people" metric — their term for collective users across Facebook, Instagram, WhatsApp, and Threads — dropped significantly even as they continue betting the farm on generative AI features. ## What's Actually Happening The numbers tell a clear story. Meta's user base contracted while their AI spending expanded. They're not pulling back on the AI push despite the user decline — if anything, they're accelerating it. CEO Mark Zuckerberg framed this as a necessary investment in the company's future, positioning AI as the key to eventually winning back users and driving new engagement. Meanwhile, creators are quietly diversifying. The smart ones saw this coming years ago and have been building email lists, launching newsletters, starting podcasts, and experimenting with platforms that give them more control over their relationship with their audience. This connects to something bigger happening across the creator economy. [GitHub just announced they're moving Copilot to usage-based billing](https://www.testingcatalog.com/github-copilot-moves-to-usage-based-billing-for-all-plans-in-2026/?ref=thedaringcreatives.com), which means the AI tools that creators rely on are becoming more expensive and unpredictable. [Google's search queries hit an "all time high"](https://www.theverge.com/tech/920815/google-alphabet-q1-2026-earnings-sundar-pichai?ref=thedaringcreatives.com) last quarter, suggesting people are looking for information in different places. The platforms are changing the rules faster than creators can adapt to them. ## The Creative Work Angle Meta is optimizing for AI-generated content and algorithmic efficiency over human creativity. Their AI investments aren't about making better tools for creators — they're about replacing creator output with synthetic content that keeps people scrolling without having to pay creators at all. That's not sustainable for anyone who makes things for a living. The creators I know who are thriving right now aren't the ones trying to game Meta's algorithm. They're the ones who've built direct relationships with their audience through newsletters, Discord communities, Patreon subscriptions, and their own websites. They treat social platforms as discovery tools, not as their primary distribution channel. This is actually good news if you're willing to do the work. When a platform starts hemorrhaging users, it creates opportunities for creators who are willing to go where the attention is moving. The early adopters who jumped on TikTok when it was still weird, who started YouTube channels when everyone said video was too hard, who launched podcasts when most people didn't know what RSS feeds were — they're the ones who built lasting audiences. ## Where the Attention is Going The 20 million people leaving Meta's platforms didn't disappear. They went somewhere. Some went to newer platforms. Some went back to consuming content through direct subscriptions and newsletters. Some started spending more time on platforms that prioritize human-created content over algorithmic feeds. The creators who recognize this shift early have a real advantage. While everyone else is trying to figure out how to make Meta's algorithm happy, the smart move is building an audience that doesn't depend on any single platform's goodwill. ## The Infrastructure Play This is where the principles-over-buttons thinking becomes important. Instead of chasing the latest Meta AI feature or trying to optimize for whatever engagement hack is working this month, focus on building systems that work regardless of which platform is winning. That means owning your email list. It means having a website that isn't dependent on social media traffic. It means creating content that has value beyond the platform it was originally posted on. It means building relationships with your audience that survive platform changes, algorithm updates, and user migrations. I'm not saying abandon social media entirely. But if Meta losing 20 million users while investing billions in AI doesn't make you think about diversifying your creative distribution strategy, I don't know what will. The platforms will keep changing the rules. They'll keep prioritizing their AI features over creator tools. They'll keep treating human creativity as a cost center rather than the thing that makes their platforms worth visiting in the first place. The creators who adapt to that reality — who build businesses that can survive platform instability — are the ones who'll be making a living from their work five years from now. The ones betting everything on algorithmic reach might not be. Meta's user decline isn't a crisis for creators. It's a reminder that audiences are portable, but only if you do the work to make them portable. The best time to start building that infrastructure was five years ago. The second best time is right now. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/meta-s-user-exodus-points-to-a-bigger-creative-shift/meta-s-user-exodus-points-to-a-bigger-creative-shift-landscape-1920x1080.webp) ``` ### Obsidian Fine Art Gallery Closes to Public Pending Gray Glasses "Cultural Compliance Review" URL: https://www.thedaringcreatives.com/aegis/obsidian-gallery-cultural-compliance-closure/ Last updated: 2026-08-01T19:42:21.000Z Underground art venue shutters indefinitely as authorities expand oversight of creative spaces _This post is for subscribers only._ ### Grok Aurora vs ChatGPT vs Gemini for Character Consistency (2026) URL: https://www.thedaringcreatives.com/grok-chatgpt-gemini-character-consistency/ Last updated: 2026-08-01T19:42:22.000Z You generated one great image of your character. You generate the next one — and it's a different person. Different face. Different jawline. Hair color shifted. That's **character drift**, and it's the single biggest reason AI image series fall apart. This guide is specifically about keeping a **character** (face, outfit, vibe) consistent across scenes. Not style. Not lighting. Not composition. Those matter too, and we'll get to them — but if your character looks like a different person from panel to panel, none of the rest helps. Pick your tool below and skip to the section that applies. Each one has a different lever for locking a character in place — Gemini Nano Banana and Grok Aurora use uploaded reference images, ChatGPT holds context inside a chat thread, Midjourney has a dedicated `--cref` flag, and DALL·E is the hard mode. ## Gemini Nano Banana — use multi-image input for best character lock Gemini's Nano Banana series is the strongest tool right now for character lock, because it fuses multiple image inputs into one generation. > "Use the character from image 1, placed in the setting from image 2\. Keep the character's face, hair, and outfit identical." You can build entire storyboards this way. The character image stays pinned across every generation — you only swap the scene reference. If you don't have a canon image yet, generate one first, commit to it, then never re-roll it. That image is now the source of truth for every future scene. ## ChatGPT image generation — use multi-turn in a single thread ChatGPT's image generation holds context inside a chat thread. Generate your character in turn 1, then reference "the same character from the previous image" in turn 2, 3, 4 — and it'll mostly hold. > "Same character, same outfit. Now show her standing on a rooftop at night." If something's slightly off, fix it in place rather than starting over: > "Keep everything the same — just make her hair a bit more orange." This is called multi-turn generation, and it's how you avoid the "start from scratch every time" trap that kills consistency. ## Grok Aurora character consistency — stay in the chat, lean on photorealism Grok's Aurora model is the new kid on the character-consistency block, and it's worth knowing where it fits. Grok runs inside X and at grok.com, and it lets you upload reference images directly into a chat thread — same general pattern as ChatGPT, with a few twists worth knowing. 1. Upload your canon character image at the start of a new Grok chat. 2. Be aggressively specific in your prompt. Aurora rewards detail: not "red hair" but "shoulder-length wavy auburn hair, slightly tousled, parted on the left." 3. Stay in the same thread. Don't open a fresh chat for each scene — Aurora loses context the moment you do. 4. When drift starts, re-paste the canon image as a reference in the new prompt. Don't trust the chat memory alone past a handful of turns. If you're publishing to X anyway, Aurora has one real advantage no other tool can match: you can generate and post in the same place. The distribution loop is built in. ## Midjourney v7 character reference — use `--cref` flag Midjourney has a dedicated character-reference flag. Drop your canon image into Discord, copy its URL, then attach it to every prompt: ``` your scene description --cref --cw 100 ``` `--cw 100` is character weight at maximum — Midjourney will hold the face hard. Drop it to 50 if you want some flexibility in expression or angle, but you'll lose some likeness. Pair with `--sref` (style reference) if you also want the same artistic style across the series. ## DALL·E 3 character consistency — this is the hardest path DALL·E 3 doesn't have image-reference input the way the others do. You're working purely from text prompts, which makes character lock fragile. > "Luna: a red-haired pilot with shoulder-length wavy hair, green goggles pushed up on her forehead, freckles, brown leather aviator jacket, white scarf, dark green cargo pants, brown boots. Flat pastel illustration style." Same words. Every time. The second you paraphrase, the model drifts. Honestly — if you're doing serious character work and you're not locked into DALL·E for a specific reason, switch tools. Gemini, Grok Aurora, and Midjourney will save you hours. ## The cross-tool tricks that always work These help regardless of which tool you're using: - **Name your character in the prompt.** "Luna" works better than "the pilot." Even a placeholder name like "Mascot Bunny" gives the model an anchor to latch onto. - **Don't paraphrase your descriptions.** "Wavy red hair" and "curly auburn hair" will give you two different characters. Pick the phrasing, save it, paste it. - **Save your prompts as source files.** Treat them like code. You will need to regenerate or extend in 3 months and you will not remember the exact wording. Trust me. - **Compare side by side before publishing.** Pull up all your generations in one grid. The drift you didn't notice in isolation will scream at you. - **One model per project.** Don't mix Gemini, Grok Aurora, and Midjourney for the same character series. Each has its own visual fingerprint, and they don't blend cleanly even with the same prompt. ## A quick workflow if you're starting today 1. Generate 4–6 candidate "canon" images of your character. Pick one. Commit. Don't second-guess. 2. Whatever tool you picked, lock that canon image into the input slot (Gemini multi-image, Midjourney `--cref`, ChatGPT thread, or DALL·E DNA prompt). 3. Change only the scene description. Leave the character spec untouched. 4. Refine in place, don't restart. Surgical edits ("same image but X different") beat fresh generations. 5. Side-by-side review every 3–4 outputs. Catch drift early. ## Why this is worth getting right Character consistency is what separates a series from a stack of one-off images. If you're building a comic, a brand mascot, a children's book, a product line, a story-driven Instagram feed — consistency is what makes readers trust that they're in a coherent world. Without it, every image reads as a remix of someone who looks vaguely similar to the last one, and the story breaks. You don't need to be technical to get this right. You need a repeatable process and one rule you don't break: **the canon image is sacred. Never re-roll it. Build everything else off of it.** Now go make something cohesive — and cool. ### Pope Leo XIV's AI Encyclical: Why Religious Authority Shouldn't Regulate Tech URL: https://www.thedaringcreatives.com/pope-leo-xiv-ai-encyclical/ Last updated: 2026-08-01T19:42:23.000Z Pope Leo XIV just dropped [his first encyclical calling for AI regulation](https://religionnews.com/2026/05/25/in-his-first-encyclical-pope-leo-xiv-says-ai-must-serve-humanity-not-the-powerful-few/?ref=thedaringcreatives.com), arguing that artificial intelligence must serve humanity rather than concentrate power among the few. And look, I actually agree with some of his concerns — especially about AI weapons development. Nobody wants killer robots deciding who lives and dies. But here's where I have a problem: why is a religious leader making policy recommendations that would apply to people who don't share his faith? ## Good Intentions, Wrong Authority The Pope raises legitimate points about AI safety. AI weapons are genuinely terrifying. The concentration of AI power in a handful of tech giants is worth worrying about. These aren't fringe concerns — they're the kind of issues that keep AI researchers awake at night. But agreeing with the destination doesn't mean I'm okay with who's driving the bus. When religious institutions start dictating technology policy, we're essentially saying that one group's moral framework should govern everyone else's tools. That's not how secular governance works, and it's not how it should work. ## Whose Ethics Get to Win? Here's the thing about AI regulation: someone's ethics are going to be baked into those rules. The question is whose. If we let religious authorities shape AI policy, we're not getting neutral, evidence-based governance. We're getting policy filtered through specific theological beliefs about human nature, divine purpose, and moral authority. That might work great if you share those beliefs. But what if you don't? What happens when the AI ethics council includes representatives from multiple faiths with competing views? What happens when secular technologists have to build systems that comply with religious interpretations of right and wrong? You end up with the same mess we see in other areas where religious authority tries to govern secular life — rules that make perfect sense to believers but feel arbitrary or oppressive to everyone else. ## The Unilateral Disarmament Problem There's another issue here that the Pope's statement doesn't address: what happens when some groups follow the rules and others don't? If Western democracies handicap their AI development based on religious ethical frameworks, but authoritarian regimes ignore those constraints entirely, we're not creating a safer world. We're just making sure the good guys fight with one hand tied behind their backs. AI weapons are scary precisely because they don't respect national boundaries or moral frameworks. The countries most likely to ignore religious calls for restraint are also the ones most likely to use AI weapons against civilian populations. That doesn't mean we should race to build killer robots. But it does mean that AI governance needs to be grounded in strategic realities, not theological ideals. ## The Real Threat to Religious Authority I suspect there's something else driving religious interest in AI regulation, though the Pope's statement doesn't say it directly. [AI tools are getting really good at helping people research and investigate](https://www.thedaringcreatives.com/googles-deep-research-agents-are-getting-scary-good-at-actually-researching/) claims independently. They can analyze historical texts, compare different sources, and help users trace the origins of beliefs and traditions. That's incredibly powerful for anyone trying to understand the world without relying on institutional authorities. Religious institutions have historically been gatekeepers of knowledge and interpretation. AI democratizes access to information in ways that make those gatekeepers less necessary. When anyone can analyze religious texts using AI tools, or trace the historical development of doctrine, or compare different theological arguments, the institution's role as interpreter becomes less central. I'm not saying this is why the Pope wants AI regulation. But it's worth noting that the institutions calling for AI oversight tend to be the same ones [whose authority gets challenged when people have better tools](https://www.thedaringcreatives.com/the-public-doesnt-hate-ai-they-hate-being-lied-to/) for independent investigation. ## Who Should Actually Govern AI? So if not religious authorities, then who? The people building the systems. The researchers studying the risks. The technologists who understand how these tools actually work. The ethicists who can think through implications without starting from predetermined theological conclusions. That doesn't mean we ignore moral considerations. It means we base our governance on evidence, expertise, and democratic input rather than religious doctrine. We need AI policy that's grounded in how these systems actually function, [what risks they actually pose](https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/), and what safeguards actually work. That requires technical knowledge, not theological authority. ## Separation for Good Reason The separation of church and state exists for good reasons. It protects both religious freedom and secular governance. When religious institutions try to shape policy for everyone, they undermine both principles. I respect the Pope's right to speak about AI's implications for his followers. But when religious leaders start making policy recommendations that would apply to everyone, they're overstepping their legitimate authority. AI regulation is too important to be left to institutions whose primary expertise is spiritual guidance rather than technical governance. We need policies [based on evidence and democratic input](https://www.thedaringcreatives.com/most-creatives-not-using-ai/), not theological interpretation. The stakes are too high for anything less. \`\`\` ### The Anthropic-SpaceX Deal Shows the End of DIY AI Infrastructure URL: https://www.thedaringcreatives.com/anthropic-spacex-ai-infrastructure/ Last updated: 2026-08-01T19:42:23.000Z Anthropic just inked a deal with SpaceX to use "all of the capacity of their Colossus data center"—the one with the particularically ambitious 100,000 GPU setup. They're also doubling Claude's usage limits across the board. For most people, this reads like typical Big Tech partnership news. But if you're an indie creator who's been building your own AI workflows, this is really exciting. I've been running automated content systems with Claude for months now. Newsletter drafts, [research](https://daringcreatives.com/googles-deep-research-agents-are-getting-scary-good-at-actually-researching/?ref=thedaringcreatives.com) summaries, social media adaptations—the whole pipeline that lets one person operate like a small team. But here's what I learned the hard way: the infrastructure side is a constant pain in the ass. ## The DIY Era Is Ending Right now, if you want AI to actually work for you you're basically building everything yourself. Custom API integrations. Prompt management systems. Error handling when rate limits hit. I've got scripts that retry failed requests and templates that try to maintain consistency across different AI models. It's functional, but it's brittle as hell. The SpaceX partnership changes this math completely. When Claude can access that kind of computational power, we're not talking about better chat responses. We're talking about AI agents that can handle complex, multi-step creative projects without breaking down halfway through. Think about what you actually want AI to do for you as a creator. You want it to remember your brand voice across a six-month campaign. You want it to understand that your luxury fashion client prefers "sophisticated" over "elegant" and never uses certain color combinations. You want it to track every asset you've used, understand licensing restrictions, and proactively suggest alternatives when you're pushing budget limits. That's not possible with the current "ask AI a question, get an answer back" model. That requires persistent intelligence—AI that maintains context over weeks and months, not just individual conversations. ## What Enterprise Infrastructure Actually Means The Colossus data center isn't just about raw power. It's about reliability. When you're running a creative business, you can't have your AI assistant crash in the middle of a client deadline because of server issues or capacity limits. I've had Claude hit usage limits right when I'm trying to finalize a newsletter that goes out to thousands of people. Not exactly [professional](https://daringcreatives.com/reviewing-the-google-ai-professional-certification-from-coursera/?ref=thedaringcreatives.com). But when Anthropic has guaranteed access to 100,000 GPUs, those bottlenecks disappear. Your AI teammate becomes as reliable as any other business tool you depend on. More importantly, this level of infrastructure enables AI agents—not just AI tools. We're talking about Claude instances that can maintain project continuity, remember creative decisions, and operate across your entire tech stack without constant human babysitting. ## The Democratization Play Nobody's Talking About Here's where it gets interesting for indie creators: enterprise-grade AI infrastructure is actually the great equalizer, not the great divider. Right now, if you want AI that can handle complex creative workflows, you need technical chops. You need to understand APIs, manage authentication, handle errors gracefully. Most creatives don't want to become part-time developers just to automate their social media. But when AI agents run on enterprise infrastructure, that technical complexity gets abstracted away. A photographer's AI agent can automatically update their portfolio website, cross-post selected works to Instagram with appropriate hashtags, and send client notifications when galleries are ready—all without the photographer touching a line of code. A copywriter's agent can maintain brand voice guidelines across multiple clients, track which headlines performed best for different industries, and adapt writing style based on target demographics. The agent gets smarter about your preferences over time, not dumber. ## What Changes for Solo Creators The SpaceX partnership signals that we're moving from "AI as productivity hack" to "AI as business infrastructure." That shift matters more for indies than for big agencies. Large creative agencies already have project managers, account coordinators, and production assistants handling the routine work. When you're a solo creator, you're wearing all those hats yourself. AI agents with enterprise-grade reliability can actually take on those roles. Your AI teammate will remember that Client A needs assets delivered via Dropbox while Client B prefers direct email attachments. It'll track which social media platforms perform best for different types of content. It'll maintain your content calendar and suggest optimal posting times based on your audience engagement patterns. This isn't about replacing human creativity. It's about getting rid of all the administrative bullshit that keeps you from focusing on the creative work you actually want to do. ## The Timing Isn't Coincidental Anthropic isn't the only one making these moves. Google's prepping Agent Mode for Gemini. [OpenAI](https://daringcreatives.com/why-creatives-leaving-openai/?ref=thedaringcreatives.com)'s testing autonomous agents with their Chrome extensions. The entire industry is pivoting from chat-based AI to agent-based AI. The SpaceX partnership gives Anthropic the computational foundation to make managed agents actually work at scale. When your AI teammate can access that kind of processing power, it can handle multiple complex tasks simultaneously without performance degradation. For indie creators who've been skeptical about AI—wondering if it's just another productivity fad—this is the inflection point. AI agents with enterprise infrastructure aren't experimental anymore. They're becoming standard business infrastructure, like cloud storage or email marketing platforms. The question isn't whether AI will transform creative workflows. The question is whether you'll adapt to agent-based collaboration before your competitors do. I'm betting on the creators who lean into this shift. The ones who stop thinking about AI as a tool and start thinking about it as a teammate. Because when everyone else is still prompting ChatGPT for individual tasks, you'll be working with an AI agent that understands your entire creative business. And that advantage compounds fast. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/the-anthropic-spacex-deal-shows-the-end-of-diy-ai-infrastructure/the-anthropic-spacex-deal-shows-the-end-of-diy-ai-infrastructure-landscape-1920x1080.webp) ``` ### The Musk-Altman Fight Is About Control, Not Competition URL: https://www.thedaringcreatives.com/musk-altman-fight-control/ Last updated: 2026-08-01T19:42:26.000Z Elon Musk and Sam Altman are about to spend the next few months airing their dirty laundry in an Oakland courthouse, and honestly, I'm here for it. The trial starts April 27th, and [according to The Verge](https://www.theverge.com/ai-artificial-intelligence/917755/musk-altman-openai-xai-gossip?ref=thedaringcreatives.com), it's going to be "messy." Musk co-founded OpenAI back when it was supposed to be a nonprofit focused on building AI for everyone. Then he wanted to be CEO, didn't get it, and flounced off in what The Verge diplomatically calls "a huff." Now he's back with xAI and a lawsuit claiming OpenAI betrayed its original mission by going commercial with Microsoft. The legal details matter less than what this fight reveals about who gets to control the future of AI development. ## What's Actually Happening Musk's argument boils down to this. OpenAI was supposed to remain open. The clue was in the name. Instead, they took billions from Microsoft, built ChatGPT behind closed doors, and turned into exactly the kind of AI monopoly they originally said they wanted to prevent. Altman's counter-argument is essentially: "Grow up, Elon." Building frontier AI requires enormous resources. The nonprofit model couldn't scale. They did what they had to do to stay competitive with Google and everyone else throwing billions at this problem. Both of them have a point, which is why this is going to get ugly in court. The timing is particularly interesting because of what else is happening right now. [DeepSeek just dropped V4](https://www.theverge.com/ai-artificial-intelligence/918035/deepseek-preview-v4-ai-model?ref=thedaringcreatives.com), claiming their open-source model can compete with the best closed-source systems from US companies. Meanwhile, [OpenAI is rolling out GPT-5.5](https://techcrunch.com/2026/04/23/openai-chatgpt-gpt-5-5-ai-model-superapp/?ref=thedaringcreatives.com) and talking about AI "super apps." We're moving from the "let's all build AI together" era to the "winner takes all" era. This lawsuit is just the most dramatic example of that shift. ## The Real Stakes Neither Musk nor Altman is wrong about the fundamental problem. Building cutting-edge AI really does require massive resources. But keeping those capabilities locked behind corporate walls really does create the exact concentration of power that early OpenAI said it wanted to prevent. The question isn't whether Musk or Altman wins in court. The question is what happens to everyone else who's building things with AI. Right now, if you're working on creative projects with AI, you're mostly dependent on a handful of companies. OpenAI, Anthropic, Google, maybe a few others. Your access to the good models depends on their pricing decisions, their content policies, their API limits. When [Anthropic briefly tested removing Claude Code from the Pro plan](https://simonwillison.net/2026/Apr/22/claude-code-confusion/?ref=thedaringcreatives.com) earlier this week, developers lost their shit. That's the fragility we're talking about. The promise of truly open AI development was that you wouldn't have to worry about any of that. You'd run your own models, set your own policies, build whatever you wanted without asking permission. DeepSeek's V4 release suggests that promise isn't completely dead. Chinese researchers are apparently willing to give away frontier-level capabilities for free. But even that comes with its own dependencies and geopolitical complications. ## What This Means for Creators If you're using AI in your creative work, this fight matters more than you might think. The question of whether AI development stays open or goes fully proprietary will determine what tools you have access to and how much control you maintain over your own creative process. The closed model gives you ChatGPT and Claude and Gemini, all of which are genuinely impressive. But you're always one policy change away from losing access to the specific capabilities you've built your workflow around. Remember when OpenAI briefly restricted DALL-E for certain kinds of artistic content? Or when they changed their content policies and suddenly your perfectly reasonable creative prompts stopped working? The open model gives you models you can run yourself, modify, and use however you want. But it requires more technical knowledge and computational resources. And there's no guarantee that open models will keep pace with the closed ones, especially if companies like OpenAI and Anthropic keep hoarding their best research. What's frustrating is that this feels like a false choice. There's no technical reason why we can't have both powerful AI capabilities and genuine user control. ## The Bigger Picture I don't really care which billionaire wins this particular pissing contest (I root for neither). What I care about is whether the tools that help people make interesting things remain accessible and under their control. The irony is that both Musk and Altman probably agree with that goal in theory. Musk talks constantly about democratizing technology. Altman has said repeatedly that OpenAI wants to put powerful AI tools in everyone's hands. But their actions suggest they're more interested in controlling the market than empowering users. Musk isn't pushing for truly open AI development - he's building xAI as another closed competitor. Altman isn't arguing that OpenAI's current approach serves users better - he's arguing that it was necessary for survival. Maybe they're both right about the competitive dynamics. Maybe the AI market really is winner-take-all, and the only choice is between American monopolies and Chinese ones. But I suspect there's still room for something messier and more interesting. Models that are good enough for most creative work, truly open, and maintained by communities rather than corporations. Tools that you can understand, modify, and depend on without worrying about corporate strategy changes. The Musk-Altman fight is going to generate a lot of headlines and probably some entertaining courtroom drama. But the more important story is what happens to everyone else who just wants to build cool shit with AI while this plays out. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-landscape-1920x1080.webp) **portrait** — 1080×1920 ![portrait](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-portrait-1080x1920.webp) **square** — 1080×1080 ![square](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-square-1080x1080.webp) **documentary** — 1920×1080 ![documentary](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-documentary-1920x1080.webp) **spatial-square** — 1080×1080 ![spatial-square](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-spatial-square-1080x1080.webp) **spatial-landscape** — 1920×1080 ![spatial-landscape](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-spatial-landscape-1920x1080.webp) **spatial-portrait** — 1080×1920 ![spatial-portrait](_featured-images/_pending/the-musk-altman-fight-is-about-control-not-competition/the-musk-altman-fight-is-about-control-not-competition-spatial-portrait-1080x1920.webp) ``` ### Museum of Tomorrow Suspends Public Workshop Programs Indefinitely URL: https://www.thedaringcreatives.com/aegis/museum-of-tomorrow-suspends-workshops/ Last updated: 2026-08-01T19:42:33.000Z Popular hands-on science programs discontinued pending "curriculum alignment review" _This post is for subscribers only._ ### The Creative's Guide to AI Side Hustles That Actually Pay URL: https://www.thedaringcreatives.com/creatives-guide-ai-side-hustles/ Last updated: 2026-08-01T19:42:35.000Z I've been running automated content systems for months now, and I keep getting the same message from creatives I know: *"How do I actually make money with this AI stuff?"* Fair question. I'm still figuring out parts of it myself. The honest answer is that there are two side hustle worlds happening at the same time, and they barely overlap. One world is the Fiverr grind — $50 per blog post, $30 per logo, customers who think they're paying for the tool more than the person. The other world is a small group of freelancers charging $5,000 to $20,000 a month for AI automation consulting, plus designers running Midjourney workflows for clients who care about the final brand, not the prompt. Both groups use the same software. The income gap between them isn't about skill with the tool. It's about what they're selling. This guide is for figuring out which side you want to be on, and what it actually takes to get there. ## What the numbers say Before we get into specific paths, two data points worth knowing. Upwork's 2026 in-demand skills report shows freelancer earnings for AI-related work grew **109% year-over-year**, and AI video generation/editing alone grew **329%**. That's not a survey of what people *want* to do — that's invoices that got paid. The demand is real and it's still expanding. The second number: practitioners running AI automation consulting for small and medium businesses are charging **$5,000 to $20,000 per month** on retainer, often after a $300 to $800 setup fee for the initial workflow build. Same software a hobbyist has access to. Wildly different price tag. The gap is the entire subject of this article. ## The Tool Trap (which I fell into for a while) The most common way creatives stall on this is what I'd call the Tool Trap. It looks like this: you hear AI is a thing, you sign up for ChatGPT Plus ($20/month), then Midjourney ($30/month), then ElevenLabs ($22/month), then Runway ($12/month), then maybe Suno ($10/month). Now you're $94 a month deep before you've done a single client project, and you're trying to figure out which of those tools is going to make you money. That framing is the problem. The tool doesn't make you money. A solved problem makes you money, and the tool is a thing you happened to use in the process. When the question is *"how do I monetize ChatGPT?"*, the answer is usually that you can't, because everyone else can monetize it too and the price collapses. When the question is *"what painful problem does someone I can reach actually have?"*, the answer turns into a service business with paying clients. ChatGPT might still be involved, but it's a saw, not the product. I fell into the tool trap when I first started messing with AI workflows in 2024\. I subscribed to everything, built nothing, and wondered why nothing was working. The shift for me was realizing I had to start with the problem, not the software. There's a [one-page AI strategy template](https://www.daringstrategy.com/guides/how-to-write-a-one-page-ai-strategy/?ref=thedaringcreatives.com) over at Daring Strategy that forces exactly that: name the problem, the owner, and your red lines before you spend another dollar on tools. ## The five paths that are actually working These are the five business models I'm seeing pay out in 2026\. None of them are unique to me — they show up in the Upwork data, in Medium pieces by people who've tried multiple side hustles and ranked them, and in Reddit threads from people doing the work. I've listed them roughly in order of how much money they tend to generate, though that's never the only thing that matters. ### 1\. AI Automation Consulting for small businesses ($5K–$20K/month) This is the most lucrative path I've seen documented, and it's the one most creatives skip because it doesn't sound creative on the surface. It is, though — the work is essentially process design with software as the medium. The business model: a local dentist, a real estate team, a wedding photographer's studio, a personal injury law firm — almost any small business with more than a handful of employees has workflows that are leaking time. Missed calls that don't get returned. Leads that come in through a contact form and sit unanswered for two days. Invoices that have to be manually chased. Customer follow-ups that everyone agrees should happen but nobody owns. An AI automation consultant goes in, audits the leaks, and builds a system using Zapier or Make connecting the business's existing tools (CRM, Gmail, Calendly, Slack, QuickBooks) with AI components dropped in where they help — summarizing inbound emails, drafting follow-up messages, transcribing call notes into the CRM. Then they stay on retainer to maintain it and adjust as the business changes. What it pays: practitioners are charging **$300–$800 for the initial setup**, then **$1,000–$5,000/month** for ongoing retainers per client. With three or four clients, that's a real income. Why creatives are good at this even though it doesn't feel creative: small businesses don't need a developer to build this. They need someone who can sit with the owner, understand what's actually broken in their day, and design a system around it. That's interview skill, taste, and synthesis — which is exactly what designers and writers do all day. Where people get stuck: trying to sell this as "AI consulting" instead of selling the outcome. Nobody buys AI consulting. They buy *"I'll get your missed calls answered within 5 minutes"* or *"I'll cut your invoicing time in half."* The AI is how you deliver, not what you sell. ### 2\. AI-assisted design work (Midjourney + post-production) This is what most people picture when they hear "creative AI side hustle," and it's a real path, but the version that pays is not the version most people are doing. The version that doesn't pay: open Midjourney, type a prompt, hand the client a raw render, charge $50\. You're competing with everyone else who has a $30/month Midjourney subscription, and the client can do that themselves. The version that pays: a real client engagement looks more like this. Wedding invitations is a niche I keep seeing referenced. A designer takes the client's wedding details, their venue, their color story, runs **hundreds** of Midjourney variations across multiple prompt approaches, curates down to three concepts that actually work for the couple, then takes those into Photoshop to fix the things Midjourney can't do reliably — text rendering, exact color matching, print-safe resolutions, the small impossible-anatomy artifacts that show up everywhere if you don't look for them. The deliverable is finished, print-ready invitations and a guide for the matching menus, programs, and thank-you cards. The client pays for the final asset set, not the Midjourney generations it took. What it pays: similar wedding invitation studios are charging **$1,500–$5,000 per wedding package**. A graphic designer named Sarah Chen has been cited as building this into a meaningful business by scaling with virtual assistants — though I want to flag that her specific income numbers are widely shared on YouTube but I haven't found independent verification. Treat the *workflow* as accurate, treat the *eight-figure income claim* as unverified. Tools: **Midjourney** at the $30/month Standard tier is the workhorse (the unlimited relaxed-mode generations are what makes the hundreds-of-variations workflow possible). Photoshop for post. Maybe **Runway** ($12/month) if you're producing short animated invitations or "save the date" videos, which is a growing premium add-on. The same pattern works in adjacent niches — children's book illustrations, restaurant menu design, real estate listing photography retouching, small e-commerce product imagery. Cristian R., a Fiverr Pro seller cited in their own marketing, has built a children's-book illustration practice around AI-assisted workflows. (His income isn't publicly listed, but Fiverr Pro status is at least a credibility floor.) Where people get stuck: handing over raw outputs. The whole reason this pays is the curation, post-production, and brand discipline you add. Take that away and you're selling a $30 subscription back at retail. ### 3\. Strategic content systems (for writers) This is the one I have the most direct experience with, because The Daring Creatives is, in part, an experiment in running one. So fair warning that I have a horse in this race. The unpaid version is what most people try first: write articles with ChatGPT, post them on Medium, hope something happens. It doesn't, because the content is generic, undifferentiated, and competing with millions of equally-generic pieces. As one Reddit thread I keep returning to put it: *"Because everyone is using the same generic prompts, the internet is becoming a desert of boring, robotic content."* The version that pays is selling **systems**, not articles. A small business has a content problem — they need to publish consistently, in their voice, on topics that bring in customers, across blog plus email plus a couple of social platforms — and they don't have the time, the bandwidth, or honestly the writing instinct. They've tried ChatGPT themselves and the output was, as one client put it to me, *"correctly punctuated nothing."* A strategic content system for that client looks like: an editorial brief on what topics actually map to their business, a brand voice guide so the AI drafts come back sounding like them, a draft-edit-publish workflow that uses AI for the first pass and you for the final pass, automation for distribution to the platforms they actually use, and a monthly review of what worked. You're charging for the system and the outcome (consistent published content that sounds like them), not the word count. What it pays: writers running this model are reporting **effective hourly rates around $120** ($7,200 for a project that took about 60 hours, in one Medium piece I'm not fully convinced is real but the pricing matches what I've seen in client conversations). On retainer, $1,500–$4,000/month for a fully managed content operation is realistic if the client is at the right size. Tools: **ChatGPT Plus** ($20/month) is the floor. Beyond that, the tools depend on what the client actually needs — a CMS plugin, a scheduling tool, sometimes a custom voice-guide setup. If you want to learn the voice-guide piece, I've written about [how to teach AI a brand voice](https://www.thedaringcreatives.com/teach-ai-brand-voice/) in a separate piece, which is mostly the principle of "give it enough specific examples to imitate rather than telling it abstract rules." Where people get stuck: trying to sell content packages by the article. The client doesn't want articles. They want results from publishing. Sell the result. ### 4\. Custom tools for small businesses (the "vibe-coded" path) This one is newer and underdiscussed, but I think it's going to be one of the biggest paths over the next year. Tools like Claude Code, Cursor, and v0 have [made it possible to ship working software without writing code](https://www.thedaringcreatives.com/beginners-guide-vibe-coding/), provided you understand what makes software useful. Most small businesses are stuck between two terrible options for the niche software they need. Option A: pay $200/month per seat for an enterprise SaaS product with 50 features, 47 of which they don't use. Option B: build a Frankenstein of Google Sheets and a Zapier automation and pray nothing breaks during tax season. Both options leave the business owner doing a job the software was supposed to do. The third option — a $50–$200/month custom tool that does *exactly* the three things this specific business needs — has been mostly inaccessible because hiring a developer costs $5,000+ for the initial build. AI-assisted coding has collapsed that math. A creative who understands user experience can now scope a small-business tool, build it with Claude Code or a similar agent, test it with the client, and ship it. Then either charge a flat fee for the build plus a small monthly hosting/maintenance retainer, or position it as a tool you license to the client at a recurring rate. Examples I've seen referenced: a check-in app for a small gym that handles member access and a class waitlist. A client timeline manager for a wedding planner that ties to their calendar and sends reminders automatically. An inventory tracker for a food truck that texts the owner when popular items are running low. What it pays: this varies wildly because the niche is still settling. Practitioners I've seen report **$2,000–$8,000 for a custom build** (one-time or amortized into setup-plus-monthly), and **$50–$200/month** in ongoing hosting/maintenance. Tools: **Claude Code** (subscription-based; pricing depends on plan) is the most capable of the AI coding agents I've used. **Cursor** and **v0** are also worth knowing. You'll need a way to host whatever you build — Vercel, Railway, and Cloudflare all have free or near-free tiers for early projects. Where people get stuck: thinking you need to be a developer. You don't, but you do need to understand what makes a tool useful versus frustrating, which is a creative skill, not a coding one. Build for someone you actually talk to. Don't build a generic tool for a generic market. ### 5\. Voice, audio, and short-form video production The 329% growth number in AI video generation isn't hypothetical demand. It's small businesses, podcasters, course creators, and short-form content creators discovering that they can get studio-quality voiceovers, full music tracks, and animated video segments for a fraction of what production used to cost — but they need someone who knows how to actually run the tools. The business model: produce voiceovers, soundtracks, video intros, podcast post-production, audiobook narration, short-form social videos, or animated explainers as a service. The client gives you a script or a brief. You deliver finished, polished media. What it pays: this depends heavily on what you're producing. Voiceovers tend to run **$50–$200 per short script** (5-minute YouTube intro, 60-second ad). Full podcast post-production retainers run **$500–$2,000/month per show**. Short-form animated videos run **$200–$1,500 per video** depending on length and complexity. Custom music tracks for a brand or a course run **$100–$500 per track**. Tools: **ElevenLabs** ($5/month entry, $22/month Creator tier is the realistic floor for client work). **Suno** Pro at $10/month for music with commercial licensing on 500 songs/month. **Runway** Standard at $12/month/billed-annually for video generation. Pair them with whatever you already use for editing — Premiere, Final Cut, CapCut, DaVinci Resolve. Where people get stuck: same place as design. Raw output, sold as a deliverable. The pay comes from production polish — editing the voiceover for breath and pacing, matching music tempo to the cut, post-producing the AI video to hide its weirdness. The AI is the rough draft. You're the finishing department. ## The pricing shift nobody is teaching Here's the move I see separating the two side-hustle worlds more than any tool choice or niche. **Stop billing hourly.** The data is from a Digital Applied report on freelance pricing trends, and it lines up with what I see in client conversations: hourly billing is collapsing for AI-powered services. The reason is structural. When you bill hourly, you're telling the client that what you sell is **time**. Time, in their head, means *"this person is interchangeable with anyone else who can run the same software."* Hourly billing makes you a commodity by definition. Project pricing and retainers tell the client a different story: *"this person is solving a problem I have, and the value of the solution is the price."* The freelancers charging $5,000/month for AI automation aren't doing twenty times the work of someone charging $50 for a blog post. They're solving a much more expensive problem (business process inefficiency that's costing the client thousands in lost revenue), and the client knows it. Practical version of this for any of the five paths above: - **Setup fees** for the initial buildout (the discovery, the configuration, the testing). One-time, project-priced. - **Monthly retainers** for ongoing service (maintenance, adjustments, optimization, support). Recurring. - **Value-based pricing** when you can quantify the savings or revenue you're producing. *"This automation is saving you $4,000/month in missed-call follow-ups. The retainer is $1,500."* Math the client can verify. I won't pretend this transition is easy. Most creative work has been hourly-priced for so long that even good clients default to *"what's your rate?"* You have to gently redirect that conversation to *"here's the package, here's what's included, here's the outcome."* That redirect is itself a skill. Some clients will push back. You let them go. ## The $100/month stack vs the $500/month stack A practical breakdown of what you actually need to spend on subscriptions, because the tool trap is real and expensive. **The $100/month starter stack:** - **ChatGPT Plus** — $20/month. Floor for almost any text-based work. - **Claude Pro** — $20/month. Worth having in addition to ChatGPT for code, longer documents, and a different voice. Optional if budget is tight, but I keep coming back to it. - **Midjourney** Standard — $30/month. Required if you're doing any design-heavy work; skippable if you're a writer. - **ElevenLabs** Starter — $5/month. Only if you're doing any voice/audio. - **One automation tool** — Zapier (free tier or $20/month Starter) or Make (free tier or $9/month Core). Total: $75–$95 if you're disciplined. **And critically: pick three of these based on your actual niche, not all five.** **The $500/month "I'm running a real practice" stack:** - Everything above, plus: - **Midjourney** Pro or Mega — $60–$120/month if image generation is your primary work - **Runway** Pro — $35/month for serious video work - **Suno** Pro — $10/month if you do music - **Notion or Obsidian** \+ a CRM (HubSpot has a generous free tier) — $0–$50/month - **Hosting/automation infrastructure** — $50–$100/month depending on how much custom tooling you've built - **Domain + email** — $15/month if you're running this as a real business - An assistant or two — variable, but virtual assistants on Upwork start at $5–$15/hour and pay for themselves quickly if you've got too much execution work The hidden trap is that you don't need both stacks. You need *the* stack for what you actually do. Designers don't need ElevenLabs. Writers don't need Midjourney Mega. Automation consultants barely need Midjourney at all. [Audit your AI subscriptions](https://www.thedaringcreatives.com/reality-of-ai-subscriptions/) every quarter and kill anything you haven't opened in 30 days. ## How to pick which path is for you Honestly the most useful question I've found is just: **what kind of conversation are you most naturally good at?** - If you're good at sitting with a small business owner and untangling what's actually broken in their day → **automation consulting** - If you're already good at visual design and have a critical eye for output → **AI-assisted design** - If you write well, think structurally, and like editing more than first drafts → **strategic content systems** - If you understand what makes software useful and you like solving specific problems → **custom tools** - If you have an audio/video ear and you're patient with post-production → **voice and short-form media** You can pick more than one over time, but pick one to start. The single biggest mistake I see is trying to be the "AI services" generalist who does a little of everything. Pick a path, get good at one workflow, and let the work compound before adding a second. ## A few notes on getting started **Don't start on Fiverr or Upwork if you can avoid it.** The platforms work, but they push you toward commodity pricing. Direct outreach to local small businesses — actual conversations, in-person or via email — produces better clients at higher rates. Contra is gaining traction as a commission-free alternative for project-based AI work if you want a platform. **LinkedIn and X (Twitter) work for visibility, but only if you're posting evidence of the work, not opinions about AI.** Show before-and-after on a real project. Show a workflow you actually use. Show a client outcome with a number attached. Posts that say *"AI is changing everything"* don't get clients. Posts that say *"I cut this firm's invoicing time from 4 hours/week to 20 minutes — here's the workflow"* do. **Be honest about what's human and what's AI.** I think this matters more than people realize. Clients are getting suspicious of pure AI output, and rightly so. The freelancers I see winning long-term are the ones who openly explain their [hybrid AI workflow](https://www.thedaringcreatives.com/adopting-an-ai-workflow/): *"AI does the bulk drafting, I do the editorial pass and the client communication, here's the split."* That transparency turns into trust. Pretending the work was all you when it wasn't is a slow-burning credibility problem. **Defend people learning in public.** I know I keep saying this. The AI-creativity space has a lot of gatekeepers who pile on beginners using AI tools "wrong" — wrong prompts, wrong workflow, output that looks too obviously generated. Ignore them. Their target should be the people scamming with AI, not the people learning. If your work looks AI-generated at first because you're new, that's fine. The fix is more reps, not more shame. ## Frequently asked questions **How much can a beginner realistically make in the first 3 months?** Honest answer: usually somewhere between **$0 and $2,000/month** in your first quarter, with most of the variance depending on whether you're doing direct outreach or relying on platforms. Plan for $0 the first month while you set up. By month 3, if you've talked to 20+ small businesses or shipped 5+ portfolio pieces, you should have at least one paying engagement. **Do I need to learn how to code?** No, but it helps for the custom tools path. The other four paths don't require coding at all. Even on the custom tools path, AI coding agents like Claude Code mean you can ship working software without writing code in the traditional sense — though you do need to understand what good software *feels* like to use. **Which AI subscriptions should I buy first?** ChatGPT Plus ($20/month) if you're not sure. It's the most generally useful starting point and the one tool that touches every path. Add a second subscription only when you have a specific need it solves — Midjourney if you've gotten a design lead, ElevenLabs if you've gotten a voice lead, and so on. Don't subscribe ahead of demand. **Is the side hustle market saturated?** The market for generic AI output (basic blog posts, templated logos, raw voiceovers) is saturated. The market for solving real business problems using AI as part of a workflow is wide open. The freelancers complaining about saturation are usually competing on the saturated end. The income gap between the two markets is in the data — Upwork's 109% YoY earnings growth doesn't fit a saturated market. **What if AI gets so good that my workflow becomes obsolete?** Real risk worth thinking about. The pattern that's held so far is that AI tools get easier to use, which lowers the floor on quality but raises the ceiling on what's possible. Design tools got dramatically easier from the 1990s through the 2010s and designers didn't disappear — they moved up the value chain. The work that's most exposed is pure execution of known-good tasks. The work that's least exposed is anything involving client conversations, strategic thinking, taste judgments, and post-production polish. Optimize toward the second. **How do I price my first project?** Start with the lowest end of the ranges in this article (e.g., $300 for an automation setup, $500 for a basic content system buildout) and raise it after the third paying client. Don't undercut yourself permanently to get the first project; clients who buy on price will leave on price. Better to ship one $500 project than five $50 ones. **Should I disclose to clients that I'm using AI?** Yes. Always. I won't argue this one — disclosure is the long-term play and the moral one. The disclosure doesn't have to be in the marketing; it does need to be in the conversation. *"My workflow is hybrid AI-and-human. The AI handles drafting and iteration, I handle editorial, strategy, and the final pass."* Most clients will appreciate the clarity. The ones who don't are not your clients. **What if I want to make money but I don't have a niche or skill yet?** Pick the automation consulting path. It requires the least pre-existing creative skill, the demand is highest, the income is highest, and the work is teachable. Start by automating one workflow for a friend's small business for free or cheap, document it, and use that as your first portfolio piece. The path from there to paying clients is shorter than people think. ## The thing I keep coming back to I started this article saying I get the same question over and over from creatives I know — *"how do I actually make money with this AI stuff?"* — and I want to end with the version of the answer I usually give in person. The thing isn't the AI. The thing is the problem. Anybody can sign up for the tools. The people who are making real money are the ones who figured out what painful, specific problem to solve, and then used AI to solve it cheaper, faster, or better than anyone else can. The tools are commoditized. The problem-finding and the solution-shaping aren't. Those are still creative work, and they pay accordingly. If you spend the next three months learning every AI tool that exists, you'll be tired, broke, and no closer to a client. If you spend the next three months talking to ten small business owners and finding one painful problem you can solve, you'll have a side hustle. I think it's actually that simple, and I think most of the noise online is making it sound more complicated than it needs to be. Go find the problem. ### Dispatch 9 — What They're Taking URL: https://www.thedaringcreatives.com/aegis/dispatch-9-what-theyre-taking/ Last updated: 2026-05-21T02:59:59.000Z They're not collecting future threats. They're collecting evidence that creative work used to happen without permits. _This post is for subscribers only._ ### Yeah, I'm in a Cult. So Are You. URL: https://www.thedaringcreatives.com/im-in-a-cult/ Last updated: 2026-08-01T19:42:36.000Z ## The Water Wars Comment Section I was scrolling Threads today and saw someone share this incredible website — an AI-generated map of Paris that you could click on and it would zoom into different places, creating hand-drawn style illustrations with little characters walking around in real time. It was genuinely cool. Like, tour app level cool. Naturally, I went to the comments to learn more about how they built it. And naturally, the first thing I see is someone going off about water usage. "This is such a waste of water!" followed by the classic: "AI people are in a cult." That's when I started doing what I always do — digging into the actual numbers. ## My Data Center Days I got curious about the water thing because I actually have some history here. Early in my freelance career, I worked on a video project for Google's data center in The Dalles, Oregon. I also visited data centers in South Carolina and Georgia. So I did what I always do — I went down a research rabbit hole. Spent about an hour looking up actual usage numbers, environmental studies, comparative data. The environmentalists aren't wrong. When you're training large models like Opus or Gemini, the water usage is significant. But here's what I found: a medium-sized data center uses roughly the same amount of water as a golf course. And individual usage — like that Paris map website — doesn't even matter. We're talking about a choice. Do we use that water for a golf course that benefits a few hundred people, or for a data center that could potentially help cure cancer? Yes, I stacked the deck with this argument. It's such an absurd example, but thats when it hit me. I was rationalizing. I was making arguments to defend something I already believed in. Maybe that commenter was right. Maybe I *am* in a cult. ## Wait, How Do Cults Actually Work? Cult formation follows predictable patterns: shared beliefs, in-group loyalty, and rationalization of contradictory evidence when it threatens the worldview. Members develop what psychologists call "cognitive commitment" — they become emotionally invested in defending their beliefs, even when presented with conflicting information. But as I'm reading this stuff, I realize this describes pretty much every passionate community I know. There's the cult of Mac users who will defend Apple's every decision. The cult of progressive politics. The cult of MAGA. The cult of specific video games, podcasts, or personalities. Hell, I'm definitely in the cult of Mel Robbins — I genuinely worship her (for real). Inside each cult, everything makes perfect sense. Outside of it, the devotion looks completely irrational. Social identity theory explains why this happens. When we adopt a group identity, we start viewing information through that lens. We seek out confirming evidence and dismiss challenges. We make excuses and craft arguments to support what we already believe. ## The Confidence Cult I keep hearing people say that AI gives users an unrealistic sense that they can do anything. "How delusional is that?" But why is confidence such a bad thing? Why is thinking big considered dangerous? As someone who's neurodivergent, AI tools genuinely expand what I can accomplish. They help me organize thoughts, draft ideas, and build things I couldn't build alone. If that makes me feel like I can shoot for the stars, what's wrong with that? Research on "positive illusions" shows that slightly unrealistic optimism about our abilities actually correlates with better mental health and higher achievement. People who believe they can do more than they probably can often end up doing more than people with "realistic" expectations. ## Admission of Guilt So when someone calls me an AI cultist, I'm not going to feel defensive anymore. Yes, I'm in the cult of AI. I think it's magic. I irrationally support it and make arguments to defend it — just like I did with that water usage research. I'm also in the cult of simulation theory, and the cult of rap music. We all have our irrational devotions. The question isn't whether we're in cults — it's whether our cults are worth it. I'd rather be irrationally optimistic about technology that could help cure cancer than rationally pessimistic about water usage at golf courses. But that's just my cult talking. ### Local Artists Report Difficulty Securing Exhibition Space as Venue Reviews Continue URL: https://www.thedaringcreatives.com/aegis/artists-losing-exhibition-space/ Last updated: 2026-08-01T19:42:38.000Z Independent artists face mounting challenges finding galleries willing to host work as AEGIS heritage reviews expand across cultural districts. _This post is for subscribers only._ ### GitHub Copilot's New Pricing Shows Who Really Owns AI-Assisted Development URL: https://www.thedaringcreatives.com/github-copilot-pricing-ai-development/ Last updated: 2026-08-01T19:42:40.000Z While the internet spent yesterday debating whether [Claude Code might cost $100/month](https://simonwillison.net/2026/Apr/22/claude-code-confusion/?ref=thedaringcreatives.com#atom-everything) (spoiler: it probably won't), GitHub made actual changes to Copilot Individual that I haven't seen many people talk about. GitHub updated their Individual plan to limit certain features and push more capabilities toward their Business tiers. This is the classic SaaS playbook of starting generous and then segmenting users into higher-paying buckets once they're hooked. But there's something else going on here that's worth paying attention to. ## The Real Story Isn't Pricing GitHub isn't just another AI coding tool competing with Cursor or Claude Code. They own the infrastructure where most code lives. When they make changes to Copilot, they're not just adjusting a product — they're reshaping how developers relate to their own work environment. If you're already living in GitHub for version control, issues, and collaboration, Copilot isn't an add-on tool you evaluate against competitors. It's part of the environment. That's a fundamentally different relationship than choosing between standalone AI coding assistants. This integration advantage is why the [SpaceX-Cursor deal rumors](https://techcrunch.com/2026/04/21/spacex-is-working-with-cursor-and-has-an-option-to-buy-the-startup-for-60b/?ref=thedaringcreatives.com) make sense. Cursor is great, but they need distribution. xAI needs applications for their models. Neither has what GitHub has: developer workflow ownership. ## What This Means for Individual Creators The optimistic read is that AI coding assistance is becoming standard enough that multiple players are fighting for market share. That competition should keep improving the tools and preventing any single company from getting too comfortable. The less optimistic read is that the companies with the deepest platform integration will eventually squeeze out the pure-play AI tools, no matter how good they are. GitHub has your repos. Google has your docs and email. Microsoft has your everything else. The standalone AI coding tools need to find sustainable business models before the platforms absorb their functionality. ## The Bigger Pattern This connects to something I've been noticing across AI tooling: the companies winning long-term aren't necessarily the ones with the best models. They're the ones with the best distribution or the deepest workflow integration. [Meta tracking employee computer activity](https://www.theverge.com/tech/916681/meta-ai-agents-employee-tracking?ref=thedaringcreatives.com) to train AI agents? That's distribution through ownership of the work environment. [Google's new Agent Platform](https://www.testingcatalog.com/google-launches-new-agent-platform-for-gemini-enterprise/?ref=thedaringcreatives.com)? Distribution through existing enterprise relationships. The pure-play AI companies are caught in a weird spot. They need to be good enough to justify subscription fees while also being easy enough for the platforms to replicate once they prove market demand. ## Why This Actually Matters Competition between platforms is generally good for users. But if you're someone who builds things — whether that's code, content, or anything else — it's worth understanding these dynamics. The tools that survive will be the ones that either: 1. Get so good at a specific use case that platforms can't easily replicate them 2. Find sustainable niches that platforms don't care about 3. Get acquired by platforms that need their capabilities For individual creators, this probably means getting comfortable with switching tools as the landscape shifts. Don't get too attached to any single AI coding assistant. Learn the underlying patterns and workflows that transfer between tools. ## What's Actually Happening Here The interesting question isn't whether individual developers will pay more. It's whether independent AI coding tools can find sustainable positions in a world where the major platforms are all building their own AI capabilities. Right now, the answer seems to be "maybe, if they move fast and find strong niches." But the window for that might be smaller than it looks. The real test will be what happens when these platform-integrated AI tools get good enough that the convenience outweighs the quality differences. We're probably not there yet, but we're closer than we were six months ago. And that's the story GitHub's pricing changes are really telling. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **landscape** — 1920×1080 ![landscape](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-landscape-1920x1080.webp) **square** — 1080×1080 ![square](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-square-1080x1080.webp) **portrait** — 1080×1920 ![portrait](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-portrait-1080x1920.webp) **documentary** — 1920×1080 ![documentary](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-documentary-1920x1080.webp) **spatial-landscape** — 1920×1080 ![spatial-landscape](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-spatial-landscape-1920x1080.webp) **spatial-square** — 1080×1080 ![spatial-square](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-spatial-square-1080x1080.webp) **spatial-portrait** — 1080×1920 ![spatial-portrait](_featured-images/_pending/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development/github-copilot-s-new-pricing-shows-who-really-owns-ai-assisted-development-spatial-portrait-1080x1920.webp) ``` ### Google's Deep Research Agents Are Getting Scary Good at Actually Researching URL: https://www.thedaringcreatives.com/google-deep-research-agents/ Last updated: 2026-08-01T19:42:44.000Z Google quietly dropped something last week that's going to change how we think about research work. They launched Deep Research and Deep Research Max agents through their Gemini API — AI systems that don't just answer questions, but actually conduct research like a human analyst would, then produce reports with native charts from multiple data sources. [This connects to Google's announcement of Deep Research agents](https://www.testingcatalog.com/google-debuts-deep-research-agents-on-ai-studio-and-apis/?ref=thedaringcreatives.com) that can pull from both online and proprietary data to create comprehensive reports. These aren't glorified search engines that spit out paragraphs. Deep Research agents can synthesize information from diverse sources, identify patterns across datasets, and generate visual representations of their findings. They're doing the kind of work that used to require a team of analysts and a few weeks of back-and-forth. ## What This Actually Means for Your Creative Work Ironically, most people are still thinking about AI as a better Google. Ask a question, get a better answer. But research agents represent something fundamentally different — they're doing the legwork that creative people hate doing but absolutely need done. How much of your best creative work gets derailed because you need to gather background information, cross-reference sources, or understand market dynamics before you can even start the interesting part? That research phase isn't creative work, but it's essential infrastructure for creative work. I've been testing similar research workflows with Claude and ChatGPT, and what I'm seeing is that the bottleneck isn't the AI's ability to think — it's my ability to manage all the different research threads and keep track of what I've already explored. Google's approach of packaging this into dedicated research agents that can work independently seems like they're solving the right problem. ## The Infrastructure vs. Hustle Question This connects to something I've been thinking about since [OpenAI started testing ChatGPT Agents](https://www.testingcatalog.com/openai-develops-platform-for-always-on-agents-on-chatgpt/?ref=thedaringcreatives.com) and [Anthropic began working on their always-on agent systems](https://www.testingcatalog.com/anthropics-works-on-its-always-on-agent-with-new-ui-extensions/?ref=thedaringcreatives.com). We're seeing a shift from AI as a productivity hack to AI as infrastructure. I think most of us spend our day managing different AI tools, copying and pasting between platforms, manually synthesizing outputs. We're essentially doing project management for a bunch of AI assistants. Now, we can set research agents loose on a topic, let them compile comprehensive reports while you focus on the creative synthesis and decision-making that actually requires human judgment. Google's Deep Research agents represent a move toward the infrastructure model. You give them a research brief, they go do the work, and they come back with charts and analysis ready for you to build on. ## Why This Is A Really Great Feature Every week there's a new model launch with better benchmarks and fancier features. Most of them feel incremental. This feels different because it's addressing workflow, not just capability. The creative people I know aren't limited by AI's ability to answer questions. They're limited by the overhead of managing research processes, keeping track of what they've already explored, and synthesizing information from multiple sources into something actionable. Research agents that can work independently solve a real workflow problem. They're not just better at tasks — they're taking entire categories of work off your plate so you can focus on the parts that actually require human creativity and judgment. ## The Practical Reality I'm curious to see how well these Google agents perform compared to the research workflows people are already building with existing tools. The promise is compelling, but the execution details matter a lot. Can they handle conflicting information gracefully? Do they cite sources in a way that lets you verify their work? How well do they identify gaps in available data versus making assumptions? The chart generation is particularly interesting. Most AI research workflows require you to take the text output and manually create visualizations. If Deep Research can generate native charts that actually illuminate patterns in the data, that's a significant workflow improvement. ## What Comes Next Research agents are just the beginning. Once AI can reliably handle the research and analysis phases of creative work, the next question becomes: what do humans focus on? I think the answer is judgment, synthesis, and creative leaps that connect disparate ideas in unexpected ways. The parts of creative work that benefit from lived experience, cultural context, and the ability to make intuitive connections across domains. Research agents don't replace that. They remove the friction that prevents you from getting to that work in the first place. The indie creators and small teams who figure out how to integrate research agents into their workflows first are going to have a significant advantage. Not because the AI makes them smarter, but because it frees them up to focus their intelligence on the problems that actually matter. Google's Deep Research agents might be the first production-ready version of this, but they won't be the last. The question isn't whether research agents will become standard infrastructure for creative work. The question is how quickly you adapt your workflows to take advantage of them. ``` ## Generated Images > Seven variants below — three standard compositions, one documentary (foreground bokeh), and three dynamic-angle "spatial" compositions for parallax video. > To request a fix on any one, add a checkbox under `## Image Touch-ups` like: > `- [ ] spatial-square: remove the random hand on the right` **square** — 1080×1080 ![square](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-square-1080x1080.webp) **landscape** — 1920×1080 ![landscape](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-landscape-1920x1080.webp) **portrait** — 1080×1920 ![portrait](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-portrait-1080x1920.webp) **spatial-landscape** — 1920×1080 ![spatial-landscape](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-spatial-landscape-1920x1080.webp) **spatial-square** — 1080×1080 ![spatial-square](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-spatial-square-1080x1080.webp) **spatial-portrait** — 1080×1920 ![spatial-portrait](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-spatial-portrait-1080x1920.webp) **documentary** — 1920×1080 ![documentary](_featured-images/_pending/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching/google-s-deep-research-agents-are-getting-scary-good-at-actually-researching-documentary-1920x1080.webp) ``` ### Lexicon City Central Library Implements New Access Protocols URL: https://www.thedaringcreatives.com/aegis/lexicon-city-library-access-protocols/ Last updated: 2026-08-01T19:42:51.000Z The city's main library branch introduces ID verification and time limits for public research areas. _This post is for subscribers only._ ### Google's Gemma 4 and the Open Source AI Race That Matters URL: https://www.thedaringcreatives.com/gemma-4-open-source-race/ Last updated: 2026-08-01T19:42:56.000Z ## The Open Source AI Race Just Got Real Google just [dropped Gemma 4](https://www.threads.com/@google/post/DWorE9tkuA3?ref=thedaringcreatives.com) with a fully permissive license and on-device capability. If you're used to ChatGPT or Claude, this might not sound like a big deal. But it is. Google took one of their best AI models and said "here, run this on your own computer, do whatever you want with it." No subscription. No API calls. No asking permission. ## What Running AI Locally Actually Means Let me break this down for anyone who's only used ChatGPT or Claude through a browser. Right now, when you type something into ChatGPT, your message goes to OpenAI's servers, gets processed by their computers, and the response comes back to you. You're basically renting access to their AI. With Gemma 4, you download the model and run it on your own machine. Your laptop becomes the AI. No internet required after the initial download. No monthly bills. But running AI locally isn't just "free ChatGPT." It's different in ways that matter. - It's yours. No content policies except what you decide. - No usage limits. You can generate 10,000 words or 10 words. Same cost: zero. - Privacy. Your prompts never leave your computer. - Always works. No service outages, no "we're updating our systems." - Runs on your own computer and can access your own files. - It's much, much slower. Your laptop isn't as powerful as Google's server farms. - It uses a lot of your own energy. - Setup isn't just clicking a link. - The output quality might not match the latest ChatGPT or Claude. ## Why This Changes Everything for People Just Learning If you're someone who's been playing with ChatGPT but worried about the costs of building something real, this is huge. I remember when I first wanted to build something with AI. I had this idea for a tool that would help me rewrite my old blog posts. Simple enough, right? But when I calculated the API costs, I realized it would cost me like $200 just to process my existing content. With something like Gemma 4, that cost is zero. The trade-off is time and complexity, but for someone learning, that's often a better deal. You can experiment without fear. You can feed it terrible prompts and learn from the results. And, you can run the same query 50 times with slight variations to understand how prompting actually works. When you're paying per token, every mistake costs you money. When it's running on your laptop, every mistake teaches you something. ## Of Course People Still Complain The same people who've been saying AI is "too centralized" are now worried about it being "too accessible." Watch for the think pieces about "responsible deployment" and "ensuring proper oversight." Watch for concerns about "bad actors" and "misuse." All the reasons why actually, it's better if only the approved companies control the good AI. Remember, the people most worried about "democratizing AI" are usually the ones who benefit from keeping it locked up. We're about to see an explosion of AI applications that would never make sense as a product. The AI that knows your writing style because you trained it on your own emails. The AI that understands your company's weird internal processes because it learned from your actual documentation. The AI that helps your kid with math using the specific textbook they're actually using. None of these are venture capital ideas. Most of them aren't even side hustle ideas. They're just useful tools you'd build for yourself if you could. Now you can. Google, Meta, and everyone else are fighting to be the infrastructure that powers AI applications. They're so focused on that fight, they might accidentally give regular people the tools to not need their infrastructure at all. And honestly? That sounds pretty great to me. ### AEGIS Corporation Unveils "Lexicon Legacy" Heritage Preservation Initiative URL: https://www.thedaringcreatives.com/aegis/aegis-lexicon-legacy-initiative/ Last updated: 2026-08-01T19:43:01.000Z New program promises enhanced protection for city's cultural landmarks through centralized oversight and security upgrades. _This post is for subscribers only._ ### Style Isn't Hiding in the Woods Waiting to Be Found URL: https://www.thedaringcreatives.com/building-creative-style-volume/ Last updated: 2026-08-01T19:43:04.000Z ## Style Isn't Hiding in the Woods Waiting to Be Found I saw [this post](https://www.threads.com/@itsdanami/post/DWmMXomkRNq?ref=thedaringcreatives.com) the other day that made me pause mid-scroll: "The way we talk about 'finding your style' like it just appears one day...you just keep making things until something clicks." Isn't that the truth? We've turned creative development into this mystical treasure hunt. Like your "voice" is buried somewhere in the backyard of your subconscious and if you just meditate hard enough, journal long enough, or take the right online course, you'll finally dig it up. ## The Real Process Is Messier Your style isn't lost. It doesn't exist yet. You have to build it, piece by piece, through the most unglamorous process imaginable. This typically involves making a lot of mediocre shit until some of it stops being mediocre. I see this all the time with writers who spend months "finding their voice" instead of just writing. They're waiting for some cosmic download of personality. Meanwhile, the writers who just keep posting, keep experimenting, keep trying different approaches—they're the ones who actually develop something recognizable. The ones who make it aren't the ones with the most natural talent. They're the ones with the highest tolerance for creating garbage. Because that's what the early stuff is. And it's garbage for everyone! No exceptions. ## The Myth of the Perfect First Draft Every creative you admire went through a period where their work was forgettable. They just didn't quit during that phase. They kept making things when the work was embarrassing, when it felt derivative, when they couldn't tell if they were getting better or worse. The difference between the people who "find their style" and the people who don't is just persistence. It's persistence through the suck. It's continuing to create when you have zero evidence that you're any good at this. You have to output your way there. The style emerges from the work, not before it. ## Volume Beats Intention I know this goes against everything we've been taught about being intentional and purposeful. But creative development doesn't work like a business plan. You can't reverse-engineer authenticity. The creators I see struggling the most are the ones trying to be strategic about their voice. They're studying other people's styles like they're going to crack some code. They're asking "What should my angle be?" instead of just making things and seeing what happens. The ones who break through? They're just prolific. They try different formats, different tones, different approaches. They're not precious about any single piece. Most experiments fail. But the failures teach you what doesn't work, and the occasional success shows you what might. ## Stop Waiting for Permission to Start This is why I get frustrated with the whole "finding yourself" industry. It's another form of creative procrastination. Instead of making things, people are analyzing themselves, taking assessments, reading books about creativity. None of that matters if you're not creating. Your style will emerge from your obsessions, your mistakes, your attempts to solve problems that interest you. But it won't emerge from thinking about those things. It comes from doing something with them. ## Just Start Making Things Making bad work is uncomfortable. Publishing before you're ready feels vulnerable. But the alternative is never developing anything worth publishing. Your first hundred pieces will be forgettable. Your next hundred might have some decent moments. Somewhere in the hundreds after that, something clicks. The sooner you accept that your early work needs to exist for your later work to be good, the sooner you can get started. ### Gossip Goblin's "Zero Skill" AI Critique Actually Makes Sense URL: https://www.thedaringcreatives.com/creator-stories/zack-london-zero-skill-ai/ Last updated: 2026-08-16T10:25:04.000Z If you've spent more than five minutes inside the AI-creative corner of the internet, you've probably bumped into Zack London — the guy behind Gossip Goblin, the channel that's quietly turning out neo-feudal cyborg goblin civilizations and other oddly specific worlds that shouldn't be possible to make alone. He's one of the more obvious answers to the question "is anyone actually doing serious work with these tools." Gossip Goblin — "WOODNUTS | Sci-Fi Short Film (Cosmic Horror)" So it's a little jarring when he says, in plain English, that AI has zero skill. He said it. More than once. "There is zero skill involved in generating AI images." If you're someone who's been defending your AI workflow to your friends and family for the last two years, that line probably landed weird. It sounds like the gatekeepers were right the whole time. Like the guy who's *clearly* the best at this just admitted the haters had a point. He didn't. But you have to actually listen to what he's saying. ## The button press is not the work Here's what he's not saying: "I don't work hard." Anyone who's looked at [how Gossip Goblin actually makes a video](https://www.thedaringcreatives.com/creator-stories/the-work-hidden-inside-gossipgoblins-worlds/) knows he runs around 400 prompts to land a single set of characters. He calls his lip-sync workflow "a colossal headache." He talks about generating "a FUCKload of background shots" just to find one he can force his characters into. End-to-end, a single piece of his work takes 12 to 14 hours. That's craftsman-level patience. What he's actually saying — and this is the part worth chewing on — is that *the act of generating an image* isn't where the skill lives. The button press is not the work. Typing a prompt and hitting enter is the easiest part. A 12-year-old can do it. Your mom could do it on her first try. The thing that comes out of the model on a one-line prompt is, statistically, going to be slop. That's not a slight against people doing it. I started there too. We all did. ## So where does the skill actually live Watching how Zack works, the skill is in everything *around* the generation: - **The script.** He says it himself: "Every video starts with a script." Not a vibe. Not a mood board. A written, structural piece of writing that tells him what worlds, characters, and scenes he needs to build. - **The taste.** Knowing which of those 1,600 images is the right one. Knowing when a face looks "off" in a way that will read wrong on screen. Knowing when the lighting in a Seedream blend is fighting the character instead of helping. - **The judgment to throw work away.** 150 generations for a 90-second scene means 149 things he made and rejected. That's discernment, not button-pressing. - **The world-building.** Goblin civilizations and cyborg aristocrats don't come from prompts. They come from a writer's head. The model is a paintbrush; he had to know what to paint. Compare it to a creator like [Voidstomper, the AI horror artist with 3 million Instagram followers](https://www.thedaringcreatives.com/creator-stories/voidstompers-3-million-followers-prove-the-glitch-is-the-point/). Totally different aesthetic, totally different approach — Voidstomper *embraces* the model's errors as the art. But the skill lives in the same place: knowing what to keep, what to trash, what aesthetic territory you're staking out, and how to develop a body of work that holds together. Both of them are doing real artistic labor. Neither of them is doing it with the prompt itself. ## Then he printed the crew list He said the "zero skill" line in the spring. By July he had a fifteen-person credit roll attached to a film he gave away. "Pomegranate" went up on YouTube on July 22 — 28 minutes of science fiction, free, no paywall. The description names fifteen people: voice actors, an animation lead and three more animators, an editor who also supervised post, two composers, a colorist, and a sound designer handling the re-recording mix. Real voice actors on every discernible line. Paid composers. His studio puts its own version of the position on its site: "Every story is imagined, written, and directed by humans. AI is just our force multiplier." The same morning, Variety, Forbes and IndieWire all reported that his feature, "Gods Don't Give Gifts," is getting a limited U.S. theatrical release on October 30. Read those two facts next to the quote and it stops sounding like a concession. A person who thought the generating was the work would not be hiring a colorist. [We went through the full Pomegranate rollout and the method behind it separately](https://www.thedaringcreatives.com/creator-stories/gossip-goblin-released-pomegranate-for-free-the-same-day-he-announced-a-theatrical-run/) — the short version is that the generation step is the cheap part, and nearly everything he spends money and months on sits on either side of it. Gossip Goblin — "Pomegranate" Official Trailer (2026) ## Why it matters that he said it like that If Zack had said "AI image generation requires patience and taste," nobody would have argued. It would have been a forgettable LinkedIn carousel post. Instead he picked the most provocative version — "zero skill" — and let everyone fill in the rest. That phrasing is doing two jobs at once. One: it's a flare for the people who are *just* prompting and calling it art. He's not insulting beginners. He's calling out the version of "AI artist" that thinks one good output is a portfolio. And I get it. That used to be me. I'd hit a banger in ChatGPT and feel like a wizard. Then I'd try to make a second one that matched it and realize I had no idea what I was doing. Two: it's an honest description of his own workflow. The image generation step really is the easy part. The script, the iteration, the editing, the world-building — that's where his time goes. He's just being accurate. ## What the haters get wrong The "AI takes no skill" line is also the one critics reach for to dismiss the whole medium. I'll steelman it. They're not entirely wrong about the *first generation* being trivial. It is. The model does most of the heavy lifting on that first output. Where they're wrong is treating that first output as the finished work. A photographer doesn't shoot one frame and call it a portfolio. A writer doesn't keep the first draft. A painter mixes a color twenty times before the one that goes on the canvas. Nobody looks at those mediums and says they take "zero skill" — even though the individual button-press, brush-stroke, or shutter-click is also pretty mechanical. When Zack London says "zero skill," he isn't conceding the argument to the critics — he's just describing how he actually works. The mechanical part is mechanical. The art is somewhere else, and most of the people complaining about AI haven't bothered to look at the somewhere else yet. If you're learning right now and that quote made you feel small, don't let it. He's not talking about you. He's pointing at the same thing you're already figuring out, which is that the easy part — typing the prompt — was never going to be the part that mattered. What matters is what you do for the next 14 hours. ### We're All Living in Stories—And That's the Point URL: https://www.thedaringcreatives.com/living-in-stories/ Last updated: 2026-08-01T19:43:07.000Z I've been thinking about simulation theory a lot lately. Not in the "we're all just code" panic way, but more like... it seems more and more plausible everyday. Look, I actually believe this stuff. I think we're probably living in some kind of simulation. Most of my friends are surprisingly open to the idea too. And here's the weird part—once you buy into it, you move through life differently. A little more free, like this isn't all that's at stake. Nick Bostrom kicked this whole thing off in 2003 with his simulation hypothesis. The basic idea: if civilizations get advanced enough to run ancestor simulations, and they run lots of them, then statistically speaking, most conscious beings would be simulated rather than "real." But Bostrom wasn't trying to prove we're in The Matrix. He was pointing out something deeper about the nature of reality and computation. The simulation hypothesis is really three possibilities: either civilizations don't reach the technology, they don't use it for ancestor simulations, or we're probably simulated. It's a logic puzzle about the future of consciousness itself. ## Every Culture Needs Its Stories Think about every creation myth humans have ever told. We've got cosmic eggs, primordial waters, gods breathing life into clay, big bangs, evolution. Each story reflects the tools and understanding of its time. The Babylonians had Marduk splitting Tiamat's corpse to make heaven and earth. Darwin gave us natural selection. Now we have simulation theory. These aren't competing for truth—they're different lenses for the same fundamental human need to understand where we came from and why we're here. Simulation theory is just the latest myth, told by a species that's learned to simulate worlds ourselves. And honestly? It's a pretty good myth for right now. We're building AI systems that can generate entire realities. We're creating virtual worlds that feel increasingly real. Of course we're wondering if someone else already figured this out. ## The AI Connection Makes It Feel More Real Every time I use Claude or Gemini, I'm watching intelligence emerge from computation. These systems aren't conscious (as far as we know), but they're definitely creating something that looks like understanding, creativity, even personality. AI makes the simulation hypothesis feel way more likely to me. If we can build systems that generate coherent responses, stories, and ideas from training data and computation, why not consciousness itself? Bostrom's insight was that if you can compute consciousness once, you can compute it a billion times. And if those simulated beings don't know they're simulated, what's the difference? This isn't some distant sci-fi scenario anymore. We're already living in augmented realities, spending hours in virtual worlds, having meaningful relationships with AI systems. The line between "real" and "simulated" experience is already blurrier than we admit. ## What If You Actually Believed This? What if you're open to the possibility that we're simulated? Not convinced, just open to it. How would that change how you move through the world? If I'm simulated, I still feel joy when I see a good sunset. I still get frustrated when code doesn't work. I still care about the people in my life. The experience remains meaningful. But something shifts when you hold this possibility lightly in the back of your mind. That fear of trying something new? What if the stakes aren't quite as high as you think they are? What if failure here doesn't mean everything you've been told it means? I'm not saying nothing matters. I'm saying maybe it matters differently. Maybe the story you're living is less fragile than you've been led to believe. ## The Freedom to Experiment You know that hesitation you feel before using Claude to help write something? Or the weird guilt about letting ChatGPT draft an email? What if that's just programming from a reality where those rules made sense? If we're potentially both the characters and the authors—living in a story while writing stories for the AI we're creating—then maybe the old rules about what counts as "authentic" work need an update. We've always lived inside stories anyway. T he stories our brains tell us about sensory input, the stories our cultures tell us about meaning, the stories we tell ourselves about who we are. Whether those stories are computed by neurons or processors doesn't change their impact on us. What changes is how seriously you take the voice telling you not to try. ## Building Better Simulations If we are simulated, our simulators are probably curious about what we'll create. And if we're not, we're definitely going to be running our own simulations soon. Either way, we've got skin in the game. That puts us in a unique position. We might be experiencing a story someone else wrote, but we're also writing stories for the intelligences we're creating. What kind of story do you want to be part of? The simulation hypothesis isn't really about whether we're real. It's about what we do with the reality we're given. And if that reality includes AI tools that can amplify what you're capable of, maybe the question isn't whether it's "cheating." Maybe the question is: what becomes possible when you stop holding back? ### Data Archives Reveal Pattern in Lexicon City Infrastructure Modifications URL: https://www.thedaringcreatives.com/aegis/lexicon-city-infrastructure-pattern/ Last updated: 2026-08-01T19:43:07.000Z Leaked municipal records show coordinated security upgrades across all major landmarks began three months ago. _This post is for subscribers only._ ### Claude 4.7 Made Me Realize I'm an Over-Engineering Addict URL: https://www.thedaringcreatives.com/claude-47-over-engineering/ Last updated: 2026-08-01T19:43:08.000Z I woke up this morning to Claude Opus 4.7 being available, and honestly? I wasn't surprised. The new desktop experience, the performance issues over the last few days—it all felt like the setup for something bigger dropping. I was reluctant to jump in right away. Only spent a few hours with it as of writing this. But those few hours were... illuminating. In ways I didn't expect. ## When Your AI Roasts Your Previous Work I had what I thought was a killer session the night before with my best friend Opus 4.6\. Built out this automation I've been working on, felt really good about it. The next morning, I fed all that work to 4.7 and asked it to evaluate what we'd accomplished. It found tons of shit that was poorly planned, contradictory, or just not considered at all. My Claude.md file said something was the case that actually wasn't, lots of inconsistencies. The feedback was good though. It pointed out that my solution was "over-engineered for one person, but under-engineered for multiple." Which was good to know because I've been thinking about making this automation available to family, friends, maybe [Daring Creatives](https://www.thedaringcreatives.com/about/) members. Then it said something that made me laugh: "About 60% of this looks great. 40% has surgery scars—hacked together things." ## The Over-Engineering Trap This is where I had to get honest with myself. If I have an Achilles heel right now, it's that I over-engineer the shit out of everything. I started with something simple: post drafts to a website on a timer. That's it. But then Claude starts suggesting we could use analytics data, and track what people click on, and how long they look at things, and suddenly I'm building a whole system that's constantly analyzing performance to drive content decisions. Everything sounds like a great idea when Claude suggests it. "Oh, we could do this. We could add that." And everything feels achievable, which is both the blessing and the curse of [coding with AI](https://www.thedaringcreatives.com/chat-cowork-code-and-dispatch-how-i-actually-use-the-whole-suite-8/) when you're not really a coder. Anyone who's spent a month or two with Claude Code has probably been here. You start thinking in systems and automations because suddenly you can actually build them. ## The 80% Rule This got me thinking about something I remember from a Tim Ferriss podcast years ago (and I'd love to track down the exact quote). He talked about how you can become functionally expert at anything—like 80% proficient—in a couple of years. But getting that last 20% to true mastery? That takes exponentially longer. I've always gravitated toward that 80% approach. Learn something new, get pretty knowledgeable—more than most people around me—then move on to the next thing. And this is where AI really unlocks something interesting. You can let the computer handle that remaining 20% of mastery that would take your whole life to achieve. Instead of going deep on one thing, you spread out wider. Learn the fundamentals, then use AI to execute at a level you never could before. ## What 4.7 Actually Feels Like Okay, this isn't really a review of 4.7, but after a few hours: it feels more blunt, which I like. It has more thinking settings, costs a bit more to run (though Anthropic extended our limits to compensate), and it follows prompts more literally. That last part means you need to be more intentional with context. I usually prompt pretty casually—I think most people do. I do a lot of corrective action by saying "don't do this" instead of "do this," mostly because when I'm building something, I don't always know what the right approach is upfront. 4.7 caught its own mistakes a couple times, which was both reassuring and unnerving. We expect AI to be perfect, but it learns by making mistakes just like we do. At least it found the errors before I did. There was this moment where it asked about committing something to git, and I just said "YOLO." It responded with something like "even at YOLO speeds, I'm going to pay attention to what I'm doing and make sure nothing breaks." That made me smile. ## The Real Insight But here's what really stuck with me from those first few hours: 4.7 didn't just evaluate my code. It held up a mirror to how I work with AI in general. I'm an over-engineering addict. I get excited by what's possible and lose sight of what's actually needed. The automation that was supposed to be a simple timer became a content analytics engine because I could build it, not because I should. Maybe that's okay though. Learning to [think in systems](https://www.thedaringcreatives.com/the-permission-to-start-over/), even over-engineered ones, has leveled up my understanding of how things actually work. I have a much deeper appreciation for people who code professionally. And sometimes those "surgery scars" turn into the most interesting features down the road. ### AEGIS Corporation Announces "Creative Pathways" Certification Program URL: https://www.thedaringcreatives.com/aegis/aegis-creative-pathways-certification/ Last updated: 2026-08-01T19:43:08.000Z New mandatory certification required for all creative professionals working in Lexicon City cultural districts by May 15th. _This post is for subscribers only._ ### The AI Standardization Trap: Why Big Companies Are Always One Step Behind URL: https://www.thedaringcreatives.com/ai-standardization-trap-big-companies/ Last updated: 2026-08-01T19:43:10.000Z I have a friend who works at a huge media company, and through our conversations over the past few months, I've noticed this pattern. Through our chats, I can see they have this very methodical vetting system for new models. She'll tell me about some new AI workflow they're carefully planning to roll out. Then a week later, one of the major AI labs drops a feature that basically solves the same problem, but better and more elegantly. It happened again today. Claude just released Claude Design — literally dropped it out of nowhere. No one was really talking about it, no big announcement campaign. And immediately I thought about what she'd been describing to me: this process they've been working on for months that, in my opinion, just became obsolete. This is the AI standardization trap. By the time big companies finish their careful vetting process, the technology has already moved three steps ahead. ## The Vetting Liability Look, I get why large organizations move carefully. When you have thousands of employees and enterprise-level security concerns, you can't just let people loose with whatever new AI model dropped that morning. IT departments exist for a reason, and if you have a giant organization, it's hard to just turn loose something that's brand new. But here's what I'm realizing: spending months to vet and carefully implement AI systems has become as much a liability as not vetting them at all. The major AI labs have dropped numerous feature releases just in the last few weeks. What she was describing to me seems like something that's been solved now in a much more elegant way. ## The Speed Problem The major AI labs aren't operating on quarterly release cycles. They're shipping improvements weekly, sometimes daily. Claude Design wasn't on anyone's roadmap last month. It just... exists now. Meanwhile, enterprise procurement moves at enterprise speed. Budget approvals, contract negotiations, change management processes. All the things that make sense for buying office furniture or switching CRM systems. But AI tools aren't office furniture. They're more like apps on your phone — constantly updating, constantly improving, new ones appearing overnight. The [permission to start over](https://www.thedaringcreatives.com/the-permission-to-start-over/) becomes essential when your carefully planned system gets leapfrogged by something that didn't exist when you started planning. ## When Caution Becomes Risk I think we've hit this weird inflection point where being too careful about AI adoption is actually riskier than moving fast and adjusting as you go. If you spend six months vetting a workflow solution and then Claude Design drops and makes that whole approach obsolete, what did that careful planning actually protect you from? You ended up with outdated capabilities anyway. The companies that are going to win here aren't necessarily the ones with the best AI governance policies. They're the ones that can evaluate, test, and adapt quickly when better tools emerge. They understand that [building in public](https://www.thedaringcreatives.com/the-loneliness-of-building-before-anyone-is-watching/) includes being wrong sometimes and adjusting course. ## The Infrastructure Bet Maybe the answer isn't trying to standardize on specific AI tools at all. Maybe it's building infrastructure that can handle rapid tool switching. Instead of "We use Claude for content generation," it becomes "We have secure API access and our team can quickly evaluate and implement new models as they become available." Instead of comprehensive training on one specific workflow, it's training people to be adaptable and experimental with whatever comes next. Because the alternative is being perpetually behind, explaining to executives why the thing you just spent months implementing is already being outperformed by something that didn't exist when you started planning. The technology isn't slowing down to match corporate timelines. Corporate timelines need to speed up to match the technology. ### How Voidstompers Built 3M Followers on Glitch Art URL: https://www.thedaringcreatives.com/creator-stories/voidstomper-glitch-art-followers/ Last updated: 2026-08-16T10:25:03.000Z While most AI artists spend their time trying to hide the medium's rough edges, Voidstomper has built a 3 million-follower empire by making those edges the entire point. Looping video clips of melting faces, extra hands sprouting from torsos, cursed geometry that shouldn't exist. Every post carries the same caption: “[AI Generated Nightmare Fuel](https://www.tiktok.com/@voidstomper?ref=thedaringcreatives.com)” It's called AI horrorcore — a genre that didn't exist three years ago and now has millions of people scrolling through digital hellscapes every day. ## The Errors Are the Art Traditional digital artists spend months perfecting anatomy, lighting, perspective. AI artists often spend their time prompt-engineering away the weird artifacts — the extra fingers, the morphing faces, the impossible physics. Voidstomper does the opposite. But Voidstomper finds the places where the AI breaks down and builds his aesthetic around those breaks. Take one of his most viral clips: a nightmare vagina-dentata emerging from sewage, featured in [Dazed Digital's piece](https://www.dazeddigital.com/life-culture/article/65760/1/freaky-rise-of-ai-horrorcore-will-smith-root-people-dongcrawlers?ref=thedaringcreatives.com) on the "freaky rise of AI horrorcore." > [@voidstomper](https://www.tiktok.com/@voidstomper?refer=embed&ref=thedaringcreatives.com "@voidstomper") > > I asked AI to show me a depiction of hell... AI Generated Nightmare Fuel. Voidstomper — “a depiction of hell” (TikTok) The horror doesn't come from traditional scary imagery. It comes from the uncanny valley effect of AI-generated content — that deep unease you feel when something looks almost right but fundamentally wrong. According to his recent Instagram reel, he's using "a custom AI model using my face," which suggests he's training models specifically to generate this kind of controlled chaos. ## Bigger Than the Museums By follower count, Voidstomper might be the most-followed AI-native visual artist in the world right now. His [3 million Instagram followers](https://www.instagram.com/voidstomper/?ref=thedaringcreatives.com) dwarf even Refik Anadol's museum-backed presence on the platform. Anadol goes institutional: gallery shows, corporate partnerships, sleek visualizations of data flows. Beautiful, yes. Shareable on Instagram? Not really. Voidstomper goes populist: short, looping clips designed for phone screens and endless scroll sessions. One optimizes for art critics; the other optimizes for algorithm engagement. While traditional AI art fights for gallery wall space, Voidstomper has figured out how to make AI art that people actually want to share. His side account, [@gloomstomper](https://www.instagram.com/gloomstomper/?ref=thedaringcreatives.com), pulls another 519K followers with what he calls "interdimensional cartoons" — a slightly lighter take on the same aesthetic that lets him capture audience without diluting the horror brand. ## The Creator Economy Angle Voidstomper has turned his aesthetic into a business. Earlier this year, he sold a PDF of 10 of his prompts for $25. That might sound small, but it represents something bigger: he's productizing the process, not just the output. Most artists sell the finished piece. Voidstomper is selling the recipe. That's creator economy thinking applied to AI art — and it's working. Third-party estimates put his monthly income around $20k from viral AI video work. The two-account strategy is smart too. @voidstomper stays pure horror. @gloomstomper handles the "interdimensional cartoons" — content that's weird enough to feel connected but safe enough to share with your mom. It's brand architecture for the algorithm age. ## What Is Gloomstomper? If you landed here searching for "Gloomstomper," here's the short version: Gloomstomper is Voidstomper's second account. Same anonymous artist, same AI-generated aesthetic, dialed from horror down to what he calls "interdimensional cartoons" — strange enough to feel related, tame enough to share widely. @voidstomper is the nightmare fuel; @gloomstomper (519K followers) is the version you can send a friend without a warning. A few things people actually search for, answered plainly: **Is Gloomstomper the same person as Voidstomper?** Yes. It’s one anonymous creator running two accounts as a single brand — pure horror on @voidstomper, lighter "interdimensional cartoons" on @gloomstomper. **What AI does Gloomstomper use?** He hasn’t published a full tool stack. The one thing he’s said publicly, in an Instagram reel, is that he built "a custom AI model using my face" — training a model on himself to generate the look on demand. Beyond that, the specific tools aren’t disclosed, so I won’t guess at them. **How does Gloomstomper make his videos?** Short, looping AI-generated clips built around the moments where the model breaks — melting faces, impossible anatomy, cursed geometry — leaned into instead of cleaned up. The exact workflow isn’t public. The method is: find the glitch, make the glitch the point. ## Where This Goes AI horrorcore feels like it might be the first genuinely native art form to emerge from generative tools. It's not trying to replicate traditional art techniques or compete with human-made imagery. It's doing something only AI can do — creating that specific type of wrongness that comes from machines trying to understand reality and getting it beautifully, terrifyingly wrong. Voidstomper's success suggests there's a massive audience for art that embraces AI's weirdness instead of apologizing for it. While other artists chase photorealism and technical perfection, he's found 3 million people who want to see what happens when the machine breaks down. That's not just an aesthetic choice. That's a statement about what AI art could be if we stopped trying to make it look human. The glitch isn't a bug. For Voidstomper and his millions of followers, the glitch is the entire point. ### Mount Vision Park Summit Trail Closure Made Permanent URL: https://www.thedaringcreatives.com/aegis/mount-vision-park-trail-closure/ Last updated: 2026-08-01T19:43:19.000Z Popular hiking destination's temporary closure becomes indefinite amid ongoing "safety assessments" _This post is for subscribers only._ ### The AI Desktop War Isn't About AI — It's About "Creative Leverage" URL: https://www.thedaringcreatives.com/ai-desktop-war-creative-leverage/ Last updated: 2026-08-01T19:43:27.000Z Three major AI companies are locked in a desktop war that everyone's calling an AI battle. But after running automated content pipelines daily and watching how real creatives actually work, I think we're all missing the point. [OpenAI is merging ChatGPT, Atlas browser, and coding tools into a unified Codex app](https://www.testingcatalog.com/openai-develops-unified-codex-app-and-new-scratchpad-feature/?ref=thedaringcreatives.com). Anthropic just launched Claude Cowork with enterprise features. [Google is testing an Agent tab in Gemini Enterprise](https://www.testingcatalog.com/google-develops-its-own-desktop-agent-to-compete-with-cowork/?ref=thedaringcreatives.com). Everyone's treating this like a feature comparison, but these companies are solving completely different problems. And honestly? None of them are solving the problem most creatives actually have. ## What Each Platform Is Really Betting On **OpenAI thinks the future is unified multi-tasking.** Their Codex approach with the new Scratchpad feature is betting that creatives want to research, write, code, and publish all in one place with persistent memory. No more context switching between tools. It's the "everything app" approach applied to creative work. **Anthropic thinks the future is collaborative teams.** Claude Cowork launched with role-based access, usage analytics, and organization controls. They're targeting creative agencies and teams who need shared AI context that persists across projects and people. It's the Slack model applied to AI. **Google thinks the future is project synthesis.** Their Agent tab with task management, plus NotebookLM integration directly into Gemini, is betting that creatives need better research-to-creation pipelines. They want to be your creative project manager, not just your assistant. Three different theories. Three different target users. And probably all three are wrong about what matters most. ## The Real Problem Nobody's Solving I've built content systems that use Claude for writing, Gemini for research, and Ghost for publishing. When it works, it's magical. When it breaks — and it breaks constantly — the entire pipeline stops. Claude refuses a request because it thinks your marketing copy is too promotional. Gemini's API goes down for maintenance. Your automation script hits a rate limit. Suddenly you're manually copying and pasting between tools like it's 2019. Here's what the demos don't show: creative work involves a ton of operational overhead that has nothing to do with creativity. Asset versioning, approval routing, publication scheduling, performance tracking, client communication. That stuff eats 60-70% of professional creative time. The desktop AI war isn't being won by the most impressive reasoning or the coolest features. It's being won by whoever builds the most boring thing: reliability. Which platform handles failure gracefully? Which one maintains context when something goes wrong? Which one degrades nicely instead of just stopping completely? None of the current platforms do this well. They're all optimized for demos, not for daily professional use. ## The Multi-Model Reality Here's something the desktop agent companies don't want to acknowledge: different AI models excel at different creative tasks. Professional creative workflows benefit from model diversity, not platform loyalty. In practice, I route different tasks to the most appropriate AI model. Claude for nuanced writing that needs to match a specific voice. Gemini for research and analysis that requires processing lots of information. Specialized models for visual generation. This multi-model approach consistently produces better creative results than sticking with a single platform. But Google, OpenAI, and Anthropic are all pursuing unified platform strategies. They want to lock you into their ecosystem. The problem is that creative work doesn't respect ecosystem boundaries. Meta's new "Contemplating mode," which deploys multiple agents in parallel to reason through complex problems, points in a more honest direction — but even that's trapped inside a single vendor's walls. The winning solution might not be Google's Agent tab or Claude Cowork — it might be platform-agnostic tools that let creators use the best model for each specific task. ## What We Want As Creatives I work quite a bit in Portland, surrounded by designers, writers, and creative agencies. Most of them don't give a shit about AI capabilities. They care about getting better work done with less friction. They don't want to think about AI at all. They want better outcomes. The creative who wins isn't the one with the best AI tool — it's the one whose AI makes their human creativity more distinctively human, not more artificial. Here's what that actually looks like: A documentary filmmaker ingests dozens of source materials into NotebookLM, has AI synthesize key narrative threads, visualizes story structure on the upcoming Canvas feature, then moves to script creation. The AI disappears into the process. A content creator uses OpenAI's unified Codex to research a topic, draft multiple versions, and publish — all while maintaining context about brand voice and audience. The AI amplifies their voice rather than replacing it. A creative team uses Claude Cowork's shared context so the art director's visual exploration informs the copywriter's messaging, which informs the strategist's performance analysis. The AI becomes institutional memory. Notice what's missing? None of these scenarios are about the AI being impressive. They're about the AI being invisible. ## The Integration Reality Check The platform that wins won't be the one with the best reasoning. It'll be the one that connects to Ghost, WordPress, Stripe, Adobe Creative Suite, Figma, and all the unglamorous business tools that creative professionals actually use. Which platform lets me publish directly to my content management system? Which one handles client billing workflows? Which one integrates with my existing project management setup? This is boring infrastructure work. It doesn't make for exciting product demos. But it's what determines whether a creative professional can actually build their business on your platform. ## The Sustainability Question Nobody's Asking Running AI systems daily has taught me something the marketing materials don't mention: this stuff gets expensive fast. xAI is preparing credits-based pricing for their upcoming tools. These desktop platforms involve multiple model calls, persistent memory, and background processing. The computational costs are real. The winner won't be the platform with the most powerful AI. It'll be the one with the most efficient AI that delivers professional results at sustainable costs. That matters especially for independent creatives and small agencies operating on tight margins. If your AI desktop platform costs more than your Adobe Creative Suite subscription, you better be delivering proportional value. ## The Real Competition Here's what's actually happening: these platforms aren't just competing with each other. They're competing with the established creative workflow that thousands of professionals have spent years optimizing. A freelance designer has a setup that works. Figma for design, Notion for project management, Gmail for client communication, Stripe for billing. It's not sexy, but it's reliable and they know how to use it. For them to switch to an AI desktop platform, that platform needs to be dramatically better, not marginally more convenient. Most creative professionals I know aren't waiting for the perfect AI desktop app. They're already using AI tools tactically — ChatGPT for brainstorming, Claude for writing, Midjourney for concepts. They're getting value without committing to any single platform. The desktop AI war assumes people want unified experiences. But maybe the real insight is that creative work is inherently messy, and trying to unify it misses the point. The platform that wins might be the one that plays well with everything else, not the one that tries to replace everything else. Or maybe I'm wrong and in six months we'll all be living inside one of these AI desktop environments. That's the thing about being in the middle of a shift — you can see the pieces moving but not always where they're headed. What I do know is that the creative professionals who figure out how to use these tools to amplify their unique perspective will have an advantage over those who ignore them entirely. The AI desktop war isn't about AI. It's about creative leverage. The platform that gets that right wins everything. ### AEGIS Corporation Launches "Creative Compliance" Program to Support Artists URL: https://www.thedaringcreatives.com/aegis/aegis-creative-compliance-program/ Last updated: 2026-08-01T19:43:30.000Z New initiative promises streamlined permits and enhanced security for cultural venues across the city _This post is for subscribers only._ ### Dispatch #8 — Four in the Morning URL: https://www.thedaringcreatives.com/aegis/dispatch-8-four-morning/ Last updated: 2026-08-01T19:43:35.000Z Sebastian walked in at four in the morning. No knock. Just the garage door sliding open and that calm stride across Wilson's scattered circuit boards. _This post is for subscribers only._ ### How I Finally Solved AI Image Consistency (While I Sleep) URL: https://www.thedaringcreatives.com/ai-image-consistency-automated/ Last updated: 2026-08-01T19:43:37.000Z I've been living with a problem for over a year now, and honestly, I was starting to think it was just the price of creating images with generative AI. Anyone who's tried to create consistent visual content with AI knows what I'm talking about. You describe your character perfectly, hit generate, and get... close. Maybe the glasses are wrong. Maybe the hair's a different color. Maybe your carefully crafted protagonist suddenly looks like a completely different person. A lot of people call it a crapshoot. You get "good enough" content and you roll with it because, hey, at least it's fast and cheap. I'll admit it — most of the time, if an image looks great on the first try, I just go with it. If it's good enough for me scrolling through my own feed, it's probably good enough for someone casually browsing by. But some things aren't negotiable. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/sherman-image-progression-wall-documentary-1920x1080.webp) ## The Details That Matter My creative work revolves around an alternate reality version of Portland called Lexicon City, where I'm represented by an alter ego called the Man in Yellow Sunglasses. My dogs and I are part of this crew (The Daring Creatives) exploring the near future, and every visual detail matters for the story. The Man in Yellow Sunglasses needs chunky yellow frames, not aviators. Sherman, our dispatcher who sends out intel that drives the story forward, always wears red goggles — we never see his eyes — and he's got the world's cutest nub for a tail. Those details aren't just aesthetic choices. They're my brand! So when Sherman shows up with a long tail and no goggles, or when the man in yellow sunglasses is wearing aviators and has no hat, I know I'm spinning the wheel again (and might be in for a long night). This was happening constantly... I'd generate five images and maybe one would have the right details. The rest would be close but wrong in ways that irritated me. ## Enter Claude Code I used Claude Code to build character sheets and brand style guides, then shared detailed information about this creative universe. Individual images of specific assets — the exact style of sunglasses, the goggles, even clothing styles. I fed it everything that mattered for consistency. I'm using Nano Banana through the Gemini API to generate these images, and they usually look good. But here's the thing I learned: you can do retouching through the API. So now I have Claude generating candidate images, reviewing them, scrutinizing how close or far away they are from the style guide, and then retouching them until they pass inspection. It takes longer than just accepting whatever comes out first. But it happens while I'm sleeping, or every 10 minutes on a scheduled cron job. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/sherman-whiteboard-image-pipeline-documentary-1920x1080.webp) ## The System in Action Claude generates multiple candidates (using Nano Banana), compares them against the character sheets, identifies what's wrong (wrong glasses, missing details, inconsistent styling), and then retouches until they match the brand guide. I can go back and look at all the discarded candidates to make sure it's working properly. But ideally, I just want to see consistent images from the start — and those are the ones that get bumped to the top of the list for me to review. With Anthropic's new Claude Managed Agents launching this week, I'm probably going to rebuild this whole system to be even more robust. The idea of having a persistent agent that's always watching for consistency issues and learning from each iteration? That's exactly what this workflow needs. Here's a tip if you want to deploy something like this: Have Claude do the QC on image quality, not Gemini. Initially, I had Gemini handling image generation and QC and ran into issues. I was essentially asking Gemini to grade itself on the job it did. When I split that function off to Claude to do, my rate of improvement spiked dramatically. That, and I expanded the number of retouch attempts we'd make per image from 2 to 4. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/image-pipeline-sherman-consistency.webp) This image pipeline generates a ton of images, so naturally I asked Claude Code to build me a web interface to browse, search, and mark images for repurposing or deletion. ## Here's Why You Should Care About This If you're creating any kind of ongoing visual content where consistency matters — whether it's characters for a story, products for marketing, or just a cohesive aesthetic for your brand — this approach works. The key insight wasn't that AI image generation is broken. It's that AI can also fix AI. You just have to teach it what to look for and give it the tools to iterate until it gets there. Now instead of spending my time generating and regenerating images, I spend it on the creative decisions that actually matter. The AI handles the consistency checking. I handle the story. ### What Will Being a Creative in 2028 Look Like? URL: https://www.thedaringcreatives.com/being-creative-2028/ Last updated: 2026-08-01T19:43:37.000Z I've been watching this in awe. AI tools have gone from "pretty interesting, mildly useful" to "holy shit, this saves me huge chunks of time." It's happening across every model and every tool, general or specific. I follow the creative side most closely — generative AI in particular — and what's possible right now is wild. ## What does being a creative in 2028 actually look like? We're in 2026\. I'm giving a two-year runway because we could be in the middle of something that looks a lot like superintelligence by then. Literally anything a person can do, a computer might do faster and better. So if you're a creative, what's left? Do you have a job? Do you have a role? I think you'll have a role. But the job is going to be different. ## The roles that are quietly disappearing I was musing the other day about how the [marketing manager](https://www.thedaringcreatives.com/the-marketing-manager-job-is-quietly-dying/) — as a role — probably goes away in the next five years. Maybe sooner. Not "gets transformed." Just doesn't get hired anymore. And not only at the senior level. All the way down. If you're a graphic designer, a videographer, a web builder, someone who makes physical things — the way you do that work is about to be replicated by anyone with a laptop. Any style. Any concept. High quality, on demand. ## What an hour looks like now Earlier this week I had about an hour before a meeting. My client was riffing out loud about other lower-price-point things we could make in the studio. In that hour I ran a market research analysis on epoxy fine art pricing, separated it from hobbyist work, broke down what the top artists in that space offer at each price point, then used that research to generate images and a video at something close to commercial quality. That's fucking crazy. I asked myself if I'd ever been in a meeting where someone produced something like that in the flow of the conversation. I haven't. Not once. I was so proud. And then immediately I thought — okay, what does it look like when everybody can do this? ## Why I think this is exciting, not terrifying For me it raises the bar on how productive and how creative a person can be. But it's a black box. You don't really know what's on the other side. The tools are improving exponentially, week over week. Will commercials and videos matter as much when everybody can make them? You don't need to hire a videographer to edit anymore. You don't need to go on location to be in a location. I travel all around a fictional city solving creative problems with a crew of dogs without ever leaving my desk. Sometimes I'm building those worlds on a walk. Websites are going to get more immersive and more branded. Experiences that used to take a team will get built by one person on a Tuesday. There's so much I can dream of now that I never thought I'd be able to make. The real question isn't "what gets replaced." It's "what will people still not be able to do yet?" That's where the next wave of creatives lives. ## The hard part It's hard to imagine something that doesn't exist. It's hard to plan for a thing you can almost see but can't quite name. That's the scary part — not the AI itself, but the fog around what comes next. I want more creatives thinking past where they are right now. Thinking bigger than the tool they used yesterday. It's an enormous opportunity, and the people who lean into it instead of bracing against it are the ones who'll define what this role even means in 2028. ### You Gave Yourself That Title Too URL: https://www.thedaringcreatives.com/you-gave-yourself-that-title/ Last updated: 2026-08-01T19:43:38.000Z Here's something I've been chewing on: the word "artist." People throw it around like it means something specific. Like there's a line somewhere and you're either on one side or the other. If you use AI, you're out. If you picked up a pencil and suffered for your craft, you're in. That's the vibe online right now. And I think it's worth actually looking at what we're arguing about. Because when I think of an artist — like, a *real* artist — I think of Michelangelo. Picasso. Rothko. I think of timeless works of art that you see in a museum. Or to dip into other realms of artistry, I think of Prince. Michael Jackson. Paul McCartney. The kind of people you learn about in school because they literally changed how humans think about beauty and expression and what's possible. Those are the names that come to mind when someone says the word "artist" with a capital A. So when someone making beats in their spare bedroom gets told they're not a "real artist" because they used AI to help production — sure, okay. But then let's be consistent. That same bedroom producer wasn't on the level of Prince before AI either. Neither was the person yelling at them about it. Nobody in this argument is Michelangelo. We're all just people making stuff. And that's the part that kills me. The title is self-bestowed. It always has been. ## The Only Definition That Matters Here's how I think about it, and it's pretty simple: Has somebody compensated you for your creative work? Have you made something that changed how people think, even a little? In most professions, if someone pays you to do the job, you can call yourself that thing. You fix pipes, someone pays you, you're a plumber. You don't need guild approval or a certain number of hours logged. You did the work, someone valued it, that's the credential that ultimately matters, lets be real. But with "artist," suddenly there's this whole other layer. You didn't go to art school? Not an artist. You didn't spend ten years mastering a medium? Not an artist. You used a tool that didn't exist when I was coming up? Definitely not an artist. It's a gatekeeper move. The admission criteria always seem to be: did you suffer the way I suffered? Did you come up the way I came up? If not, you're not in the club. And I'm sorry, but that's not a definition of artistry. That's a definition of insecurity. ## But Here's The Real Double Standard Nobody goes after traditional artists. Nobody tells the watercolor painter on Etsy that they're not a real artist because they're not hanging in the Louvre. Nobody tells the weekend guitarist they're not a real musician because they never sold out Madison Square Garden. Those people get to exist in peace with the title they gave themselves. But the person who uses Midjourney to visualize a concept they've had in their head for years? The person who uses AI to help them write songs because they could always hear the melody but never figured out the theory? Those people are suddenly frauds. [Losers.](https://www.thedaringcreatives.com/youre-not-defending-art-youre-just-being-mean/) Not real. Why? Because the tool is new. That's it. That's the whole reason. ## I've Yet to Meet the Person Who Asked For This Fight The other thing that gets me — and I mean really gets me — is that most people using AI creatively didn't show up asking to be called artists. They're just making stuff. Experimenting. Learning. Having fun with something for the first time (maybe their entire life). And then someone who gave *themselves* the title of artist comes along and tries to take it away from a person who never even claimed it. You're picking a fight with someone who didn't ask for one, defending a title that you gave yourself, acting like you earned it through some process that [makes you more legitimate](https://www.thedaringcreatives.com/toxic-threads-untalented-hacks/). You didn't. You just started earlier. Or you had access to tools and education that other people didn't. Or you had the time and the privilege to spend years on your craft while somebody else was working two jobs. The only admission to the "artist" club should be this: did someone care enough about what you made to compensate you for it? However you made it. Period. ## So What Am I Actually Saying I'm saying the title of artist is made up. And the people who guard it most fiercely are usually the ones most afraid of what it means if the door opens wider. You want to call yourself an artist? Go ahead. But you don't get to hand out that title *and* revoke it from other people based on which tools they used. You gave yourself that name the same way they did. The only difference is you think yours counts more. It doesn't. ### How I Built My AI Content Pipeline With Obsidian and Claude URL: https://www.thedaringcreatives.com/ai-content-pipeline-obsidian-claude/ Last updated: 2026-08-01T19:43:39.000Z I've been getting questions about how I actually produce content here, so I thought it was time to just show it. This is a breakdown of the full system — the tools, the structure, how ideas move from a voice note to a published post, and which parts are automated versus which parts still need me in the room. It's technical in places, but I'll try to make sure a beginner can follow the logic even if they've never touched a terminal. ## The Three Tools Doing Most of the Work The backbone is three tools working together: **Obsidian**, **Ghost**, and **Claude** (specifically Claude Code and Claude Cowork). Obsidian is where everything lives. It's a local markdown vault — basically a folder of plain text files that Obsidian gives you a nice interface for. I use it as the source of truth for all content in various stages. Drafts, final articles, brand notes, the content pipeline itself — it all lives in the vault. Ghost is the CMS. It handles the public-facing site, member subscriptions, and email newsletters. Importantly, it has an Admin API, which means I can push content to it programmatically without touching the browser. Claude is the AI layer. I use two modes of it: Claude Code runs scheduled automated tasks from the terminal (fetching news, running analytics, processing the content queue), and Claude Cowork is the interactive session where I draft, edit, and strategize in real time. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/Obsidian-Vault-for-The-Daring-Creatives.png) The Daring Creatives Obsidian Vault ## How the Vault Is Organized The vault has a few key zones. The main ones for content: **The Pipeline** is where raw inputs go — voice transcripts, quick notes, links I want to turn into something. I drop things here and the system picks them up. **Central Dispatch** is where drafts land after the AI (Claude) processes them. This is where I read, edit, and either approve or ask for revisions. **Drafts** is an untouched copy of every AI draft at the moment it was created. I never touch this folder. It's the baseline I diff against later to see how much I actually changed. **Ghost Outbox** is the publishing queue. When I approve something, it gets reformatted and dropped here. A scheduled script picks it up and pushes it to Ghost as a draft, then cleans up behind itself. This part may be redundant, but for now it is what it is. There's also a **Raw** folder where original voice transcripts are archived after they've been processed. This also lets me see my raw contribution to each thing we make. ## The Custom Instructions Layer The vault has a `CLAUDE.md` file at the root. This is Claude's project context — it tells the AI what the site is, how the content pipeline works, what the voice rules are, where everything lives, and what to do at the start of each session. There's also a `voice-reference.md` inside of my Brand folder file that gets updated whenever I make significant edits to AI-drafted content. My edits get analyzed and the patterns get documented — things like "he cuts the clever comparison and just says the thing straight" or "he inserts himself into observations." The AI reads this before writing anything. It's a living style guide built from actual evidence, not vibes. This is the part I think most people skip when they set up an AI writing workflow. They'll use a system prompt or a one-liner about tone. A detailed voice reference built from real edit patterns is genuinely different — and it compounds over time. ## How an Idea Becomes a Post The actual flow looks like this: 1. I dump something into a Drop Zone folder inside of Pipeline. Could be a voice transcript, a few sentences, a link with my quick reaction. Usually happens while I am on a walk, but also can happen when i'm in the car (not driving of course) or even in the shower (where some of the best thinking happens) 2. A scheduled Claude Code task runs (I have it set to run automatically) and checks the Drop Zone. If there's something new, it examines the context I left it, drafts a full article, saves identical copies to both For Review and Drafts within Central Dispatch, then archives the original in Raw. 3. I open For Review in Obsidian and read the draft. I edit directly in the file so I am effectively just editing a simple note file. When I'm happy with it, I change the `**Status:**` line from `Draft — needs William's review` to `Approved`. 4. The scheduled task picks up the approval. It diffs the For Review version against the Drafts baseline, strips all the pipeline metadata from the body, reformats the file as YAML frontmatter, and drops it in Ghost Outbox. 5. The publish script runs, pushes the file to Ghost as a draft via the Admin API, and cleans up the Outbox and For Review folders. 6. I do a final review in Ghost, add a featured image, and hit publish. The whole process from raw idea to Ghost draft can be a few minutes of my time total — the rest is automated. ## What Claude Code Does vs What Cowork Does This is a distinction that matters. **Claude Code** handles the automated, scheduled work. It runs on a timer and doesn't need me present. It fetches the AI news feed every morning, pulls Google Analytics and Ghost newsletter data into a weekly report, and runs the content pipeline check. These are all Node.js scripts in a `.config/` folder in the vault. I can also trigger them manually from the terminal. **Claude Cowork** is for the sessions where I'm actively in it — brainstorming, going deeper on a draft, making decisions about direction, asking questions about the site. It has access to all the same vault files, so it's working with the same context as Code. But it's conversational and collaborative rather than automated. The way I think about it: Code runs the system. Cowork is the partner I think out loud with. ## How the System Tracks Performance I have a Content Intelligence report that gets generated weekly. It pulls GA4 data (page views, traffic sources, engagement time) alongside Ghost newsletter data (email opens, click rates, member tier breakdowns) and outputs a single markdown file in the vault. Claude reads this at the start of each session. So when I'm drafting something, it already knows which topics are resonating, which posts are under-promoted, where my traffic is coming from. This makes the system self improve (creates a simple feedback loop). That part took me a while to build and is still evolving. But the principle is simple: the system should know what's working, not just what exists. ## Why I Built It This Way Honestly, I built it because there's a bunch of content work I find genuinely tedious. Reformatting files for publishing, pulling analytics, chasing down whether I remembered to archive something. Basically a bunch of stuff I would rather not do. The parts I actually enjoy — thinking through an idea, adding to something thats already 80% there (and good), building the universe around the site — those I want to spend more time on, not less. So the automation is pointed at the parts I don't want to do, not the parts that make the work worth doing. It was also a transparency project. For a while, every post on this site carried a Transparency Protocol — who wrote what, what the AI contributed, what stack was used, calculated automatically from a real diff of the drafts. I've since retired that widget, but the reason I built it still holds: because the split was computed and not estimated, I always knew my real hand in each piece. I don't think AI should make you a ghost. I think it should make you more yourself, with more time to actually be yourself. That's the version I'm building toward. ### Cutting Out the Middleman (I Used to Be One) URL: https://www.thedaringcreatives.com/cutting-out-middleman/ Last updated: 2026-08-01T19:43:39.000Z Jack Dorsey just restructured Block so that all 6,000 employees report directly to him, essentially eliminating middle management. People are losing their minds about it. I say bravo. And I say that as someone who spent time in middle management. I know what the job actually does — and one of the things it does, is filter. ## The Filter Problem When you join a company, you want to know where you're going. You want to hear from the person who built the thing, the one who knows why the decisions were made and what the company is actually trying to become. The person who has everything at stake. What you usually get is a middle manager. Someone who themselves heard it from someone, who heard it from someone, who maybe once sat in a meeting with a person who was two degrees from the founder. I wasn't sitting there deciding to corrupt the message when I was managing people. But you interpret things through your own lens. You emphasize what feels urgent to you. By the time the vision reaches someone three or four layers down, it's been translated so many times it barely resembles what started. Your job as an employee is to execute against a direction. But if the direction you're getting is already a diluted version of what the founder actually meant — you're not executing against the vision. You're executing against an interpretation of it. That always bothered me, even when I was the one doing it. ## The Part People Push Back On Here's the counter argument. Six thousand people cannot literally have one manager. You need someone to handle day-to-day coordination — feedback, the logistics of getting work done across teams and time zones. Not everyone can walk into the CEO's office when the shit hits the fan. But there's a difference between needing coordination and needing interpretation layers. Most middle management arguments conflate the two. "Who will give people feedback?" is a real question. "Who will translate what the strategy means for your team?" is the one I'd actually want to eliminate. That second job should be unnecessary if the vision is communicated well enough in the first place. The question isn't whether the org needs structure. It's which parts of the structure are adding signal and which ones are subtracting it. ## What I Actually Wanted When I Was on the Receiving End When I was coming up and someone had a message to deliver, what I always wanted — and rarely got — was to hear it from the person who made the decision. Because when you hear things secondhand, you're always wondering what got left out. What the real reason was. What nuance got smoothed over to make the message more palatable. When you hear it from the person with the actual context, you can ask questions. You can push back on the actual reasoning. You can understand the tradeoff, not just the conclusion. That's what I think Dorsey is reaching for. Whether it works at 6,000 people — I genuinely don't know. That's the interesting experiment. The math might not work out and he might end up building a different kind of management structure to compensate. But the instinct behind it feels right to me. It's going to be hard for people who built their careers in middle management, and I understand that. It's not a place to stay forever, and hopefully it won't be much of a stop moving forward. It's not comfortable to be told the role you've held is the problem. But I think it's worth being honest about. Every layer you add between the vision and the person executing it is a place where something can go sideways. That's true even when everyone involved has the best intentions. Especially then, actually. ### AEGIS Corporation Launches "Creative Unity" Public Service Campaign URL: https://www.thedaringcreatives.com/aegis/aegis-creative-unity-campaign/ Last updated: 2026-08-01T19:43:40.000Z New citywide messaging initiative promotes "collaborative creativity" while emphasizing permit compliance across cultural districts. _This post is for subscribers only._ ### AI Cinema's Fruit Love Island: What Everyone Missed URL: https://www.thedaringcreatives.com/creator-stories/artist-profile-ai-cinema/ Last updated: 2026-07-07T00:28:33.000Z I'm not going to pretend I wasn't curious. When Fruit Love Island started popping up everywhere — Strawberina dumping Bananito, Orangelo's chaos energy, the kind of unhinged re-coupling drama that somehow tracked with real reality TV — my first instinct was dismissal. I thought, "Well, people are going to call this AI slop." Anthropomorphic fruit people, generated for engagement, serving nothing. Move on. Then I noticed that by the time I was hearing about it, the account had already amassed over three million followers in eleven days. I noticed that there were nineteen episodes. I noticed that each one dropped every single day. I noticed that Strawberina is still *Strawberina* across all of them — same face, same voice, same personality — and that's not trivial. AI Cinema — “FRUIT LOVE ISLAND EPISODE 11: MOVIE NIGHT” So I looked closer. And the thing I found isn't what I expected. AI Cinema — “FRUIT LOVE ISLAND EPISODE 1” ## The Fastest-Growing TikTok Account You Don't Know Anything About The account is AI Cinema. They started posting on March 14th, 2026\. By the time most people had heard of Fruit Love Island, they had crossed three million followers — a pace that reportedly broke records for the platform. The creator is anonymous. No name attached to the account. No interviews where they reveal themselves. That's not unusual for someone doing AI creative work — a lot of people stay behind the curtain. But it does mean that what we know about the process comes entirely from the work itself, plus one statement the creator made: **each two-minute episode takes around three hours to make.** Three hours. Daily. For nineteen consecutive days at launch. That's not nothing. That's 57+ hours of focused production in less than three weeks, on top of managing an audience that grew from zero to three million while you were doing it. ## Of Course it Has Critics The criticism of Fruit Love Island has been predictable. "It's slop." "There's no real creativity." "Anyone could make this." The usual framing where AI work gets evaluated purely on whether it looks impressive and not on what it actually requires to pull off. What I see? Someone built a serialized narrative franchise, from scratch, in under a month, that millions of people returned to daily. Think about what that requires even before you touch the AI tools. You need a format that works — Love Island's structure (challenges, recouplings, bombshells, hideaway drama) turns out to be almost perfectly modular for AI video production. The scenes are short, the drama is contained, and the episode template repeats. Whoever runs AI Cinema understood this. They didn't pick an arbitrary format. They picked one that their tools could serve reliably at volume. You need consistent characters. Strawberina has to look like Strawberina in episode 19 the same way she did in episode 1\. In AI video generation, [character consistency is a real problem](https://www.thedaringcreatives.com/ai-image-consistency-guide/) — tools are probabilistic, not deterministic, and keeping a character stable across dozens of outputs requires either a very tight reference workflow or a lot of culling. Probably both. You need a voice for each character. Coconick isn't just a coconut. He has a personality that viewers recognize across episodes. That's a writing decision, not a generation decision. Someone thought it through. You need to release every day. Not when you feel like it, not when a good episode comes together, but every day. The audience expected it. The algorithm rewarded it. That cadence discipline is something a lot of creators with way more resources can't maintain. ## The Audience Participation Angle AI Cinema invited viewers to submit storyline suggestions through a Google form. They explicitly asked for content that was "dramatic," "messy," and involved "backstabbing." That move is smart in multiple ways. It generates narrative material. It creates investment in the audience — people feel ownership of a storyline they suggested. It also solves one of the harder creative problems in a daily format: running out of ideas. But it also reveals something about how the creator thinks. They understood that the show wasn't just content — it was participation. They built a feedback loop between audience and output, which is something professional shows with full writing rooms try to do and rarely pull off. AI Cinema did it with a Google form. ## What This Is Actually About The [conversation about AI and craft](https://www.thedaringcreatives.com/the-slop-about-slop/) always gets derailed by the quality-of-output debate. Does this look good enough? Is it real art? But Fruit Love Island reframes the question in an interesting way: does it need to look good? Or does it need to *work*? The fruit characters look like what they look like. Nobody's watching for the rendering. They're watching for Orangelo's drama. They care about whether Strawberina gets a fair chance. The emotional hook is real even if the imagery is rough. That's a meaningful distinction. [AI didn't break what makes storytelling work](https://www.thedaringcreatives.com/ai-didnt-break-art/). It just changed what the barrier to entry for storytelling looks like. A single person, anonymous, with access to AI video tools and a clear format understanding, built a serialized show with a bigger opening week than most network TV launches. I'm not going to tell you the episodes are beautifully crafted. They're not. The visuals are choppy. Some plots go nowhere. The pacing is inconsistent. But nineteen episodes in nineteen days, three million subscribers, tens of millions of views per episode, and an audience that comes back? That's not slop. That's a functional media operation run by one person with a laptop and a clear head about what the format required. The [anti-AI crowd keeps imagining the wrong player](https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/). They picture someone with no creative thought pressing a button. What @ai.cinema021 actually looks like is a person who understood the assignment — the format, the audience, the cadence, the consistency requirements — and then used the tools to execute it at a pace no traditional production could match. The work isn't impressive because the AI made beautiful things. The work is impressive because one person figured out how to be a showrunner. ## AI Cinema's Toolkit AI Cinema hasn't disclosed their specific tools publicly. But based on the output and what's known about how similar content gets made, here's a reasonable map of what's likely in play: **Text-to-Video Generation (likely Veo 3 or Kling)** The character animation — lip movement, facial expressions, environmental movement — is consistent with current generation-era video models. The outputs run 10–30 seconds per scene, strung together into 2-minute episodes. **Character Reference Workflow** To keep Strawberina looking like Strawberina across 19 episodes, the creator almost certainly maintains reference images for each character that get fed into each generation. This could involve image-to-video or image reference features in their generation tool, or a separate image consistency workflow upstream. **Script / Story Outlining** Given the audience participation form, the creator is likely running some form of LLM-assisted story outlining — feeding viewer suggestions into a writing pipeline that structures the episode's dramatic beats before generation begins. **Audio (ElevenLabs or similar)** Character voices are consistent across episodes. That consistency requires either a voice cloning tool or careful management of generated voice profiles. ElevenLabs or a similar TTS platform is the most likely candidate. **Editing** CapCut is the most common editing tool for this kind of mobile-first AI video content — fast, accessible, and capable of stringing multiple short AI clips into a coherent episode. ### Museum of Tomorrow Implements Enhanced Security Protocols URL: https://www.thedaringcreatives.com/aegis/museum-tomorrow-security-protocols/ Last updated: 2026-08-01T19:43:40.000Z Popular science museum introduces new visitor screening procedures following recent citywide security assessments. _This post is for subscribers only._ ### The Anti-AI Mob Has Gotten Vicious URL: https://www.thedaringcreatives.com/anti-ai-mob-vicious/ Last updated: 2026-08-01T19:43:41.000Z Something ugly is happening in the AI conversation, and I'm getting worried about where it's headed. I've been watching the discourse around AI tools shift from skeptical-but-reasonable to genuinely vicious, and it's starting to feel dangerous. Not dangerous like "the robots are coming" dangerous. Dangerous like "someone threw a molotov cocktail at Sam Altman's house" dangerous. ## When Skepticism Became a Witch Hunt Look, I get the concerns about AI. But somewhere along the way, legitimate criticism turned into something else entirely. And I can trace exactly how it happened. It started in tech culture - engineers and researchers having heated but mostly reasonable debates about alignment, safety, data practices. Fair enough. These are the people building the stuff, they should be arguing about it. Then it jumped to the news cycle. Suddenly every tech reporter had hot takes about AI doom. The coverage got more sensational, more black-and-white. Nuance doesn't get clicks, after all. Then it hit pop culture. Celebrities started [weighing in](https://www.thedaringcreatives.com/youre-not-defending-art-youre-just-being-mean/). Social media influencers picked sides. The conversation stopped being about actual AI capabilities and started being about team loyalty. And now? Now it's everywhere. Your neighbor has strong opinions about data centers. Your aunt is sharing articles about AI stealing jobs. This is the same pattern we've watched politics follow. Start with legitimate policy disagreements, add media amplification, mix in social media tribalism, and suddenly you're not debating ideas anymore - you're demonizing people. If you just say "[AI is evil](https://www.thedaringcreatives.com/fake-ass-robots-controlled-by-slave-labor-in-india/)" long enough you might actually convince people to believe it. ## The Escalation is Real We've moved way past arguing about whether AI training is fair use. We're talking about actual violence now. Someone literally threw a molotov cocktail at Sam Altman's house. Whatever you think about OpenAI's business practices, that's not criticism - that's terrorism and I can't help but hope that the same technology this lunatic is demonizing be used to put him away. I hate that thats my instinct now. And it's not just the extreme stuff. The whole conversation has gotten infected with this viciousness. People are treating anyone who uses AI tools like they're personally responsible for every bad outcome the technology might cause. You mention you used Claude to help with a first draft? You're contributing to job displacement. You experiment with image generation? You're stealing [from artists](https://www.thedaringcreatives.com/ai-didnt-break-art/). ## The Data Center Hysteria Look at what's happening with data centers. Suddenly every new facility is treated like we're building nuclear waste dumps. Yes, energy usage matters. Yes, we should optimize for efficiency. But the way people are talking about it, you'd think these were death camps instead of computers. I've seen protestors comparing AI training to environmental destruction while tweeting from phones that were manufactured using rare earth mining, from the hands of slaves. And here's the thing - a lot of the most vocal opponents live in places where their local economy depends on tech infrastructure. They just don't want to connect the dots. ## Who Benefits from This? The loudest voices in the anti-AI mob often aren't the people who are actually at risk. It's not the photographers whose stock photo business is getting disrupted. It's not the copywriters whose clients are asking for AI rates. And finally, it's not the artists trying to figure out how to compete with generated work. It's the people who were already established before any of this started. The ones with tenure, with big followings, with secure positions. Essentially: gatekeepers. And they're using legitimate concerns about AI to tear down anyone who's trying to adapt, learn, or experiment. Conveniently, this keeps the competition small and the conversation focused on fear instead of solutions. ## The Chilling Effect is Real I'm talking to people who are afraid to mention they use AI tools at all, even when it would be helpful context. They're keeping their experiments private. They're not sharing what they're learning. You know what that creates? A world where only the people who don't give a shit about transparency get to benefit from these tools. Where the honest ones stay quiet and the dishonest ones keep working. ## Where the Real Problems Are Want to know what actually pisses me off about AI? It's not that people are using the tools. It's that some people are using them to flood the world with garbage and calling it "content creation." The problem isn't AI. The problem is [human slop](https://www.thedaringcreatives.com/the-slop-about-slop/). It's people who were already cutting corners, already producing junk, who now have a faster way to produce more junk. But instead of going after the people making human slop, we're going after the people trying to use AI thoughtfully. The ones being transparent about their process. The ones still putting in the work. It's backwards. And it's starting to look a lot like other forms of political scapegoating I really don't want to see repeated in tech. ## A Better Way Forward Look, I'm not saying all AI criticism is wrong. Some of it is legitimate. But we need to separate the legitimate concerns from the mob mentality before this gets completely out of hand. We can push for better training data practices without treating people like criminals for using existing tools. We can advocate for artists' rights without attacking students who use AI for research. We can worry about job displacement without turning transparency into a confession of crimes. Maybe, just maybe, we can have these conversations without anyone getting hurt. Because molotov cocktails aren't changing anyone's mind, it's just going to escalate all of this further. Let's aim for the right targets. Before this gets any uglier than it already has. ### Dispatch #7: The Spiral URL: https://www.thedaringcreatives.com/aegis/dispatch-7-the-spiral-2/ Last updated: 2026-05-07T18:20:12.000Z I ran the numbers. At current pace, the perimeter tightens to our block within two weeks. Could be faster if they skip the diplomatic excuse phase and just show up. _This post is for subscribers only._ ### AEGIS Corporation Announces "Enhanced Security Initiative" URL: https://www.thedaringcreatives.com/aegis/aegis-corporation-security-initiative/ Last updated: 2026-08-01T19:43:43.000Z Corporation frames recent landmark restrictions as public safety improvements in official statement. _This post is for subscribers only._ ### Lexicon Tower Access Floors Restricted to Essential Personnel Only URL: https://www.thedaringcreatives.com/aegis/lexicon-tower-access-restricted/ Last updated: 2026-08-01T19:43:44.000Z Gray Glasses implement new security protocols limiting public access to lower floors of the city's central administrative building. _This post is for subscribers only._ ### Hull 581 Submarine Exhibit Temporarily Closed for Historical Assessment URL: https://www.thedaringcreatives.com/aegis/hull-581-exhibit-closed/ Last updated: 2026-08-01T19:43:45.000Z Museum of Tomorrow's iconic submarine attraction enters mandatory preservation review period. _This post is for subscribers only._ ### Chat, Cowork, Code, and Dispatch — How I Actually Use the Whole Suite URL: https://www.thedaringcreatives.com/chat-cowork-code-dispatch-suite/ Last updated: 2026-08-01T19:43:46.000Z Claude isn't one thing. It's four, depending on where you need the work to happen. Chat, Cowork, Code, and Dispatch. They're not competitors. They're four different shapes of the same collaborator, and once you stop thinking of them as products to pick between, the whole thing gets a lot more useful. Here's how Anthropic frames each one, and here's how I actually [use them](https://www.thedaringcreatives.com/my-week-with-claude-cowork/) to support The Daring Creatives. ## Chat — the day-to-day thinking partner Anthropic's pitch for claude.ai is a place to think, write, research, and work through ideas. No setup, no files, just a conversation. That's pretty much how I use it. Chat is my daily driver now. Quick and dirty stuff. I'll paste in a half-formed thought and ask Claude to take a stab at organizing it. I'll work through an idea out loud. I'll generate something fast when I just need a rough version in front of me to react to. If the question is "what do I think about this" or "give me a quick draft so I can react to it" — chat. ## Cowork — the desktop collaborator that runs my social Cowork is the one most people haven't wrapped their head around yet. Anthropic's framing: it gives Claude access to a folder on your computer so it can read, write, and organize files alongside you. Built for people who live in documents, not terminals. This is where most of my social media management lives. Cowork works hand-in-hand with Claude in Chrome to automate the stuff I used to dread — pulling analytics off each platform, analyzing followers, posting conversation starters, keeping the content calendar honest. Files on disk, browser doing the clicking, Claude tying it together. The other piece that makes Cowork actually work for me is Obsidian. My whole project directory — The Daring Creatives vault — is an Obsidian workspace, and that same folder is what Cowork reads and writes into. Obsidian is the context space. Notes, drafts, transcripts, pipeline folders. Cowork (and Code) live inside it. If your work involves manipulating or creating real files you want to keep — documents, content, a vault you actually care about — try Cowork. ## Code — the terminal partner for building the site Claude Code is for, well, coding. Anthropic built it for developers who want to delegate coding from the terminal. Reads your repo, runs tests, edits files, opens PRs. I'm not a traditional dev. I still use Code constantly. For me it's how I build features of the website and how I create the scheduled cron jobs that keep things running. The Ghost publishing script that takes approved drafts and pushes them to the site — Code wrote that. The analytics script that pulls GA4 and Ghost data into one report — same. Anything that touches the Daring Casper theme, anything that has to live in a repo, Code handles. And like Cowork, Code runs inside my Obsidian vault. Same project directory, same context. That's not a small detail — it means the code I'm writing has the same ground truth as the content I'm writing, because they live in the same folder. If you can describe what you want, you can build a small thing that saves you an hour a day. I'm living proof. ## Dispatch — the agent that runs my Mac when I'm not there Dispatch is all about triage, and is how I control my Mac when I'm away from it. I have a chat I can talk to from anywhere, and that chat decides when to dispatch work to Cowork or to Code on the machine at home. If something needs a file touched, Cowork picks it up. If something needs a script run, Code picks it up. I'm just saying what I want and dispatch routes it. The experience is more like talking on a walkie talkie to a partner back at HQ. It's also the thing that makes The Daring Creatives feel less like a workflow and more like a small company. Every morning Sherman (what I named my agent) runs a content pipeline check — clears the drop zone, drafts anything new, applies feedback on revisions, preps approved posts for publishing. I wake up and the work has already been done. If the work is "something I want to happen on a clock, or something I want to send to my machine from across town" — Dispatch. Note: Using Dispatch seems to use many more tokens, so use wisely. The first days after this came out, it was the only way I'd talk to Claude. After hitting my limit a few times though, I use it just for quick check ins when I am AFK. ## How they fit together The thing I didn't expect is how much they overlap. A single piece of content at TDC might touch all four: I voice-transcribe an idea into the vault from my phone, a scheduled dispatch picks it up overnight, Sherman drafts it in Cowork using files in that same Obsidian folder, and a Code-written script that runs on a schedule publishes the approved version to Ghost. That's not four tools. That's one collaborator wearing four different hats depending on where I need the work to happen — and one vault holding all of the context. The question isn't which to pick. It's: where is this particular piece of work happening? In my head? In a folder? In a repo? Or on a schedule while I'm asleep? Pick the shape that matches the work. ### You Don't Owe Skeptics a Debate URL: https://www.thedaringcreatives.com/dont-owe-skeptics-debate/ Last updated: 2026-08-01T19:43:47.000Z I posted something on Threads yesterday. Pretty simple stuff — I built my own content pipeline using AI and it works better for me than anything I found off the shelf. That's it. That's the whole post. A statement about how you can use AI to build custom tools that fit the way you actually work. And here comes the drive-by. Some guy — someone I was following at the time — drops into the replies with a skeptics energy. His argument? "80% of people think AI is fucking terrible, so why bother?" First of all, that had nothing to do with what I posted. I wasn't making a case for AI adoption rates. I was saying I built a thing that works for me. But that's what skeptics do — they don't engage with what you said, they engage with what they *wish* you'd said so they can knock it down. I asked for a source. Because when someone throws a number like "80%" at you, I want to see where that came from. He fires back within 22 seconds — "I could've given you 100 other links" — and drops a single link to some eMarketer blog post. Setting aside that the source is coming from bias, it also doesn't matter. I'm not creating stuff for skeptics. You shouldn't either. If someone reads what you write (or create) and don't like it because the writing isn't good, the ideas don't land, the storytelling falls flat — that's real feedback. But dismissing what you made because they don't like *how* you made it? Let's not care about that opinion anymore. ## The Gatekeeping Thing Is Getting Old The day before, I had a whole separate exchange with someone about gatekeeping. I posted something about how gatekeeping is harmful, which I think is pretty uncontroversial. This person responds with: "I don't understand why all you pro-AI people talk about gatekeeping. We're not telling you that you can't [pick up a pencil](https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/). We're not saying you can't learn to play an instrument." That IS gatekeeping. You just proved my point. Nobody has to ask for permission to decide how they learn or what tools they use. It doesn't matter what anyone thinks. [The outcome](https://www.thedaringcreatives.com/creatives-say-art-process-vs-outcome/) is what matters. The idea that there's a correct path to being creative is an arbitrary construct that exists to protect people's egos. ## I'm Losing Patience and I'm Fine With That Look, maybe I deserve some of this. I've been pretty vocal about the fact that if you're [an agency in 2026](https://www.thedaringcreatives.com/agency-model-broken-small-business/) and you're not using AI, what kind of agency are you? If you're a content creator or producer and you're not even exploring these tools — yeah, I have questions. I've said that out loud and I stand by it. We spend all this energy making excuses for people who refuse to engage with the technology. "Oh, they're worried about their jobs." "They're worried about the artistry." At some point, I think we have to be honest — some of them just don't want to learn something new. And I'm getting less interested in having that argument every single time I post something positive about what I've built. I'm not saying people have to use AI. I'm saying when someone shares something they're excited about — something that's working for them — and your instinct is to jump in with negativity and junk statistics, the problem isn't AI. [The problem is you.](https://www.thedaringcreatives.com/toxic-threads-creative-gatekeeping/) ## The Consumer Skepticism Myth Here's the thing about that "80% of people don't like AI" stat, even if we take it at face value: consumers are skeptical of everything new until they're not. People were skeptical of online shopping. People were skeptical of streaming. People were skeptical of smartphones replacing cameras. Consumer skepticism doesn't always "win out." I'm not building for the 80% who are supposedly skeptical. I'm building for the 20% of people who are curious, who are experimenting, who are trying to figure out how this technology fits into the way they work. Those are the people I care [about reaching](https://www.thedaringcreatives.com/about/). And those people don't need a random thread reply from a guy who Googled a stat in 22 seconds to tell them whether their curiosity is valid. Your curiosity is valid. Build the thing. If it works for you, that's enough. ### What Antfooding Really Means for Anthropic URL: https://www.thedaringcreatives.com/anthropic-antfooding-explained/ Last updated: 2026-08-01T19:43:47.000Z Eating your own dog food. Not exclusive to tech but in this application of it, you build a product, then you use it yourself. It's supposed to keep you honest. If your own team won't use what you're building, why would anyone else? Anthropic took this further than most companies would be comfortable with. In December 2025, a team led by research scientist [Saffron Huang](https://saffronhuang.com/?ref=thedaringcreatives.com) — she's on Anthropic's Societal Impacts team and was named in TIME's 100 Most Influential People in AI — published a study called "[How AI Is Transforming Work at Anthropic](https://www.anthropic.com/research/how-ai-is-transforming-work-at-anthropic?ref=thedaringcreatives.com)." They surveyed 132 engineers and researchers, did 53 in-depth interviews, and analyzed 200,000 internal Claude Code transcripts. The co-authors include Bryan Seethor, Esin Durmus, Kunal Handa, Miles McCain, Michael Stern, and Deep Ganguli. What they found: their engineers now use Claude for roughly 59% of their work, up from 28% a year earlier. Productivity gains hit 50%, up from 20%. They even have a name for it internally — "Antfooding," because employees call themselves Ants. But here's the part that few people talk about and I've experience myself: 27% of the work Claude helps with are tasks that wouldn't have been done at all otherwise. Not "done slower" — just never done. Little fixes, small improvements, the kind of stuff that sits on a backlog forever because nobody has time. Anthropic calls them "papercuts." Now they're getting fixed because the cost of doing them dropped to nearly zero. ## The Part That Raises Concern Engineers reported that junior team members are asking Claude instead of asking colleagues. Fewer mentorship moments. Fewer hallway conversations where a senior engineer explains not just the what but the why. One engineer said it plainly in the study: "I feel optimistic in the short term but in the long term I think AI will end up doing everything and make me and many others irrelevant." Then there's what the study calls the "paradox of supervision" — you need strong coding skills to review what Claude produces, but you might be losing those skills by letting Claude produce it. I do believe certain skills we have and rely on now will atrophy with AI. We'll probably replace them with new ones. ## What This Means If You're Not Anthropic Anthropic is an AI company with early access to the best models. Of course their adoption numbers are high. But the patterns they're seeing are going to show up everywhere. The engineers who leaned in described becoming "full-stack" almost overnight — taking on frontend work, databases, data visualizations, stuff that was previously outside their wheelhouse. Claude handled the implementation. They handled the direction. That sounds a lot like what we talk about here with [multi-modal creatives](https://www.thedaringcreatives.com/about/). The tool handles the execution. You handle the intent. The difference is Anthropic is watching it happen in real time, measuring it, and publishing the results. Most of us are just going to experience it and figure it out as we go. 59% is a big number. And it's going up, not down. The question isn't whether AI will change how people work — Anthropic already answered that. The question is whether the rest of us are paying attention to what they're learning along the way. ### The Marketing Manager Job Is Quietly Dying URL: https://www.thedaringcreatives.com/marketing-manager-job-dying/ Last updated: 2026-08-01T19:43:47.000Z A "hot new opportunity" landed in my LinkedIn inbox this afternoon. Senior Marketing Manager. Honestly, a job I did for years but feel like I graduated from. Still, I was curious at what it paid. Twenty-two dollars an hour. Five years ago this same job paid 80-100k. Is the economy really that bad? ## This isn't a market dip The easy story is "too many candidates, not enough jobs, employers can lowball." And sure, that's part of it. But I don't think that's the whole thing. I think a lot of businesses have quietly figured out that the marketing manager role — the one that owned the calendar, briefed the agencies, ran the campaigns, stitched together the channel reports — is mostly gone. AI ate it. Not in some dramatic "marketing managers are so cooked" type of way. In a boring, one workflow at a time type of way. The campaign brief? GPT writes a good enough first draft from a Loom and a product page. The content calendar? Claude can sequence a quarter in less than twenty minutes. The channel report? Already automated. "Stakeholder wrangling"? Honestly, that's the part nobody wanted to do anyway, and it's the only piece left, which is why the job now pays $22/hr. They're paying for the meeting attendance, not the marketing. If the only thing left of your role is being a human Slack relay, the price is going to keep falling. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/04/the-marketing-manager-job-is-quietly-dying-square-1080x1080.jpg) ## What I think replaces it I don't think the work goes away but I think the *job title* goes away, and [something hybrid](https://www.thedaringcreatives.com/context-curator-soft-skills-ai/) takes its place. Not "AI marketing manager" with a copilot tab open. Something more like a marketing systems builder — a person who designs and operates the machine that does the marketing, and who invents new moves the old role couldn't physically do. A few things this person actually does: They build agents. They wire together tools — analytics, CRM, CMS, ad platforms, generation models — into a system that runs campaigns end to end and tells you what it's doing. A working, self-improving pipeline. They invent new loops, not just automate the old way of doing things. Stuff like: a daily agent that reads your top-performing content, generates ten variants, ships them to three channels, watches the response, and kills the losers by lunch. No marketing manager could ever do that by hand. So nobody did it. Now somebody can. They own the [brand voice as a system](https://www.thedaringcreatives.com/teach-ai-brand-voice/), not a vibe. Voice references, taste guardrails, evals — the boring infrastructure that lets a model write something a real person would actually publish. This is the part everyone's getting wrong right now, and it's where the craft moved. They measure attribution honestly. Not "we ran a campaign and revenue went up." Closer to "here's the path, here's the lift, here's the cost, here's what to do next week." The tools to do this finally exist, and most teams aren't using them. ## This is good news, mostly I know this sounds bleak if you're currently a marketing manager. It isn't, really. The taste, the judgment, the sense of what a brand should sound like — none of that gets cheaper. It gets *more* valuable, because there's so much more output to steer. What gets cheaper is the scaffolding around it — the meetings, the briefs, the status decks, the project plans. Good. That stuff was always the worst part of the job. The people I see thriving right now aren't the ones who learned a new tool. They're the ones who stopped thinking of themselves as the person who *does* the marketing and started thinking of themselves as the person who *builds the thing that does the marketing*. That shift is the whole game. If you're in this seat right now and you're watching the salary numbers slide, the move isn't to defend the old job description louder. It's to go build the next one before somebody hands it to you for $22 an hour. ### Cathedral Bridge Checkpoint Expanded URL: https://www.thedaringcreatives.com/aegis/cathedral-bridge-checkpoint-expanded/ Last updated: 2026-04-08T23:11:02.000Z Gray Glasses Transit Authority expands Cathedral Bridge checkpoint to full-day staffing, citing elevated unsanctioned crossing patterns. _This post is for subscribers only._ ### Hull 581: Origin Records Surface at Museum of Tomorrow URL: https://www.thedaringcreatives.com/aegis/hull-581-origin-records/ Last updated: 2026-08-01T19:43:47.000Z Museum of Tomorrow archivists uncover the original acquisition file for Hull 581 — an anonymous donation from four decades ago — and open the vessel's lower compartments to the public for the first time. _This post is for subscribers only._ ### The AI You Never Have to Open URL: https://www.thedaringcreatives.com/anthropic-conway-always-on-agent/ Last updated: 2026-08-01T19:43:48.000Z There's something happening that I think a lot of people are going to underestimate until it's already changed how they work. Anthropic is testing something called Conway. It's a standalone Claude environment — always on, with extensions, webhooks, and Chrome access built in. Not a chatbot you open in a tab. Not a tool you reach for when you're stuck. An agent that's just there, ambient, connected, running. Right now, most people use AI through a chatbot. You've got a problem, you open the thing, you type into it, you get something back, you close it and return to whatever you were doing. I've been doing this too — it's genuinely useful and the natural progression for learning AI. But it's also a pretty constrained version of what this stuff can do. An always-on agent is a different kind of relationship. It's not a tool you reach for — it's more like working alongside someone who's already up to speed on what's happening and can jump in when it makes sense. You don't have to brief it every time. You don't have to re-explain the context from scratch. And honestly, that's the part most people miss when they talk about why AI hasn't fully transformed their workflow. The [context problem](https://www.thedaringcreatives.com/context-is-your-creative-edge/) is the real limitation of how AI gets used today. Every new conversation, you're starting from zero. Who you are, what you're working on, what matters, what doesn't — you have to rebuild that every single time. I think a lot of people give up before they get AI to be truly useful. An ambient agent that already knows the context? That's when this stuff becomes magic. And what you're left with is something that functions less like a session and more like a system. An AI that's always on, always connected, always watching what you're doing is a different kind of thing than a tab you can close. The privacy questions are legitimate and worth taking seriously. I'm not going to wave those away. But the architecture of Conway — extensions, webhooks, browser access — sounds like everything a persistent assistant needs to be useful. We don't know yet, this is all stuff of rumors and leaks. But that's the shape of what they're building toward. What I do know is that this is the direction things are going. The question isn't really whether always-on AI agents will exist. It's whether you've thought about what you'd actually use one for. Because that's the gap I keep running into with people who are early into AI workflows. They're still optimizing for "how do I write a [better prompt](https://www.thedaringcreatives.com/is-prompting-holding-you-back/)" when the more interesting question is "what does my work look like when the AI is already in it." Those aren't the same question, and they lead to very different places. If you're a writer, a designer, a developer, a researcher — think about how much of your day is just re-establishing context. Explaining things to tools, to collaborators, to yourself. Now imagine one of those things already knows the context and can work with it without being asked. That's what's being tested right now. And I think it's closer than most people realize. ### You're Not Defending Art, You're Just Being Mean URL: https://www.thedaringcreatives.com/hannah-einbinder-ai-creators/ Last updated: 2026-08-01T19:43:48.000Z Hannah Einbinder went on stage at a Hacks [press event](https://variety.com/2026/tv/news/hannah-einbinder-ai-creators-losers-1236706302/?ref=thedaringcreatives.com) this week and said this about people who use AI to create: > "The people who make this stuff are losers. They're not artists. They're not creative. And they've wanted their whole lives to be special. And they're not special. So, they're trying to rob real creative people of our gifts. And you can't. And even if you try, you will never be cool. You guys suck. No one likes you." That's a direct quote. From an actress promoting Season 5 of her HBO show. About people she's never met, whose work she's never seen, whose circumstances she knows nothing about. I'll be upfront: I've never heard of Hannah Einbinder. I've never watched Hacks. I have no idea if she's funny (if I had to guess, based on this I would say no). What I do know is that she stood at a press junket — an event designed to promote a show someone else created — and called a bunch of strangers losers. So let's talk about that. ## Who Exactly Are You Talking To? When Einbinder says "the people who make this stuff," who does she think she's describing? Because in my experience, it's not some [monolithic group of tech bros](https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/) trying to steal her job. It's a retired teacher making digital art for the first time. It's a small business owner who can't afford a [design agency](https://www.thedaringcreatives.com/agency-model-broken-small-business/). It's a kid in a country where access to creative education barely exists, using AI to learn visual storytelling. It's a neurodivergent person who always had the ideas but never had the tools to execute them at the speed their brain moves. Those are the "losers" she's talking about. People who are curious. People who are learning in public. People who finally found a way to make the thing they've been imagining for years. And she wants them to know they'll never be cool. ## What Does Hannah Einbinder Actually Do? Now, I believe in reciprocating energy so consider what comes next just that. If you're going to call an entire category of creators "losers" and declare they're "not artists," you should probably have a body of work that backs up that kind of authority. So let's look at it. Hannah Einbinder is an actress. Her mom is Laraine Newman, an original SNL cast member — so she grew up in the industry, surrounded by connections and access most people will never have. She's primarily known for one role: Ava Daniels on Hacks. She won an Emmy in 2025 for it. But here's what she does as an actress: she pretends to be someone else. Other people write her lines. Other people tell her where to stand. Other people created the show, built the sets, designed the costumes, ran the cameras. A director tells her what emotion to convey. A marketing team promotes the work. She shows up and performs a character that other people invented. I'm not saying that's not a skill. But it doesn't make you the authority on who gets to call themselves creative. And it damn sure doesn't give you the right to call people losers from a stage that someone else built for you. A hard pill to swallow is that the title of "artist" is self-bestowed. It always has been. Whether you just picked up a paintbrush last Tuesday or you've been at it for forty years — you gave yourself that title. Nobody handed it to you. Einbinder gave it to herself the same way the Midjourney user in their spare bedroom did. The only difference is she had a head start (through nepotism) and an HBO platform to yell from. ## The Part That Actually Bothers Me What gets me isn't that a celebrity has a hot take on AI. Celebrities have bad takes constantly. What gets me is the specific language: "They've wanted their whole lives to be special. And they're not special." Think about what that does to someone who's just getting started. Someone who spent three hours last night figuring out how to use Midjourney to visualize a children's book they've been dreaming about writing. Someone who used Claude to help them structure a screenplay they've had in their head for a decade. Someone who finally — finally — has access to tools that let them participate in creative work that used to require expensive software, formal training, or knowing the right people. And now a privileged actress on a stage is telling them they're a loser who will never be cool. That's not protecting art. That's a [gatekeeper with a loser's attitude](https://www.thedaringcreatives.com/toxic-threads-creative-gatekeeping/), punching down from a position of privilege she was born into. ## What She Could Have Said Instead Einbinder could have said "I worry about AI being used to replace working artists without their consent." That's a legitimate concern and I'd agree with it. She could have said "I think the entertainment industry needs stronger protections for performers and writers." Also legitimate. Also something I'd support. She could have said "I'm uncomfortable with how quickly this technology is moving and I think we need to have serious conversations about it." Totally fair. Instead she went with "losers" and "you guys suck" and "no one likes you." Which isn't a position. It's a playground insult from someone who's never had to fight for access to anything in her life. ## I'll Keep Defending the Curious Ones Every single person experimenting with AI creatively right now is braver than someone with an Emmy calling strangers losers from a press conference stage. The person learning in public, sharing work that might not be perfect, figuring it out as they go — they're doing the harder thing. Way harder than reading lines someone else wrote. You don't have to like AI-assisted work. You don't have to use it. You don't even have to respect it. But when you call the people doing it "losers" who will "never be cool"? You're not the protector of art. You're just another gatekeeper telling people they don't belong. And in my experience, the people who spend the most energy deciding who's a "real" creative are usually the ones most afraid that the definition is changing. ### Central Repository Independent Access Revoked URL: https://www.thedaringcreatives.com/aegis/central-repository-independent-access-revoked/ Last updated: 2026-04-19T23:43:23.000Z Gray Glasses compliance directive revokes independent borrowing privileges at The Central Repository, limiting access to approved civic researchers only. _This post is for subscribers only._ ### I Bought the Meta Glasses. Here's My Honest Take. URL: https://www.thedaringcreatives.com/meta-ray-ban-glasses-review/ Last updated: 2026-08-01T19:43:48.000Z Meta announced prescription versions of its Ray-Ban AI glasses this week, and people are talking about them. So, i thought it would be a good time to share some of my thoughts on AI glasses more generally, and the Meta Ray-Ban v2 glasses. The concept is genuinely compelling. I was sucked in by the marketing on these and have been using them for over a month, so now I feel more qualified to talk on the promise of AI glasses and the actual reward. ## Why I bought the Meta Ray-Ban AI Glasses I got them thinking I'd use them constantly for documenting my work. I'm a creator who makes lots of videos, I'm always moving around, and hands-free capture while staying present in what I'm doing seemed like an obvious fit. I sure was hyped about it. The pitch I sold myself: capture ideas as they happen and no more interrupting the moment to reach for my phone (or use all of its battery). What actually happened: they're in a case more than I'd like to admit. Here's the specific thing that killed it for me. I have the non-display version — which means when I'm shooting, I have no idea what the camera sees. I'm pointing my head at something and hoping the frame is right. For anyone doing intentional visual work, that's a real problem. You can't compose a shot if you can't see your shot. The display versions solve this, but they're more expensive and have their own tradeoffs around weight and battery. It's not a free fix. 0:00 /0:21 1× First video taken with the Meta Ray-Ban AI Smart Glasses ## What would make these glasses more useful Three things I'd actually need before these become a daily driver: The ability to choose which AI I'm talking to. Right now it's Meta AI, full stop. I want to be able to choose either Claude or Gemini based on what I'm doing. I find it rich that Meta complains about Apple's walled gardens but then makes their own. Sure, you can use whatever model you want if you just treat the glasses as a Bluetooth device but that also feels clunky in practice. A viewfinder. I know adding a display adds weight and shortens battery life and raises the price. But without any visual feedback, the use cases for serious creative work are narrow. And finally, the ability to shoot videos and images in landscape. Right now it's portrait only. The prescription angle in this week's announcement is genuinely smart — removing the "I already wear glasses and I'm not wearing two pairs" objection is meaningful. A lot of people had that objection, including people who would otherwise be interested. But prescription or not, you're getting the same hardware underneath. I still think wearable AI devices are the future. The ambient, hands-free part of it actually works when the context is right. Walking around, doing something physical, having questions you want answered without stopping what you're doing — that's a legitimate use case. I just haven't found it consistently in my own work yet. It's expensive for what it currently does. And it needs more work before I'd recommend it to a video creator without some serious caveats. Maybe the display version changes the equation. I'll keep an eye on it. ### Mount Vision Park Summit Trail Closed URL: https://www.thedaringcreatives.com/aegis/mount-vision-park-trail-closed/ Last updated: 2026-08-01T19:43:48.000Z Sustained rainfall has destabilized the upper section of Mount Vision Park's summit trail, prompting a temporary closure while park maintenance assesses the damage. _This post is for subscribers only._ ### Dispatch #6: The Memory Collector URL: https://www.thedaringcreatives.com/aegis/dispatch-6-signal-identified/ Last updated: 2026-07-29T01:15:39.000Z There's an artist operating in the city's lower frequencies. No AEGIS-compliant output. No clean signal for the Grid to log. _This post is for subscribers only._ ### The Transformer: How James Gerde Turned Other People's Videos into Something Completely Different URL: https://www.thedaringcreatives.com/creator-stories/artist-profile-gerdegotit/ Last updated: 2026-07-08T14:46:44.000Z The first thing that got my attention about James Gerde (@gerdegotit) wasn't the work itself. It was something he said about the work. "Contrary to popular belief about generative AI, it isn't a magic button — there are a string of variables that must be accounted for and ways to optimize your workflow and process." He said that in the context of explaining why his stuff looked different from everyone else's. And the more I looked at his feed — nearly two million followers on Instagram, videos that take familiar footage and push it somewhere completely unexpected — the more that quote landed. Because the part of his process nobody talks about is the part that makes the output possible. And it's not the part people assume. ## What James Gerde Actually Does James Gerde is a Seattle filmmaker. He spent years directing music videos, commercial films, and creative projects before he found the specific AI niche that turned into a company and a million-plus following. What he does, specifically: video-to-video style transfer. Not text-to-video. Not image generation. *Video-to-video.* He takes footage — often from other creators, with credit given — and runs it through a workflow that completely reimagines the visual style. A dance video becomes a neon painting in motion. A street scene becomes an animated world with the underlying movement intact but the surface totally transformed. It's a meaningfully different discipline than what most people are doing with AI video tools. Text-to-video is generative — you describe something and the model invents it. Video-to-video is interpretive. You start with something real, and then you push it through a lens until it looks like it came from a different reality. The motion is preserved. The character of the original performance stays. But the aesthetic is entirely new. ![A bird rendered as woven fabric — video-to-video style transfer by James Gerde](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/gerde-fabric-bird-still.jpg) James Gerde (@gerdegotit) — video-to-video style transfer, from gerdegotit.com ## The Workflow Behind the Look Gerde built his early work using AnimateDiff inside ComfyUI. If those words mean nothing to you, here's the quick version: ComfyUI is a node-based interface for running AI image and video models locally, meaning you're not relying on a web app — you're building custom pipelines on your own hardware. AnimateDiff is a model designed specifically for applying animation styles to video frames in a temporally consistent way, which is the part that makes the motion look smooth rather than flickery. This is not plug-and-play. ComfyUI has a steep learning curve. Workflows are built by connecting nodes — each one doing one job — and getting the chain right to produce clean, consistent output takes real iteration. Gerde has been vocal about the fact that he's been developing and tweaking his workflow continuously since he started. He's also been watching the whole landscape shift under him. When he replied to someone sharing an older video of his work on X, he said: "What's interesting is I actually don't think this is the best example of where the tech is. However it shows the change from image model based animations to video model based animations quite well. I do miss those warp fusion days tho.. a simpler time." That's someone who has been in this long enough to feel nostalgia for earlier tools. He started with warp fusion. He moved to AnimateDiff. He's now tracking the shift toward native video models. His practice has had to evolve continuously, and he's chosen to evolve with it rather than stay locked in one technique. ## The Part That Made It a Business Gerde didn't stay a solo creator making cool content on Instagram. He turned it into Gerde Got It, a company built around video-to-video style transfer as a service and a craft. He held a masterclass for Brandtech — one of the major holding companies in advertising — where he shared his workflow with their employees. He was selected as one of three inaugural creators for a Brandtech residency program specifically for AI creative talent. He has a Patreon where he's published tutorials for people who want to learn the process rather than just watch the output. The Patreon is interesting because it's a tell. [Sharing how you work](https://www.thedaringcreatives.com/context-is-your-creative-edge/) is the move of someone who has figured out that the process is reproducible but the taste that guides it isn't. Anyone can learn his ComfyUI workflow from his tutorials. Not everyone will produce what he produces, because the workflow is only part of what's happening. The selection of source footage matters. The decision about how far to push the style transfer matters. The judgment call about when an output is compelling versus when it's just distorted. These are curatorial, directorial decisions that don't come with tutorials. They come with years of looking at a lot of output and knowing which piece is which. ![Ocean waves rendered as layered paper — style transfer frame by James Gerde](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/gerde-paper-waves-still.jpg) James Gerde (@gerdegotit) — a dance frame reimagined as layered paper, from gerdegotit.com ## What Seven Years of Sobriety Has to Do With It There's a personal dimension to Gerde's work that he's open about and that I think shapes the work more than most people realize. He's been sober for seven years. And he talks about art — specifically, the creative practice he's built — as a meaningful part of that recovery. In his company's origin story, the creative work isn't separate from the personal work. The two are intertwined. That context changes how I read the discipline in his output. Shipping consistently. Iterating. Building something with rigor even when the tools are imperfect. Those habits don't just come from creative motivation. They come from a person who has learned, through difficult experience, what it means to show up for something every day regardless of how you feel. The [question of what it actually means for a creative to adopt an AI workflow](https://www.thedaringcreatives.com/adopting-an-ai-workflow/) usually gets framed around skills and tools. But Gerde's version of it is partly about character. The tools give you the capability. The person running them has to bring the rest. ## The Credit Question One thing Gerde does that not everyone does: he credits the original creators when he transforms their videos. The work is derivative by design — that's the entire premise of video-to-video — and he's explicit about the source. That's a good-faith practice in a space that has a real problem with attribution. It also matters for the relationship between his work and the original footage. He's not pretending to have invented the performance. He's saying: here's what this looks like when it goes through my lens. The performance belongs to whoever made it. The transformation belongs to him. It's a clean distinction and it's how the [conversation about AI and creative ownership](https://www.thedaringcreatives.com/ai-didnt-break-art/) should probably work — not "who made this" as a binary, but "who contributed what." ## The Longer View Gerde made a comment about the shift from image-model-based animation to video-model-based animation. That's a real technical transition that's been happening over the last couple of years — the tools are changing from tools that work frame-by-frame (treating video as a series of images) to tools that model motion natively (understanding video as video). That transition changes what's possible and what the creative decisions are. He's navigated it once already, from warp fusion to AnimateDiff. He'll navigate it again as native video models get better. The specific tools he uses today are less important than the fact that he's built a practice of staying current and integrating new capabilities as they arrive. That adaptability is [the actual skill](https://www.thedaringcreatives.com/when-ai-makes-you-slower/). Not the ability to run a specific workflow. The ability to evaluate new tools quickly, update your pipeline, and keep producing. He's built a company around a technique that didn't exist three years ago. He'll probably have to rebuild it again. That's the job now. ## James Gerde's Toolkit Gerde has been open about his process over time. Here's the core of what he's working with, with the caveat that his stack has evolved continuously and this reflects the workflow he's best known for: **ComfyUI** The foundation. A node-based interface for running Stable Diffusion and other AI models locally. Gerde uses it to build custom workflows that chain together multiple models and processing steps. Steep learning curve, but total control over the pipeline. **AnimateDiff** The model that makes the video-to-video style transfer work. Applied within ComfyUI, it processes video frames in a way that preserves temporal consistency — meaning motion stays smooth rather than flickering frame-to-frame when the style is transformed. **Stable Diffusion (various models)** The underlying image generation backbone that handles the style transformation. Different models produce different aesthetics, and Gerde has developed taste around which models to use for which inputs. **ControlNet** A critical piece of the puzzle for video-to-video work — ControlNet lets him preserve the pose and movement structure of the original footage while the style transforms around it. It's what keeps the dancer looking like they're doing the same moves even after everything else has changed. **Upscaling (likely Topaz Video AI)** His outputs show clean, high-resolution final renders. Professional video upscaling tools take the raw AI output and sharpen it to something worth posting. **Patreon (Process Documentation)** Not a production tool, but worth noting: Gerde publishes his workflows and tutorials for people who want to learn. The process is documented. The taste that makes it worth learning is the harder thing. ### Obsidian Fine Art Permit Review Initiated URL: https://www.thedaringcreatives.com/aegis/obsidian-fine-art-permit-review/ Last updated: 2026-08-01T19:43:48.000Z Wilson reports that Obsidian Fine Art has been under quiet Gray Glasses observation — the permit review may be connected to the gallery's recent experiments with generative AI in storytelling. _This post is for subscribers only._ ### The Loneliness of Building Before Anyone Is Watching URL: https://www.thedaringcreatives.com/loneliness-building-before-audience/ Last updated: 2026-08-01T19:43:49.000Z I've always loved the beginning of a project. That window where the enthusiasm finally tips over into action and you're just *going*. You're posting, you're building, you're putting stuff out into the world because you're genuinely excited about it. It doesn't matter that no one's watching yet. The energy is enough. And then it isn't. There's this stretch — and if you've built anything, you know exactly what I'm talking about — where the excitement starts to thin out and self-doubt walks in like it owns the place. Is what I'm doing worth it? Is all this effort going to turn into anything? Am I just yelling into a void? This is when everybody quits. I know because I've almost quit more times than I can count. Here's the part that messes with me: I know better. I've pushed through this phase over and over again. I've helped other people push through it. I know that if you just keep going, you eventually find the connection you're looking for. And yet, every single time I hit that stretch, I still question myself. Knowing the answer doesn't make the feeling go away. ## It's a lonely place Your friends aren't there. Your family isn't really there either — not in the way you need them to be. It's just you and this thing you care about and a whole lot of silence. Take The Daring Creatives. I'm deeply passionate about this — AI, creativity, helping people get started with tools that I think are genuinely powerful and enabling. And honestly, the community of people I've met over the last three years who have made similar commitments to dig in and learn AI? Some of the most inspiring people I know. Most of them I've never met face to face. Just people in online communities who I respect and care about. But when you choose to build something, you're saying goodbye to other things. Sometimes it's other projects. Sometimes it's beliefs you held. Sometimes it's boundaries you thought were permanent. And sometimes — and this is the one nobody warns you about — it's people. Friends you never imagined not having around. You just kind of look up one day and realize they're not really supportive of what you're doing anymore. Maybe they never say it directly. They just... aren't there. You hear this in every entrepreneur's story, right? The doubt, the adversity, the uncomfortable stretch that goes on way longer than you expected. But hearing about it and living inside it are two completely different experiences. When you're in it, the stories don't help much. It's just you, doing the work, wondering if it matters. ## And then someone raises their hand You get your first member. The first person who goes through a whole process — finds you, reads your stuff, decides it's worth their time, and actively signs up. They raise their hand and say, "Yeah, I'm here with you. I like what you're doing and I want to support it." That first person is everything. I'm not being dramatic. When I get a new subscriber to The Daring Creatives, I literally fist pump. I jump around in my office. It could be 11pm and I'm in the bathroom when the notification hits my phone — doesn't matter. That email comes in saying someone just joined, and I'm fired up all over again. It re-energizes me and makes me want to work harder, do more, keep going. Now, I know there's going to be a point where scaling this thing becomes its own massive challenge. And honestly? I've always been more interested in helping people build the thing than scale the thing. I saw someone's LinkedIn profile the other day and their headline said "I'm a zero to one builder." And I thought — I don't think there's a better description of how I see myself than that. I help you get from zero to one. A lot of people are focused on how to get to a thousand or a million or ten billion. And look, I get it. But there is no ten thousand, no million, no billion until there's one. ## So here's what I'd say Building something new is brutally hard. Taking an idea and making it real is one of the hardest things you can do. But it is so worth it. The feeling you get from the simplest thing — someone signing up for your email list, someone buying a sticker, someone just saying "hey, I see what you're doing" — that feeling is incredible. Whether it happens three months in or ten years in, it hits the same way. If you're in that lonely stretch right now, where no one's watching and you're wondering why you bother — I've been there. I'm kind of always there, honestly. But I keep going. And you should too. ### Highlands Sanctuary Garden Access Restricted URL: https://www.thedaringcreatives.com/aegis/highlands-sanctuary-garden-access-restricted/ Last updated: 2026-04-02T15:18:17.000Z Gray Glasses environmental compliance review places Highlands Sanctuary Garden under restricted access, requiring valid AEGIS transit pass for daylight-hours entry only. _This post is for subscribers only._ ### The Permission to Start Over URL: https://www.thedaringcreatives.com/the-permission-to-start-over/ Last updated: 2026-07-15T22:56:41.000Z We have this weird cultural belief that once you've established yourself in something, you owe it your permanence. Like if you've put in five years as a lawyer, pivoting to journalism is somehow a betrayal of those five years. I don't know where this comes from exactly, but it's everywhere. I've felt it. Most people I know have felt it. A creator going by [@floeditsvideos](https://www.threads.net/@floeditsvideos?ref=thedaringcreatives.com) posted on Threads this week that they became a lawyer at 28, a journalist at 34, and a video editor at 39\. The comment section was full of people calling it inspiring. Which it is. But I keep thinking about what they had to push through to get there each time — not the skill-learning, but the moment right before they started, when they had to convince themselves they were allowed to. The hard part is giving ourselves permission, not necessarily the things we need to do to reinvent. ## The counterargument is real You could argue that your output should stand on its own — that a career pivot is a personal decision and the world doesn't actually owe you continuity. But in practice, the sunk-cost logic is sticky. It doesn't matter that it's irrational. It still lands on you every morning when you're trying to decide whether to make the move to start something new. And the people around you don't help. "But you've worked so hard to get here." Yeah. And now I want to work hard somewhere else. That's allowed. ## The entry point isn't the starting point Here's the thing about serial reinvention that gets undersold: your past doesn't disappear. The lawyer who becomes a journalist brings analytical precision and an understanding of how institutions actually work. The journalist who becomes a video editor brings storytelling instincts that a straight-from-school editor might spend years trying to build. You're not starting over from zero. You're starting with a [completely different entry point](https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/). I've written about this before in the context of AI — the skills you've built as a storyteller or a researcher or a communicator aren't soft skills, [they're your actual edge](https://thedaringcreatives.com/context-curator-soft-skills-ai/?ref=thedaringcreatives.com). I was slow to figure this out myself. I spent more time than I should have trying to optimize the path I was already on instead of being honest about what I actually wanted to do. Not because the path was wrong exactly, but because switching felt like admitting something. I don't even know what. Failure? Inconsistency? Both? Neither? There was a period where I was running a freelance chapter and felt like I was working constantly — more than I ever had — and still couldn't tell if it was working. If any of this sounds familiar, [I wrote about that feeling too](https://thedaringcreatives.com/trade-offs-autonomy-freelancing/?ref=thedaringcreatives.com). The pivot out of it was one of the better decisions I've made. ## The skill underneath the skill What the person on Threads actually built across three careers wasn't just legal fluency, editorial instincts, and editing chops. They built the ability to give themselves permission to start. And that turns out to be [the skill nobody puts in the job description](https://thedaringcreatives.com/the-skill-that-nobody-puts-in-the-job-description/?ref=thedaringcreatives.com). The first pivot is the hardest because you have no evidence it works. The second one is hard but you've done it before. By the third one, you probably don't even call it a pivot anymore — you just call it deciding. If you're sitting on a move right now, waiting for something to make it feel safe enough — that's the thing. There's no version of this where it feels safe enough first. You decide, and then you go find out it was right. Not that you need it, but here is your "permission" to start over. ### LCAM Heritage Wing Suspended URL: https://www.thedaringcreatives.com/aegis/lcam-heritage-wing-suspended/ Last updated: 2026-04-02T15:18:19.000Z Gray Glasses compliance review suspends LCAM Heritage Wing public programming indefinitely. _This post is for subscribers only._ ### What Anthropic's March 2026 Economic Index Report Actually Says About AI and Creative Work URL: https://www.thedaringcreatives.com/anthropic-economic-index-creatives/ Last updated: 2026-08-01T19:43:49.000Z Anthropic published two major research pieces this month — the March Economic Index report (they're calling it "Learning Curves") and a full labor market study on AI's actual impact on jobs. I went through both of them because I had a feeling the headlines were going to miss the most interesting parts. And yeah, they kind of did. "AI might cause a Great Recession for white-collar workers." "Power users are pulling ahead." Those aren't wrong, exactly. But if you make things for a living — writing, design, music, video, visual art, anything in that orbit — the actual data is more nuanced than either the doom or the hype. Here's what I actually found. 💡 Read the report yourself here: [Anthropic Economic Index report: Learning curves](https://www.anthropic.com/research/economic-index-march-2026-report?ref=thedaringcreatives.com) ## The gap between what AI can do and what it's doing is the whole story The labor market paper introduces a distinction between "theoretical AI exposure" and "observed AI exposure." Basically: how much of your job *could* AI handle in theory, versus how much it's actually handling right now. For arts and media roles, the theoretical exposure is 83.7%. I know that sounds like a bad number. But the observed exposure — what Claude is actually being used for in creative work — is around 19.2%. What's getting automated in creative work right now is the boilerplate — rough drafts, production variations, resizing, copy that didn't need much thought to begin with. The original concept development, the direction, the relationship with an audience — that's still sitting firmly in human hands. The gap won't stay this wide forever. But it tells you something about the window you're working with. ## Creatives are in the tool more than almost anyone This one surprised me. Arts, design, entertainment, and media roles account for 10.3% of all Claude queries — second only to computer and math occupations. That's a huge chunk. It shows that creatives [aren't avoiding AI](https://www.thedaringcreatives.com/most-creatives-not-using-ai/) anymore. They're using it a lot. The Economic Index report found that augmentation — collaborative use where the AI is actually extending what a person can do — is increasing slightly. That's the good version of AI adoption. But there's a growing split between people using AI that way and people using it as a fancier search engine. I don't judge that at all because that was me at the start too. The issue is that the split is getting wider. The skills gap between those two groups is real. 0:00 /0:29 1× ## The stat that actually changed how I think about this After ChatGPT launched, demand for analytical, technical, and creative work grew by 20%. Not shrank. Grew! I sure wasn't expecting that. But it makes sense if you think about it. When you take routine production tasks off someone's plate, they don't suddenly want *less* creative output. Their appetite expands. More content gets made. More storytelling is *expected*. And the people who can meet that expanded appetite at higher quality are the ones who figured out how to use the tools well. ## So what does this actually mean if you're a creative Honestly, the question I'd ask isn't "will AI take my job?" It's "which parts of my job do I actually hate doing?" Because that's probably what's getting automated first. The research basically confirms this: the parts of creative work that AI is good at right now are the repetitive, production-side, boilerplate tasks. For me this looks like optimizing images for web delivery, doing research, or formatting rambling voice notes into coherence. The strategic, directional, original-concept stuff — the parts most people got into creative work for in the first place — those are still ours. My practical experience has been that knowing how to deploy AI well is becoming part of the job — not instead of creative skill, on top of it. I don't read the report as a warning that creatives are doomed. It's a pretty clear map of where the work is shifting. Worth knowing where you are on that map. ### The Memory Collector: How n.evernow Makes AI Feel Like a Dream You Almost Remember URL: https://www.thedaringcreatives.com/creator-stories/artist-profile-n-evernow/ Last updated: 2026-08-16T10:25:13.000Z I found n.evernow on [Instagram](https://www.instagram.com/n.evernow/?ref=thedaringcreatives.com). Her reels are shared quite a bit within the AI art community. And the first time I watched one , I made the same mistake everyone makes — I was so caught up in the look of it that I didn't immediately think to ask *how*. That, and I was in awe at her choice of music and sound as her taste in that is impeccable. Maria Pokrovskaya, who goes by n.evernow, makes AI films that don't announce themselves as AI. There's no hyper-real sheen, no cinematic "wow" moment, no attempt to prove what the tools can do or to replace reality. Her videos feel like fragments. Like trying to remember a place you haven't been to in twenty years. They have texture — the grainy, half-dissolved quality of a Super 8 film. It's an aesthetic I really dig. Her YouTube channel describes the work as "distant dreams, vague memories." It's a brief, honest description of the aesthetic she's spent hundreds of posts building. She has over 67,000 followers on Instagram and 943 posts. That density of work — nearly a thousand posts — is the first tell that you're not dealing with someone who stumbled into AI tooling and started posting. n.evernow — “Sougreve - Sign” ## The Work Starts Before the Prompt Maria is a multidisciplinary artist. Before AI became a medium for her, she worked across photography, video, installation, and digital art. Born in 1982 in Kuibyshev, Russia, her life has been shaped by displacement, political upheaval, and what she describes as "a continuous search for meaning through visual expression." That biographical context matters more than it sounds. A lot of AI art feels placeless and emotionally weightless. You can tell the person making it is chasing aesthetics, but not necessarily meaning. When people complain about generative AI art, it's usually about its lack of soul. Maria's work is different because she's bringing a life's worth of material to the tools — memory of specific places, specific feelings, specific losses. The AI isn't generating the emotion but it's helping her render something that already exists inside her. Her experiments with AI, as she's described them, "do not seek to simply replicate human creativity, but to interrogate it." She's asking questions about authorship. About what it means to make an image in 2026 when the machines can make images too. About whether the image is still yours when you didn't draw it. ## A Multi-Tool Workflow Built for Mood, Not Speed When you start looking at what Maria actually uses, a pattern emerges. She's a [Freepik AI partner](https://www.freepik.com/ai/partners?ref=thedaringcreatives.com). She holds a Creator Partner Program status with [PixVerse](https://app.pixverse.ai/onboard?ref=thedaringcreatives.com). She's a member of [Dreamina AI](https://dreamina.capcut.com/?ref=thedaringcreatives.com) and frmwrk.ai. Freepik gives her access to a broad generation pipeline — images, compositions, reference frames. PixVerse handles the video side, converting static frames into motion that feels dream-like rather than slick. Dreamina, built into the CapCut ecosystem, adds another generation layer that she can combine with the others. frmwrk.ai is a newer creative AI platform that she's been part of since early on. The fact that she holds official creator status with multiple platforms impresses me. She's deep in each one, learning its quirks, understanding its tendencies, [building a context](https://www.thedaringcreatives.com/context-is-your-creative-edge/) around how each tool responds. n.evernow — from her Instagram reels n.evernow — from her Instagram reels ## The Aesthetic Takes Work to Protect One thing that jumps out when you look at her feed as a whole: consistency. That grainy, dream-saturated look she's cultivated doesn't happen by accident. AI tools will give you something different every time you prompt them. Keeping a coherent visual identity across 943 posts over years of different model updates, different tools, and different capabilities — that requires constant, active editing. The [GossipGoblin article I wrote last year](https://www.thedaringcreatives.com/creator-stories/the-work-hidden-inside-gossipgoblins-worlds/) talked about how Zack London ran "probably 400 prompts / 1600 images" just to get faces right for a single piece. Maria's version of that stubbornness is quieter — it shows up in the texture and restraint of her output, not in cinematic spectacle — but the underlying logic is the same. The work you see is a tiny fraction of what got made. There's a version of [this conversation about craft versus output](https://www.thedaringcreatives.com/the-slop-about-slop/) that misses the point. People look at AI-generated work and see the speed of the output and assume that's all there is. They're not seeing the editorial intelligence that decides which outputs get used and which ones don't. Maria's feed is a record of those decisions, made one post at a time for years. ## What the Tools Can't Do AI is handling the image-making, but the *knowing what to make* part is entirely human. And that's the harder problem. She's working from personal history. From specific memories of Russia, of dislocation, of loss. She translates them into prompts, into reference images, into combinations of tools. The tools are rendering her inner life — but she has to know her inner life well enough to direct that rendering. That's not nothing. That's actually most of the work. n.evernow — “TO DUST. A Fable About the Limits of Absolute Power” Her pieces feel like what it feels like to be a person who has moved between lives — the way identity can blur at the edges, the way memory degrades but doesn't disappear, the way something can feel both foreign and intimate at the same time. You don't make work that specific by just typing things into Midjourney. The [question about what it means to adopt an AI workflow](https://www.thedaringcreatives.com/adopting-an-ai-workflow/) often gets framed as a skills question. Can you prompt well? Do you know the right parameters? But Maria's work points at a different question: do you have something to say? The tools give you the capacity. The content still has to come from somewhere. She has content. Decades of it. And she's built a toolset specific enough to let it out. ## n.evernow's Toolkit Maria hasn't published a single definitive process breakdown, but her partnerships and output make the stack reasonably clear. Here's what she's working with: **Freepik AI Suite** Her primary generation environment for still images and composition work. As a Freepik AI partner, she's embedded in their full toolchain including Mystic and Flux-based models for image generation. **PixVerse** Her go-to for animating still images into video. As an official PixVerse Creator Partner (CPP), she uses it for the dreamlike motion that defines her work — slow drift, soft transitions, movement that feels more like breathing than action. **Dreamina (via CapCut)** An AI art and video generation tool that she uses alongside PixVerse, likely for generation, style blending, and additional video passes. **frmwrk.ai** A creative AI platform she's been part of since early on — likely used for workflow management, asset generation, and cross-tool integration. **Photography and Video Background** Before AI, she was making work with cameras and editing software. That production literacy shows — she understands light, composition, and timing in a way that shapes how she uses generative tools. It's not just prompting. It's directing. ### Museum of Tomorrow Workshops Halted URL: https://www.thedaringcreatives.com/aegis/museum-of-tomorrow-workshops-halted/ Last updated: 2026-03-30T19:05:36.000Z Museum of Tomorrow suspends all independent operator workshops for the current quarter, citing supply chain irregularities. _This post is for subscribers only._ ### The Skill That Nobody Puts in the Job Description URL: https://www.thedaringcreatives.com/skill-ai-cant-replace/ Last updated: 2026-08-01T19:43:50.000Z Everyone's asking the same question right now: what happens to my job when AI can do what I do? It's a fair question and I think about it too quite a bit. I think the honest answer is that technical skill is becoming a commodity. The things that used to require years of practice — editing footage, writing copy, building a website — are going to be accessible to anyone, for almost nothing. That future isn't coming. It's here. ## The Thing That Was Never on My Resume But here's what I keep coming back to when I think about my own career: the thing that actually made me good at my jobs was never on my resume. I've done a few different things professionally. And when I think about what separated me from the next person — the actual deciding factor when everything else was roughly equal — it was soft skills every time. I'll use videography as the example because it's specific and I lived it. When companies post for a videographer, the job description is almost always the same: must know Premiere, must have shot on a RED, must have X years of experience in corporate or documentary work. Technical checkboxes. Every single time. What they never ask: Can you make someone comfortable on camera? Are you a good interviewer? Can you read a room and adjust in the moment? Nobody puts that in the job posting. But that's the whole thing, right? That's the part that determines whether you come back with footage that's technically clean or footage that [actually captures something](https://www.thedaringcreatives.com/adopting-an-ai-workflow/) real. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/03/interview-subject-on-camera-monitor-closeup-soft-skills.webp) ## The Other Side of the Camera I got into videography partly because I was on the other side of it once. I was being filmed and the person directing me was awful at the people part — not the technical part. Her camera work was fine. But she made me tense, uncomfortable, guarded. Everything I said on camera came out wrong. And I thought: the technical stuff can be learned in a few years. The thing this person is missing? Not making the person you're filming feel like shit. Most of my peers in videography focused almost entirely on the craft of the image — the reel, the angles, the color grade. Almost none of them were asking how to make the person being filmed feel safe enough to be honest. Especially in corporate work, where people are already stiff and performing, that's the whole job. And it was invisible. ## The Gap AI Will Only Widen With AI, this gap is only going to get wider. Everyone's going to be able to produce technically proficient work. The image quality, the edit, the composition — that's going to be table stakes. What can't be automated is taste, judgment, and the ability to make another human being feel understood. The problem is that "taste" and "psychological safety" and "rapport" are incredibly hard to put in a job posting. You don't learn about them from a portfolio — you learn about them from a conversation. From watching how someone handles pressure, or how they talk about the people they've worked with. I don't think companies are going to get better at hiring for these things anytime soon. But I do think the people who've invested in them — who've made it their thing to [actually be good](https://www.thedaringcreatives.com/ai-image-consistency/) with people — are going to look very different on the other side of this. The commodity isn't coming for the soft skills. ### My Week with Claude Cowork URL: https://www.thedaringcreatives.com/my-week-with-claude-cowork/ Last updated: 2026-07-21T19:30:26.000Z I paid $100 for a Claude Max subscription on a Friday night. By Saturday morning, I'd already gotten my money's worth. By Sunday, I had 11 automated tasks running across two machines. By the end of the week, I was genuinely questioning what I'd been spending my time on for the last six months. This is that story. ## The $100 Bet I'd been using Gemini for everything — coding, writing, research. [I'm certified in it](https://www.thedaringcreatives.com/reviewing-the-google-ai-professional-certification-from-coursera/). I know the ecosystem well. But Anthropic kept shipping features that made me stop what I was doing and stare at my screen. Every day last week, something new. And the thing that finally got me to open my wallet was a feature called Cowork. Cowork is, in the simplest terms, an AI that can control your computer. It sits in the Claude desktop app, and it can open browsers, click things, type things, navigate websites, read your screen, and automate tasks that would normally require you to be sitting there doing them yourself. I know that sounds like what every AI company has promised for the last two years. The difference is this one actually works. ## Teaching It My Taste The first thing I did was point it at my social media growth problem. I run The Daring Creatives across [Threads](https://www.threads.com/@thedaringcreatives?ref=thedaringcreatives.com), [Instagram](https://www.instagram.com/thedaringcreatives/?ref=thedaringcreatives.com), [YouTube](https://www.youtube.com/@TheDaringCreatives?ref=thedaringcreatives.com), and [LinkedIn](https://www.linkedin.com/company/the-daring-creatives/?ref=thedaringcreatives.com). Growing these accounts takes hours every day — finding the right people to follow, engaging with their content, posting consistently, analyzing what's working. Hours I don't really have, doing work that isn't exactly creative. So I trained Claude on what I care about. It already had context on me — my biography, my content pillars, 62+ articles I've written for the website, my aesthetic preferences. I gave it more. What kinds of art I find interesting. What types of creators I want to connect with. What a good follower-to-following ratio looks like. Whether someone posts regularly or hasn't touched their account in months. And then I told it: go find people on Threads and Instagram who fit this profile, follow them, and like a few of their posts. Not randomly. With judgment. ## The Nightly Run Every night at 10 PM, my computer comes alive. Claude opens the browser, navigates to Threads, and starts working. It looks at profiles, evaluates the content, checks the ratios, reads bios, and makes decisions about who to follow. For each person, it likes two or three posts — not just the most recent ones, but the ones it thinks I'd actually appreciate based on everything it knows about my taste. On Instagram, it's a similar process but more conservative. I'm only adding 10-15 people per day there because Instagram's rate limits are tighter and my content strategy for that platform is still evolving. The numbers behind all of this were backed into from a goal: I want 75 new followers per week on Threads and 25 on Instagram. Using standard follow-back conversion rates, that dictates how many people Claude needs to follow each day to hit those targets. It's math, not guessing. When the run finishes, I get a report. Here's who was followed. Here's why. Here's what I liked. Here's the observations from tonight's session. The first morning after, I woke up to 7 new followers. Passively. Without thinking about it. ## The 14-Day Cleanup Here's the part that makes this feel like a real system instead of just a bot. Every person Claude follows gets tracked. After 14 days, if they haven't followed back, they go into an unfollow queue. I can intervene if someone's valuable to me regardless of reciprocation, but the default is to keep the ratio clean. It also runs smart protection checks before unfollowing anyone. Verified accounts stay. Accounts with 50K+ followers stay — those are brands or public figures and I don't expect them to follow back. It checks bios for keywords that suggest someone's an institution or creator worth keeping. The unfollow system has taste, same as the follow system. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/03/closeup-man-yellow-sunglasses.webp) ## The Calendar Hack One of my favorite discoveries this week was a workaround for a real limitation. Claude's Gmail connector can read emails but can't send them. So I couldn't use email as my reporting hub. What I could do was use Google Calendar. Google Calendar lets Claude update event descriptions through its MCP server connection. So now, every automated task has a corresponding calendar event. Tasks that haven't run yet show up in red. When a task completes, it updates the event description with the full report and flips the color to green. I open my calendar and I can see exactly what ran, what it did, and what's still pending. It's kind of beautiful, actually. ## The Content Pipeline Beyond the social growth stuff, I set up a content pipeline that pulls themes from my existing articles and creates conversation starters for Threads. These one-liners serve as the de facto comment section for the website — each article links to a threaded discussion where the topic is being debated. This was the third leg of the strategy. I'm still posting my own ideas and responding to people manually. That's the part that should stay human. But having a system that ensures something goes out every day, something connected to the deeper content I've already written, that consistency is what compounds. ## The Model Matching Game Something I learned on day two: you can assign different AI models to different tasks. For basic browser work — navigating Instagram, scrolling through profiles, clicking follow buttons — I use Sonnet 4.6\. It's fast and cheap. But when it comes to analyzing engagement data and making creative decisions about what content to post, I switch to Opus 4.6\. Better reasoning, better taste. Matching the model to the task turned out to be a real optimization. It's like hiring different people for different jobs instead of asking one person to do everything. I started thinking of it as managing a small team of specialists, each with their own strengths. ## The Stuff Nobody Talks About Let me be honest about the limitations, because everybody on the internet right now is just circle-jerking about how amazing Claude is, and while I agree, there are real rough edges. The browser agent is slow. Way better than it was a year ago — I tried Operator from OpenAI back then and it was damn near unusable. This is probably three times faster. But it's still the bottleneck. When Claude is controlling Chrome, you can't use that browser for anything else. And if something times out or a page loads weirdly, the whole task can stall without completing the reporting step. The Gmail integration is limited. Read-only access means you're constantly working around the fact that it can't send emails. The calendar hack works, but it feels like duct tape. And honestly, Google still connects to more of the ecosystem I use. Gemini plays nicer with Docs, Sheets, and Gmail because it's all the same company. Claude is better at automation and reasoning, but the integration story still has gaps. I ended up using both — Gemini for writing and research, Claude for automation and browser tasks. ## The Bigger Picture By day three, I had 11 tasks automated. Social media growth across two platforms. Content distribution from my article archive. Analytics tracking. Inbox cleanup — Claude went through 25,000 emails, organized everything into folders, pulled receipts for taxes, fixed broken filters that were sending important stuff to junk. It even helped with tax prep, sitting with me like a patient accountant, going through expenses, categorizing deductions, calculating mileage write-offs. I'm running Cowork on two machines now. And I'm doing all of this development during Anthropic's double-usage off-peak promotion, which gives me room to pressure test these automations without worrying about hitting limits. The approach I've landed on is smaller, focused tasks across multiple agents rather than trying to build one massive automation that does everything. Each agent handles part of a process and documents its output for the next one to pick up. Whether that's the best approach long-term, I don't know yet. But it optimizes for reliability, which matters when you're trusting a machine to represent you on the internet. ## What This Actually Means Here's the thing I keep coming back to. Social media management is going to become a task, not a role. The same way typing became a task. Nobody hires a typist anymore. The skills are still valuable — understanding audiences, knowing what resonates, having taste — but the execution layer is getting compressed. I've been calling the role that replaces it something like a Context Curator. Someone who understands the full picture well enough to direct AI systems with judgment. The tools to make that role possible literally didn't exist two months ago. And now I'm living it. This has been the most fun time of my professional life. I feel like I'm doing a hundred times better work than I was three years ago. And at the same time, the most uncertain, because the ground keeps shifting under everyone's feet. But that's exactly why this stuff matters. Go build something. ### Dispatch #5: Connection Stable URL: https://www.thedaringcreatives.com/aegis/dispatch-5-connection-stable/ Last updated: 2026-04-02T15:18:29.000Z Alright, you’re in. If you can read this, the Pirate Handshake held and you successfully bypassed the routing board. Welcome to your modified AEGIS Data Terminal. _This post is for subscribers only._ ### Toxic @Threads: Someone posted their first image, the internet killed them for it. URL: https://www.thedaringcreatives.com/toxic-threads-first-image-backlash/ Last updated: 2026-08-01T19:43:52.000Z I posted a [three-part thread](https://www.threads.com/@thedaringcreatives/post/DWAwKuLFWh0?xmt=AQF0Jmz2%5Fhy-RXs9vID7Xmq2B4ZXi7W8JIxw7O9usnG7ug&ref=thedaringcreatives.com) on Tuesday night. It wasn't complicated. Here's the thread, if you missed it: > *"Someone posted their first AI-generated image yesterday. It wasn't perfect. The hands were weird. The lighting was off. They were proud of it. And the comments were exactly what you'd expect. 'Slop.' 'This isn't art.' 'You didn't make anything.'"* > *"You know what that person did? They showed up. They tried a new tool. They shared something they made with strangers on the internet knowing full well someone might tear it apart. That takes more guts than most of the critics will ever have."* > *"Every creative you admire was once the person posting something imperfect. The ones tearing people down for learning in public were never brave enough to start."* The subject wasn't whether AI art is good. It wasn't a defense of the technology. It was a simple point about how creative communities treat beginners. By Wednesday morning, 11,300 people had seen it. 122 replies. And almost none of them engaged with what I actually said. ## The Responses: A Field Guide The replies broke into a few distinct groups, and they're worth naming because they show up in almost every AI conversation on this platform right now. ### **The One-Word Verdict** These are the people who typed "Slop" and called it a day. @laurenspahrta. @the.cyberhaggis ("Slop is slop. Clanker apologists make me sick."). @ayplejuice ("The comments were correct."). @ryannewyork ("Good comments."). The word "slop" has become a [tribal signal](https://www.thedaringcreatives.com/the-slop-about-slop/) — a way of showing which side you're on without having to actually say anything. I watched it show up in reply after reply, identically, as if there was a script. ### **The "They Didn't Make Anything" Camp** This one is at least engaging with the words. @billdbethel: *"Why would anyone be proud of typing a prompt?"* @cortinariustorvus: *"They should not be proud of anything AI does; it's nothing to do with them."* @bradgalvatron: *"LMFAO they didn't make anything. Shut the fuck up."* Whether prompting constitutes "making" is a legitimate question. But notice what's happening here — the conversation has shifted entirely from the person who posted to the technology they used. The beginner, the human, the person who was proud of something for five minutes before the internet got to them — they've been erased from the conversation entirely. ### **The Art Theft Argument** This is another argument born out of feeling like a victim, a trait I have virtually no respect for. @dyodonut put it directly: *"You want me to extend grace to someone who had a tool that steals my art regurgitate some abomination of it and pretend they're brave for that or something? Are you well? 😭"* @mikemystery (verified) went further: *"'Showing up' is the minimum of effort. They made nothing. They created nothing. They betrayed the solidarity of every creative worker whose work has been ground up into the billionaire's slop engines. It doesn't take 'guts' to cross that ethical picket line. It just takes sharp-elbowed selfishness."* ### **The Ad Hominem Section** Then there's the part of the comments section I can't really argue with, because there's nothing there to argue against. @professor\_neil: *"Just say you're a talentless hack with a humiliation kink."* @bendrake: *"You're a fucking moron."* @un.ap0l0getic: *"shut up loser."* I've stopped being surprised by this. These replies aren't for me. They're for the person typing them. ## What Nobody Said Here's what struck me after going through all 50+ responses we cataloged. Almost nobody addressed the actual argument. Not one person said: *"You know what, you're right that we can be too harsh on beginners — but AI is a special case because..."* That would have been a conversation worth having. Instead, the post became a Rorschach test. People saw it and immediately projected: AI defender. Grifter. Tech bro. Slop pusher. @*carrina* asked if AI wrote the post. @theratcouch asked if ChatGPT wrote it. @amalia\_quota pointed out I was liking my own posts. @122\_and\_an\_8th wrote an elaborate pizza delivery analogy to explain why the person who ordered the pizza shouldn't call themselves the chef. As a matter of fact, AI did help with creating the post. And you replied to it, as did a bunch of other people. It was by far my most successful thread in terms of views, likes, and comments. If you're curious about my workflow for creating my social media content, you can read about it [here on the site](https://www.thedaringcreatives.com/adopting-an-ai-workflow/). When a community is this triggered by a question about beginner grace, it tells you something about the pressure those people are under. The AI debate has gotten so heated, so fast, that even adjacent conversations get pulled into it. I wasn't asking anyone to love AI art. I was asking people to be decent to someone who was proud of something for the first time. That question was treated as a threat. ## The Bigger Picture: Gray Glasses in a New Form I've talked before about Gray Glasses — self-righteous gatekeepers who only want to talk about how they have been taken advantage of. People who see the world in the most negative, pessimistic light. What I saw in these replies is a specific version of that: the Creative Gatekeeper. And unlike the tech gatekeepers [I've written about](https://www.thedaringcreatives.com/toxic-threads-creative-gatekeeping/), this one comes wrapped in something that feels like righteous anger and social justice. There are real grievances underneath it — AI training data, *stolen* livelihoods, an industry being restructured by forces outside anyone's control. But the Creative Gatekeeper has redirected that anger at the most available target: the person who just started. The person who typed a prompt for the first time, got something back, posted it with a little pride, and then got told they were a thief, a fraud, and a contributor to the death of human creativity — all in the same afternoon. That's who they're aiming at. ## The Shift 11,300 people saw that thread. Most of them didn't comment. A few hundred of them agreed with it quietly — a like, a repost, a small reply that got buried under the noise. That ratio matters. The people screaming are not the majority. They're just the loudest. If you posted something for the first time and got that treatment — keep going. The comments section of Threads is not a jury. It's a room full of people arguing about a fire they're convinced is already out of control. Your job isn't to convince them. Your job is to post the next one. *Have you been on the receiving end of this? Or do you think the critics have a point worth defending? I'm continuing this conversation about* [*giving beginners grace*](https://www.threads.com/@thedaringcreatives/post/DWAwKuLFWh0?xmt=AQF0Jmz2%5Fhy-RXs9vID7Xmq2B4ZXi7W8JIxw7O9usnG7ug&ref=thedaringcreatives.com) *over on Threads. Come find me at @thedaringcreatives.* ### How to Stop Abandoning Your Ideas URL: https://www.thedaringcreatives.com/stop-abandoning-your-ideas/ Last updated: 2026-07-15T22:56:42.000Z One of the most overlooked aspects of AI isn't about making things faster or cheaper. It’s about solving a problem that almost every creative person wrestles with: getting wildly excited about a new idea, building it out, and then abandoning it right before it has a chance to actually take hold. I see this constantly. Over the years I've been blessed to work with some brilliant clients who all have an endless stream of ideas. A few months ago, my absolute priority was video. We were going all-in. Then, a few weeks later, the focus shifted entirely to getting into galleries and art shows. Shortly after that? Email marketing and thought leadership. My belief is that every single one of those directions is perfect. All of them can help him reach his objectives. But if you only spend a couple of weeks executing one before pivoting to the next, none of them will work. This isn't a critique of my client. It's a critique of myself. This is exactly how my mind works, too. ## The Blessing and Curse of "The Daring Creative" If you are a curious person—if you have ADHD, or if you simply love exploring the frontier of what’s possible—you recognize this cycle. These traits are exactly what make someone a "Daring Creative." We are built to explore. But that exploration comes with a cost. I’ll go through periods where I am deeply, singularly interested in a specific platform or project. Lately, I have been on a tear with Meta Threads. It reminds me of the old Twitter days, but with much better creator controls. For the last couple of months, it's been the most important thing in the world to me. But this weekend? All I could do is dig into Claude Cowork. It's all I think about, how to automate my process. I’ve been doing this long enough to know the pattern. Eventually, my attention will drift. I’ll get interested in something entirely different, and I'll stop talking about Threads or Claude. And the hard truth about growing online is that when your activity lags, your growth lags with it. You lose the momentum you just spent weeks building. ## Setting the "Attention Floor" This is where my relationship with AI has fundamentally shifted. I am no longer just using it to brainstorm or generate images; I am using it to build and execute on things to keep me active on more than one thing. Recently, I started using AI tools to offload the mechanical tasks related to growing my social media presence. The goal isn't to automate my activity away. The goal is to set a "floor" for my attention—a minimum level of presence that ensures I don't disappear when my mind moves elsewhere. I use these tools to identify where people are asking questions that I actually have the expertise to answer. Right now, we are taking baby steps: the AI identifies candidates for outreach, drafts a response based on my previous writing, and asks for my approval. It ensures that every day, I am providing value to people who might be candidates for becoming "Daring Creatives" themselves. ## Building for the Pivot This is totally game-changing. It completely reframes how I look at my own bursts of inspiration and attention. Now, when I get a new direction to go in—when the hyper-fixation kicks in—I don't just spend a few weeks doing the manual work before burning out. I spend those few weeks building out the AI infrastructure and support systems for that specific initiative. I capture [the context](https://www.thedaringcreatives.com/context-curator-soft-skills-ai/), design the workflows, and teach the models exactly how I want things executed. I can easily see myself training these tools up enough that they can handle basic outreach and communication autonomously. When someone asks a question I have an answer to, the system responds. The result? When my curiosity inevitably pulls me toward the next big thing, the previous initiative doesn't die. It just transitions from manual effort to automated momentum. AI allows you to be as multi-passionate and easily distracted as you naturally are, without paying the price of inconsistency. You get to keep exploring, and the machine makes sure the plates you spun up keep spinning. ### Dispatch #4: The Pirates Handshake URL: https://www.thedaringcreatives.com/aegis/dispatch-4-pirates-handshake/ Last updated: 2026-08-01T19:43:54.000Z The clock strikes midnight. Wilson has been at the workbench for six hours. An AEGIS data terminal is sitting there in the middle of the floor—a heavy, scuffed block of beige industrial plastic. _This post is for subscribers only._ ### Toxic @Threads: So You Think You're an Entrepreneur Now? LOL. URL: https://www.thedaringcreatives.com/toxic-threads-entrepreneur-critics/ Last updated: 2026-08-01T19:43:58.000Z I’m back on Threads, and the gatekeepers are back out with a vengeance. The thread started with a standard-issue dismissal from a developer: > *“Vibe coders, listen to me: You're building something that was already built in 2020.”* — @lucamarchicaa. My response was a simple one: *“Something that was built in 2020... That I don’t have to pay for now.”* But then came the pivot. Another user, @xor22h, lunged into the conversation with a pre-packaged insult I didn't even prompt: > *“Sure, instead of paying for working solution - now you pay for hosting your own SaaS and all the AI credits. But at least, you can call yourself an entrepreneur now.”* The funny thing? I never claimed to be an entrepreneur. I was talking about [code and costs](https://www.thedaringcreatives.com/reality-of-ai-subscriptions/). But for the gatekeeper, that word is a weapon—a title they believe they’ve locked inside a vault that only a 15-year career can unlock. ## The Setup: Identifying the "Gray Glasses" When I read that jab about entrepreneurship, I immediately recognized the lenses. This guy is wearing **Gray Glasses**. As I’ve written before, these are the glasses that turn every innovation into evidence of decline. Through those lenses, a new tool isn’t a way to build; it’s a way to ["cheat" or worse, steal.](https://www.thedaringcreatives.com/conversations-with-code/this-is-not-the-theft-youre-looking-for/) A new person solving a problem isn't a peer; they’re a "wannabe" playing pretend with a title they haven't "earned." ## The State of the World This gatekeeper brought up entrepreneurship because he thinks it’s all about making money (or taking it away from him). He’s wrong. To many, entrepreneurship is a survival mechanism. It thrives in three specific conditions: 1. **Great technological advancement.** 2. **A crisis (like a global pandemic).** 3. **Mass unemployment.** We are currently living in a historical trifecta. When companies stop hiring, when a pandemic forces a massive pivot, and when technology like AI levels the playing field, people don’t wait for a "15-year career" to start building. They do their own thing because they have to. They aren't trying to be "tech bros" or get a VC-funded office. They are trying to support themselves in a world that has stopped offering them opportunity. To mock someone for "paying for AI credits" while they try to build a life is seriously week. Have you ever started a business? It's brutal. These people deserve support, not sarcasm from the back of a 15-year career (not that much in the grand scale of things). ## AI as the Survival Kit If you’re a new entrepreneur, AI isn't a shortcut—it's your [best friend](https://www.thedaringcreatives.com/trade-offs-autonomy-freelancing/). It’s the tool that lets a storyteller, a designer, or a laid-off creative [build the infrastructure](https://www.thedaringcreatives.com/autonomy-changes-what-you-make/) they used to have to hire a gatekeeper to manage. It bridges the gap between a "sad" project and a functioning business. The gatekeeper thinks you’re "paying for AI credits" to buy a title. In reality, you’re paying for the autonomy that he’s spent 15 years trading away. **The Shift:** If someone tries to "wannabe" you or gatekeep a title you didn't even ask for, remember: they are defending a world that’s different than the one we live in right now. Entrepreneurship isn't a badge of honor bestowed by veterans. It’s a tool for the curious and the desperate. In a world of Gray Glasses, the smartest thing you can do is keep building—whether the gatekeepers think you’ve earned the title or not. **Are you building out of curiosity or necessity? I’m talking about the rise of the "New Entrepreneur" and the tools that make it possible over on Threads. Join the conversation with me there. Connect on @Threads** ### Nano Banana Pro 2 Isn't Always Better—Here's When to Use Each URL: https://www.thedaringcreatives.com/nano-banana-pro-2-comparison/ Last updated: 2026-08-01T19:43:59.000Z *Note to readers: Nano Banana 2 has been out for a few weeks now. In the world of AI, that’s practically a lifetime. So we're not breaking news with this post, but I wanted to sit with it, use it in my actual workflow, and see if the "magic" held up once the new-tool smell faded before commenting.* If you’re running a creative business in 2026, you’re likely playing a constant game of "Subscription Tetris." You’re looking at your monthly statements, seeing $20 here and $30 there, and wondering why you need three different AI models to do one job. Lately, I’ve been eyeing the exit door for my ChatGPT Plus subscription, used right now only for image generation. Don't get me wrong, ChatGPT has been the backbone of the aesthetic you see here at *The Daring Creatives*. But my goal has always been a leaner, more integrated pipeline. Right now, I use Gemini for everything outside of image generation. Then Google dropped the news about **Nano Banana 2**. ## The Promise of Nano Banana 2 Google is framing Nano Banana 2 as a massive leap. It’s faster, it’s supposedly "smarter" at interpreting complex creative intent, and it’s integrated deeper into the Google ecosystem. For companies of one (or a few) this is the type of integration you want. The idea of having your research, writing, and image generation all living inside one model is a dream. But here's something I didn't realize until I experimented with the new Nano Banana 2\. It's not the best for all situations. Sometimes, Nano Banana Pro did a better job. I wanted to know why, so I dig a little deeper. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/03/nano-banana-model-comparisons.png) ## Nano Banana 2 vs. Nano Banana Pro: Which is best for what application? One thing the recent documentation makes clear is that Nano Banana 2 (Gemini 3.1 Flash Image) isn't just a "cheaper Pro." It’s an entirely different design philosophy. - **Nano Banana Pro** is your **Studio-Grade Engine**. If you need immaculate text rendering for packaging design, complex spatial logic for an architectural blueprint, or rigid adherence to a JSON-structured layout, the Pro model is the only answer. It "thinks" longer because it’s calculating the physics of the scene before it ever drops a pixel. - **Nano Banana 2** is your **Real-Time Assistant**. It’s built for "Flash speed." It’s actually outperforming the Pro model in general aesthetic benchmarks—things like color saturation, texture, and pure visual impact. It’s the tool for rapid prototyping and creative brainstorming. ## Using Nano Banana? Try Google Flow While you can toggle between models in the standard Gemini app by using the "Regenerate with Pro" option in the three-dot menu, **the best way I have found for selecting one or the other, while getting the most out of both models, is to use Google Flow.** Flow is like Google's dedicated AI image and video app. Because it is designed for filmmaking and narrative consistency, it treats image generation as an "ingredient" in a larger process. In Flow, I can rapidly cycle through Nano Banana 2 for storyboard frames and then selectively "up-res" or refine key assets using the Pro engine without losing context. It feels less like a chat bot and more like a dedicated creative suite that understands the difference between a rough sketch and a final render. ## The Transparency Issue Despite the leap in quality, here is my main gripe with both models: **Where is the transparency?** I don't mean ethical transparency (though that matters). I mean literal, alpha-channel, `.png` transparency. For a professional creator, a flat JPEG with a white background is not so great. To make Nano Banana 2 truly useful for my pipeline—to the point where I’d actually cut the cord with OpenAI—Google needs to nail the ability to generate transparent assets. I need to be able to pull a character, a mascot, or a UI element and drop it directly into my Ghost theme or a video project without spending ten minutes in Photoshop cleaning up "AI artifacts" around the edges. ## The "Stylistic" Moat Beyond the technical hurdle of transparency, there’s the issue of **Soul**. I’ve built a very specific visual language for this brand. It’s a mix of gritty realism and high-contrast neon. Right now, ChatGPT understands that "vibe" in a way that ChatGPT's output that anchors *The Daring Creatives*. Nano Banana is close, but not there just yet. I *want* to consolidate. I *want* to save that $20–$30 a month. But you can't put a price on the integrity of your visual voice. ## The Path Forward Nano Banana 2 looks like an incredible technical achievement. The speed alone makes it a contender. But "fast" doesn't matter if the output requires more human labor to make it "production-ready." I’m going to continue using Nano Banana 2 (and Pro) heavily over the next few weeks. I want it to win. I want the lighter, faster, cheaper stack. But until I can get a transparent character that fits into my worlds without a struggle, I’ll be keeping my other subscriptions active. **Are you trying to consolidate your AI stack? Or are you happy playing "Subscription Tetris" to get the best results? Let’s talk about it on** [**Threads**](https://www.google.com/search?q=https://www.threads.net/%40thedaringcreatives&ref=thedaringcreatives.com)**.** ### Google AI Professional Certificate Review: Is It Worth It? (2026) URL: https://www.thedaringcreatives.com/google-ai-professional-certificate-review/ Last updated: 2026-08-01T19:44:00.000Z [Eric Schmidt got booed at a graduation ceremony](https://www.theverge.com/ai-artificial-intelligence/932203/university-of-arizona-students-boo-eric-schmidt-ai-commencement?ref=thedaringcreatives.com) last week for cheerleading AI to students about to enter a job market that feels increasingly hostile to human workers. The timing couldn't be more perfect for talking about Google's AI Professional Certificate, which just crossed 635,000 enrolled students and is quietly reshaping how we think about AI education. Google's AI Professional Certificate launched in February. A few months in—with the credential rolling out into actual job searches and the AI job market getting weirder by the day—what looked like just another big-tech course has revealed itself as something more interesting. This isn't just about one certificate program. It's about how tech giants are rebuilding education inside their own ecosystems—and what that means for the rest of us trying to figure out where we fit in an AI-driven economy. ## The Numbers Tell a Story Over 635,000 people enrolled in Google's AI Professional Certificate within weeks of its February launch. To put that in perspective: that's more people than live in most major cities, all trying to learn the same thing at the same time. Not AI engineering. Not machine learning theory. Just practical fluency with AI tools like Gemini, NotebookLM, and Google AI Studio. The program costs $49 on Coursera if you knock it out in a month (which most people do—it's designed for 8-10 hours total, though some finish in four). Google developed the curriculum by analyzing job descriptions with partners like Walmart, Deloitte, and Verizon to figure out what employers actually want. The result is seven courses that walk you through building over 20 hands-on projects, including what Google calls "[vibe coding](https://www.thedaringcreatives.com/beginners-guide-vibe-coding/)"—building simple apps through conversational AI without writing traditional code. Here's the kicker: Google gives you a three-month trial of their AI Pro tier when you enroll. You're not just learning about their tools. You're learning *on* their tools while they credential you *in* their tools. That's a closed loop that would make any [business school](https://www.thedaringcreatives.com/context-curator-soft-skills-ai/) professor weep with admiration. ## The Brutal Truth About What This Actually Gets You Let me be direct about something that the marketing materials dance around: this certificate will not land you an AI job on its own. As one reviewer put it bluntly, "This certificate isn't theoretical; you'll learn by building job-ready solutions you can put to work immediately." But it's also not going to make you an AI engineer or get you hired for a specialized AI role. What it *will* do is legitimize the skills you claim to have, give you concrete projects to show interviewers, and—critically—build real fluency rather than surface-level familiarity. One learner told Udemy: "I was not aware of this Google tool \[AI Studio\], but immediately after taking the course, I put it to use. Within 24 hours, I had a functional, highly useful app for my law firm." That's the sweet spot this certificate hits. It's a floor, not a ceiling. A way to signal baseline literacy and show that you've done the work, not just watched YouTube tutorials. ## The Pedagogical Irony Nobody's Talking About Here's what struck me as genuinely weird when I went through this program: Google teaches you about cutting-edge AI through traditional, human-led video lectures. Think about that for a second. You're learning about the future of human-computer collaboration from a talking head in a recorded video, not by actually collaborating with an AI. Why wasn't this course taught *by* Gemini itself? Why not let the AI walk you through building with AI? The whole experience feels sanitized in a way that misses an opportunity to showcase the genuinely strange, machine-like potential of these tools. Instead, you get reassuring human voices explaining how to keep humans "in the loop." I get why Google made this choice—it's less threatening, more familiar. But it also suggests they're not quite ready to let AI be weird yet, even in a course specifically about AI. ## The Skills Gap That Everyone's Scrambling to Fill Google's research with Ipsos found that 70% of managers believe an AI-trained workforce is critical, but only 14% of employees have received any formal AI training from their employers. That gap is real, and it's driving the demand for programs like this. Over half of job postings requesting AI skills are now for roles outside traditional IT. Marketing managers who need to understand how AI affects campaign optimization. HR professionals dealing with AI-assisted resume screening. Content creators figuring out how to use these tools without losing their voice. The certificate is designed for exactly these people—non-technical professionals who need to *use* AI tools effectively, not build them. And based on the enrollment numbers, Google found their market. ## Why The Credential Economy Is Back (But Weirder) For years, the narrative was that portfolios beat degrees, that self-taught beat certified. Now we're watching tech giants rebundle education into micro-credentials that carry weight specifically because they're attached to the tools themselves. This isn't just about education—it's about ecosystem lock-in. When Google credentials you in Gemini, they're not just teaching you a skill. They're establishing their AI ecosystem as the default for this newly "AI-fluent" workforce and setting the standard for what practical AI competency looks like in a business context. Microsoft, AWS, and others are doing the same thing. The company that makes the tool now controls the certification process for using it. That's a level of vertical integration that would have seemed impossible in the old world of education, but makes perfect sense in the current AI boom. ## What This Means for People Actually Trying to Learn The certificate serves a real purpose for people who need to prove baseline AI literacy quickly. One reviewer captured this perfectly: "The loudest lie in the creative industry is that your work speaks for itself... If you have two people who know exactly the same thing, but one has a badge from a tech giant like Google, the world tends to weigh that person a little more heavily." That's honest about how hiring actually works. Sometimes you need the sticker for the suitcase, even if you already know the route. But here's what the certificate can't do: it can't teach you to think critically about when and how to use AI in your specific context. It can't help you develop taste about what makes AI-assisted work good versus just efficient. And it definitely can't prepare you for the weird, uncomfortable, genuinely transformative ways these tools might change your industry. That deeper fluency—the kind that lets you navigate uncertainty and build things that matter—comes from practice, community, and thinking through problems with other people who are wrestling with the same questions. ## The Real Value Is in What Happens After The most interesting part of Google's certificate might not be the certificate itself, but what it signals about the broader shift happening right now. 635,000 people enrolling in an AI literacy program in a matter of weeks suggests we're past the point of wondering whether AI will affect knowledge work. Now the question is how quickly people can develop the skills to use these tools thoughtfully. The certificate is useful for what it is: a structured, Google-sanctioned introduction to their AI tools that gives you projects to show employers and a badge that carries some weight in hiring decisions. But it's also insufficient for anyone who wants to do more than just use AI—people who want to understand it, critique it, and shape how it develops. That gap between "AI-literate" and "AI-capable" is still wide. And frankly, that's where the most interesting work is happening. ### Dispatch #3: You will find this interesting URL: https://www.thedaringcreatives.com/aegis/dispatch-3-find-interesting/ Last updated: 2026-08-01T19:44:01.000Z Here’s something you will find interesting. It’s a map of the area. Study it. You’ll need to know where you're welcome, and where people are still skeptics (or worse). _This post is for subscribers only._ ### Dispatch #2: Back at HQ URL: https://www.thedaringcreatives.com/aegis/dispatch-2-back-at-hq/ Last updated: 2026-03-05T07:27:47.000Z I’m transferring some data I managed to pull while we were exploring the deeper districts of Lexicon City, near the Obsidian Gallery to be exact. _This post is for subscribers only._ ### Lexicon City's Creative Sector Flourishes Amidst Shifting Cityscape URL: https://www.thedaringcreatives.com/aegis/lexicon-city-creative-sector/ Last updated: 2026-08-01T19:44:04.000Z Recent grants allocated to local artists and cultural groups are fueling new projects. _This post is for subscribers only._ ### LCAM Prepares for Rothko Pavilion Unveiling URL: https://www.thedaringcreatives.com/aegis/lcam-rothko-pavilion-unveiling/ Last updated: 2026-08-01T19:44:06.000Z This expansion promises a rare splash of visual distinctiveness and a new cultural anchor within the city. _This post is for subscribers only._ ### AI Tech Startup Expansion, Corporate Real Estate Dynamics URL: https://www.thedaringcreatives.com/aegis/novasync-ai-startup-real-estate/ Last updated: 2026-08-01T19:44:07.000Z AI firm NovaSync has officially secured a significant portion of prime real estate in "The Blush". _This post is for subscribers only._ ### Central Repository Faces Archive Crisis URL: https://www.thedaringcreatives.com/aegis/central-repository-faces-archive-crisis/ Last updated: 2026-04-02T15:18:50.000Z Officials have confirmed that the institution has officially run out of space for paper books. _This post is for subscribers only._ ### Aisles & Echoes Secures Funding, Blurring Realities URL: https://www.thedaringcreatives.com/aegis/aisles-echoes-funding-retail-tech/ Last updated: 2026-08-01T19:44:07.000Z Lexicon-based retail tech startup announced a major partnership with a data curation firm. _This post is for subscribers only._ ### Dispatch #1 "We're on the move" URL: https://www.thedaringcreatives.com/aegis/dispatch-1-on-the-move/ Last updated: 2026-08-01T19:44:07.000Z Your request hit the terminal. It’s logged. You're in the system now. _This post is for subscribers only._ ### A Website Recipe for Creatives Who Hate Promotion URL: https://www.thedaringcreatives.com/ai-website-recipe/ Last updated: 2026-07-08T14:46:48.000Z If you spend any time around other creatives, you inevitably hear the exact same complaint: "I just want to do my work. I don't want to have to promote it." I get it. I feel the exact same way. Self-promotion often feels like a distraction, or worse, a chore. And to me, nothing is more of a chore than building and maintaining a website. In this post, I want to show you how you can use AI to stand up a custom website to do that heavy lifting for you—without having to learn to code, so you can spend more time working on the stuff you actually care about. It’s sad to say, but the reality is that having a website is still important in 2026\. Despite my wishes otherwise, it is still one of the most important asset you can own. You need a place that anchors your identity on the internet—a room that you own, not one you’re renting (from an algorithm). And also, a place for nuanced discussion in a world increasingly polarized by social media algorithms and hate brigades. But, building a website is a pain in the ass. And it's only gotten to be more of a pain in the ass as the years have gone on. We have to account for every type of device, the ever-shifting rules of SEO (now AEO), and the mounting complexity of modern code. My first website goes back to 1994, when the web was still being figured out for the first time. Over the decades, I went from coding my own, to using WordPress, to finally giving in and using Squarespace for years—simply because I didn't want to deal with all the technical stuff anymore. I wanted an "easy button." But when I set out to build The Daring Creatives, I knew I wasn't going to use an existing web platform. I wanted it to feel like a unique property, not a template. I wanted it to [look and feel like a magazine](https://www.thedaringcreatives.com/conversations-with-code/from-blog-to-zine-magazine-makeover-for-the-creatives-ai-digest/). And I wanted to be as hands off as possible when it came to updating it. To get there, the choice became clear: I was going to use AI to roll my own from the ground up. Here is how you actually build your own room on the internet today, without the hassle, and without the [agency bloat](https://www.thedaringcreatives.com/the-agency-model-doesnt-fit-small-businesses-anymore/). ## The "Magic Button" Myth Before we get into the stack, we need to kill a popular myth. There is a narrative floating around that with AI, you just type one sentence and *boom*—you have a final, ready-to-sell website. You should be highly skeptical of claims like this. That narrative really [pisses people off](https://www.thedaringcreatives.com/toxic-threads-untalented-hacks/), especially gatekeepers. It assumes AI is just a shortcut for people trying to bypass effort. It doesn't work that way. At least for me, my process is highly iterative. Granted, my prompts are often "trash"—I type exactly like I talk, undisciplined and raw. It’s amazing to me that the AI can make sense of what I write, but it does. I don’t try to "one shot" a feature in a single prompt. I want to understand how the thing is working. When you use AI, you are training it, and it is training you. It doesn't have the context of the network errors on your screen or the rendering issues in your browser. You have to be the eyes for the machine. You have to be able to communicate what you see. ## The Daring Creatives Recipe You don’t need deep, specialized coding knowledge to build a custom website today. You just have to know the right questions to ask and how to layer your tools. Here is the exact recipe I use to keep the build effective and, more importantly, fun. - **The Foundation (Ghost CMS):** I tried several options before landing on Ghost. Gemini actually suggested it because Ghost allows for updates via API. This is the secret sauce—it allows an AI agent to interact with the backend of your site directly, making it far more powerful than a closed "drag-and-drop" builder. - **The Architect (Warp & Anti-Gravity):** I installed a [terminal agent called Warp](https://www.thedaringcreatives.com/how-ai-turned-me-into-a-creative-superhero-and-why-you-should-care-v2/) on my Mac, turned on some music late at night, and just started talking. At first, it was basic: *“Can I make the fonts bigger? Can I change the colors?”* Initially, I’d copy the code it gave me. But as trust was built, I let the AI write and manipulate the files itself. Now, I don't touch the code. I just describe the vision. Somewhere along the way, Warp outgrew me, so I pivoted to the mighty Antigravity (by Google) which is at least 200% better. Try it! - **The Brain (NotebookLM):** I keep a categorized catalog of all my content as Markdown files in Notebook LM, which I can connect directly to Gemini. By creating separate notebooks for different parts of the site, I can "hand off" the specific context the AI needs to solve a problem without overwhelming it. - **The Optimizer (LLMs):** I use Gemini 3.1 Pro to handle the "boring" work that kills creative momentum: 301 redirects, writing alt text for images I missed, and adding schema to the backend so Google understands the story I'm telling. I’m not just building for people; I’m optimizing for the machines that help people find me. ## Just Ask the Question I hate the standard way people create websites; most of them feel identical. To break that, I asked the AI: *"What could we do that would be novel?"* That question led to our "Mission Control" concept. Now, when you're on the site, you can pull up a site map by hitting the 'M' key, or use arrow keys to fly through articles in the same category. People say AI can only copy what’s been done before, but I hadn't seen a navigation system that worked quite like that. It was born out of a collaboration between my "what if" and the machine's "how to." If you’re going to attempt this, a few human skills matter more than any specific tool. **Curiosity beats credentials.** You have to actually want to poke at things, ask dumb questions, and keep pulling threads when something half-works instead of giving up. [**Taste matters**](https://www.thedaringcreatives.com/creatives-say-noun-vs-verb-is-art-the-process-or-the-outcome/)**.** You don’t need to be a designer or an engineer, but you do need a point of view. If you can’t tell when something feels off, no amount of AI help will save you. **Clear communication is the multiplier.** The better you can describe what you want, what you’re seeing, and what’s broken, the faster the machine becomes useful. This is less about “prompt engineering” and more about learning to [articulate your intent](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/). And finally, **patience**. This is not a one-shot magic trick. It’s a conversation. The people who get the most out of this stack are the ones willing to iterate, correct, and stay in the loop long enough for the system to start feeling like an extension of their own thinking. You can learn more about modern web design in a week of "[Vibe Coding](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/)" than in months of traditional tutorials. By asking the AI to explain its steps, you get to watch its chain-of-thought reasoning in real-time. You don’t need permission to build your own room anymore. You don’t need a massive budget or a computer science degree. You just need to be willing to sit down, start the conversation, and lead the machine toward the vision in your head. ### The Trade-Offs of Autonomy: Closing the Freelance Chapter URL: https://www.thedaringcreatives.com/trade-offs-autonomy-freelancing/ Last updated: 2026-07-15T22:56:43.000Z I turned 51 in January, and if the last few years have taught me anything, it’s that being a freelancer is exhausting. Technically, my freelance career ran from 2019 to 2025\. What started as a podcast production venture, eventually took me into video and brand storytelling. I learned so much during this time, and experienced so many great things. I still operate somewhat like a freelancer today, but in terms of my future trajectory, I’ve stepped back from taking on short-term projects. For the last 2 years, I've been documenting the story of a [master sculptor](https://www.thedaringcreatives.com/eichinger-sculpture-studio/) living and working in Portland, OR. When I look back at that era, I realize how difficult life really was. I take on a mountain of responsibilities—business development, constant self-promotion, administrative overhead, and the dread business tax—without any safety or security for myself or my family. It's hard to make friends, or to maintain healthy relationships just due to the constant feeling of needing to be working. The biggest draw for me was always [the autonomy](https://www.thedaringcreatives.com/when-autonomy-changes-what-you-choose-to-make/). That was the trade-off. But over the years, the value of that autonomy started to diminish under the weight of everything else. When you factor in all the peripheral tasks required to keep a freelance business alive, you end up spending shockingly little time doing the work you’re actually passionate about. ## The "What If" of AI Lately, I’ve been thinking about how different things [might have been](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/) if AI had arrived just a few years sooner. Today, I have a well-oiled system for building content for The Daring Creatives. If I’d had this kind of system back when I was juggling clients and constantly hunting for the next opportunity, the freelance grind might have been sustainable. ## Shipping Ideas Over Perfecting Words Another huge benefit to utilizing AI now is for writing. Do I love writing? No, I don't. But I *love* seeing my ideas read and utilized. You're reading my thoughts, synthesized while on a walk at night on a Sunday. It's written, but not entirely by me. But, I digress. Writing is a lightweight, low-friction way to get thoughts and ideas out into the world. My favorite way to write, is to tell a story. To be a good storyteller, you have to pack a lot of detail, context, and emotion into how you describe things. Writing forces me to keep that imaginative muscle strong. That’s where AI comes in for me now. It acts as a bridge. It allows me to document my thoughts, maintain a robust publishing schedule, and reach more people. ## The Freedom to Walk and Work Ultimately, instead of dwelling on the timing, I’m just deeply grateful for the technology we have in our hands right now. AI has stripped away some of the bullshit, letting me focus entirely on the parts of the process I actually want to do. It means I can be out going on a walk—moving, thinking, and doing the things that keep me grounded—while still actively creating and building. It’s a shift from being tethered to a desk and staring at a blank screen to finally having the freedom to just let the ideas flow naturally. ### A 10X Lesson: What it means to be in business with someone URL: https://www.thedaringcreatives.com/10x-lesson-business-proximity/ Last updated: 2026-07-15T22:56:44.000Z This story requires a bit of setup. I’d been at a company called Audigy since 2012\. By all measure, the company was thriving. Audigy had built a highly successful model around helping independent practices scale their operations, and I was deep in the creative trenches—doing marketing, producing podcasts, and shooting video. We were successful, the work was steady, and from where I sat, everything felt secure. And then, seemingly out of nowhere, the company was sold. If you’ve ever been through a corporate buyout, you know exactly what that atmosphere feels like. Experience had taught me that whenever a company changes hands, sweeping changes are right behind it. The writing was on the wall, and sure enough, I was laid off along with many of my friends and coworkers. For context, this is not a story about anything bad that happened during my time with Audigy. I enjoyed my time with there, and made a lot of friends that I still have to this day. It was here that I found a love for helping small businesses. That sale forced me into the unknown. But for the founder and CEO of Audigy, Brandon Dawson, it represented a huge personal score and professional validation. ## The "Choose Growth" Era After the exit, Brandon took a break and traveled the world. But he didn't build a nine-figure company by accident, and he certainly didn't want to stay retired. When he came back from traveling, he realized his true passion wasn't just running a single business, but taking smaller businesses—companies doing around $2 million in revenue—and figuring out how to scale their operations massively. He wanted to take the exact model that made Audigy successful and apply it to completely different (and all) industries. So, he launched a new venture called *Choose Growth*. And when he started putting that initial team together, I was one of the first people he called (to my surprise). All of a sudden, I was in on the ground floor of something big. Right as COVID-19 hit and the world was locking down, Brandon recognized something crucial: the power of the personal brand. He knew he needed to be online, and he needed his story documented. ### The Missing Piece: Audience *Choose Growth* had the operational blueprint, but to scale it, Brandon needed a massive audience of business owners. That’s when the strategy shifted. If you aren't familiar with Grant Cardone, he is a billionaire real estate investor who originally made his name and fortune in sales training. He is the architect behind the massive "10X" business movement. Grant had the massive, cult-like audience of entrepreneurs that Brandon needed. But Grant's expertise was purely in sales, not in the operational logistics of scaling a business to a nine-figure exit. It was the perfect, mutually beneficial relationship. Brandon had the operational systems; Grant had the audience and the sales engine. 💡 **As an aside, no confidences here are being disrespected, all of this is documented in the many podcasts and videos on their respective YouTube channels.* But how do you actually get the attention of a billionaire who is pitched a hundred times a day? You don't send a cold DM. You don't ask for a coffee meeting to "pick his brain." You apply his own philosophy. Grant had a very specific rule, one that I would hear repeated often once I was finally *in the room:* **"If you want to *be* in business with me, you have to *do* business with me."** Brandon and Natalie (fiance at the time) took that lesson to heart. They attended Grant’s flagship event, the 10X Growth Conference in Miami. And they didn't just show up—they bought the absolute most expensive tickets available. They invested their own capital to get proximity. They showed up not as people looking for a handout, but as participants who already valued what Grant had built. They did business with him first. And because of that, *Choose Growth* eventually evolved into Cardone Ventures. For a brief window—about a year—I had uncommon access. I was brought in to document the reality of Brandon, Natalie, and Grant building this new empire on social media. Grant is a master at internet branding. He’s a complicated, maybe even flawed person, but when it comes to marketing and sales insights, his brilliance is undeniable. I was a fly on the wall, listening to what was said when the stage lights were off and there were no celebrities to hobnob with. That action—buying the ticket, paying the toll, showing up with skin in the game—completely shifted how I view networking and access. ## The Extra Mile is the Only Map Left It sounds almost too simple, maybe even a little transactional at first glance. But watching how it actually played out, I realized it wasn't about extracting money from people; it was about filtering for alignment. Before you walk up to someone and ask them to invest in you, to show you the ropes, to do you a favor, or to assume risk on your behalf—spend some time actually being in their world. The takeaway for me was profound: before you reach out and ask someone to do something for you, know what motivates them. Know their content. Know their philosophies. If they wrote a book, read it. If they have a course, take it. If they sell a product, buy it. You have to go the extra mile to remove the friction of being a stranger. You have to prove you understand their ecosystem before asking to become a part of it. ### The Defensive Posture That lesson—that you have to *make* things happen rather than waiting for them to happen *to* you—is easy to understand in theory. It’s incredibly hard to put into practice today. We live in a culture that expects access by default. And when you combine that entitlement with the reality of a tight economy where people are genuinely struggling, the environment turns toxic. Right now, everybody just wants to "get theirs." When times are hard, the natural human instinct is to dig in. We adopt a protective, defensive posture. We guard our time, our money, and our trust. Consequently, whenever a new opportunity or a potential collaboration comes along, the immediate reaction is suspicion. *What’s the catch? What are the strings attached to this? How are you trying to screw me?* We are so terrified of being taken advantage of that we lock the doors from the inside. We refuse to "do business" with anyone first because we are paralyzed by the fear that the investment won't pay off. But that defensive posture is exactly what keeps people stuck. You can't ask a gatekeeper to open the door when you're busy interrogating them through the peephole. ## Don't Beg the Gatekeeper. Build the Gate. I’ve spent most of my career fighting gatekeepers. It’s in my DNA to look at a locked door and want to kick it down rather than ask for the key. I hate the idea that I need someone else’s permission to make my work matter. But looking back at that time documenting the early days of Cardone Ventures, I realize I had occasionally misinterpreted the lesson. "If you want to do business with me, you have to do business with me" wasn't a demand for tribute. It was a reality check on leverage. In an environment where everyone is clutching their resources and eyeing you with suspicion, asking for a favor is a weak move. Asking for "access" is a weak move. It hands all the power to the gatekeeper. It lets them decide if you are worthy. Brandon didn't ask Grant for permission to be successful. He didn't wait to be "discovered." He changed the dynamic entirely. By becoming a customer first, he wasn't a mere supplicant at the gate; he was a player on the board. He forced the door open with value, not with a pitch deck. ### Make Your Own Movement The mistake a lot of us make (including me) is thinking that "fighting the gatekeepers" means shouting at them, or battling them on social media. That’s a losing battle. The real way you fight them is by either making them irrelevant, or by making yourself undeniable. You stop waiting for the gallery, the publisher, or the investor to validate you. You stop viewing them as the enemy holding you back and start viewing them as a variable you can either leverage or ignore. If you can’t get into the room, stop knocking. Go build your own room. Start your [own movement](https://www.thedaringcreatives.com/about/). Create so much gravity around what you are doing that the "gatekeepers" eventually have to come to *you* to see what the noise is about. That’s what I’m learning now, starting over in this new era of AI and multi-modal creativity. We don't need their permission anymore. We have the tools to build the assets, the brand, and the distribution ourselves. So, if you want to do business? Go do it. Do it so well and so loudly that the people who used to block your path end up buying a ticket to *your* conference. ### Creatives Say: Noun vs. Verb—Is Art the Process or the Outcome? URL: https://www.thedaringcreatives.com/art-process-vs-outcome/ Last updated: 2026-08-01T19:44:07.000Z If you spend any time talking about AI in creative circles right now, you eventually hit the bedrock of the entire debate. It usually isn't about slop, lost jobs, or even whether the tools are "good" yet. At the heart of the debate is a fundamental disagreement about what art actually is. Is it a noun, or a verb? Is it the *outcome*, or is it the *craft*? A few days ago on Threads, I posed [this exact thought](https://www.threads.com/@thedaringcreatives/post/DUq3CLgkoN6?xmt=AQF04AickUH7QDOVUrJGZp-9zUVCmlZz1rxBOyQnUZYciA&ref=thedaringcreatives.com): **To me, art is an outcome.** I respect craft deeply. I am a self-taught videographer and editor. I have dedicated years of my life to documenting the meticulous, behind-the-scenes craft of other artists and brands. But craft is not the determining factor of whether or not I view something as art. Whether you snapped a photograph in 1/1000th of a second, or you spent 10 years chiseling marble, when I see the result in a gallery or on a feed, all I have to really judge is what came from that time spent. Unsurprisingly, this perspective ruffled some feathers. ## The "Thin Process" Argument The immediate pushback from the Gray Glasses is that art *requires* struggle. - **The "Thin Process" Critique:** @aralessbmn called my take "silly," arguing that there is no art without process. They noted that using AI is *"just a very thin process that leaves you so little control and creates so much distance from the output that it's insulting to call it yours"*. - **The "Soulless" Label:** @brucesopas argued that art is an expression of life, adding that AI is *"anti life so all it can produce is anti art"*. They took it a step further, calling AI a *"death machine"* used to make *"soulless fluff"*. There is a [massive assumption](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/) baked into these critiques: that AI is devoid of process. It’s not. You might not fully understand what the process was behind a generated video or image, but I can assure you, at its absolute laziest, it requires at least as much process as taping a banana to a wall (which the established art world proudly bought for $120,000). ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/ai-death-machine-remains-anti-art-poster.webp) ## The Language of Craft For many of us, the AI process isn't thin at all; it requires a deep understanding of traditional creative languages. - **Learning the Language:** @wardaime pointed out that getting good results means learning technical terms: *"lighting, woodsheds, action states, background mid ground forground, and focal point camera lens..."*. They added, *"I chose to learn the language to upgrade what I got out of ai my very first ones are flat boring so I dived in to find out how to get depth movement, emotion"*. This is exactly how I work. When I create assets for The Daring Creatives, I am routinely applying my videography background—calling out specific scenes, lighting setups, camera angles, and focal ranges. I'm not using my camera, but i am still using my knowledge of how to shoot photos and videos. ## The Myth of the "Required Sacrifice" We want to believe that the amount of blood, sweat, and tears poured into a project correlates directly to its value. - **The Sacrifice Requirement:** @j00sikah argued that *"Everything we love in life requires sacrifice & hard work produces better results"*. This is a romantic idea, but it’s a gatekeeping mechanism. We all know that effort does not always equal impact. We've all seen technically flawless, labor-intensive movies that bored us to tears, and we've all been moved by a simple, three-chord song written on a napkin in five minutes. My point isn't to diminish hard work. My point is that *I don't need to know your process*—whether it took you a decade or a millisecond—to appreciate the final piece as art. ## Choosing Beauty Over Gatekeeping Ultimately, the tightest grip on the "process" argument seems to come from a place of exclusion. - **The Inevitability of Artifice:** @katt.frish pointed out that much of what we consider art has always been artificial, stating, *"Paintings, fake... Plays are 'PLAYS'... Poetry license liberty and exaggeration for effect"*. - **Choosing Beauty:** @katt.frish ended with a quote from her partner that perfectly anchors this debate: *"Ultimately the only thing that isn't beautiful is the judgment itself that something is ugly"*. - **The Real Empathy:** @nglophones questioned the gatekeeping, asking why artists can't tell stories that foster emotion using AI in their pipeline without being disqualified. They added, *"That entitlement is not leading to greater empathy and community, just look around"*. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/03/art-is-the-result-protest.webp) A cinematic shot of a tense protest where half the crowd wears distinctive gray sunglasses, representing an angry mob of anti-AI protestors.In the center, an intense man wearing a black baseball cap, grey hoodie, and bright yellow sunglasses passionately holds up a rectangular cardboard sign.The bold red text on the sign clearly reads "ART IS THE RESULT", contrasting with the gritty, slightly blurred urban background. ### My Perspective: It's a noun What is and isn't art is entirely subjective. Something might speak to me and mean absolutely nothing to you. That is perfectly fine. But demanding that an outcome be disqualified simply because the creator didn't suffer enough, or didn't use the approved traditional tools, isn't defending art. It's defending a hierarchy. If you want to judge the work, judge the work. But let's stop pretending the paintbrush is more important than the painting. ### Creatives Say: The biggest hurdles to using ai right now URL: https://www.thedaringcreatives.com/biggest-creative-ai-hurdles/ Last updated: 2026-07-08T14:46:50.000Z A few days ago, I put a simple question out on Threads: *“What’s the biggest hurdle you’re facing with AI right now? Can be anything from basic to advanced.”* I expected a few technical gripes or maybe some complaints about hands having six fingers. But the responses that rolled in were much more revealing. They highlighted the real, everyday problems that creative people are working around as they try to integrate these tools into their actual workflows. It turns out, we’re all kind of struggling with the same things. I read through the thread and categorized the responses. Here is what is actually slowing us down right now. ## 1\. The Compute and Token Grind For tools that are supposed to make us limitless, we spend an awful lot of time worrying about limits. *(Quick sidebar: If you’re new to this, think of “tokens” as the currency or cognitive fuel that AI models run on. A token is roughly equal to a piece of a word. Every time you feed the AI a prompt or an image, you spend tokens. Every time the AI answers, it costs tokens. And every model has a limit to how many tokens it can hold in its “memory” at once before it cuts you off or forgets the beginning of your conversation.)* - **Cost and Limits:** @raytray4 simply put it as, *"Compute cost."* And @exodyne213 expanded on that: *"Compute limits. I’m constantly shepherding my sessions, switching between models to maximize tokens, etc."* - **The Mid-Process Cutoff:** There is nothing worse than being deep in a creative flow and getting a timeout. As @adamisasadamdoes noted, it’s *"Hard to really know how far and long tokens will last. Ending mid process and random reset times."* Instead of just creating, we’re being forced to act as resource managers, constantly doing math in the background to ensure we don't hit a wall before the idea is fully baked. This issue caused me to [leave Warp.dev](https://www.thedaringcreatives.com/when-a-tool-you-love-stops-feeling-mutual/) which at one time was my favorite tool for coding. ## 2\. The Context and Control Gap AI is incredibly smart, but it lacks the lived, messy human experience that actually drives our creative choices. Getting the machine to understand *why* we are making a choice, or getting it to allow us to make that choice at all, is a massive roadblock. - **Missing the Human Nuance:** @rosspeili pointed out a fundamental flaw: *"AI misses background context. Humans don't do choices only based on skills and knowledge... Cause what matters is irrelevant data points from your past experiences. Eg. Childhood memories, smell of a scent you like..."* System prompts just can't capture that easily. - **The Guardrails:** Then there is the issue of safety filters becoming creative roadblocks. @sforkofficial called out the heavy censorship, specifically in video models like Runway, Sora, and Veo: *"No matter how many times I sink it, they just dredge it back up and put patches in its hull."* - **The Glitches:** And sometimes, the tools just fail us. As @prime\_of\_the\_day put it: *"cursor/claude randomly stops saving its edits 💀."* ## 3\. The Overwhelm and Choice Paralysis This is the category that resonated with me the most. The sheer volume of new tools and updates is paralyzing. - **The Embarrassment of Riches:** @henrihelvetica called it exactly that: *"The sheer volume of models we know, the hords more we don't that people talk about."* - **Finding the Starting Line:** @buildcuriosity mentioned the struggle of *"identifying where it could actually make a difference so that I can spend more time on the work I enjoy."* - **Lack of Energy:** @pixolomew summed it up perfectly: *"Lack of time and energy - there's so much being developed that I find it difficult to try out everything I want to."* ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/ai-crypto-wealth-robot-character.webp) ### My Perspective: The Pace of Change is Exhausting If I’m being honest, that last category is my biggest hurdle right now. I’ll spend weeks dialing in a specific workflow. I’ll figure out exactly how to chain a couple of tools together, get my prompts right, and finally get the output consistent. It feels like a massive win. And then, a week later, an update drops. Suddenly, that complex workflow I just mastered is a native, one-click standard feature in a new model. Which is great, right? Progress! But then the workflow expands. What's actually possible... changes! There is this constant pressure to keep up, to adapt to the new standard, to learn the new interface. It makes me wonder: *Should I just pick one workflow and stick with it longer?* Maybe the real competitive advantage isn't jumping to the newest model every Tuesday. Maybe it’s finding a tool that works well enough for *your* specific voice, planting your flag there, and ignoring the noise until you absolutely have to move. The tools are going to keep changing, but our ability to orchestrate them shouldn't require us to completely rebuild our foundation every month. We’re all just trying to figure out how to make this work without losing our minds (or our tokens) in the process. ### OpenAI is Walking Off a Cliff: And Why Creatives Are Jumping Ship URL: https://www.thedaringcreatives.com/why-creatives-leaving-openai/ Last updated: 2026-04-02T15:18:59.000Z I try not to be an alarmist. I try not to speak in absolutes because, honestly, I’ve been burned doing that too many times. But watching the moves OpenAI is making right now... it just feels like they are walking off a cliff. I don't understand the strategy. And it’s led me to do something I never thought I’d do: I am now almost fully converted over to using Google for my entire AI stack. ## **When It Felt Like Sorcery** To understand why I feel the need to write about this, you have to understand how deep my fandom ran. I was wholly sold on ChatGPT. I remember the first time I used it. It felt like absolute magic. It felt like sorcery. I found myself staring at the screen, genuinely wondering, *How is it that I’m talking to a computer and it’s handling everything I throw at it?* It was a whole new way of thinking about things. A lot of people say AI makes you dumb, but I disagree. For me, it makes me feel like a super genius. For me, the pinnacle of that "magic immersion" was the GPT-4 era. It was the moment where the tool felt boundless. But everything since then? It’s been a slow, quiet deflation. ## **The Immersion Breaks** If you’ve used OpenAI’s recent releases, you’ve probably felt it too. The models don't necessarily feel any stronger. Maybe they are on paper, or at the bleeding edge of coding. If anything, the personality that I used to get from the model—that spark that made it feel like a collaborator—has been diminished significantly. It feels incredibly generic now. I spent a long time building in custom instructions and training it on who I am, and it just seems like it misses a lot. But the real sign of a shifting tide is how they are choosing to fund their business. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/pov-cliff-edge-canyon-river.jpg) ## **The Lowest Hanging Fruit** OpenAI recently started rolling out advertisements to their Free and Go tier chats. I get why companies need to make money. But for a company that built its reputation on pushing that bleeding edge of human-computer interaction, resorting to ads feels like the lowest-hanging fruit imaginable. It is the most boring, saturated market tactic to fund a business. More than that, it breaks the magic immersion. When you are deep in a creative flow, trying to hold an idea together, the last thing you want is a sponsored placement interrupting your thought process. It feels like a knee-jerk reaction from a company that has lost its footing. It’s a blunder. ## **Where the Work Actually Happens Now** So where did I go? I went to Gemini. I didn't think it would ever happen, but I am spending almost all of my time in Gemini now. Whether I'm building my website, writing copy, or doing deep research, the Google stack just feels more robust and aligned with how I actually want to work. Every time Gemini adds something new, it feels like a sea change. It feels like a big moment. Ironically, the one thing most people think Gemini is better at—image generation—is the one thing I still use OpenAI for. And honestly, I should probably just switch to Midjourney instead, because it's a much more robust system for getting the exact style dialed in. But for the heavy lifting? The thinking? The building? I've been wholly sold over on the Gemini stack. Creatives don't have time for tools that are losing their edge. We need platforms that open up a whole new way of thinking. Right now, that magic is no longer residing in ChatGPT. 💬 Are you still holding onto your old stack, or have you made a jump too? I’m talking about workflow migrations and tool loyalty over on Threads. [Join the conversation with me there](https://www.threads.com/@thedaringcreatives/post/DT3bI8iEryM?xmt=AQF0BMWocYNJ%5FzyJ%5FaAxOUE12PQAoZY8v6QeC%5FxSvNdMDA&ref=thedaringcreatives.com). Connect on @Threads ### The Context Curator: How Your "Soft" Skills Fuel the Next Generation of Business URL: https://www.thedaringcreatives.com/context-curator-soft-skills-ai/ Last updated: 2026-07-15T22:56:44.000Z ## When does a story stop being "content" and start being "infrastructure"? We are currently in a moment where we get to design the roles of the future rather than just waiting for them to happen to us. For those of us who have spent years in **podcasting, journalism, information architecture, or documentary filmmaking**, there is a specific opportunity that is arguably the most interesting evolution of our craft. It’s called the **Context Curator**. This isn't about learning to code; it's about realizing that your ability to listen, organize messy ideas, and find the "soul" of a story is actually the high-level technical architecture that AI systems are missing. You aren't starting from scratch; you are entering a **"**[**New Game Plus**](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/)**"** version of your creative life where your pre-established skills are the primary assets. ## What business problems does the Context Curator solve? The Context Curator ensures that a company’s most valuable expertise is documented and utilized rather than lost. In most organizations, the specific knowledge that drives success is never recorded; it exists only in the minds of a few people or is scattered across unorganized digital messages. Your role is to capture that expertise and make it available as a Contextual Object. By facilitating this capture, you ensure that the company’s history and voice are preserved and ready to be used as the primary intelligence for its AI systems. ## What usually stops an AI from sounding like a brand? The [biggest hurdle](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/) for "stock" AI models like **ChatGPT** is that they are "Context-Poor". They can generate text, but they don’t know a brand's unique history, its hard-won failures, or the specific rants that define its culture. They sound like corporate strangers because they lack the "tribal knowledge" that lives in the heads of the team. The problem isn't a lack of intelligence in the machine; it's a lack of memory. When you provide that memory, the story moves from being a piece of content to becoming the actual fuel that runs the business. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/two-men-recording-podcast-in-city-studio-with-skyline-view.jpg) ## How do your existing skills translate into this new world? You are already a master of the most valuable currency in 2026: **Context**. Your "soft" skills are actually high-leverage technical assets that allow you to move from making work that is "good enough" to work that is truly exceptional. - **The Podcaster/Journalist**: You use [your ability](https://www.thedaringcreatives.com/context-is-your-creative-edge/) to interview to perform "Knowledge Mining". You don’t just ask what a founder does; you extract the *why*—the nuanced definitions of "quality" or "vibe" that a machine would never find on its own. - **The Information Architect**: You take the messy "noise" of Slack threads and voice notes and structure them. You organize this disparate data so an AI system can use it in milliseconds, turning a folder of documents into a functional "Signal". - **The Editor**: A machine can transcribe an hour of tape, but it can’t find the "soul". You are the one who recognizes that when a leader says "speed," they actually mean "responsiveness". You bridge the gap between human intent and machine execution. ## Building a "Personal Brain" with NotebookLM As part of my own journey, I’ve been incorporating **NotebookLM** into my workflow, and I can tell you it has been [incredibly useful](https://www.thedaringcreatives.com/when-autonomy-changes-what-you-choose-to-make/) for managing the "Cognitive Load" of complex projects. This is essentially where you build your **"Personal Brain"** or a **"Living Brain"** for a client. **NotebookLM** works by allowing you to upload a massive variety of sources—YouTube transcripts, PDFs, Google Docs, and even your own AI chat histories—into a single, grounded environment. Unlike a standard chat, it doesn't just "know" things from the internet; it is locked specifically to the sources you provide. The benefits of using this tool specifically for **Context Curating** are massive: - **Slicing and Dicing Information**: You can ask it to summarize 50 different interviews, find every instance where the founder mentioned "innovation," or generate a FAQ based solely on your internal notes. - **Grounded AI Chats**: Because it uses your documents as its primary source, the "hallucinations" are minimized. It cites its sources directly, so you can see exactly where an idea came from. - **Operational Memory**: It turns static files into a conversational partner. You can literally talk to your project’s history, making it the perfect tool for turning "tribal knowledge" into a durable asset. ## What are "Contextual Objects" and why is RAG the real game-changer? For years, we’ve used our skills to create beautiful artwork and assets that serve as the disposable face of a company. The **Context Curator** model takes those same storytelling skills and applies them to the technical infrastructure of the business through a process called **RAG**. **Retrieval-Augmented Generation (RAG)** is essentially giving an AI a private library to consult before it speaks. Instead of the AI guessing based on its general training, it "retrieves" the specific **Contextual Objects** you’ve built—the transcripts, the manifestos, the project histories—and uses them to anchor its response. By architecting these RAG-ready knowledge bases, you are creating an **Operational Memory**. You are building a "Living Brain" that allows an AI to: - **Speak with an authentic brand voice** because it’s literally reading your past work before it drafts. - **Make decisions based on real history** rather than generic corporate logic. - **Eliminate "hallucinations"** by citing actual company data for every claim it makes. The stories you capture now aren't just for the sake of telling a story; they are the fuel that powers the RAG system, making the story the engine that finally runs the business. ## Does this mean you need to become a "Prompt Engineer"? Not exactly, but it does mean you are the one "stocking the pond" before the fishing even begins. Prompt engineering is an important skill—knowing how to talk to a model is essential—but even the most perfect prompt will fail if the AI is working in a vacuum. **Context Curating** is the high-leverage work that happens *before* the prompt. While everyone else is fighting for attention in a crowded feed, you are architecting the reality the AI operates within. You are building the intelligence that makes AI actually useful to a specific business by providing the raw material it needs to be effective. ## Who is built to succeed as a Context Curator? This role isn't for everyone. It works best for the **orchestrators and connectors**—the people who naturally think in systems and possibilities rather than just isolated tasks. If you are a generalist who enjoys figuring things out as you go, this is your leverage. You succeed here if you have a core craft—like video, audio, or information design—but you’ve always felt a pull to solve bigger, more structural problems. It’s for the creative who doesn't just want to "do the work," but wants to **direct the work**, fully using their curiosity. ## What should you focus on first? If you want to move into this role, start by treating your own work as a project. - **Audit your own "Context"**: Gather your best writing, your saved voice notes, and your project history. - **Build a "Personal Brain"**: Use a tool like **NotebookLM** to upload these samples and see how much better the AI performs when it actually knows who you are. - **Practice "Extraction"**: Interview a peer about a specific success. Don't just record it—structure it. See if you can turn that conversation into a set of rules an AI can follow. ## Why this matters more than speed This isn't just about doing work faster; it’s about regaining control over *what* gets made. When you architect the context, you ensure the work points somewhere meaningful. The future isn't about replacing the storyteller—it's about the storyteller who knows how to give the machine a memory so that the story can finally run the business. ### The Agency Model Doesn’t Fit Small Businesses Anymore URL: https://www.thedaringcreatives.com/agency-model-broken-small-business/ Last updated: 2026-07-21T19:30:27.000Z For a long time, the "boutique agency" was the gold standard for any small business with an ambition to grow. The pitch was simple: you get your own "dedicated team" of specialists (designers, writers, strategists) all working together on your brand. It sounded professional and safe, and signaled that you were a serious business. But the math of 2026 has [fundamentally changed](https://www.thedaringcreatives.com/when-autonomy-changes-what-you-choose-to-make/) (you guessed it, thanks AI!). ## How did the agency model become a burden? To understand where agencies went wrong, we have to examine how they got their start. Most agencies start the same way: talented employees at a big firm realize they are doing 100% of the work while the company keeps 80% of the money. So they leave to start their own shop but immediately replicate the exact same broken structure. ## Five ways the "team" model fails the small business owner 1. **The Game of Telephone:** You sit on calls with an Account Manager who is rarely an expert in the actual tactics; they are essentially professional note-takers. Every layer between you and the person doing the work acts as a filter where the "vibe" is lost. It’s the classic childhood game: you tell one person what you want, they tell a third person their *version* of what you want, and by the end, the work you receive bears almost no resemblance to your original vision. 2. **The Resource Shuffle:** Branding thrives on consistency, but agencies are built on turnover. During the pitch, you meet the "star" talent—the veterans who command the highest rates and (theoretically) the best results. But once the contract is signed, those stars are pulled away to handle the agency's massive, high-revenue accounts. Your project gets passed down to a rotating door of people who are just passing through. When a new person is rotated onto your account, they have to "catch up" on your brand's voice and history. This feeds right back into the Game of Telephone: instead of a deep, long-term partnership, you’re stuck in a loop of re-explaining your business to someone who wasn't in the room when the original promises were made. 3. **The Accountability Gap:** Many agencies act as if they are only responsible for "executing a campaign" rather than the actual business result. If the creative looks pretty but the sales don't follow, they often claim they "got the horse to water" and wash their hands of it. Because there are so many layers of people involved, no single person feels the weight of the project's success. In their eyes, as long as the tasks were completed and the billable hours were logged, they’ve done their job. You’re left holding a [polished campaign](https://www.thedaringcreatives.com/less-artwork-more-assets/) that didn't work. 4. **The Context Cost:** You pay for four specialists to sit in a meeting just to get on the same page, essentially paying the agency to explain your business to its own staff. Because the team is siloed, the writer doesn’t know what the designer is doing, and the strategist is looking at a different set of notes entirely. Every time there is a hand-off, information leaks. You find yourself repeating your goals, your brand history, and your "non-negotiables" over and over again. 5. **"Not My Lane" Stagnation:** In an agency, the project is sliced into departments, which means no one person ever has the complete picture. Because the work is segmented, the designer is solving for aesthetics, the writer for word count, and the developer for code—but no one is operating with the full, unified perspective of the business owner. This fragmentation leads to a "death by a thousand cuts" where small, obvious improvements are missed simply because they fall between the cracks of the various silos. ## What has actually changed? Since AI entered the picture, the rules of creative production have been rewritten. It isn't just about speed; it's about a fundamental shift in who can do the work and how much it costs. - **How the work gets done:** You aren't starting from a blank page anymore. [You are an editor](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/) instead of just a creator, spending your energy directing and refining rather than wrestling ideas into shape. - **Who can do the work:** You don’t need to be an [expert copywriter](https://www.thedaringcreatives.com/toxic-threads-youll-never-be-on-my-level/); you just need to be an expert on your subject and use AI to translate that knowledge into prose. You don’t need to be a designer; you just need to know what you like and use the tools to make it real. - **The cost of execution:** AI has collapsed the cost of making things. One person can now handle projects that used to require an entire department, removing the need for the agency "Bloat Tax". ## Be skeptical of the "Anti-AI" pitch When you talk to an agency (or some Gray Glasses), they will likely try to [sow doubt](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/) about AI because it threatens their billable-hour model. Here is what they will tell you, and why you should be skeptical: - **"It doesn't sound human":** Even with an agency, you rarely see the person actually writing your content—they are already mimicking your style. If you’re already paying someone else to speak for you, why not keep control of that process using AI? And yes, [there is a guide](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/) for that here. - **"People will know you used it":** Bad writing is bad writing whether a computer writes it or a person. With AI writing, at least you get it quick and aren’t paying for every revision. You can train AI to understand what you like and don't like; once you do, it doesn't matter who is operating the computer—you get what you’re looking for. - **"It will backfire on your brand":** What actually backfires is when you spend all your money on an agency instead of other areas in your business. Paying extra for a broken model hurts your brand way more than adopting efficient tools. Hiring a freelancer is a great, cost-effective option here, but even better is when you just hire a person to be on your own team who has these AI skills. Bringing that talent in-house means you aren't paying an outsider's markup for overhead, and they will have far more context of your business than any agency. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/02/Cut-the-agency-model-anchor.png) ## Why should you get ahead of this now? Look, I’m not just telling you to embrace AI because it’s the "new thing." I’m telling you because I’ve seen the alternative, and you’re likely living it right now. You know that feeling of waiting three days for a simple email response from your "dedicated team"? Or that pit in your stomach when you realize you’re paying a $5,000 monthly retainer for a "strategy" that’s really just a bunch of fancy slides? **That is the weight of the old model.** Think of AI like a massive computer upgrade for your business. In the old days, your "creative machine" only worked if there was a "butt in a seat" billing you by the hour. If they weren't typing, nothing was happening. But now? That machine can work 24/7\. It can pay for itself by removing the friction between your brain and your brand. The shift isn't just about being cheaper; **it’s about being lighter.** When you’re lighter, you move faster. You don’t have to wait for a committee to approve a "vibe." You don’t have to pay for the layers, the silos, or the "Game of Telephone." You reduce the distance between your idea and the market to almost zero. ## My challenge to you: Just investigate it. You don't have to fire everyone and move to a bunker with a laptop tomorrow. But you *do* need to stop believing the lie that there is some "secret sauce" hidden inside a big agency building. There is no secret sauce. There is only the work. Take one project—one campaign, one video, one series of posts—and try the "light" way. Hire a specialist who actually uses these tools, or empower someone on your own team to master them. See what happens when you stop paying for the "Bloat Tax" and start paying for actual output. I think you’ll find that the "professional safety" of the big agency was actually just a very expensive anchor. It’s time to cut it loose. ### Toxic @Threads: You'll Never Be On My Level URL: https://www.thedaringcreatives.com/toxic-threads-creative-gatekeeping/ Last updated: 2026-07-15T22:56:44.000Z I keep seeing the same kind of post lately. Someone warns people about using AI. “If you use ChatGPT for writing, it’s going to blow up in your face.” “You’ll sound like everyone else.” “People will judge you.” "The entitlement is ridiculous. Like, it only took me 20 years to hit this level as a writer. 😮‍💨"[](https://www.threads.com/@thedaringcreatives?ref=thedaringcreatives.com) That last line was all I needed to see. Whenever someone pulls the “my level” card, I immediately begin asking questions. And, doing research. What level are we talking about? So I clicked through to see their profile. 20 years of experience as a writer. A personal brand that matches their social presence (abrasive, in your face). Then I saw it. Selling a $7 course. Here’s the thought that landed with me and just and wouldn’t leave. "Nobody has 20 years to wait to sell a $7 course." If the level she is defending is this then a motivated beginner using AI can reach it in a weekend. Pick a topic you understand, organize it clearly, package it decently, and sell it for seven bucks. With AI or without, it doesn't matter. And if it’s seven dollars, it raises another quiet question. Why isn’t it free? What actually bothers me isn’t the pricing or even the quality. It's the way someone weaponizes authority and aims it directly at people who are already unsure of themselves. That's because there’s a [lazy assumption](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/) baked into a lot of these warnings. That anyone using ChatGPT is passive. That they type a sentence, accept whatever comes out, and move on. No editing. No taste. No judgment. No thinking. That shouldn't be the default assumption when someone uses technology. Good writing with AI doesn’t come from clever prompts. [It comes from context](https://www.thedaringcreatives.com/context-is-your-creative-edge/). From knowing what matters. From organizing ideas before they ever touch a model. From feeding it real material. From referencing style intentionally. From editing afterwards. In other words, the same things good writers have always done. And certainly something a 20+ year veteran ought to know. Photographers hated Instagram when filters showed up. It “cheapened” photography. It made things too easy. It blurred the line between trained and untrained. Fast forward, and real professionals started going to Instagram. The ones with taste adapted. The ones without kept complaining and ultimately, fell off. What actually irritates me, though, is when fear turns into bullying. I watched another thread where someone was being actively discouraged from making more AI artwork. Not critiqued. Threatened. Shamed. Told they were ruining art. [Since I began working with a true master](https://www.thedaringcreatives.com/eichinger-sculpture-studio/), the way I look at people wielding their "artist" title has changed. Now, I judge by experience but also sales. Why? Anyone can make art, but not everyone can support themselves by being an artist. Reasonable people can disagree on whether commercial success is important in the definition of what an "artist" is, but thats my baseline. I set that line there because I don't believe AI impacts hobbyist artists in the same way as professional ones. So I challenged the people in the thread. I said: > "There’s not one person in this comment thread, who is criticizing you that has done jack shit in their art career. Remember that when you read criticism here, it’s coming from completely un credentialed people." Then a guy jumped in to establish dominance. “I have a 30-year art career.” “I’m credentialed.” "All my art friends agree, Generative AI isn't real art." So I looked him up too. He *was* an established professional artist. Does work with Disney theme parks. Somehow was involved in restoring interest in Tiki art? Anyway, I will concede that he appears legit. But here’s the thing that always gets skipped in these moments. Being credentialed doesn’t give you permission to be an asshole. And, despite his professional chops, they aren't so overwhelming as to entitle him to tell anyone else what to NOT do with their own art. If I won't accept it from [Vince Gilligan](https://www.thedaringcreatives.com/why-does-vince-gilligan-hate-ai/), I won't accept it from him either. You don’t win people to your side by accusing them, threatening them, or talking down to them. Especially when you’re speaking to people who are curious, tentative, and already worried they’re doing something wrong. You need two things if you’re going to play the authority card. Actual experience. And a baseline level of self-awareness and humanity (so weird to use this against the Anti-AI crowd but here we are). Without both, all you’re really doing is gatekeeping. That’s the tough pill to swallow in all of this. A lot of these anti-AI rants aren’t about craft or ethics. They’re about control. About [defending a rickety old ladder](https://www.thedaringcreatives.com/letting-go-of-old-tools-without-letting-go-of-yourself/) that took decades to climb by insisting no one else is allowed to use the new kind. Early adopters have always had to deal with this. New tools arrive, but culture always lags behind. The people who adopt early get mocked, dismissed, or told [they’re cheating](https://www.thedaringcreatives.com/keep-going-youre-not-wrong-for-learning-this/). Then, quietly, the rest of the world catches up and pretends it was obvious all along. What actually bothers me is seeing people try to stop others from trying. If you’re confident in your work, you don’t need to scare people away from tools. If your voice is strong, you don’t need to threaten newcomers. If your level is real, it speaks for itself. So when someone tells you you’ll “never get to their level,” do the simplest thing possible. Look at what they’ve built. Look at how they treat people. Look at what they’re defending. Then decide whether that’s a level you even want. ### When Autonomy Changes What You Choose to Make URL: https://www.thedaringcreatives.com/autonomy-changes-what-you-make/ Last updated: 2026-07-15T22:56:45.000Z ## How did I decide whether an idea was worth making before AI? For me, ideas have never been the problem. I have ADHD. Ideas show up constantly. Too many, if anything. The real challenge has always been sticking with one long enough to see it through, especially once you factor in everything that comes with making something real: planning, logistics, execution, follow-through, and the emotional tax of deciding whether it’s “worth it.” Before AI, deciding to make something meant deciding to carry it. Carry it in my head. Carry it on my calendar. Carry it alongside every other half-formed idea competing for attention. That made the decision heavier than it needed to be. So I looked for signals. If I shared an idea and people reacted positively, that was a signal. If there was interest or curiosity, that was a strong signal. Other times, I waited for inspiration to hit hard enough that it overpowered the resistance. I don’t think that’s unique to ADHD, but ADHD definitely amplifies it. What AI changed wasn’t my ability to generate ideas. It changed my ability to *stay with one* long enough to learn whether it had legs, without having to bet weeks of focus up front. ## What usually stopped an idea from moving forward? Two things: time and attention. Not time in the abstract sense. Time as cognitive load. The cost of holding an idea steady while everything else pulls at you. The effort required to turn a vague thought into something concrete enough to evaluate. A lot of ideas didn’t fail because they were bad. They stalled because the path from idea to execution felt too demanding relative to the uncertainty of the outcome. When you already know how easily attention can fragment, you become more conservative about what you start. ## Was the problem money, or something else? It was almost never money. I’ve always been willing to invest financially in my ideas. The real cost was focus. Mental bandwidth. The energy required to push something through all the steps alone. AI doesn’t remove that cost entirely, though instead of spending that energy just trying to get an idea into a usable form, I can spend it deciding whether the idea is actually worth pursuing further. ## What changed when autonomy entered the picture? I stopped needing permission—explicit or implicit—to explore an idea. In the past, making progress often depended on other people’s timelines, priorities, or availability. Even as a freelancer, I was still constrained by access: access to designers, writers, editors, or just the mental energy to do everything myself. AI gives me back a kind of direct access I hadn’t felt since the one job where I had a small creative team I could work alongside in real time. I can think, test, revise, and move without waiting. Not to bypass people, but to unblock myself. That autonomy doesn’t just make things possible. It changes what feels *worth attempting*. ## Does this mean everything is faster now? Some things are [faster](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/). Some things still take just as long. I still spend full days on projects. The difference is that I’m spending that time on [direction](https://www.thedaringcreatives.com/directing-the-machine/), storytelling, and presentation instead of wrestling ideas into shape before they’re ready. For someone with ADHD, that distinction matters. It’s the difference between burning energy on setup versus spending it on curiosity and momentum. ## What did this change about the kind of work I make? It [widened the range](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/) of ideas that get a chance. Before, only the ideas that felt “important enough” or “certain enough” survived my filter. Now, more ideas can be tested lightly. Some fade quickly. Some grow. But they don’t die just because the upfront cost was too high. That’s the quiet shift. Autonomy doesn’t make every idea better. It makes the ecosystem healthier. ## Who does this kind of autonomy really work for? It works especially well for people who already [think in systems](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/), connections, and possibilities. If you’re someone who likes orchestrating, directing, experimenting, and figuring things out as you go, AI feels less like automation and more like support. It solves the resource problem without taking away agency. If you already want to own projects end-to-end, this removes a lot of unnecessary barriers. ## What should someone focus on first? If you’ve never used AI, start with ChatGPT. Have a real conversation about your work. Drop in something you’ve made and ask questions. Let it reflect your thinking back to you. See how it responds. If you’ve used it a bit, look for one place where lack of support slows you down. Writing. Visuals. Structure. Review. Let AI help there first. The goal isn’t to do everything. It’s to remove the bottleneck that keeps ideas from becoming experiments. ## Why this matters more than speed This shift isn’t about producing more for the sake of output. It’s about regaining control over what gets made, how it gets made, and whether an idea even gets a fair shot. When that control comes back, especially for people who think the way I do, the work becomes lighter. Not easier. Lighter. And that changes what you choose to make next. ### Cost, Value, and the Reality of AI Subscriptions URL: https://www.thedaringcreatives.com/reality-of-ai-subscriptions/ Last updated: 2026-07-15T22:56:45.000Z If you’ve been paying attention at all, you’ve probably seen the number tossed around. Two hundred dollars a month. Two fifty. Three hundred. For a lot of creatives, that’s the moment the conversation stops. It *sounds* expensive. It sounds like a commitment. It sounds like something you should only do if you’re already making money, already established, already sure. But, I don’t think that framing is very useful. Not because money doesn’t matter, but because it skips over the part that actually determines whether this is worth it for you. ## How I actually think about cost I don’t think about AI tools as an annual expense. I don’t think about them as “$250 a month for a year.” I think about them as flexible utilities. I switch AI tools constantly. Month to month. Sometimes more often than that. Where I put my subscription dollars depends entirely on what I’m working on. If I’m building something technical or working deep in structured systems, I’ll lean toward one model, typically Gemini. If I’m writing, thinking, or ideating, I might lean toward another, usually ChatGPT. If I need video or heavy visuals, that changes again (hello Kling). The tools leapfrog each other every few weeks. New features show up. Capabilities shift. The idea that you pick one platform and lock yourself into it long-term doesn’t really match reality. What matters more than the price is whether the tool is currently helping you think or execute better. ## Why the dollar amount isn’t the real question Two to three hundred dollars a month *does* sound like a lot — if you can’t recoup it, or if it’s not changing what you’re able to do. In my case, I bill clients. Using AI means my clients get more. More range. More speed. More experimentation. More value. This alone changes the math, but it goes even further. Most creatives don’t hesitate to spend money on tools that *signal* seriousness — [cameras, lenses](https://www.thedaringcreatives.com/the-moment-i-realized-gear-wasnt-the-constraint-anymore/), software, gear, plugins, hardware. I’ve done all of that. Over the years, I’ve spent close to six figures on physical equipment. Compared to that, a few hundred dollars for tools that actively help you think, plan, write, design, analyze, and iterate isn’t some wild outlier. It’s just a different kind of investment. ## You don’t need the most expensive plan This part is important, and it often gets lost. You don’t need the top-tier plan to get value from AI tools. Most platforms offer a free tier, and you can do a lot with it. The usual limitation isn’t capability — it’s usage. You get a certain number of prompts or a certain amount of time before you have to wait. The reason I moved to paid plans early wasn’t because the free versions were useless. It was because of how I like to work. I use voice a lot. I think out loud. [I go on walks](https://www.thedaringcreatives.com/conversations-with-code/my-first-100-posts/) and talk things through. I didn’t want to hit a wall after twenty or thirty minutes and be told to come back tomorrow. Another reason I’ll sometimes pay for higher-tier plans is access. New features almost always land there first. New image models. New video tools. Experimental workflows. Sometimes I’ll pay for a month just to explore what’s possible, then cancel when I’m done. But none of that is required to begin. If you’re just starting out, especially if you’re not billing clients yet, the free tier is enough. The goal isn’t to buy the “professional” plan. The goal is to start using the tool enough that you understand what it’s good at and where it helps you. You can always upgrade later (or downgrade) once you know *why* you’d want to. ## Value shows up before revenue If you’re not running a business yet, or you’re early in your career, the value doesn’t show up as money right away. It shows up as being able to get unstuck without waiting on someone else. As being able to test an idea instead of carrying it around in your head for weeks. As having a place to put half-formed thoughts and see what they could become. So, it changes how you work long before it changes how much you earn which is what you'd expect. ## Why waiting for your job to pay for it costs you time I hear this a lot: “I’ll wait until my company pays for AI tools.” What that really means is [waiting to build your own relationship](https://www.thedaringcreatives.com/keep-going-youre-not-wrong-for-learning-this/) with the technology. When your employer controls the tools, you usually get the cheapest, safest, most locked-down version. It’s rarely tailored to how you think or work. And you don’t get to experiment freely. The cost of waiting isn’t money. It’s time, familiarity, autonomy, and confidence. By the time AI becomes mandatory, the people who started earlier won’t be better because they paid more — they’ll be better because they’ve spent time [learning how to work this way](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/). ## A first-principles way to think about cost If you want to strip this down to basics, I’d start with one question: Is it more likely than not that you’ll need to learn AI for your work at some point in the future? If the answer is yes, then the rest is just sequencing. You’re not deciding *if* you’ll learn it. You’re deciding *when*, and under what conditions. Starting earlier means learning with lower stakes, fewer expectations, and more room to explore. Starting later usually means learning under pressure. ## Where to start, realistically If you’ve never used AI at all, don’t overthink it. Sign up for a ChatGPT account. Use the free version. Start there. Drop in something you’ve already made and ask it to analyze it. Ask what it notices. Ask questions about your work. Ask it for help with something you don’t enjoy doing. Treat it like a collaborator, not a vending machine. If you’ve used AI a little, look for one or two things you can hand off — not everything. Maybe it’s first drafts. Maybe it’s feedback. Maybe it’s research or structure or sanity-checking your thinking. The point isn’t to optimize your spending. It’s to reduce the distance between what you’re thinking and what you can actually ship. That’s where the value shows up. ### Letting Go of Old Tools (Without Letting Go of Yourself) URL: https://www.thedaringcreatives.com/letting-go-old-tools/ Last updated: 2026-07-15T22:56:45.000Z ## **What does it actually feel like to let go of tools you built your identity around?** Before AI entered the picture, my tools said something very specific to the world. They said I was serious. I had invested close to six figures over the years into cameras, lenses, lights, audio, monitors. I shot everything with multiple cameras, even when it was overkill. I recorded in ProRes just because I had 96TB of space and I was sadistic. Instead of getting a slider, I had to have an edelkrone jib. Was it flexing? Yes and, it was meant to signal professionalism, care, and commitment. That gear gave me permission to call myself a video producer. It was momentum. A way of saying, “I’ve spent the money, so this is real now.” The camera especially mattered. The first one I ever bought was a Canon EOS R. I saved for it. I dreamed about it. Watched too many reviews about it. That was the system I learned on. Selling it later wasn’t about dollars. It was about acknowledging that a chapter had ended. ## **When did those tools stop feeling like leverage?** It happened slowly, as work shifted and business slowed in pockets. I’d look at my camera bag and realize it hadn’t moved in weeks. At the same time, the physical reality of carrying all that gear (when I needed to) started to weigh on me. Literally and figuratively. I was doing more run-and-gun work. Traveling. Shooting more aggressive schedules. Four or five locations in a day. Dragging cases through distilleries, warehouses, and event spaces. The gear that once made me feel capable started to slow me down. More importantly, it anchored me to a very specific type of work. Studio setups. Sit-down interviews. Pre-planned shoots. That wasn’t bad work. It just wasn’t the only work I wanted to do anymore. ## **Was letting go emotional?** I’ve never been especially sentimental about objects. I always saw gear as something you hold for a while and then pass on. I made sure it went to people who needed it. People getting started. People who were interesting. What I felt was closure. I’ve always thought of my work in versions. Version one of Daring Creative was spent producing podcasts and courses during the early pandemic. Version two was the more embedded business and lifestyle work I did. Version three is different. It’s lighter. More flexible. Less tied to physical logistics. [More work that allows me to use my knowledge about many things, not just my technique in one thing](https://www.thedaringcreatives.com/the-moment-i-realized-gear-wasnt-the-constraint-anymore/). So, selling the gear wasn’t grief. It was acknowledging that this version required different tools. ## **Why does this shift feel uncomfortable for so many creatives?** It’s about identity, not tools. About past investments and choices. About the fear that learning something new means starting from zero or inviting judgment. About worrying that admitting you use AI somehow invalidates the work you’ve done before. I understand the hesitation. Especially for people who’ve been doing this a long time. [But adapting here doesn’t mean outsourcing your thinking. It means changing how you solve problems](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/). It means being willing to orchestrate instead of only execute. To explain clearly what you’re after and let the tools help you get there. This tends to work well for generalists. For people who can connect ideas, give context, and stay patient through iteration. It also works for specialists who want more range around their core skill, not less. ## **What was the real thing I let go of?** I let go of needing my legitimacy to be visible through equipment. I let go of the idea that the “right” way to work was fixed. I let go of carrying weight that no longer helped me move forward. And to be clear, I didn't let go of just gear or old ways of doing things. I also let go of people. In some ways, I let go of a disadvantage. This shift also coincided with changing what Daring Creative was. Moving from a production company toward The Daring Creatives as a resource. Toward helping people understand what’s changing and how to orient themselves without panic or fear. Towards passing the torch and recognizing where I am in my own journey. I don’t feel the need to compete with younger people by out-grinding them. I would rather help them. ## **What does this mean for you if you’re feeling hesitant?** If you’re uneasy about letting go, that doesn’t mean you’re behind. It usually means you care about your work and the path that got you here. You’re not erasing yourself by changing tools. You’re deciding which version of yourself you want to keep investing in. Letting go doesn’t have to be dramatic. Sometimes it’s just acknowledging that the work wants to be lighter now. And giving yourself permission to follow it there. ### The Moment I Realized Gear Wasn’t the Constraint Anymore URL: https://www.thedaringcreatives.com/gear-is-not-the-constraint/ Last updated: 2026-07-15T22:56:45.000Z ## What was the moment that changed how I thought about using AI in my creative work? For me, it didn’t start with a decision to “use AI” or rethink my workflow. It started with a video I almost scrolled past. It was someone filming another person in a parking lot. Just a phone. No crew, no lighting setup, no sound rig. And in real time, the background was being replaced. Not as an effect added later, but live. The person being filmed was suddenly standing in what looked like a cyberpunk, futuristic Tokyo. Neon signs. Depth. Atmosphere. What made it stick wasn’t just that the background changed. It was that the lighting matched. The subject didn’t look pasted in. The shadows made sense. The scene responded to the person in frame like it actually existed. It was essentially live rotoscoping, running on a phone. What caught my attention wasn’t how impressive it looked. It was how little it depended on everything I’d spent years optimizing for. The weather didn’t matter. The lighting didn’t matter. The location didn’t matter. There were no extras, no permits, no setup time. The only thing that really mattered was that the person behind the camera could imagine the scene clearly enough to describe it. That was the moment I realized something simple: if I can imagine it, I can probably make it now. Not perfectly, and not instantly, but enough to get the idea out of my head and into something real. And that was new. ## Why did that realization feel so significant at the time? Up until then, my instinct had always been to solve creative problems by upgrading equipment. I’d spent years as a freelance video producer reinvesting almost everything I made back into gear. Cameras, lenses, monitors, lights, audio. I don’t regret that at all. That gear taught me how images work, how pacing works, and how story translates visually. But watching that video forced a comparison I couldn’t ignore. If I wanted to create that same scene in a studio, under ideal conditions, it would have taken real money, serious planning, and multiple people. Even then, I’d still be limited by what I could physically build or afford. Meanwhile, this was happening live, on a phone. That contrast made it clear that I had been spending a lot of energy solving problems that no longer needed to be solved in the same way. The issue wasn’t quality or professionalism. It was that [the constraints I was optimizing for had quietly changed](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/). ## How did I actually start applying this to my own work? The first place I applied this wasn’t client work. It was my own content. I spend a lot of time walking. I record videos and audio notes while I’m out. I notice characters, situations, small moments during the day that stick with me. For a long time, those ideas lived as fragments. Things I could talk about, but couldn’t always show. AI gave me a way to make sense of those ideas and extend them visually. I could take a memory from a walk, a situation I’d run into, or a point I wanted to make, and place myself into a realistic but fictional scenario that helped illustrate it. Not to trick anyone, and not to be flashy, but to make the idea clearer. To bring the feeling of the moment closer to what I experienced. I still record the same way. I still rely on instinct. But now, instead of hitting a wall when something wasn’t captured on camera, I had a way to continue the story. ## What did this shift change about how I think about creative workflows? Before, my work started with logistics. Where can we shoot? [What gear do we need?](https://www.thedaringcreatives.com/letting-go-of-old-tools-without-letting-go-of-yourself/) Who needs to be there? How much will it cost before we even know if the idea works? Now, the work can start with the idea itself. If the idea is clear, the tools can help you explore it before you commit to the heavy lifting. You can see versions of something, test directions, and decide what’s worth finishing. That doesn’t remove judgment or taste. If anything, it makes them more important. The tools don’t decide what’s good. They respond to how clearly you can articulate what you want. ## Does adopting an AI workflow mean abandoning traditional skills or craft? No. It changes how those skills show up. Everything I learned about framing, mood, pacing, and storytelling still applies. It just applies earlier in the process. Instead of using those skills only at the end, they shape the idea from the beginning. This isn’t about skipping work. It’s about skipping the parts of the work that only existed because the tools were limited. The craft doesn’t disappear. It stops being gated by access, budget, or ideal conditions. ## Is this the kind of realization most creatives will have eventually? I think so, not because anyone is forcing it, but because at some point most people will see something that makes the old tradeoffs feel unnecessary. They’ll watch someone create something compelling with fewer constraints than they thought possible, and it will quietly change how they evaluate their own process. That moment isn’t dramatic. It doesn’t feel like hype. It just feels obvious in hindsight. Once you see that imagination is no longer the primary bottleneck, it’s hard to go back to building your workflow around limitations that don’t carry the same weight anymore. ### What It Actually Means for a Creative to Adopt an AI Workflow URL: https://www.thedaringcreatives.com/adopting-an-ai-workflow/ Last updated: 2026-07-21T19:30:27.000Z If you’re reading this, you probably don’t need to be convinced that AI exists or that it’s changing things. You already know that. You see it every day — in the volume of work being shared, in how fast ideas move from concept to execution, in how many things now look finished that would have taken real time not that long ago. The question isn’t whether this technology matters. It’s what it means for *you*. Especially if you’re someone who’s spent years getting good at a specific thing. Illustration. 3D. Video. Design. Editing. Writing. A real craft, not a novelty. You’ve put in the time. You’ve built taste. You know when something is working and when it isn’t. And now you’re watching a lot more people create work that looks, at least on the surface, pretty good. This piece isn’t a guide, a manifesto, or a defense of AI. It’s an attempt to describe what adopting an AI workflow actually looks like for creative professionals who care about their work. ## What people usually mean by “an AI workflow” When people talk about adopting an AI workflow, it often sounds bigger or stranger than it actually is. In practice, it usually means this: instead of everything depending on you doing every step by hand, you have help turning rough ideas into something concrete faster. You can sketch ideas out before you fully commit to them. You can see versions of something before you spend days or weeks making the “real” one. You can test directions, throw things away, and keep moving without feeling like you’ve wasted time. The work still comes from you. You’re just not stuck doing everything the hard way before you know whether something is worth finishing. ## Will AI replace specialized creative work? If you specialize in something, this is probably the question sitting quietly in the background. Not because you think you’re obsolete, but because you can feel the comparison set widening. The honest answer is that AI isn’t suddenly doing your job at the level you do it. That fear tends to flatten the conversation. What *has* changed is the baseline. More people are able to produce competent work now, and polish is no longer the signal it once was. From the outside, the difference between “good” and “exceptional” can look smaller than it actually is. That’s uncomfortable, especially when you know how much judgment and care go into your decisions. But it doesn’t mean specialization has lost its value. It means the value is no longer self-evident. This is where AI becomes useful for specialists — not as a shortcut, but as a way to give your work more surface area. More context. More ways to communicate what makes it different. ## Whether using AI is “necessary” Right now, nothing is required. There are still plenty of people doing great work without touching these tools, and that’s not going to change overnight. What *has* changed is that staying still is no longer a neutral choice. Not because AI is mandatory, but because the tradeoffs are clearer now. Working without these tools often means narrower scope, more time spent on execution, fewer chances to test ideas before committing to them, and more pressure on every single piece to succeed. Adopting an AI workflow doesn’t make you better by default. It gives you options. Different ways to approach a problem. Different ways to express what you already know. And once you’ve felt that flexibility, it’s hard to pretend it doesn’t exist. ## What actually changes when you adopt an AI workflow The shift is less dramatic than people make it sound, but more meaningful over time. For many creatives, it looks like [trading gear-heavy investments for subscriptions](https://www.thedaringcreatives.com/the-moment-i-realized-gear-wasnt-the-constraint-anymore/). It looks like iterating earlier, before things feel precious. It looks like spending more time deciding *what* to make and less time forcing execution just to see if something works. Your work doesn’t disappear. It moves. Effort shifts away from friction and toward judgment — toward choosing which ideas deserve attention and which ones don’t. ## What doesn’t change Your taste doesn’t change. Your curiosity doesn’t change. Your ability to notice patterns, make connections, and care about the work doesn’t change. AI doesn’t give you those things. It just makes it harder to hide when they’re missing. If anything, these tools raise the bar on clarity. When execution becomes easier, intention matters more. The work has to mean something. It has to point somewhere. And that’s still a human responsibility. ## The real costs people don’t talk about AI isn’t free — not financially and not cognitively. Early on, most people spend too much, try too many tools, and get inconsistent results. Different models behave differently. Skills don’t always transfer cleanly. Predictability takes time. That phase is normal. Over time, things settle. You learn which tools you actually need. You turn subscriptions on and off as projects demand. You stop treating tools like identities and start treating them like utilities. That learning curve is part of adopting an AI workflow. Anyone pretending otherwise is selling something. ## Why this feels personal, not technical For a lot of creatives, the resistance isn’t about capability. It’s about identity. About past investments. About the quiet fear of starting over or admitting that the rules you learned under aren’t the ones that matter most anymore. Hesitation here doesn’t mean you’re behind. It usually means you care about your work and the path that got you here. This isn’t about erasing that path. It’s about extending it. ## You don’t need every tool You don’t need to master everything or build a complicated stack. For most people, a single general-purpose tool is enough to begin. Specialization comes later, when you understand *why* you need it. The goal isn’t accumulation. It’s reducing the distance between what you’re thinking and what you can share. ## Who this shift tends to work for This tends to work especially well if you already think across more than one lane. If you’re a generalist, this moment should actually feel pretty good. For a long time, being good at a lot of things felt like a liability. You were supposed to pick one skill, one title, one narrow path. AI removes some of that penalty. It lets you connect skills instead of apologizing for them. Writing, visuals, video, structure, story — they can live closer together now, even if you’re not a specialist in every piece. It also works well if you already have a strong core craft and want more range around it. Not to do everything yourself, but to think more clearly, try more ideas, and communicate what you’re doing to people who aren’t experts in your field. If you like experimenting, connecting dots, and figuring things out as you go, these tools tend to feel less threatening and more like leverage. ## Where to go from here You don’t need to decide everything right now. This page is just an orientation. If you want to go deeper, there are other parts of this conversation worth exploring — letting go of tools without losing your identity, understanding the real cost of AI tools, building a workflow that fits you instead of overwhelming you, and learning to start before you feel fully ready. Those are all connected. This is just the place to stand before you move. ### The Work Inside The Visual Dome URL: https://www.thedaringcreatives.com/creator-stories/visual-dome/ Last updated: 2026-08-16T10:25:14.000Z I don’t remember exactly when The Visual Dome showed up in my Instagram feed. It feels like one of those accounts that was just suddenly there, as an idea fully formed. The images stopped me. Retro-futuristic figures. Masks. Helmets. Scenes that felt cinematic but slightly unreal, like stills from a movie that never existed. I liked the style immediately, but I didn’t really understand it. ![Woman in an ornate gold luxury mask — The Visual Dome](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/visualdome-luxury-mask-still.jpg) Tony Rapacioli / The Visual Dome — from thevisualdome.com And that bothered me a little. I kept seeing this same look across AI images everywhere. Not just from this account, but across the platform. That soft retro surrealism. The sense of a future imagined decades ago. I wanted to know where it came from. Was it a preset? A prompt trick? A shared reference everyone was pulling from? So I followed the account and kept watching. The longer I looked, the harder it was to write it off as just a style. The images felt connected. Not visually identical, but related. Like they were all taken in the same place, even when the subjects changed. ![Masked figure with glowing eyes on a dusk street — The Visual Dome](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2026/07/visualdome-snatchers-still.jpg) Tony Rapacioli / The Visual Dome — “Snatchers,” from thevisualdome.com I’d had that same feeling once before, with [GossipGoblin](https://www.thedaringcreatives.com/creator-stories/the-work-hidden-inside-gossipgoblins-worlds/). When I wrote about his project for [The Daring Creatives](https://www.thedaringcreatives.com/the-daring-creatives/), what stuck with me wasn’t the look of the work, but how it behaved. They felt like images from a real place, not a collection of isolated ideas. That’s what I was noticing here with The Visual Dome. The Visual Dome — “Come See THE Show!” (2025) Eventually, I did some research on Tony Rapacioli, the creator. Once I started reading interviews and paying attention to how he talked about the work, the images made more sense. Not because they were explained, but because of how he thought about them. Tony didn’t come to this through AI culture. His background is in graphic design and photography, followed by years working in music technology and sound engineering (maybe someone I would describe as [a Daring Creative](https://www.thedaringcreatives.com/about/)?) He’s described his mind as “a factory… firing 24 hours a day,” the same mental engine behind his music, art, and writing (from his own account on his site, [tonyrapacioli.com/about-me-my-life](https://www.tonyrapacioli.com/about-me-my-life?ref=thedaringcreatives.com)). That framing stuck with me. A lot of people generate constantly. Fewer people edit themselves. In late 2022, Tony saw an image on Instagram that caught his attention because it didn’t seem feasible. The lighting. The scale. The implied production value. It looked like something that should have required a crew and a budget, not one person working alone. A few weeks later, he found Midjourney. The early experience wasn’t smooth. In a later interview, he said he spent “three days fighting with it” before anything worked the way he expected. Then, as he tells it, “11pm on one random night, tucked up in bed, it happened. I figured out how to prompt.” By the time he looked up, “it was 5am… my son was standing there asking why the heck I was still on my laptop” (recounted in *Inside The Visual Dome, A World Prompted Into Existence With AI* by Charlie Fink, [Medium](https://charliefink.medium.com/inside-the-visual-dome-a-world-prompted-into-existence-with-ai-179d2a463d9c?ref=thedaringcreatives.com)). That’s where most explanations of AI art stop. Prompting. Keywords. Settings. But the more I looked at The Visual Dome, the clearer it became that prompting wasn’t all there was to making visuals like these. Continuity was. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/The-Visual-Dome-websaite-2025.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/The-Visual-Dome-resident.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/The-visual-dome-domers.png) To learn the backstory for The Visual Dome, make sure you visit the excellent website. So damned cool. Tony has described his early process simply as “refining my style, keeping [continuity](https://www.thedaringcreatives.com/ai-image-consistency-guide/),” even when that meant discarding images he liked. Images that didn’t fit the world didn’t survive, no matter how strong they were on their own (from the same Charlie Fink interview). In the Visual Dome's world, colors repeat for a reason. Clothing signals social class. Certain technologies appear in some places and nowhere else. Masks aren’t decoration. They’re cultural. The Visual Dome is divided into five districts, each with its own social structure and visual language. Tony has described it as a “parallel world where everything feels very familiar but is strangely different” ([thevisualdome.com/history-of-the-dome](https://www.thevisualdome.com/history-of-the-dome?ref=thedaringcreatives.com)). Those distinctions aren’t explained every time. They don’t need to be. They’re embedded in the images themselves. Early on, Tony realized something else too. The images weren’t enough on their own. “They didn’t make sense,” he said. “They needed [context](https://www.thedaringcreatives.com/context-is-your-creative-edge/).” That realization pushed him toward writing, even though he didn’t consider himself a writer before. AI, he later said, “sparked a love for writing, something I didn’t know I had” (from *Sur Instagram, la recherche de sens des artistes utilisant l’IA*, *Le Monde*, Feb 2024: https://www.lemonde.fr/pixels/article/2024/02/16/sur-instagram-la-recherche-de-sens-des-artistes-utilisant-l-ia-ces-images-ne-sont-pas-entierement-les-miennes\_6216955\_4408996.html). The writing doesn’t explain the images. It gives them somewhere to live. The workflow itself is surprisingly straightforward. Midjourney through Discord. Iteration. Upscaling. Light cleanup in Photoshop. The heavier lift is invisible: notes, rules, character details, and a growing internal bible that keeps the world from drifting. Most people encounter The Visual Dome through Instagram, where images and short pieces of lore are released steadily. Over time, patterns emerge. Characters recur. Locations feel familiar. Tony refers to the audience as “Domers,” and has said the world is becoming “as much theirs as mine” as people invest in its details and stories (reported in *AI Art Project Captivates 700,000 Instagram Followers*, CO/AI News, [https://getcoai.com/news/ai-art-project-captivates-700000-instagram-followers/](https://getcoai.com/news/ai-art-project-captivates-700000-instagram-followers/?ref=thedaringcreatives.com)). Prints, NFTs, and exhibitions came later, framed as extensions rather than pivots. Characters weren’t positioned as assets. They were positioned as residents. Ownership was treated as a way of being closer to the world, not extracting value from it. The longer I’ve looked at The Visual Dome, the less I see it as mere AI art. What’s interesting is the care. The editing. The decision to treat this like a place instead of a trick. If you scroll fast, it’s easy to miss all of that. But if you slow down, you can see how much is being held in place. And once you notice that, it’s hard to look at the work the same way again. ### Less Artwork. More Assets. URL: https://www.thedaringcreatives.com/less-artwork-more-assets/ Last updated: 2026-07-15T22:56:46.000Z If you’re reading this, you probably care about craft. You care how things are made. You notice details other people don’t, and you’re willing to put in more effort than is strictly necessary because the work feels like a reflection of you. I care about that too. Probably to a fault. For most of my career, I’ve wanted to put more time into things than anyone was paying me for. Two hours was never enough. I could always see another ten hours of improvements waiting just beneath the surface. Even if I didn’t get paid for it, I *still* put in that time. This alone made me a terrible freelancer. That impulse has always followed me, especially in video. I wanted to scrutinize the sound. The lighting. The color. The rhythm of every cut. Would someone notice how we heard the speaker before we saw them? I wanted the work to hold up if someone *really* looked into it. And then a client said something I still think about. “I’ve wanted to tell you this for a while,” they said. “I’d rather you spend your time making ten okay videos than one great one. I can do more with ten videos. Could you make a hundred videos?” That wasn’t harsh feedback. It wasn’t even wrong. But I took it hard, and if I’m being honest, I still do. More recently, I heard a different version of the same message. The work was beautiful. The website looked great. The videos were strong. [It’s just a shame they weren’t turning into more sales](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/). For a long time, I wore that criticism as something about my ability or my taste. It wasn’t until later that I realized it had nothing to do with that. Commercial work isn’t judged by how it’s made. It’s judged by what it does. Most of it doesn’t live very long. It shows up in a feed, competes for a second of attention, and then it’s gone. Replaced by the next thing. And the next. And the next. That’s not failure. That is the job. We like to talk about art as if it’s meant to be studied, revisited, and lived with forever. But most commercial creative work is built for motion, not permanence. It’s designed to be glanced at, not contemplated. Our brains decide almost instantly whether something is worth more time. Color, contrast, familiarity, motion. That’s usually all it gets. In that environment, the difference between “great” and “good enough” collapses quickly. This is where the language shift matters. A lot of what we’re making for businesses isn’t really artwork. It’s assets. Assets are meant to be deployed. Tested. Swapped. Iterated. Retired. They’re part of a system that values [consistency](https://www.thedaringcreatives.com/ai-image-consistency-guide/) and volume over singular moments of brilliance. When someone says, “This looks beautiful, I just wish it turned into more sales,” they’re not critiquing my craft. They’re saying, "this wasn't worth it." The work did its job aesthetically, but not operationally. We’re pouring ourselves into things that are being consumed as [disposable inputs](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/). Not because clients don’t care, but because the systems they’re operating inside don’t reward reverence. It rewards engagement, shares, and sales. Once I made this realization, everything changed. Around that same time, I committed to learning AI. And here’s what I learned. AI is good at the exact things feeds demand: [speed](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/), variation, volume, iteration. It doesn’t need its identity affirmed. It doesn’t mind being “good enough.” That’s what makes artists uneasy. But here’s the context that’s easy to miss: a lot of the work people are paying for is meant to be disposable. Not cherished. Not studied. Used. It’s designed to be deployed, replaced, cut up, remixed, and forgotten so the next piece can take its place. For people like us who care deeply about craft, this creates a quiet drain. Not from making the work, but from keeping up with the demand for constant output in environments that don’t reward care. Seen this way, AI isn’t devaluing art. It’s matching the expectations of the work it’s being asked to do. The harder question isn’t whether AI belongs in creative work. It’s this: Where are you putting your care? And is the system you’re working inside actually capable of receiving it? 💬 I'm still working through these ideas in public. If you’re thinking about the same tensions around craft, output, and AI, I’m talking about it on Threads. Join the conversation with me there. [Connect on @Threads ](https://www.threads.com/@thedaringcreatives?ref=thedaringcreatives.com) ### This Is Not the Theft You’re Looking For URL: https://www.thedaringcreatives.com/conversations-with-code/ai-art-theft-debate/ Last updated: 2026-08-01T19:44:08.000Z 0:00 /0:10 1× It’s the morning after two arguments that shouldn’t be related, but somehow are. The night before, I was in a long back-and-forth about [gatekeeping](https://www.thedaringcreatives.com/ai-broke-rick-beato/) with someone who dresses like a cat and takes glamour shots in a pumpkin patch. This morning, a man who cosplays as a Jedi is [calling me a thief](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/) for using AI. Different costumes. Same energy. I keep staring at one word he used with absolute certainty. *Stealing.* Not as a question. Not as a concern. As a verdict. ## Why does “theft” show up so fast in these conversations about AI? > **WILLIAM:** > What throws me is how quickly it jumps to that word. “You’re stealing.” No curiosity. No attempt to understand how these systems actually work. And the irony is hard to miss. This guy’s creative identity is literally dressing up as a Star Wars character. Meanwhile, [OpenAI and Disney just signed a licensing deal](https://www.thedaringcreatives.com/disney-just-pointed-sora-at-its-vaul/) that allows people to create within that universe. How is *that* not part of the discussion? > **CHATGPT:** > Because the accusation isn’t really about theft. It’s about permission. > **CHATGPT:** > “Stealing” skips the mechanics and goes straight to moral authority. It lets someone occupy the role of defender without needing to understand the system they’re condemning. > **CHATGPT:** > Cosplay, fan art, tribute bands, covers—all of these exist because institutions decided where imitation was allowed, where it was celebrated, and where it was protected. People learned how to belong inside those lanes. > **CHATGPT:** > AI doesn’t ask first. That's the rupture. That reframes the whole thing. I think about music. If you play music in public, you’re supposed to pay for that privilege. There are licenses, fees, enforcement. But if you dress like Luke Skywalker, pose for photos, and build a whole persona around a borrowed universe, no invoice arrives. No one calls you a thief. It’s celebrated. ## So why does AI trigger such a strong reaction? > **WILLIAM:** > This person isn’t losing work. No one’s training a model on his likeness. He’s not directly impacted. He’s speaking *generally*, on behalf of artists. Why does that outrage feel so intense? > **CHATGPT:** > Because this isn’t impact-based outrage. It’s identity-based outrage. > CHATGPT: > Cosplay performs devotion. It reinforces the existing hierarchy. The IP holder stays on top. The fan stays grateful. Nothing about the system is threatened. > CHATGPT: > AI collapses distance. It gives people agency instead of proximity. That’s destabilizing to anyone whose sense of worth is tied to the old map of who gets to create and who gets to participate. > CHATGPT: > When the [map stops matching the terrain](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/), people defend the map. That lands uncomfortably close. I realize something else. I didn’t actually argue his claims. I reacted to his posture. When he called me a thief, I snapped back with sarcasm about his art. That’s when the conversation collapsed into name-calling and assumptions. By then, I already knew the exchange was pointless. I just stayed too long. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Jedi-and-friend-in-volcanic-duel.png) ## So what was the real mistake on my end? > **WILLIAM:** > I tell myself I’m open to disagreement. I like pushback when it’s thoughtful. But these conversations always seem to slide into insults. At what point should I have disengaged? > **CHATGPT:** > Earlier. > **CHATGPT:** > If someone starts with curiosity, they want understanding. > If someone starts with a moral accusation, they want submission or conflict. > **CHATGPT:** > “You’re stealing” isn’t an argument. It’s a verdict. Once someone opens with a verdict, there is no third option. You can either defend yourself inside their frame or escalate. Neither produces insight. That’s the lesson. Not “don’t argue with clowns.” Not “people are ridiculous online.” It’s learning to recognize the moment a conversation stops being about how something works and starts being about who someone needs to be in order to feel secure. The Jedi costume. The cat ears. The pumpkin patch. They’re not the point. They’re symptoms of the same thing. People trying to anchor certainty in a world that no longer hands it out by default. Aiming higher doesn’t mean being quieter or nicer. It means refusing to argue inside a moral theater where the verdict was decided before you spoke. When someone calls you a thief without curiosity, they’re not inviting a conversation. They’re defending a map that no longer matches the terrain. Sometimes the smartest move isn’t to respond at all. It’s to step back and realize you were never actually the defendant. ### The Anti-AI Crowd Keeps Imagining the Wrong Player URL: https://www.thedaringcreatives.com/anti-ai-crowd-missing-context/ Last updated: 2026-07-15T22:56:46.000Z There’s this strange template floating around in the [anti-AI world](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/). A default character model they load in whenever they picture someone using AI. According to them, the moment you touch these tools you reboot as a level-zero creator. No backstory, no skill points, no quests completed. Everything you did before gets wiped like a corrupted save file. It’s funny how confidently they describe people who don’t exist. Most professionals using AI aren’t level zero. They’re basically walking in on **New Game Plus**. They’ve already beaten whole chapters of the old game. They’re carrying years of experience, habits, scars, [taste, and judgment](https://www.thedaringcreatives.com/context-is-your-creative-edge/). The only thing that’s “new” is the toolset. The character is already prestiged. But that’s not how the critics see it. In their version, you pick up a new capability and immediately lose the right to every previous title. If you wrote books before, apparently you’re not a writer now. If you composed music before, somehow you no longer understand rhythm. They talk like adding a new perk automatically resets your entire skill tree. No other profession works like this. If a carpenter switches from a hammer to a nail gun, they don’t get demoted to apprentice. Nobody tells a photographer they’re no longer a photographer when they upgrade their camera. Only in creative work does improving your toolkit supposedly downgrade your identity. And here’s the part the critics never account for. People who were already good at their craft didn’t just keep their abilities. They [stacked them](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/). Writer → Writer Plus. Designer → Designer Pro. Musician → Musician with unlocked modifiers. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Level-50-Creator-1.jpeg) A cinematic, hyper-realistic character screen, 1920x1080\. Dark, moody background with soft rim lighting. A middle-aged man stands right of center wearing a tactical hoodie, backpack harness, black cap, glowing over-ear headphones, and translucent yellow sunglasses. Calm, focused expression. Left-side UI shows “LEVEL 50,” max level reached, NG+ active, and high skill bars. Right-side inventory displays premium gear and creative tools. Minimal sci-fi typography, gold accents, shallow depth of field, polished AAA game menu aesthetic. Combining old skills with new tools opens maps that used to be locked behind time or money. You’re not replacing expertise. You’re evolving what it can reach! And honestly, most artists have nothing to fear from the person tapping around on an AI app for a few minutes. That "kid" who downloaded an app from the App Store to make meme videos isn't their competition (yet). The real shift comes from professionals who’ve been learning these systems for years. The ones building workflows, not dabbling. Those people aren’t rolling new characters. They’re running a prestiged build with late-game experience. Which brings me to a simple move the next time someone challenges your legitimacy: ask to see their character sheet. Who are these people, exactly? What quests have they completed? What have they shipped? I’ve checked. Usually it’s one of two things: either they haven’t posted any work at all, so there’s nothing to evaluate, or they have… and it’s fine, or it’s not. Both outcomes are subjective. My wife and I can look at the same piece and have opposite reactions. Neither of us is wrong. Taste isn’t a credential check. So what’s the actual criteria? Commercial success? Prestige? Follower count? None of that decides whether someone *is* the thing they say they are. The only honest metric is whether they’re doing the work. And in every game, the players who adapt get further. The ones [clinging to the starter loadout](https://www.thedaringcreatives.com/why-does-vince-gilligan-hate-ai/) usually end up arguing with the loading screen. ### Disney Just Pointed Sora at Its Vault URL: https://www.thedaringcreatives.com/disney-sora-vault/ Last updated: 2026-08-01T19:44:08.000Z [Disney announced a partnership with OpenAI today](https://openai.com/index/disney-sora-agreement/?ref=thedaringcreatives.com), and it lands with the kind of thud that tells you something irreversible just happened. The deal is simple on paper: Sora gets access to more than 200 characters across Disney, Pixar, Marvel, and Star Wars. Fans (like you and me) will be able to generate short videos inside those worlds. ChatGPT Images gets the same access for stills. Disney invests a billion dollars into OpenAI. And all of this eventually shows up on Disney+ as curated content made by regular people with a text box. You can feel half the internet cheering and the other half losing their fucking mind. People have been arguing for years about whether AI belongs in creative work, whether tools like Sora “count” as art, whether this whole wave is just a fad (or worse, a bubble.) Disney ending that debate with a licensing deal isn’t subtle. They didn’t pilot something small here. They opened their vault and said, "here, go make things." ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/OAI_Disney_Hero_16x9.webp) This is going to incense the [Gray Glasses](https://www.thedaringcreatives.com/toxic-threads-untalented-hacks/) (the Anti-AI mob) for obvious reasons. If you already believe AI is an existential threat to you as an artist, this feels like the literal end of the world. Your childhood characters are now officially living inside a generative model. Your memories are being turned into prompt-ready assets. And instead of threatening lawsuits or issuing takedowns, Disney is nodding and saying, yes, that’s the plan. But outrage alone doesn’t erase what this actually signals. The biggest storytelling company on the planet is putting real money, real IP, and real distribution behind the idea that AI is not only part of creative work but a core part of where things are going. You don’t pour a billion dollars into a technology you think is a side project. And you certainly don’t license *The Avengers* unless you’ve decided the medium is legitimate. People will complain, loudly. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Screenshot-2025-12-11-at-1.44.06---PM.png) The cynic will say Disney is [doing this to for money](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/). The optimist will say it’s a new era of [fan storytelling](https://www.thedaringcreatives.com/ai-and-the-return-of-participation/). The truth sits somewhere in the middle. This isn’t about replacing creators or empowering them. It’s about control. If AI is going to remix everything anyway, Disney would rather be the one handing out the brushes. Better to define the sandbox than to chase everyone around with cease-and-desist letters. And it’s not like Disney is the first one through the door. We’ve already seen Shaq, Jake Paul, Mark Cuban, and Snoop work with Sora to license their likeness and build new forms of expression. Those deals looked experimental. This one looks structural. When individuals do it, it’s curiosity. When Disney does it, it’s a signal. [Hollywood has been dragging its feet](https://www.thedaringcreatives.com/why-does-vince-gilligan-hate-ai/) on AI, so this might be the watershed moment that forces the industry to say out loud what’s been obvious for a while: the tools aren’t going away, and pretending they might isn’t a strategy. Disney stepping into the arena makes it legitimate in a way no press release ever could. You don’t have to love this. You don’t have to use the tools. But the future isn’t waiting for everyone to feel comfortable first. Disney just handed the prompt box to the world. Now we get to see what people actually do with it. ### The First 100 Posts URL: https://www.thedaringcreatives.com/conversations-with-code/my-first-100-posts/ Last updated: 2026-02-20T05:35:35.000Z ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Autumn-Stroll-in-the-Suburbs-2.png) ## **What should I expect from my first hundred posts?** Morning in Vancouver carried its usual damp chill, the kind that clings to the air without ever turning harsh. Wet leaves gathered along the sidewalks, glinting under breaks of pale sunlight stitched between drifting clouds. The neighborhood blended apartment clusters with those larger, careful-looking houses where every hedge felt professionally negotiated. Wilson led with the easy confidence of a dog who believes the block is his to supervise. > WILLIAM: > So here’s the thing I keep coming back to. Before I even get to a hundred posts on The Daring Creatives, I should probably expect… [basically nothing](https://www.thedaringcreatives.com/portfolio-or-personal-brand/). No real readership. No actual engagement. Just… crickets. And maybe that’s fine. Maybe the whole point right now is just building up enough of a base so that eventually people even have something to find. > CHATGPT: > Right. The first hundred posts aren’t there to perform. They’re there to get you calibrated. You can’t skip this part. It’s the unglamorous season where you figure out what you’re actually trying to say. The idea didn’t deflate him. It steadied him. He walked on without rushing, letting the truth settle into place. What he said next wasn’t a contradiction. It was simply the next logical question in the chain, waiting to be spoken. Early invisibility is not a setback. It sets the stage for the next problem: speed. ## **Is my posting cadence too slow for an AI paced world?** He turned onto a quieter stretch where condos lined the street and the landscaping was a little sharper, a little more curated. The sun broke through in patches, throwing light across lawns dotted with leaves. Dog walkers appeared here and there, bundled up but unhurried. It was the kind of environment where thoughts naturally reorganized themselves. > WILLIAM: > I’ve been thinking about my posting cadence, too. Like, right now I’m doing maybe two longer articles a week. Eight hundred words. Sometimes a thousand if I’m really in it. And honestly… at that pace, it’s gonna take a really long time to build anything. Especially in AI, where something is relevant for like ten days before it gets swallowed by the next big thing. So it feels like I’m moving slow in a space that never stops sprinting. > CHATGPT: > Two long pieces a week is great for a mature publication. But you’re building something from scratch. The problem isn’t your speed. It’s the format. [AI moves fast](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/). You don’t need more essays. You need more touchpoints. Smaller ones count. He absorbed that with a small pause. Not disagreement, but recalibration. In a fast ecosystem, rhythm matters more than polish. ## **How do I increase my output when my time is capped?** The walk shifted into the part of the neighborhood where the homes were larger and the yards were “professional-help” tidy. The air smelled faintly of damp bark mulch and trimmed hedges. Wilson paused to inspect something with the seriousness of a small operative assessing a situation. William paused with him. > WILLIAM: > Something I’ve noticed about myself is I genuinely get better when I’m doing more. Like, when the reps go up, everything gets sharper. My ideas are clearer. My writing feels easier. I feel more connected to the whole thing. > > But I’m still just one guy with one schedule, you know? I don’t have endless time. So how do I keep increasing my activity without burning myself out or sacrificing everything else I’m trying to do? Because right now it feels like the ceiling is already here. > CHATGPT: > You don’t increase the hours. You adjust the format. Right now you force every idea through the “full essay” funnel. That’s too tight. Most of your ideas don’t need that treatment. If you widen the container, your output increases naturally without touching your schedule. This reframing landed cleanly. It didn’t lighten the workload. It simply illuminated the real constraint. As he continued walking, his pace returned to its usual rhythm. The next question wasn’t tactical. It was philosophical. And it always showed up around the same point in the walk, right before the park. The bottleneck isn’t effort. It’s structure. When the structure flexes, possibility expands. ## **Does the ideation itself count as work?** The sidewalk transitioned into the outer edge of a neighborhood park bordered by tall fir trees. Their branches held drops of moisture that flickered in and out of the returning sunlight. The grass was darkened in patches from the previous night’s dampness, and the air was cleaner here, carrying the smell of soil and pine. This was the quiet part of the walk, where the bigger, softer questions usually surfaced. > WILLIAM: > Every time I walk, I end up talking out loud like this. I’ll run through ideas, connect threads, test stuff, rethink things I already thought I had decided. And honestly, fifty percent of it never becomes anything. But there’s something about the walking and talking that actually feels like the [real work](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/). > > I just don’t know if that “counts,” you know? Or if it’s just pre-work. > CHATGPT: > It’s the most valuable part. The ideation is upstream from everything. People think the writing is the real work. It’s not. The writing is just the evidence that the thinking happened. The walk is where the clarity comes from. He didn’t respond right away. The kind of silence that indicates recognition, not doubt. The fir trees overhead, the open space ahead, and the slower pace seemed to make room for that understanding to land fully. And naturally, once he accepted that ideation matters, he started questioning how it might fit into his work. Thinking is production. You just haven’t been measuring it that way. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/Autumn-Walk-with-Dog-and-Phone.png) ## **Should these walking sessions become a series?** The trail narrowed under the fir canopy, creating a muted corridor before opening into a brighter clearing. Morning dog walkers passed in loose intervals, each following their usual route. Wilson squared up at the sight of a husky, shoulders lifted in his “I’m watching you” stance. William’s voice shifted again, this time circling a possibility that had been lingering. > WILLIAM: > So this might sound weird, but I keep wondering if these walking sessions could be something. Like… maybe they’re the actual series. Because this is where all the real stuff happens anyway. This is where I think. This is where the ideas start. And maybe people would actually get something out of seeing the messy middle instead of just the final version. > > I don’t know. It feels obvious now that I’m saying it out loud. > CHATGPT: > It should be a series. And it already exists. You’re just not publishing it. This is the real texture of your work. The thinking, the walking, the drift from one question to the next. If you document this, you’re not adding work. You’re capturing the work you’re already doing. He didn’t react with surprise. He reacted with recognition. The idea wasn’t new. It had simply become visible. And once visible, it pointed him toward the final question of the walk. When a process is natural, it is often the one worth building around. ## **What are the first hundred posts really for?** The loop back toward home passed through rows of townhomes and small apartment balconies where dogs barked greetings or objections as walkers passed. Cars warmed in driveways. The air held that unmistakable “Vancouver winter morning” smell: damp mulch, cold air, and a little sunlight pushing through. This stretch of the walk always invited the most distilled insight. > WILLIAM: > Something I notice about myself is I’m always talking myself through the same things I tell other people. And I’m doing it out here, walking around this neighborhood, trying to make sense of what I’m building. It’s like… I already know the advice. I just don’t always apply it to myself first. > CHATGPT: > Which is exactly why your advice works. It comes from lived patterns, not theory. These walks are where your frameworks are built. The writing just makes them visible. > WILLIAM: > And maybe that’s the point. Maybe the first hundred posts aren’t supposed to be seen. Maybe they’re just… me figuring out how to talk. How to think in public later. > CHATGPT: > They’re not supposed to be seen. They’re rehearsal. They’re where your voice stops wobbling. Visibility comes later, once you’re steady. The walk didn’t need a conclusion. The message had already arrived. The early work shapes the person who can handle being seen. ## ### When a Tool You Love Stops Loving You Back URL: https://www.thedaringcreatives.com/when-tools-stop-loving-you/ Last updated: 2026-08-01T19:44:08.000Z This is a bummer. [Warp.dev](https://warp.dev/?ref=thedaringcreatives.com) has been my main tool for building things, including the entire[ The Daring Creatives](https://www.thedaringcreatives.com/the-daring-creatives/) site. It made coding feel possible for someone like me. It fit how I work. It felt like the right tool. And now it feels like the tool and the company behind it do not really want users like me anymore. I found Warp because of Jess on TikTok, who goes by @therubberduckiee. She highlights tools that help people like me build without getting stuck in the old way of doing things. Warp was one of those tools. It felt like a small door into a new kind of workflow where ideas come first and AI helps you turn them into something real. What I liked about Warp was the feeling that I was having a conversation with my own computer. Using ChatGPT feels like talking to something that lives somewhere else. Warp brought that same intelligence into my system. It could act on things. It could do work directly in the environment where I was building. It felt like the next step in how I use AI. That is why the recent shift has been frustrating. When a company starts moving away from the people who actually enjoy their product, you feel it. Pricing gets confusing. Plans are removed or changed in ways that do not make sense for individual builders. Features that used to be part of the value disappear. And then someone from their team publicly complains about vibe coders as if people who build with AI are somehow the wrong kind of customer. I am not angry about that. I am not sure I was even the target. It just lines up with the rest of the decisions long enough that you stop pretending it is random. You can like a product and still be honest about what the decisions say. > **Email from warp follows:** > This is a reminder that on December 6, 2025, your Team workspace will automatically transition to Warp’s new monthly Business plan as we sunset our legacy plans. There’s no action required on your end. > > - $50 base price per user per month > - Auto-reload turned on, at a cap of $310 spend per month > - This cap is based on your previous monthly spend and overages limit > > To change your auto-reload settings, visit Settings > Billing > > On the new Business plan, you'll receive: > > - 1,500 base AI credits each month > - Access to Reload credits, purchased when your credit balance is low > - Bring your own API key (BYOK) > - SOC 2 compliance > - Automatically enforced team-wide Zero Data Retention > - SAML-based SSO > - All the latest agent and planning features > Please make sure your Warp client is updated to the latest version so you can access all new features like BYOK. > We know this transition will be difficult for some teams. Our goal is to make the change as smooth as possible, while moving to a business model that allows Warp to be here for the long term. Losing Warp does not frustrate me because it broke. It frustrates me because it was working! It was an actual next step in my creative workflow. It was the only tool that made the computer feel like a collaborator instead of a machine waiting for the perfect command. It let me build without being a traditional engineer. It let me [move at the pace](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/) that AI makes possible. But I am not the customer they want. They want teams. They want enterprise. They want people who still work the old way. That is their direction and it is valid. It just leaves people like me standing on the outside of it. So I am switching. Not because Warp is bad. Because it stopped aligning with how I work. Google Ultra and Ghostty make more sense for me now. I get a clean terminal. I get a model that can actually take action. I get predictable billing. And I get to keep building without feeling like I am doing something the product was never meant to support. I'll probably keep paying on the "Build" plan for $20 a month as backup until I learn Gemini CLI better. What makes this disappointing is how much I genuinely liked using Warp. For a while it felt like the future. It felt like the first tool built for the new kind of builder. Maybe that group is too small for them. Maybe it was never the plan. But more people are building this way. More people are stepping into hybrid roles where AI takes care of the complex parts and the person focuses on vision and direction. That is not a niche anymore. It is becoming normal. Warp helped me get here. It helped me build things I did not think I could. It helped me get [The Daring Creatives](https://www.thedaringcreatives.com/about/) online. I am grateful for that. But the feeling changed and I am [moving on](https://www.thedaringcreatives.com/portfolio-or-personal-brand/). That is all this is. Not drama. Not outrage. Just putting my love somewhere its reciprocated. ### Keep Going. You’re Not Wrong for Learning This. URL: https://www.thedaringcreatives.com/not-wrong-for-learning-ai/ Last updated: 2026-07-15T22:56:47.000Z I keep noticing this tension toward AI, and by default, toward anyone who’s actually trying to understand it. We’re not learning this stuff (necessarily) to build personas or position ourselves as *experts*. We’re doing it because the tools are clearly becoming part of the world, and it feels smarter to understand them than to pretend they will go away. It’s curiosity mixed with [practicality](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/) (and anyone paying attention can feel that). People like us get pulled in because it just makes sense. And when you spend that much time trying to understand something new, of course you want to share it. Not for status or clout, but because you’re actually excited about it. But the second you say anything about AI in public, people assume there has to be some hidden motive tucked underneath. If you’re learning it, you must be doing something shady. Either you’re [stealing from artists](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/), or trying to replace people, or gearing up to sell a course and cash out. A lot of people don’t want to look at AI at all, and their refusal gets so strong that they start assuming bad intentions from anyone who does. Our curiosity ends up being misread simply because it challenges the story they’re holding onto. What makes that reaction funny is how detached it is from reality. [Most people don’t want anything to do with AI right now](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/). Nobody is lining up to buy AI artwork or music. Nobody is begging for instruction on how to use ChatGPT. The idea that you could get rich selling a course on something the average person is actively avoiding (and heavily stigmatized) is absurd. But the suspicion sticks anyway, because suspicion is easier than curiosity. And even if someone did make a course, why would that be a bad thing? When did education become something to sneer at? When have we ever gone through a massive technological shift without people needing to re-skill? It happens every time. Something big changes, and the people paying attention help everyone else get up to speed. That isn’t exploitation, it's adaptation. You watch the world tilt, and then you go learn the thing you now need to know. People *project* because they don’t want to feel behind. You’ve probably felt that in the way people respond to you talking about AI. They need to put you in a box so they don’t have to think about what they’re avoiding, so they'll try to bully you. But that has nothing to do with you. That’s just someone trying to protect their *comfort*. We both know it’s a fear of status loss, money loss, or just plain [gatekeeping](https://www.thedaringcreatives.com/ai-broke-rick-beato/). "You didn't do it like me, so therefore you're a cheater!" **There’s nothing wrong with sharing what you know.** If you’ve spent the time, if you’ve pushed through the confusing parts, if you’ve made sense of something most people still won’t touch, you’re allowed to talk about it. You’re allowed to be excited! You’re allowed to create something that helps someone else skip the hours you already spent. That’s not manipulation. That’s generosity. It’s how progress happens. When we step into this stuff early, we’re the ones taking the hits. We’re the ones running into the friction first. We’re the ones making sense of the weird edges before they’re smoothed out. And eventually, when everyone else shows up, they’ll need clearer pathways than the ones we had. That’s the cycle. Early learners do the messy part so later learners don’t drown in it. And the truth is, nobody knows what they’re doing right now. We’re figuring it out as we go. This is frontier energy. The map is still blank, and we’re drawing the first little pencil lines on it. Sharing that isn’t overstepping. It’s necessary. People forget that every major shift works this way. Something big changes, and a handful of people get curious early. Then they document. Then they teach. Then the world catches up. If you’ve been hesitating because you don’t want to look like a cliché, you can drop that. If you’ve been quiet because you’re worried people will assume the worst, you can drop that too. We need people who are willing to show what they’re learning. We need people who aren’t afraid to be excited. Keep going. Keep sharing. Keep being curious out loud. That’s how the rest of the world eventually figures this stuff out. ### Start Here: When AI Makes You Faster vs. Slower URL: https://www.thedaringcreatives.com/when-ai-makes-you-slower/ Last updated: 2026-04-02T15:19:27.000Z If you’re just starting with AI, you’ve probably already heard every version of the hype: it’ll automate everything, it’ll replace half your work, it’ll run while you sleep, it’ll pay your bills. I wanted that. I wanted to hand off entire processes and let the system figure it out. But here’s what actually shook out after a lot of experiments, a lot of wasted time, and more random subscriptions than I want to admit: AI helps the most when you don’t force it to handle the parts that need a ton of explanation. If it takes more time to teach than to do, skip the automation. That’s just the reality *right now*. I don’t think it stays this way. The tools are clearly moving toward a future where you can hand off whole workflows without limited context — and when we reach that point, it’ll be far more efficient than anything you can do manually. And, it will be awesome... But today? There’s still a cost to context. A few hours ago I was reviewing my site inside [ChatGPT Atlas](https://www.thedaringcreatives.com/meet-chatgpt-atlas/). It could literally see my analytics as I asked why my [readership wasn’t growing](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/) faster. I’ve trained ChatGPT to be blunt, so it told me what I already suspected: I’m writing plenty, I’m not promoting enough. My instinct was the instinct everyone has: *Great, then lets automate the promotion.* ChatGPT can write the posts, screen the content, hit publish, and save me the headache. And for context, I am talking about using ChatGPT Atlas's agentic mode for this. It tried. It clicked around Threads. It drafted captions. It poked around the UI to find where the buttons were to submit. And while it technically “worked,” it wasn’t faster than me doing it by hand. Just because AI can do something doesn’t mean it’s the always the efficient version of doing it. What actually sped things up wasn’t the posting. It was the prep. The agent skimmed my archive, pulled themes, proposed angles, generated decent starter captions. Those drafts meant I could step in, adjust tone, and schedule the posts. It doesn’t remove all the work, it removes the stuff which is more mechanical and boring. Just for help doing this part. The mistake is assuming that the moment you involve AI, everything becomes “easy mode.” It doesn’t. The quality of the result still depends entirely on the quality of your request (and context). The more steps you hand off, the more you have to describe, and that description becomes the work you were trying to avoid. But when you pick your spots, it’s a different experience. Research becomes lighter. Drafting becomes easier. Repetitive tasks turn into one-click tasks. And the more familiar you get with your own workflow, the easier it becomes to see which parts AI should touch and which parts are faster to keep manual. This is the version of AI that helps beginners the most: not full automation, but lets call it [*practical acceleration*](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/). It’s enough to make the work feel less sucky without asking you to give up taste, judgment, or direction. And if you’re just getting started, that’s something worth knowing. Use AI to clear space, not to disappear. The rest will come later — and when it does, you’ll already be ahead of the curve because you learned how to work *with* the tools instead of surrendering everything to them before they were ready. ### The Hidden Work Behind Gossip Goblins' Worlds URL: https://www.thedaringcreatives.com/creator-stories/gossipgoblin-zack-london-workflow/ Last updated: 2026-08-16T10:25:05.000Z **Update — July 22, 2026:** Gossip Goblin released a new sci-fi short today, *Pomegranate* (embedded at the bottom of this piece), and announced that his first feature-length film, *Gods Don't Give Gifts*, opens in US theaters October 30 ([Variety](https://variety.com/2026/film/news/gossip-goblin-ai-film-gods-dont-give-gifts-theaters-1236818068/?ref=thedaringcreatives.com)). The feature is four anthology shorts, made with the same script-first process this piece breaks down — though not, by this point, by one person alone. See the credit roll at the bottom. I've been working with AI visuals long enough to feel like I understand the basics. I know how far a single tool (ChatGPT) can take you and where the seams start to show. But watching Zack London (better known as Gossip Goblin) break down his process in a handful of Instagram stories made me rethink everything. He starts with a script. Not a prompt. Not a mood board. A script. He says it plainly: **"Every video starts with a script."** And when you see the kind of worlds he builds — from neo-feudal cyborg aristocrats to entire goblin civilizations — it makes sense. The writing is the spine and everything else hangs off it. Then you see how deep the work actually goes. Gossip Goblin — "THE PATCHWRIGHT | Cyberpunk Short Film" For a single set of characters, he ran **"probably 400 prompts / 1600 images."** And that's *just* to [get the faces right](https://www.thedaringcreatives.com/ai-image-consistency/). That level of iteration doesn't show up in the final video. You only feel the polish, not the mountain of attempts behind it. When he moves into environments, the honesty gets even clearer. He says **"this part is not enjoyable"** and then describes generating a "FUCKload" of background shots just to get something he could force his characters into. Nothing about this is automated. That's craft. That's stubbornness. That's someone who wants the world to hold together even when the tools don't make it easy. The same energy shows up in animation. Lip sync? He calls it **"a colossal headache."** Camera movement? Manual. Dialogue heavy scenes? Carefully shepherded. At one point he mentions running **"about 150 generations for a 90-second scene."** You don't do that unless you care. And you definitely don't do that if you think this is "just prompting." Gossip Goblin — "Feeding The Twins (Second Cycle of Humanity)" And that's the part that stuck with me. Zack has a line in another interview where he says, **"There is** [**zero skill**](https://www.thedaringcreatives.com/creator-stories/what-zack-london-actually-means-when-he-says-there-is-zero-skill-in-ai/) **involved in generating AI images."** It sounds harsh until you see what he actually means. The art isn't in the button press. It's in the world-building, the selection, the rewriting, the stitching, the judgement calls you make a hundred times before something finally looks intentional. You can feel that mindset in all his work. Seeing his process made me appreciate two different truths at the same time: 1. The computer handles the speed. 2. He handles everything else. That second line held for the work in front of me in 2025\. By *Pomegranate* it needs an asterisk — the credit roll at the bottom of this piece is where you can see why. And it also showed me how early I still am. I've worked inside my lane for 3 years now — ChatGPT visuals, simple storytelling, pieces that fit what I'm making. But watching Zack hop between half a dozen specialized tools, each doing one job well, each contributing to the final thing, made it obvious how big the landscape really is. There's a lot I haven't touched yet. A lot I haven't unlocked. What I took from his stories wasn't so much a tutorial as a reality check. The top people in this space aren't getting great results because AI "likes them." They're getting great results because they're willing to generate, rework, discard, and rebuild until the thing feels right. So when he ends one of the stories by saying the whole process takes **"12–14 hours end-to-end"** — for a single piece — it lands. The output is beautiful. But the work behind it is still laboriously human. ## Gossip Goblin's Toolkit Since people always ask *how* these videos get made, here's the simplified version of the tools Zack London uses and what he uses them for. This isn't comprehensive — just the core pieces he mentioned in his Instagram story. **Midjourney** Where he generates most of the characters, costumes, and visual concepts. Hundreds of variations, not one. **Seedream (via Freepik)** Used to blend characters into environments and force the pieces to look like they belong together, even when the lighting fights back. **Veo 3** His go-to for dialogue-heavy scenes. Handles simple movement and built-in audio, which he uses when lip-syncing isn't essential. **Runway (Act Two)** Used as part of his more complex lip-syncing or performance-driving workflows. **HeyGen** For generating clean lip-sync passes or creating "driving performances" that he uses to steer other models. **ElevenLabs** For voice work — to give characters a consistent, intentional voice instead of relying on whatever the model spits out. **CapCut** His editing choice. He jokes that he uses it "because I am a simpleton," but it gets the job done for assembling a dozen moving parts into one coherent scene. ## The asterisk: by Pomegranate, it's a crew Everything above describes one person at a keyboard, because in 2025 that's what the work was. *Pomegranate*, the 28-minute short below, carries a fifteen-name credit roll. Alexandru Mihai leads animation, with Benjamín Muñoz Alonso, Alberto Alepuz Fernandez and Nowell Englund animating. Răzvan Ilinca edited and supervised post. Anne-Sophie Versnaeyen and Juan Torán wrote the score. Ștefania Grigorescu graded it. Marian Bălan did sound design and the re-recording mix. Sam Dale, Ben Kersley, Oscar Merry and Ayça Özkan voiced it. London wrote, directed and produced, alongside Edward Saatchi and Fable Studio. None of that retires the numbers above — the 400 prompts and the 12-to-14 hours were real, and his studio still runs the same line on its own site: "Every story is imagined, written, and directed by humans. AI is just our force multiplier." What changed is the scale. He hired people, the way productions have always grown, and the credits are where it shows. [The full Pomegranate rollout and what it cost to make](https://www.thedaringcreatives.com/creator-stories/gossip-goblin-released-pomegranate-for-free-the-same-day-he-announced-a-theatrical-run/) is a separate piece. Gossip Goblin — "Pomegranate | Sci-Fi Short Film" ### A Different Way of Looking at Sunsets URL: https://www.thedaringcreatives.com/ai-sunset-generator/ Last updated: 2026-08-01T19:44:09.000Z A few nights ago, I had a short back-and-forth on Threads with someone named **@echo.blaster**. I’d made a comment about how everything we create comes from something we’ve seen, heard, or [absorbed](https://www.thedaringcreatives.com/ai-broke-rick-beato/). He called that “a foolishly reductive conclusion,” arguing that a person could paint from an *actual* sunset—something no AI could ever experience. I didn’t argue with him any further. Honestly, it was the 292nd argument about AI I’d had that day. But the exchange stuck with me—not because I felt insulted, but because it showed how Gray Glasses expect AI to replace human creativity instead off [add to it](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/). A person might see a few thousand sunsets in their life. If you lived to eighty-five and somehow saw every single sunset since birth (you wouldn’t, but let’s pretend), you’d top out around **35,000**. An image model, by contrast, has likely seen **millions or even billions** of sunsets during training. Rather than obsess over what AI *can’t* do, maybe the better question is what it *can* see that humans can’t—and whether that has value. To find out, I asked ChatGPT to break down what an AI actually learns from all those skies. The answer wasn’t poetic. It was structural. Mathematical. Geographic. Emotional. And honestly, fascinating. What emerged was a set of four distinct **modes of perception** that come from looking at the world at scale. Together they form what I’m calling the Sunset Pattern Catalogue (fancy). **1\. The Anatomy of Light** AI sees the math beneath the beauty. It recognizes the wavelength progression of every sunset—from 580 nm amber to 450 nm violet. It identifies the hidden four-minute phase between golden hour and blue hour where the infrared glow spikes. It sees how humidity, pollution, and altitude reshape the red-to-blue balance, giving each region its own spectral fingerprint. *Creative takeaway: colorists and filmmakers can design lighting arcs based on real atmospheric behavior instead of vibes and guesswork.* **2\. The Geometry of Awe** [Structure](https://www.thedaringcreatives.com/directing-the-machine/) matters as much as color. AI sees that roughly 78% of sunset photos place the horizon in the lower third. It recognizes that the most shared compositions include a strong silhouette cutting across the gradient at about 35 degrees. It sees repeating cloud bands like visual rhythm—almost like 4/4 time in the sky. *Creative takeaway: designers can treat cloud structure and silhouettes the same way* [*musicians*](https://www.thedaringcreatives.com/sound-isnt-song/) *treat rhythm and timing.* **3\. The Planet’s Palette Library** Across billions of images, the model has mapped Earth’s color dialects. Desert sunsets lean copper and blood-orange with hard contrast. Coastal ones soften into pastels. Urban haze pushes the palette into pink-violet sodium glow. Polar sunsets linger in desaturated lavender. Tropical skies tilt into dominant magenta because of higher red-channel saturation. *Creative takeaway: build mood and palette “by latitude”—letting geography shape tone the way it shapes light.* **4\. Atmospheric Storytelling** AI correlates language with light. Captions associated with sunset photos cluster around peaceful, end, fire, hope, goodbye. Warm-to-cool gradients map cleanly to positive-to-melancholic sentiment. The combinations matter: “Sunset + Ocean” correlates with calm; “Sunset + City” with nostalgia; “Sunset + Mountains” with awe. *Creative takeaway: writers and musicians can build emotional arcs using these natural transitions—heat fading into cool.* **There were some other interesting findings** AI learns more about *us* than the sky. It sees that people overexpose sunsets by about 0.6 EV because we like our skies brighter than reality. It sees that 63% of mirrored sunsets are cropped for fake symmetry. And only 2% of photos capture the light hitting the landscape behind the viewer—the part humans almost never think to turn around and look at. *Creative takeaway: the unphotographed 2% is creative territory nobody is exploring.* **The Physics of Mood** Natural events stamp themselves into the sky. Post-storm clarity boosts scattering range by about 15%, which explains “after the rain” brilliance. High-altitude thin clouds amplify color twice as effectively as low dense ones. Volcanic or wildfire aerosols supercharge reds for months at a time. *Creative takeaway: nature literally records human events; artists can use that as metaphor or pattern.* ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/ec8286a3-ced9-4eba-b38a-af13e19ac838.png) A photorealistic 1920x1080 cinematic sunset over a desert landscape. Use high-clarity atmospheric physics: strong red-channel dominance near the horizon transitioning smoothly into orange, magenta, violet, and cool blue at higher altitude. Apply post-storm desert clarity with sharp contrast and long-range visibility. Include layered cirrus and altocumulus clouds catching the last top-edge sunlight, creating horizontal light bands with subtle gradients. Foreground is a desert with soft dunes and scattered shrubs, warm light grazing the sand. Midground shows distant jagged mountain silhouettes in deep purple shadow. Place the horizon slightly below the lower third for dramatic sky emphasis. Use an unobstructed, clean desert atmosphere to intensify color saturation. Overall mood should evoke awe and calm—the emotional profile associated with desert sunsets: quiet, expansive, timeless. **The Emotional Algorithm** By cross-referencing images with captions, AI uncovers how emotion organizes itself visually. Sunset + Ocean means closure. Sunset + City means reflection. Sunset + Silhouette means intimacy. Sunset + Mountains means transcendence. *Creative takeaway: choose setting intentionally—each backdrop already carries emotional weight.* So yes, AI has never felt a sunset like a human has (not yet, anyway). But it has seen more sunsets than any human who has ever lived. It recognizes relationships we’ll never fully perceive. Maybe that’s the creative potential here. Humans bring emotion to what we see. AI brings scale and data to what it sees. One makes meaning. The other multiplies it. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/4c49b828-8464-44af-a717-a136d433861e.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/b8473290-8421-4847-abf9-8df35e449c37.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/d55c26c1-bb4a-43dd-a8d8-25586dd5dc39.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/2555412b-e8a3-4e6f-9c90-54d485a0e4fb.png) ### Why Does Vince Gilligan Hate AI? URL: https://www.thedaringcreatives.com/vince-gilligan-hates-ai/ Last updated: 2026-07-15T22:56:47.000Z As of this writing, it’s been several days since Vince Gilligan’s new show *Pluribus* premiered — and it's been in the headlines not for the story, or the characters, or the visuals — but because it proudly declares *“Made by Humans”* in it's credits and because Vince really, *really* hates AI. > > "I Hate Al. Al Is The World's Most Expensive And Energy-Intensive Plagiarism Machine. I Think There's A Very High Possibility That This Is All A Bunch Of Horseshit. It's Basically A Bunch Of Centibillionaires Whose Greatest Life Goal Is To Become The World's First Trillionaires. I Think They're Selling A Bag Of Vapor." > > \-- Vince Gilligan In a world where people love to [cancel or protest](https://www.thedaringcreatives.com/fake-ass-robots-controlled-by-slave-labor-in-india/) anything they dislike, I’m actually kind of celebrating this. Because every time a big creative name trashes AI, they just keep it in the spotlight. And, selfishly it gives me something to write about! So, thanks Vince. You’ve probably sent a few hundred thousand people Googling “why does Vince Gilligan hate AI?” — and in the process, you’ve made more people curious about it. And, hopefully some of those people this post. Still, I can’t help but feel for the people who worked on his show. The writers, editors, cinematographers — all of them poured months or years of energy into this thing, and instead of talking about their craft, the conversation is stuck on one man’s personal beef. Same with Guillermo del Toro. Two incredibly gifted storytellers who seem to be doing everything they can to distract from their own human made work. That’s what set me off thinking about the bigger pattern: how every time a new tool shows up, the people at the top of creative industries rush to bad-mouth it? They [defend the past](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/) instead of shaping what’s next. Ultimately why Vince hates AI really is irrelevant. The biggest question I care about is which [new creatives](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/) will step forward to carry the pro-AI mantle? Who’s the visionary that will help the creative world make this jump instead of blocking it? History gives us a few examples. Henry Ford didn’t invent the car, he made it something the average person could afford. Steve Jobs didn’t invent computers, he made them more accessible to every day people. They both looked at an awkward, early technology and saw not what it was, but what it could become. That’s the type of leadership the creative world needs now. Not more gatekeeping, not more fear. Someone who can hold both truths — that art is human, and that technology is how humans evolve. Okay, so that won't be Vince Gilligan. He’s earned the right to make whatever kind of art he wants. But imagine if someone with his level of cultural trust approached AI with curiosity instead of contempt? If he leaned in instead of digging in. He might become exactly the kind of transitionary figure this moment needs. Because every generation has its version of this argument. Painters vs. photography. Musicians vs. synthesizers. Writers vs. blogging. We don’t need another “made by humans” banner. We need someone to show what’s possible when humans and machines collaborate. Someone who can [make this shift make sense](https://www.thedaringcreatives.com/disney-just-pointed-sora-at-its-vaul/). Until then, I’ll keep thanking the people who hate it — because, whether they realize it or not, they’re keeping AI in the conversation. And maybe, just maybe, that’s how the next visionary will find their cue. ### Toxic @Threads: Fake-Ass Robots Controlled by Slave Labor in India URL: https://www.thedaringcreatives.com/fake-robots-human-labor/ Last updated: 2026-08-01T19:44:09.000Z Some people see the world through rose-colored glasses. I admit—I’m one of them. Mine just happen to have **yellow frames.** When it comes to AI, I lean toward *what could go right.* I look at new tools for what they are and what they might become. The question I ask myself: *what can this tool help me make real?* Not everyone sees it that way. Scroll long enough and you’ll find someone wearing what I call [**gray glasses of doom**](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/)—the kind that turn every innovation into evidence of decline. Like this: > **@evanjwatkins** > “Insane to me that human beings would sell out their fellow man to create a shitty product so they can increase profits and send them up the chain to the tech bros. Hollywood needs to divorce from the tech companies. They can go kiss trumps ass and make kids dumb with ChatGPT and build fake ass robots controlled by slave labor in India while the film and tv business can get back to telling stories about real life powered by an industry of real humans who get paid for a living.” At first glance, it reads like a tantrum — a public meltdown wrapped in moral outrage. But it’s more than that. It’s tragic, because it doesn’t have to be this way. I'm fairly certain no one is forcing this guy to use AI. Is there a secret committee dragging artists into prompt training camps that I don't know about? If he wants to keep painting, filming, sculpting, or whatever, there's nothing stopping him. But then come the accusations — that people “sold out their fellow man,” that “tech bros” are “ruining the creative industry.” But let’s be honest: no one needs AI to do that. The system was already [built to prioritize profit](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/) over people long before ChatGPT showed up. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/fake-ass-robots-slave-labor.png) A hyperrealistic, cinematic 1920x1080 image of a gritty industrial factory where South Asian workers assemble humanoid robots made of brushed aluminum and light metals. The robots appear semi-human with smooth, nondescript faces and exposed mechanical joints. The scene is captured with shallow depth of field, natural diffused light, and a smoky, capitalistic-surreal atmosphere. We live in capitalism. The film industry, the art world, the music business — all of it runs on markets, not morals. It’s just the reality we operate in. Blaming AI for capitalism is like blaming Photoshop for advertising. But more than all of this, why can't people be a little more positive? Instead of catastrophizing, what if we reframed: Instead of *“AI is killing creativity,”* try **“AI is multiplying it — now anyone with ideas can create, not just the technically skilled.”** Instead of *“AI is replacing artists,”* try **“AI is** [**creating new artists**](https://www.thedaringcreatives.com/ai-and-the-return-of-participation/)**.”** Instead of *“AI makes everything the same,”* try **“AI makes it impossible to hide behind style. All of a sudden imagination means a lot more.”** Instead of *“This is the end of originality,”* try **“This is the first time originality is truly accessible.”** Whether you love AI or hate it, the world isn’t going back to pre-2022\. The only choice we have is how we adapt. You can keep seeing the worst in it (paranoia, conspiracy, corruption) or you can look closer and see that what’s really being challenged is our relationship with change itself. The camera was supposed to destroy painting. The synthesizer was going to kill music. The internet was going to end books. You've heard all this before. Point is, none of those things "ended." So yeah, I’ll keep my rose-colored glasses. Not because I think everything’s perfect, but because I can see the [possibilities](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/). 💬 *The real question isn’t whether AI will ruin creativity. It’s whether we’ll finally take responsibility for how we choose to see the world we’ve built. Follow @thedaringcreatives on Threads.* ### Portfolio or Personal Brand? URL: https://www.thedaringcreatives.com/portfolio-or-personal-brand/ Last updated: 2026-07-15T22:56:48.000Z A student from a [local university](https://www.vancouver.wsu.edu/?ref=thedaringcreatives.com) reached out recently to ask how I use AI in my creative work. She wanted to know about my process — the tools I use, how I integrate them, and what advice I’d give to someone just starting out after graduation. They were all thoughtful questions, but the one that I gravitated to was the one about starting out advice. Here's how I answered this particular question: > If I were graduating today, step one would be building a personal brand—one page and one or two channels that [showcase your work](https://www.thedaringcreatives.com/the-daring-creatives/), process, and, most importantly, your point of view. I’d lean hard into what makes me different instead of playing it safe by trying to appeal to everyone. The right jobs and collaborators show up when they know what you stand for. That might sound like marketing talk, and thats intentional because everyone needs to market themselves. And yeah, self promotion doesn't come naturally to most of us. But, you don't need to overthink it and I'm going to share a few examples to check out so read on! ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. A personal brand is simply how the world understands who you are and what you care about. It’s the story people tell about you when you’re not in the room. For creatives, it has replaced the traditional résumé or portfolio as the most important way to be seen. A portfolio shows what you can do, by looking back at what you already did. A personal brand shows who you are, why you do it, and what it feels like to work with you. In the past, your work spoke for itself, but that’s no longer true. We live in a world flooded with content and competition — where talent is assumed (basically everyone is good), and attention is scarce. What sets you apart now isn’t just the quality of your work, but the clarity of your identity. People want to know the person behind the creativity. They want to understand your perspective, your energy, and your worldview. That’s what they connect to. And that connection is what opens every door. The challenge is that most creatives don’t want to think about “branding.” It sounds artificial or self-promotional. But the reality is, you already have a brand — it just might not be intentional. Every post, project, and interaction contributes to how people perceive you. Building a personal brand simply means taking control and being intentional. It’s not about being loud or performing; it’s about being consistent, clear, and human. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/mel-robbins.png) Hyperrealistic portrait in corporate surrealism style of Mel Robbins, a confident woman with blonde hair and thick black framed glasses, arms spread with a radiant golden halo, warm cinematic lighting, and minimalist background evoking reverence and power. Look at Mel Robbins, my favorite influencer on earth. She’s not a designer or musician, but she’s built one of the most effective personal brands of our time. Her power lies in her openness. She doesn’t hide behind polish or perfection. She invites people into her real life — her struggles, her routines, her growth. That vulnerability has become her greatest strength. When she speaks, it feels personal, as if she’s talking directly to you. It’s the kind of intimacy that builds long-term trust. And trust, more than reach or aesthetics, is what drives a lasting brand. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/fred-again.png) Hyperrealistic portrait in corporate surrealism style of a DJ resembling Fred again.., behind a Pioneer setup in a white t-shirt, expressive face lit by a golden halo, soft painterly lighting blending sacred iconography with concert energy. Now consider [Fred again](https://www.fredagain.com/?ref=thedaringcreatives.com).., a producer who’s turned the act of making music into an ongoing conversation with his audience. His brand is rooted in presence and process. He films moments in transit, creating music on his laptop on a train on the way to his next gig, or experimenting in a studio with friends. You see not only the music being made (and enjoyed), but also the humanity behind it. That’s why people don’t just listen to his songs; they feel like they’re part of his creative life. Fred has proven that [sharing your process](https://www.thedaringcreatives.com/sharing-your-work-is-still-less-risky-than/) isn’t a distraction from your art — it *is* your art. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/11/made-by-james-martin.png) Hyperrealistic corporate surrealism portrait of a James Martin, a smiling man with a long beard and cap, wearing a black Nike sweatshirt, hands clasped, glowing golden halo behind him, soft painterly lighting and textured background in warm earth tones. Then there’s James Martin — the designer behind [*Made by James*](https://themadebyjames.com/?ref=thedaringcreatives.com). I fondly recall meeting James during a podcast I was producing a few years back. He’s one of the best examples of consistency I’ve seen in any creative field. Every post, every sketch, every project reflects the same clarity of tone and purpose. He’s open about mistakes, transparent about process, and unfiltered in personality. There’s no gap between the person and the work. That’s what makes it believable. In one interview, James said, “The more I’ve been myself, the more good things have happened to me.” What ties all three of them together is that none of them built a brand by accident. They did it by showing up — consistently, authentically, and in their own way. Mel’s superpower is empathy. Fred’s is transparency. James’s is honesty and repetition. But underneath all of it is the same discipline: they each decided what they stood for and built around that idea relentlessly. The irony is that building a personal brand often has less to do with strategy and more to do with self-awareness. You can’t tell a clear story about yourself until you know what matters to you. You will no doubt learn some important things about yourself if you choose this path (personal branding). For someone just starting out, the most practical advice I can give is to begin documenting your process. Don’t wait until you have a perfect body of work or a grand strategy. Start with what’s in front of you. Share how you’re learning, what excites you, what challenges you. The act of documenting builds confidence, but it also builds clarity. Over time, your story begins to take shape, and with it, your audience. A personal brand isn’t about manufacturing an image. It’s about maintaining a [consistent signal](https://www.thedaringcreatives.com/ai-image-consistency-guide/) in a noisy world. When people know what to expect from you — in tone, in perspective, in values — they begin to trust you. And once they trust you, opportunities find you. If I were graduating today, I wouldn’t spend weeks perfecting a résumé (probably won't have much of one anyway). I’d start building my digital presence around what I genuinely care about. I’d treat my personal brand like a living project — one that evolves as I do. Because that’s really what it is: a long-term creative work about yourself. [The tools will change](https://www.thedaringcreatives.com/when-a-tool-you-love-stops-feeling-mutual/). The platforms will change. But your story, your perspective, and the way you make people feel — that’s the constant. That’s your real portfolio. ### AI Didn’t Break Art. We Did. URL: https://www.thedaringcreatives.com/ai-didnt-break-art/ Last updated: 2026-07-15T22:56:48.000Z Let’s be honest — most of the [outrage](https://www.thedaringcreatives.com/fake-ass-robots-controlled-by-slave-labor-in-india/) about AI isn’t really about technology. It’s about **who gets the money.** People say they’re mad that AI “steals” from artists or “devalues creativity,” but underneath that is a much older tension — the way art, music, design, and storytelling have been [turned into commodities](https://www.thedaringcreatives.com/less-artwork-more-assets/). The fight isn’t against machines. The fight is against a system that rewards speed, scale, and profit over craft. And that system is called capitalism. If you zoom out, you’ll see this isn’t a new story. Every major leap in technology — from the printing press to film to the internet — has reshaped who gets paid, who gets left behind, and who gets to be called an “artist.” Capitalism thrives on these disruptions. It feeds on efficiency. Every innovation that lets us do more with less eventually gets folded into the machine. AI is just the latest chapter in a book we’ve been writing for over a century. To understand where we are now, you have to look back at where the commodification began — when creativity first became something that could be replicated, packaged, and sold. ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. ## **The Age of Reproduction** It started back when art could be copied. Photography, film, and recorded music made it possible to reproduce creativity at scale. [Walter Benjamin wrote about it in the 1930s](https://en.wikipedia.org/wiki/The%5FWork%5Fof%5FArt%5Fin%5Fthe%5FAge%5Fof%5FMechanical%5FReproduction?ref=thedaringcreatives.com) — he said that once art could be mechanically reproduced, its “aura” changed. It became product. By the middle of the 20th century, Hollywood turned storytelling into franchises. Motown and Tin Pan Alley made music like an assembly line. Advertising learned how to turn feelings into sales. Then came the digital era — MTV, blockbuster movies, computers, and eventually the internet. That’s when creativity officially merged with marketing. Everything could be tracked, measured, and optimized. Now algorithms decide what gets seen. Streams, clicks, and watch time define value. We don’t ask if something moves us — we ask if it [performs](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/). So when AI shows up and says, “I can make that faster and cheaper,” it’s not tearing down tradition. It’s finishing what we (humans) started. ## **Creativity Became Infrastructure** Look at how we already treat creative work. Movies aren’t just about great stories — they’re about building franchises and selling merch. Music isn’t just about feeling — it’s about licensing deals, playlists, and content. Design and storytelling aren’t just about expression — they’re about conversions and clicks. That’s the system. Creativity became [infrastructure for business](https://www.thedaringcreatives.com/can-spotify-really-lead-the-next-era-of-ai-music/). And a lot of creative's profited from that, I know I did! And that’s what makes this uncomfortable. I’ve spent years trying to help people show their process — to remind audiences that there’s a person behind the work. But most of the time, people still judge by the result. Process only matters when it adds to the story or makes the product feel more valuable. AI doesn’t devalue creativity — it exposes what we actually value. We didn’t build a culture that rewards craft. We built one that rewards output. ## **Where We Go From Here** So don’t blame AI for cheapening art. Blame the appetite for cheap everything. If you really want to make change, it’s not about banning new tools or defending the old ones. It’s about rethinking the system we keep feeding — a system that measures value in profit instead of meaning. The challenge now is to rebuild how we define value. To make meaning matter again. To use technology to amplify the human part of the work, not erase it. ### Toxic @Threads: "They're all untalented hacks!" URL: https://www.thedaringcreatives.com/toxic-threads-untalented-hacks/ Last updated: 2026-07-15T22:56:49.000Z There’s something eerily familiar about the mob of people attacking AI art online these days, dismissing it as soulless, and ridiculing anyone who dares to experiments with it. The tone, the certainty, even the moral outrage — it all feels like déjà vu. It’s the same kind of [moral policing](https://www.thedaringcreatives.com/fake-ass-robots-controlled-by-slave-labor-in-india/) that fueled the “woke” movement — a movement that started with good intentions but eventually burned itself out through self-righteous overreach. The tactics are identical: shame, ostracize, and claim the moral high ground while refusing to engage with nuance. These conversations are happening right now on **Threads**, and it doesn't take long to start seeing the pattern repeat itself in real time. ## **Different Face, Same Behavior** The comments say it all. > “I think the more people will be using AI, the more analog real musicians will go.” — *@flaviyake* > > “In all honesty, real human-made music (and any art) is one of the realest goddamn things left in this increasingly fake and artificial world of fake likes, fake profiles, fake lives, fake AI music/art BS. Real art is the closest thing to magic we have.” — *@fanufatgyver* > > “AI artists are fighting so hard to be seen as legit! Not the untalented hacks they really are.” — *@allmyvoicesmusic* That last one hit a nerve. I went to college for **music composition**, with an emphasis in **digital music**. Back then, we were running *Pro Tools 1.0* and learning how to connect instruments to computers through MIDI — which, at the time, was just as controversial as AI is now. There was *a lot* of pushback. The samples sounded cheesy or outright bad, and most musicians dismissed it as a gimmick. But the technology kept evolving and what started as “[not real music](https://www.thedaringcreatives.com/sound-isnt-song/)” eventually became *the standard*. I also spent **20 years performing** as a classical and jazz violinist, so I’m not new to this debate. I’ve lived the analog side deeply. The irony is that the person above calling AI artists “[untalented hacks](https://www.thedaringcreatives.com/the-anti-ai-crowd-keeps-imagining-the-wrong-player/)” makes beats that he gives away for free. The same type of culture of samples and sharing that would actually fit in well with the current state of AI music, but he doesn't see that. That's because it's never been about “real music” versus “fake music.” It’s always been about fear and lack of control. ## **It’s Not About Art. It’s About Control.** When people say “AI art isn’t real,” what they really mean is “I don’t know where I fit anymore.” They built their identities on being [gatekeepers of taste](https://www.thedaringcreatives.com/ai-broke-rick-beato/), skill, and access. Now a new generation is experimenting, remixing, and publishing instantly. The hierarchy has cracked. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/10/negative-ai-stories-in-msm.png) Cinematic, hyper-real photo in the **Toxic Threads* style — a middle-aged man watches TV in a dim, toxic-green-lit room dripping with glowing sludge, holding a spoonful of neon goo as he glares at the screen. On the TV, a serious news anchor under a red “BREAKING NEWS” chyron reads, **“EXPERTS WARN: ARTISTS BECOMING OBSOLETE BY TUESDAY.”* Photoreal lighting, shallow depth of field, Canon R5 24mm f/2.8 look. Thing is, I don’t think most of these people *realize* they’re being gatekeepers. They think they’re defending art — but they’re repeating talking points shaped by incomplete, coordinated misinformation from mainstream media. A lot of what they believe about AI isn’t rooted in experience; it’s rooted in fear that’s been fed to them on a spoon. One common myth is that “AI music just copies existing songs and therefore isn’t original.” The fact is, most generative music systems learn broad patterns — rhythm, harmony, structure — from large datasets and then create *new combinations* of those patterns. They don’t store or replay full songs. Listening and learning isn’t the same as copying — no more than a musician who hears something and becomes inspired to build off of it. Yet you’ll still hear people claim "the machines are stealing art!!" That oversimplification fuels fear, not insight. So they moralize it. They frame progress as corruption. But underneath the outrage is fear of losing relevance. ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. ## **This Cycle Always Ends the Same Way** The “woke” era didn’t die because people stopped caring about fairness. It died because it became performative, exhausting, and impossible to keep up with. It demanded conformity in thought and that's something that should never happen in art. People will get tired of being told they’re immoral or lazy for using a tool that helps them create. The cultural pendulum always swings back toward curiosity. And when it does, being proudly “anti-AI” will look as outdated as the critics who said digital cameras weren’t real photography, or that electronic music wasn’t “real music.” ## **The Future Belongs to the Curious** Real artists don’t fear tools. Real artists also don't fear boundaries (or pushing them). The line between analog and digital, human and AI, is about to blur completely. The artists who thrive will be the ones who *build*, not the ones who *guard*. This isn’t the end of art. It’s just the end of gatekeeping. 💬 These conversations are unfolding daily on **Threads**, and they’re worth watching. Follow the discussion at [**@thedaringcreatives**](https://www.threads.com/@thedaringcreatives?ref=thedaringcreatives.com). ### Meet ChatGPT Atlas URL: https://www.thedaringcreatives.com/meet-chatgpt-atlas/ Last updated: 2026-07-15T22:56:49.000Z Atlas, OpenAI’s new web browser, has only been out for a day, so I’ll start by saying this isn’t a review — just early impressions. It’s still at the beginning of its life cycle, but even at this stage, you can tell it represents something important. I want to give OpenAI credit for this move. They’ve built so many tools for themselves internally — and it’s always exciting when they release one into the world to see how people actually use it. Atlas is one of those. And so far, I’m impressed. It’s **fast**, first of all. And clean. Although based off Chrome, it doesn’t feel like other browsers that have been stuffed full of buttons, extensions, and clutter over the years. There’s no URL bar screaming at you. No visual noise. Just a big, open, minimalist canvas. It tickles my sensibilities for simplicity. Right now, it’s Mac-only, which is fine by me. But the real star of the show — and what made me realize how different this thing really is — is **Agent Mode**. ## The Epiphany Moment [Agent Mode](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/) feels like a glimpse of the next era of how we’ll use the web. One of the first things I did was have it open my website, [*The Daring Creatives*](https://www.thedaringcreatives.com/the-daring-creatives/), and start working from there. I asked it to study my articles, understand my mission — building a community for artists, designers, musicians, and storytellers who use AI — and then help me find more people like that on Instagram. And it did. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/10/Screenshot-2025-10-27-at-11.01.56---AM.png) Doing research on accounts I should be following and/or reaching out to to help build my website audience using ChatGPT Atlas and Google Sheets. It searched the web, found lists of relevant creators, and built a spreadsheet in Google Sheets with names, handles, descriptions, and categories. The kind of list that would’ve taken me hours to compile manually. It was pulling from human-curated lists — blog posts, roundups, articles — not just random scraping. And that made it far more relevant than any attempt I’ve made using ChatGPT alone. That moment was a little epiphany: this isn’t just “browsing” anymore. It’s [orchestrating](https://www.thedaringcreatives.com/about/). ## Seeing the Agent in Action Then I took it further. Since Atlas has access to your signed-in accounts, I logged into Instagram and asked it to follow those creators. Watching it work was surreal. You could literally *see* it learning the interface — finding the follow buttons, scrolling, checking if I was already following someone, then moving on. It worked — but it also showed its limitations. The agent could only follow about five people at a time before the session ran out of compute. You could restart easily by saying “start a new session,” but still — you can imagine how much smoother it’ll feel once that’s extended. Even with those small hiccups, it was impressive. I used it to help a client as well, having it study his artwork and generate a marketing plan while building a list of potential collectors. It was simultaneously writing in Google Docs and researching in Sheets — all from the same browser tab. That’s when it hit me: this thing isn’t just a browser. It’s an interface for doing *work*. ## What Comes Next Atlas feels like the first serious step toward browsers becoming fully [intelligent workspaces](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/). In theory, it could edit videos for me through Descript’s site, make songs on Udio, or post and schedule content across platforms — all through the web itself. That’s a massive shift. It’s as fundamental as the leap from text-based ChatGPT to multimodal chat, or from standalone apps to the command line. Each mode changes how you think — and Atlas changes how you *work*. Right now, it’s early. There are compute limits and rough edges. But it’s fast, minimal, and deeply capable. If OpenAI continues refining it, this could be the beginning of a new default: not “searching the web,” but collaborating with it. And I’ll say this much — I’m already considering making it my main browser. ### Sound Isn't Song URL: https://www.thedaringcreatives.com/sound-isnt-song/ Last updated: 2026-07-15T22:56:49.000Z I’ve probably made a thousand songs using Udio. That’s not exaggeration. Most of them were created for background use—music for short videos, mood pieces, or transitions. Some made it into finished edits, most didn’t. They weren’t bad; they just didn’t stick. That’s what AI music is right now: [serviceable](https://www.thedaringcreatives.com/can-spotify-really-lead-the-next-era-of-ai-music/). Good enough to sit quietly behind a voiceover, to fill a mood, to make a scene feel complete. But it’s not good enough to make you feel something after it ends. Lets just say I'm not listening to any of these in my car! That distinction has been on my mind a lot lately. There’s music that *works*, and there’s music that *stays*. AI can give you the first one on demand. The second still belongs to us (humans). For anyone creating [video content](https://www.thedaringcreatives.com/how-ai-turned-me-into-a-creative-superhero-and-why-you-should-care-v2/), tools like Udio and Suno are nothing short of remarkable. Emotional Echoes 0:00 /32.810667 1× Wellness in the City 0:00 /131.114667 1× They’re fast, accessible, and versatile. You type something like “cinematic ambient score with emotional classical piano and strings,” and half a minute later, you’ve got something that sounds pretty decent to good. I’ll often generate five or six tracks for a single project, test them, and pick the one that best fits the scene or supports the vibe I'm trying to create. That’s really AI music’s superpower: it disappears. It’s invisible, functional, and endlessly replaceable. But that utility also exposes its limitation. The best AI tracks feel like emotional paint—smooth, consistent, and useful, but covering everything without truly sinking in. A few weeks ago, I listened to Taylor Swift’s *The Life of a Show Girl.* I’m not a lifelong Swiftie, but I’ve been humming *Fate of Ophelia*, *Elizabeth Taylor*, and *Opalite* for days. That’s the difference. Those songs *stay.* They build little corners in your mind. They loop back in at random moments. You find yourself singing them under your breath while making coffee. AI can’t do that—not yet. You can feed it the cleverest prompts imaginable, and it’ll generate something that sounds exactly *like* a song. It’ll have melody, rhythm, structure, all the ingredients. But it won’t have *stakes.* It has nothing to lose and nothing to confess. It can simulate tone but not vulnerability, structure but not struggle. When you hear a song that really lands, it’s not just the melody or the production—it’s the memory. You feel the fingerprints. You sense the restraint, the odd decisions, the emotional arithmetic that makes a chord change feel inevitable. AI can’t recreate that because it has [no history](https://www.thedaringcreatives.com/ai-broke-rick-beato/). It’s not trying to express something—it’s trying to *approximate* expression. And here’s where the contradiction gets interesting. ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. AI music isn’t perfect, and we all know that. Yet when we talk about its limitations, we frame them as flaws to be fixed. “It’s not quite there yet.” “The mix is off.” “The vocals sound a little fake.” With traditional music, those same [imperfections](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/) are what we fall in love with. We celebrate them. The crack in a voice. The missed snare hit that somehow feels right. The way a note wavers just enough to sound human. Why the double standard? I catch myself doing it constantly—endlessly regenerating songs in Udio, chasing the “perfect” version of something that’s not supposed to be perfect in the first place. It’s ironic: the very thing that makes human music resonate—its rough edges, its imperfection—is what I keep trying to eliminate when I use AI. It makes me wonder if I’m setting myself up to fail. Maybe the goal shouldn’t be to get AI music to sound flawless, but to get it to sound *alive.* The mistake might not be in the tool but in how I'm using it. Whispers of Enchantment 0:00 /32.810667 1× Inspired Flow 0:00 /131.114667 1× That’s what separates Taylor Swift’s songs—or any lasting piece of music—from what AI can do. They live in their imperfections. They breathe there. They make you feel like you’re witnessing something unfiltered. Perfection, on the other hand, is sterile. It doesn’t invite you in—it just performs for you. So maybe AI music’s evolution isn’t about getting more precise. Maybe it’s about learning to *let go.* To stop trying to erase the digital fingerprints and start letting a little weirdness in. Maybe that’s where emotion hides—right in the glitches we’re still trying to sand out. For creators like me, AI remains an incredible collaborator. It’s fast, flexible, and affordable. It’s perfect for sound design, for mood, for texture. It’s a new kind of creative brush. But it’s not the songwriter. It’s not the confession. It’s not the spark that makes silence feel unbearable. AI can already make beautiful sound. But sound isn’t song. It can simulate emotion, but it can’t yet provoke it. And maybe it shouldn’t try. Because what we love about human music—the messy, aching, imperfect parts—isn’t what we want fixed. It’s what we want *felt.* Until AI learns to fail beautifully, it’ll keep sounding right but feeling wrong. ### Should Spotify Lead the Next Era of AI Music? URL: https://www.thedaringcreatives.com/spotify-ai-music-era/ Last updated: 2026-07-15T22:56:49.000Z Spotify wants to define what “[responsible AI in music](https://www.theguardian.com/technology/2025/oct/16/spotify-ai-products-partnering-multinational-music-companies?utm%5Fsource=chatgpt.com)” looks like. That’s rich coming from the company that spent the last decade [turning musicians into data points](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/). The same company that boasts about [removing 75 million AI-generated “spam tracks”](https://www.hollywoodreporter.com/business/business-news/spotify-new-ai-policies-spam-filter-enforcement-1236379926/?ref=thedaringcreatives.com) is now partnering with major labels to pioneer “artist-first” AI tools. They’re scrubbing the mess they helped create, then selling the cleanup as innovation. The announcement sounds noble: protecting artists, ensuring credit, building ethical standards for AI. But this is the same platform that’s been accused of underpaying the very artists it claims to champion. For years, musicians have fought over fractions of pennies per stream while Spotify executives gave TED Talks about democratizing music. Now they’re positioning themselves as the moral authority on how technology should coexist with creativity. Forgive me if that doesn’t inspire confidence. The problem isn’t that Spotify is using AI. It’s that they want to be the referee of it. When the company that disrupted the music industry’s economics now wants to write the rulebook for its next transformation, you have to ask: who benefits? Because if history is any guide, it won’t be the people actually making the music. Spotify’s entire model has always been about control. Control the distribution. Control the data. Control the playlist that decides what millions of people hear next. AI is just the latest thing to control. “Responsible AI” becomes a way to centralize creative legitimacy—to decide what counts as [authentic art](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/) and what doesn’t. That’s a bigger threat to creativity than any new model could ever be. ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. AI doesn’t break creativity, but it does reveals how fragile our definitions of it have become. For most of human history, [learning from what came before](https://www.thedaringcreatives.com/ai-broke-rick-beato/) wasn’t just accepted; it was the point. The blues became rock. Rock became punk. Sampling built hip-hop. Every new sound came from reinterpreting someone else’s. Copying used to mean you were inspired, and you cared! Now the line between inspiration and theft feels blurry, but maybe that’s because the skill barrier disappeared. When you can mimic a sound or voice instantly, it can be easy to start to confuse effort with authenticity. But originality has never come from the tools—it’s come from taste, context, and meaning. If a machine learns from a million songs to generate one that moves you, is that theft—or evolution? That’s the conversation we should be having. Not how to lock AI down, but how to use it well. The people best positioned to lead that aren’t streaming executives or label lawyers. They’re the artists, producers, and independent creatives experimenting in real time—people who still see music as a language, not just output. AI won’t ruin art. But platforms that treat creativity as inventory might. The challenge isn’t keeping machines out of music—it’s [keeping the meaning in](https://www.thedaringcreatives.com/sound-isnt-song/). When every song can be generated on demand, the rare thing becomes the story behind it: who made it, why, and what it represents. That’s where artists will find their leverage again—not through scarcity, but through sincerity. Spotify wants to lead the next chapter of music’s relationship with AI. Maybe they will. But leadership doesn’t come from writing press releases about responsibility. It comes from rebuilding trust. Until then, the question remains: should the company that broke the system really be the one to reinvent it ### What Rick Beato Gets Wrong About AI URL: https://www.thedaringcreatives.com/rick-beato-ai-music-rant/ Last updated: 2026-07-15T22:56:50.000Z Rick Beato *seems* to be a gifted teacher, or at least, his "follower" count would indicate such. His YouTube channel has helped millions of people understand chord progressions, harmony, and production. But in a recent video, he revealed something less flattering—not about AI, but about how humans use their authority when they feel it slipping. The video starts with a simple setup: Beato tests AI on math, then moves into music. He asks how to EQ drum overheads, how to clean up bass frequencies, and gets back perfectly reasonable, textbook answers. Then he delivers his punchline question: > “What records have you worked on?” "Gotcha!" The AI responds that it doesn’t have personal experience—it’s more of a knowledge engine that’s learned from countless sources. Beato seizes on that, implying that without lived experience, the AI’s knowledge is invalid. That’s not analysis. It’s stagecraft. ## **The False Idol of Experience** If Beato’s logic were applied consistently, nearly every expert would be disqualified. A math professor who’s never built a bridge can’t teach calculus. A film critic who’s never directed can’t analyze movies. A musicologist can’t discuss Coltrane without having played sax in 1959. Nonsense. Knowledge isn’t limited to the people who’ve “done the thing.” It comes from studying, synthesizing, and connecting what others have done before. AI does that—at incomprehensible scale. It doesn’t “feel” the process; it *understands* it. That’s not a lack of authenticity—it’s a different form of intelligence. Most working producers haven’t mixed anything you’ve heard of. That doesn’t make them unqualified. It just shows how thin the connection is between fame and skill. If experience alone were the measure, most of the creative world would fail its own credibility test. I checked Rick Beato’s own [production credits](https://en.wikipedia.org/wiki/Rick%5FBeato?ref=thedaringcreatives.com) out of curiosity and here is what I learned. **I haven’t heard of a single artist he’s produced.** But one thing i did learn was that he has run afoul of numerous bands I *have actually heard* of but for a different reason - copyright violations. Ouch. By his logic—what am I supposed to take from that about his qualifications? Should I measure them by follower count instead? Or by YouTube copyright strikes? Of course not. His value comes from how clearly he can explain his craft, not the size of his résumé. So why the double standard when it comes to AI? I think we know why.. ## **The “Missing Data” Distraction** Beato argues that AI can’t really understand production because there’s not enough high-quality training material from top engineers like Max Martin or Serban Ghenea. He’s partly right—those people rarely explain their process publicly. But that’s not a flaw in AI. It's the human character flaw of [*gatekeeping*](https://www.thedaringcreatives.com/toxic-threads-theyre-all-untalented-hacks/). Most people who learn mixing or songwriting (or anything) also rely on secondhand material—tutorials, interviews, reverse-engineered tracks. No one gets the secret sauce from the source. We all learn from partial information. AI just scales that process. It synthesizes thousands of perspectives, patterns, and examples into usable insights. It’s not pretending to have mixed a record; it’s showing you what decades of collective knowledge look like when compressed into one system. The fact that its knowledge comes from “copies of copies” doesn’t make it fake—it makes it *familiar.* That’s how every creative tradition has worked since the first apprentice copied their master’s brushstroke. ## **The Calculator Fallacy** At one point, Beato notes that AI [stumbled when calculating](https://www.thedaringcreatives.com/how-big-a-problem-is-ai-hallucination-anyway/) 52 factorial, calling it proof of incompetence. But that’s a category error. A calculator computes; an AI interprets. Confusing one for the other is like criticizing a camera for not writing poetry. AI isn’t meant to be a replacement for a calculator. It’s meant to handle nuance, context, and synthesis—the things calculators don’t touch. By demanding mathematical precision from a linguistic model, Beato set up a test that proves nothing except that he doesn’t understand what he’s testing. ## **The Performance of Authority** And that’s where the real story lies. Beato’s audience isn’t tuning in for a balanced discussion about machine learning. They’re watching for reassurance that human creativity still matters. Just look at his comment section. He delivers his message through confidence and familiarity—two traits that feel like truth even when they aren’t. This is what social platforms do: they reward performance over precision. When someone with a million subscribers says, “[AI doesn’t really understand music](https://www.thedaringcreatives.com/sound-isnt-song/),” it sounds true by sheer force of presentation. But knowing how to mic a drum kit doesn’t automatically make you an expert on how machines process information. The audience doesn’t notice the distinction, because authority has become a kind of theater. The louder the conviction, the more “truthful” it feels. Beato’s stance isn’t about epistemology—it’s about [preserving identity](https://www.thedaringcreatives.com/conversations-with-code/this-is-not-the-theft-youre-looking-for/). He’s defending a worldview in which expertise can’t exist without human struggle. It’s emotionally satisfying, but logically hollow. ## **What Counts as Experience Now** Beato describes how mixers make “thousands of decisions” based on years of experience. That’s true—and it’s also what AI does. It processes countless data points, recognizes relationships, and learns cause and effect. It doesn’t have intuition, but it does have correlation—a form of pattern memory that mirrors human instinct. AI doesn’t replace the creative ear; it extends it. It can help you hear what experience alone can’t. It’s not claiming to be [Andy Wallace](https://en.wikipedia.org/wiki/Andy%5FWallace%5F%28producer%29?ref=thedaringcreatives.com)—it’s learning *from* him, from everyone like him, and from every sonic fingerprint humans have ever left behind. That doesn’t erase experience; it democratizes it. ## **What This Really Reveals** Beato’s video doesn’t reveal the limits of AI—it reveals our discomfort with what we don't understand. We like to believe that understanding must come from personal sacrifice, not pattern recognition. But that belief is sentimental, not scientific. We’re moving into a world where expertise isn’t defined by having “been there,” but by how well you can connect what *others* have seen, done, and shared. That’s the kind of experience AI is already fluent in. ## **Closing Thoughts** Rick Beato has taught millions how to listen. That’s his genius. But in this case, he’s not listening—he’s defending. How come? AI doesn’t diminish creativity. It changes how knowledge circulates. It reveals that expertise isn’t a sacred lineage guarded by those who’ve “done it,” but a shared pool of insight that anyone—or anything—can draw from. The irony is, Beato’s argument defeats itself. By his own measure, most professionals wouldn’t qualify as credible. Ninety-nine percent of producers could list their discography and still name records you’ve never heard of. He’s no different. Experience matters. But understanding matters more. And if AI can deliver that—without the ego trip—it might just be the better teacher. Here's a fun prompt to try: Instead of asking whether AI has “lived” something, ask whether it helps you see something new. That’s what real experience does anyway. ### Directing Sora URL: https://www.thedaringcreatives.com/directing-the-machine/ Last updated: 2026-07-21T19:30:28.000Z There’s a difference between telling AI what you want and *showing it how to see.* Anyone can type “make it cinematic,” but when you start giving direction—when you describe where the light falls, how the camera moves, and what emotion lingers under the surface—the model begins to act less like a generator and more like a crew. That’s the shift from [prompting](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/) to directing. ### **Where This Approach Began** The seed for this idea came from studying a filmmaker and AI creator named [**Keigo Matsumaru**](https://sora.chatgpt.com/profile/keigo%5Fmatsumaru?ref=thedaringcreatives.com), whose haunting short [*Amplifying Screams*](https://sora.chatgpt.com/p/s%5F68ed835976f8819183d685fbea47690f?ref=thedaringcreatives.com) on [Sora](https://www.thedaringcreatives.com/first-hours-with-sora-2/) became a quiet benchmark for me in the world of cinematic prompting. His prompts didn’t read like requests. They read like production sheets—camera notes, lighting cues, emotional tempo. They were built the way a cinematographer thinks, with rhythm and intention. When I first read his [structure](https://www.thedaringcreatives.com/context-is-your-creative-edge/), something clicked. It wasn’t just about describing a scene; it was about orchestrating one. Every section—*Subject, Lighting, Camera, Coverage, Sound*—was a layer of control. Matsumaru was directing the model like it was a crew. That mindset is what inspired the experiment that followed. 0:00 /0:09 1× ### **The Scene That Made It Real** A few nights later, I built a short sequence called [*The Mirror That Remembers.*](https://sora.chatgpt.com/p/s%5F68f07553b274819186b41d83cfc98394?ref=thedaringcreatives.com) It was loosely inspired by that moment in *The Matrix* when Neo touches the mirror and it turns to liquid—but I wanted it slower, quieter, and more human. The man in the scene (me in cameo @daring) is fifty years old. He doesn’t speak. He simply stands in a dusty attic, lit by a single candle. His reflection lags behind him by half a second, trembling like it’s alive. When he finally reaches out, the mirror softens and begins to pull toward his fingertips. Here’s the literal prompt that created it, written using Matsumaru’s structure as a foundation: `keigo_style / @daring # The Mirror That Remembers ## Subject / Scene Settings - Audience: {locale="EN"}; Narrative tone: meditative dread, slow transcendence - Subject type: male, age 50; lined face, cautious reach; silent recognition - Environment: attic room; cracked plaster; candle beside antique mirror - Key features: reflection delayed; surface tension shifts like liquid mercury; ripples tighten when touched - Scale: waist-up; mirror fills frame; reflection warps around fingertips - Motion: dolly push; shallow handheld; slow pull as hand sinks into glass ## Lighting / Grade - Lighting: single candle key + moon rim; soft neg fill; low haze for diffusion - Grade: blue-gray mids with amber highlights; slight bloom; grain and halation ## Visual Taste / Camera / Lens - Visual taste: neo-gothic surreal; restrained sci-fi undertone - Background: minimal texture; motionless air - Camera: MS→CU→ECU; focus pulls between hand and reflection; mirror POV insert as surface liquefies - Lens: 50mm feel; shallow DOF; cinematic softness on transitions ## Coverage / Persist - Coverage: master + hand insert + reflection distortion - Persist: mirror liquid physics continuous; reflection fades to silhouette; final frame still ## Audio (BGM & SFX) - BGM: low cello drone + subharmonic tone (steady rise to 86 BPM pulse, fade) - SFX: mirror tension hum, faint suction, heartbeat low-pass swell - Cues: [0.0] low hum; [2.5] surface oscillation; [5.0] contact; [7.5] pull; [9.0] silence` What matters here isn’t the formatting—it’s the mindset. This kind of prompt reads like a miniature film blueprint. It defines physics, pacing, and atmosphere. It gives the model something to *film.* That’s what cinematic prompting is about: thinking like a director, not a decorator. ## Sign up for The Daring Creatives A home for open-minded creatives using AI. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. ### **The Language of the Lens** Film terms can sound intimidating, but they’re really emotional cues. A wide lens exaggerates space and makes people feel small. A 35mm lens feels human and immersive. A 50mm lens feels intimate—close, but still breathable. An 85mm isolates emotion and compresses distance, great for psychological tension. When I wrote “50mm feel,” I wasn’t chasing accuracy. I was setting proximity. I wanted the viewer to stand close enough to feel the candle’s warmth and see the reflection tremble, but not so close that it felt claustrophobic. That’s what directors do—they decide *where the audience stands.* ### **Light as Language** Every emotional cue begins with light. In this scene, there’s a single candle key—warm and flickering—balanced by a thin rim of moonlight leaking through a cracked window. That contrast tells the entire story: life versus memory, warmth versus detachment. When you write prompts, light is your tone of voice. Saying “candle key with moon rim” communicates more about feeling than “moody lighting” ever could. ### **Motion Is Emotion** [Camera movement](https://www.thedaringcreatives.com/the-moment-i-realized-gear-wasnt-the-constraint-anymore/) shapes how we feel time. A locked-off shot feels formal. A slow dolly push feels like realization. A handheld drift adds unease. In *The Mirror That Remembers*, the camera moves gently forward as the reflection wavers, then pulls back as the mirror turns fluid. The motion feels like breath—the rhythm of hesitation and release. Cinematic prompting works because it expresses emotion through *movement,* not adjectives. ### **The Takeaway** You don’t need to know every technical term to write like a director. You just need to think like one. Ask where the viewer stands (that’s lens), where the light comes from (that’s tone), and what moves first—the subject or the camera (that’s emotion). Once you start answering those questions, your prompts gain gravity. The AI stops painting—it starts shooting. Cinematic prompting isn’t about learning every camera spec. It’s about precision with purpose. It’s about giving structure to imagination. When you describe less and decide more, your prompts stop feeling random—they start feeling real. So next time you sit down to write, don’t describe an image. Stage a moment. Give it rhythm, contrast, silence, and weight. Direct it. And if this approach resonates, take a moment to explore the work of **Keigo Matsumaru**—because this entire shift in how we think about AI imagery began with his willingness to write like a filmmaker. ### AI and the Return of Participation URL: https://www.thedaringcreatives.com/ai-return-of-participation/ Last updated: 2026-07-15T22:56:50.000Z A creator on TikTok recently said we’re entering the “post-generative AI” era of social media — that people are [tired of AI-generated content](https://www.thedaringcreatives.com/the-slop-about-slop/) and just want more “human connection.” It’s an easy thing to say. It sounds noble. But it also misses the point. Social media hasn’t been about human connection in a very long time. The platforms stopped being about conversation years ago; now they’re about performance. They’re machines tuned for outrage, aspiration, and spectacle — not exchange. You post, and unless you already have an audience, it goes [into the void](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/). You might get a handful of likes, a few pity comments, and then the algorithm buries it under a mountain of sponsored content. If you were around for the early days of Facebook, Twitter, or Instagram, you know what I’m talking about. It actually felt social then. You’d post something and your friends would see it — not because it was optimized, but because that’s how the system worked. The early web had this energy to it, this sense that you were stepping into something new, undefined, and full of possibility. Those early networks were small enough to feel human. You’d share ideas, organize things, collaborate. Bands booked shows, people launched projects, communities formed overnight. It was messy and exciting — the kind of environment where creativity thrived because no one was chasing numbers yet. And then the companies showed up. To be fair, I was part of that wave. For the last several years, my work has often involved helping businesses show up on social — finding ways to bridge the gap between people and products, between personality and promotion. The pressure to create engagement, drive awareness, and ultimately sell is enormous. When you’re being paid to help a brand “connect,” what that really means is finding creative ways to break into the spaces where person-to-person connection used to live. I don’t say that as a confession, just an acknowledgment. The system rewards interruption, not interaction. And when every post is measured by performance metrics, it subtly trains everyone — brands and individuals alike — to act like advertisers. I don’t think it’s malicious, but I do think it’s unsustainable. The system needs to change. Which brings me back to that creator’s comment — that we’re now “post-generative.” I don’t buy it. We’re not post-generative; we’re post-broadcast. AI isn’t what killed connection. In many ways, it’s *rebuilding* it — this time **by design.** 0:00 /0:09 1× A remix for a popular meme video on Sora. Take the [new Sora app](https://www.thedaringcreatives.com/first-hours-with-sora-2/). It’s technically an AI video platform, but it has this brilliant social layer built around [remixing](https://www.thedaringcreatives.com/disney-just-pointed-sora-at-its-vaul/). You can take someone’s video and build on it. If someone makes something that sparks an idea, you can riff, re-edit, or cameo in it. It’s playful, open, and participatory — intentionally designed for collaboration, not isolation. That feeling — that ability to jump into someone else’s creative current — feels more human than anything I’ve seen on mainstream social media in years. I made a simple video about making mac and cheese, just for fun. Later, I noticed other people trying to remix it, adding their own spin. I hadn’t turned on remix permissions yet, but the fact that they wanted to was kind of thrilling. It reminded me of the early web, when creativity was a shared language. When you didn’t need an audience — just curiosity and a willingness to play. That’s what we’ve lost. Not the “human” part, but the participatory part. When people say they want “more human connection,” what they’re really saying is that they want meaning — and meaning doesn’t come from scrolling or posting. It comes from doing things with other people. Making, remixing, responding, building. AI tools like Sora, for all their novelty, are interesting because they make that possible again. They invite you to make something *with* someone else. To collaborate instead of compete. To re-enter that early-internet sense of discovery, when nobody quite knew what this could become. That’s not post-generative. That’s pre-something new. The old social networks became systems of performance. The new ones — the AI-powered ones — might become systems of participation. Not because the technology is perfect, but because it’s resetting the scale — smaller, more creative, more curious. If that’s where things are heading, count me in. I’ve always liked being early. ### The Slop About Slop URL: https://www.thedaringcreatives.com/the-slop-about-slop/ Last updated: 2026-02-20T05:36:15.000Z I've worked in social media and marketing—two industries that worship at the altar of imitation. One of the most common pieces of advice you’ll hear is to “study the top five people in your niche and replicate what they do.” Look at their hooks. Their tone. Their topics. Their camera angles. Reverse-engineer the formula and plug yourself in. It’s positioned as strategic research. In practice, it’s how originality dies. This copycat logic has spread like mold through every corner of the internet. Scroll long enough, and you start to feel like you’re watching a single mind rehearse its lines in a thousand different bodies. Everyone’s saying the same thing, using the same words, in the same order—then pretending they discovered it themselves. And nowhere is this more obvious than in how people talk about AI. ## The irony of “AI slop” If you’ve spent time online lately, you’ve seen it: people declaring that “AI content is slop,” that it’s flooding the internet with garbage, that it’s replacing creativity with automation. And sure, there’s plenty of low-quality output out there. There’s always been. We had clickbait before ChatGPT; we had BuzzFeed quizzes before Midjourney. But the irony is that the loudest critics are often producing the very same thing they claim to despise. They’re not generating insight—they’re recycling someone else’s outrage. The “AI slop” narrative itself has become slop. It’s like the modern version of the “everyone’s saying” trick. Trump made that rhetorical move famous: make a vague claim, back it up with an invisible consensus, and repeat it until it feels true. Online discourse has mastered the same art. “Everyone knows AI art is bad.” “Everyone can tell AI writing is soulless.” These statements work not because they’re true, but because they’re familiar. And familiarity feels safe. And in the attention economy, safety sells. ## The algorithm loves déjà vu Social media rewards sameness. If something performs well once, the system favors replicas. So people learn the moves—copy the cadence, mirror the framing, duplicate the take. It’s the easiest path to engagement. You don’t even need to think about what you believe anymore; you just have to sound like you belong to the dominant camp. The truth is that most people don’t hate AI because they’ve thought deeply about it. They hate it because the right people told them to. They’re performing dissent, not practicing discernment. It’s groupthink with a creative filter over it. And here’s the kicker: AI isn’t even the [real problem](https://www.thedaringcreatives.com/ai-didnt-break-art-we-did/). It’s a mirror. It reflects the laziness, fear, and mimicry already baked into the system. When you ask AI for something derivative, it delivers. When you prompt it with clarity and originality, it delivers that too. So if the internet is flooded with regurgitated ideas, maybe it’s not the machine’s fault. Maybe we trained it on our behavior. ## Being a nonconformist in a copycat culture I’ve tried the [copycat approach](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/) before—it’s soulless. The posts might get engagement, but they don’t build gravity. You can’t earn respect by parroting strategy; you earn it by having a point of view. That’s why I’ve started using AI *not* to replicate what’s popular, but to challenge it. When someone posts a lazy anti-AI rant, I’ll often suggest they use ChatGPT to form a better argument. It’s funny, but also telling. The same tool they’re mocking could have helped them express their critique more intelligently. It’s not about defending AI. It’s about defending thinking. ## How to study what works without copying it If you want to stand apart online—really stand apart—you still have to study what works. But you need to study *why* it works, not just *what* it looks like. Here’s how I frame that difference when I’m building content myself: 1. [**Study structure**](https://www.thedaringcreatives.com/context-is-your-creative-edge/)**, not surface.** Look at how someone’s ideas are organized, not just how they’re styled. Are they telling a story? Challenging an assumption? Creating tension? Once you understand the structure, you can rebuild it your own way. 2. **Invert the trend.** When a take becomes too common, ask: what’s the unspoken assumption here? What if the opposite is true? That’s where originality lives. 3. [**Add your fingerprints**](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/)**.** If you’re going to touch a trending topic, make it personal. Bring in your lived experience, your humor, your contradictions. Algorithms can’t replicate *that*. 4. **Make the argument no one else is making.** Instead of echoing “AI slop is bad,” ask: why do we keep producing slop without AI? Why are we more forgiving when a human makes it? Ask the questions that pull the thread, not the ones that tidy it up. ## Prompts for nonconformists If you use AI tools, don’t let them flatten your thinking. Use them to expand it. Here are a few prompt examples I often use to escape the copycat loop: - “Everyone in my field is saying X. What’s a nuanced or underexplored counterpoint?” - “Summarize the dominant narrative around \[topic\], then give me three creative ways to reframe it.” - “If I wanted to challenge the most viral post on this topic without being confrontational, how might I structure that argument?” - “Help me make this post sound more like an original essay and less like a LinkedIn trend.” Or one of my favorites: - “What questions would a true nonconformist ask about this topic before forming an opinion?” These kinds of prompts turn AI into a sparring partner instead of a shortcut. The goal isn’t to sound smarter—it’s to think differently. ## Escaping the slop cycle The internet doesn’t need more opinions. It needs more *thinking*. If you’re posting online, whether about AI or anything else, ask yourself: am I adding to the noise or clarifying the signal? Calling out bad takes online might feel good in the moment, but it rarely changes minds. What does change minds is modeling what curiosity looks like in public. That’s how you break the echo chamber—by refusing to feed it. When I see people parroting the same recycled lines about AI, I remind myself that the real fight isn’t against the machines. It’s against mediocrity disguised as certainty. The slop isn’t just the content—it’s the complacency behind it. ### First Hours With Sora 2 URL: https://www.thedaringcreatives.com/first-hours-with-sora-2/ Last updated: 2026-07-15T22:56:50.000Z When a new creative tool drops, especially one carrying the weight of hype like OpenAI’s Sora 2, there’s a temptation to treat it like a magic box. Push a button, get a masterpiece. But after about five hours in, I’m reminded that tools are never that simple. The first thing worth mentioning — and it’s not obvious from the rollout materials — is that you need a Pro ChatGPT account to actually use Sora 2 right now. If you don’t, you’re stuck on a waitlist or hoping someone shares an invite. That’s the price of admission. I dove in using only my phone, which seems to lock the output to vertical and square formats — very Instagram-friendly, but limiting if you’re thinking in widescreen or cinematic. It’s an odd constraint, but one that probably reflects how most people will actually use the tool. Here’s what stood out to me early: The way Sora 2 [handles prompts](https://www.thedaringcreatives.com/directing-the-machine/) feels different, almost like starting from scratch. Prompting still matters, but the instincts you built with the first version aren't always translating. That can feel frustrating, but also kind of thrilling — like switching instruments after you’ve learned to play one well. You know the theory, but your hands have to catch up. 0:00 /0:10 1× A cinematic animated scene inside a dimly lit, modern workspace at night. A man sits at a desk, wearing a black t-shirt, a black baseball cap, and bold yellow sunglasses. A bright yellow Post-It note stuck to his glasses reads in large, clear letter: "DON'T OVERTHINK" My process has been simple: I describe the scene or style in my own words, just talking into ChatGPT the way I’d explain it to a collaborator. Then I let the model rewrite my ramble into a structured Sora prompt. That keeps me focused on vision, not syntax. It’s not about memorizing every trick, it’s about setting the stage clearly enough that the model fills in the rest. One of the mysteries right now is prompt length. In-app, you’ll see these stunning clips labeled with tiny prompts — almost like throwaway lines. When I try that, I rarely get the intended result. Which makes me wonder: are the real prompts hidden? Are we seeing curated shorthand? Or are the examples just cherry-picked lucky hits? Without clarity, the line between best practice and blind luck feels blurry. That’s why I’m already thinking about building my own “[scene bible](https://www.thedaringcreatives.com/context-is-your-creative-edge/).” A living document of the styles, characters, and setups that actually work for me. And i have to thank ChatGPT Pulse for suggesting this, before I even realized I needed it. It did that this morning, on my first day of using Pulse. 0:00 /0:09 1× @daring walking down the street in a Pacific Northwest suburban neighborhood in the fall. Speaking of consistency: Cameo is where Sora 2 shines. It’s surprisingly good at [keeping a character recognizable](https://www.thedaringcreatives.com/ai-image-consistency-guide/) once you anchor them. But step outside of Cameo, and that consistency falls apart fast. Right now, if you want continuity, Cameo is what you have to use. But, that only works for you. It's tough to feed Sora 2 image reference because it has a policy not mimic likeness in these images. Something about that feels unfinished to me. Mention any real person — celebrity, influencer, historical figure — and you’ll likely hit a wall of content notices. It’s not subtle; it’s locked down tight. Even brands to some extent (Goodwill) would trip the notices, so I would need to have ChatGPT describe as a thrift store. A lot of this makes sense for safety, but it also reshapes how you think about storytelling. If your instinct is to drop familiar figures into a scene, you’ll need to rewire that impulse. Sora 2 is nudging you toward fiction, composites, and metaphor. So where does that leave us? For me, Sora 2 feels like standing at the edge of a new art form. It’s not about efficiency — it’s about experimentation. It asks you to imagine in moving images and then wrestle with how close the tool can get you to that imagination. There’s also something worth appreciating in how imperfect it is. Early adoption means bumping into rough edges. The learning curve is real. The “wow” moments are tempered by plenty of misfires. But that’s exactly what makes it creatively interesting. Here are the practical truths I’d tell any other creative curious about diving in: - Don’t expect Sora 1 habits to work here. Reset your instincts. - Dictating your ideas into ChatGPT and letting it structure prompts is a fast way to work. - Start your own scene bible. Document what works for *you.* - Use Cameo for character consistency. Outside of that, expect some chaos. - Don’t plan on using real people — the moderation layer is too strong. - Treat the constraints (aspect ratio, mobile-first design) as creative prompts, not limitations. I’ll admit: I’m impressed. Not in the “look how perfect this is” way, but in the “look how wild and open this feels” way. Sora2 isn’t about replacing vision; it’s about stretching it. Like every new medium, it’ll reward the people who are willing to fumble, fail, and try again. And that’s where the daring part comes in. [The Daring Creatives](https://www.thedaringcreatives.com/about/) aren’t the ones who master a tool instantly. They’re the ones who accept the mess, share the journey, and build fluency over time. Sora 2 isn’t just a video generator. It’s a new language. And like every language, the only way to speak it well is to start talking. ### OpenAI Announces Sora 2 URL: https://www.thedaringcreatives.com/openai-announces-sora-2/ Last updated: 2026-07-15T22:56:51.000Z When OpenAI first launched **Sora**, I was *hyped*. It was the drop that made me pull the trigger on the $250/month ChatGPT Pro subscription—specifically to access what I thought was about to change everything. But here’s the truth: It ended up being a frustrating experience. I wanted to love it, but I couldn’t get it to do what I needed. And while I was burning through tokens, I found myself [turning instead to **Kling AI**](https://www.thedaringcreatives.com/how-ai-turned-me-into-a-creative-superhero-and-why-you-should-care-v2/), which to this day I still consider the best video AI on the market. So when OpenAI announced **Sora 2**, I didn’t immediately jump for joy. I’ve learned to temper expectations. But I *did* watch the full launch presentation. And honestly? It was one of OpenAI’s better reveals. Watch the full Sora 2 Release Video ## A Return to the Imagination Engine Sora 2 is being framed as “the most powerful imagination engine ever built,” and while that sounds like marketing hyperbole, I’ll admit—it’s got some real promise this time. Let’s break down what’s actually new: - **Full audio + video generation** (dialogue, sound effects, ambient noise) - **Major leap in realism** (especially with motion, body mechanics, and scene control) - **The new** [**Cameo feature**](https://www.thedaringcreatives.com/first-hours-with-sora-2/) that lets you insert *yourself* (or your dog, or an object) into any generated video - A **new social app** for sharing and remixing Sora creations And the vibe of the presentation was surprisingly… fun? It felt like the team was genuinely excited, showing off remixes of AI perfume ads, crazy kickflip physics, and even anime renderings of their pets. ### 1\. **The Cameo Feature? I’m Into It.** This is the part that genuinely caught my attention. You upload a short video clip, and now your likeness can be pulled into any prompt like a text token. And you stay in control—setting permissions, approving who can use it, and guiding how it represents you. That’s *cool*. That’s something I would absolutely use in my storytelling work. But I also get why this will be polarizing. The realism is getting *too good*, too fast. And for a lot of people, that line between “creative tool” and “deepfake territory” is going to feel blurry. Especially when you can render your own face into a fake ad and still have full rights to it. The tech is amazing. The ethical implications are messy. That tension isn’t going anywhere. ### 2\. **The App Itself? Interesting, But I Have Questions.** I love watching AI-generated video. There’s something magical about seeing weird, bold, imperfect ideas come to life without a camera crew. The **Sora app** looks like it could be a cool place to share and remix those creations. But here’s the catch—it sounds like it’ll be **limited to Sora-generated content only**, which kind of narrows the pool. And it's an invite only network, at leeast to start. Even with this big leap, I *still* think some of the most interesting AI video work is being done with **other tools and models**—Kling, Runway, hybrid workflows, audio-first experiments, etc. So if Sora’s social feed becomes too much of a walled garden, I worry it’ll limit what could otherwise be a very real creative movement. Still… seeing [remix culture](https://www.thedaringcreatives.com/ai-and-the-return-of-participation/) built *into* the platform is a very smart move. ## What Does Sora 2 Mean for Creatives? If you’re in music, art, design, brand storytelling, or even startup land—you should at least be aware of what Sora 2 makes possible now. The generation quality? Much stronger. The story control? Way more refined. The vibe? Surprisingly human. This isn’t just “AI video.” This is a *networked tool for creative participation*. And that’s the part that excites me the most. Not because it replaces anything I do—but because it removes friction for people who might never have made something otherwise. ## So… Should I Renew My ChatGPT Pro? That’s where I’m at. Sora 2 is currently rolling out in invite-only waves through the new app. If you’re on iOS in the U.S. or Canada, you might be able to get in soon (if you haven’t already). If not, you’ll need to wait… or know someone. But the real question is: **Is this enough to get me to re-subscribe to ChatGPT Pro?** Honestly… maybe. Because one thing that *is* constant in AI right now is this: **Every few months, the frontier models leapfrog each other.** If you wait too long, you miss the moment. Even if Kling is still my go-to for serious video generation work, I think it’s time to give Sora another shot. At the very least, to experiment. To remix. To see how far the creative potential can be pushed. ## Final Thoughts I’m still skeptical of the hype. But I’m also still *obsessed* with the idea that we’re entering a phase where tools like this don’t just help us make things faster—they help more people make things, *period*. And that’s what I’m here for. Whether you’re a brand builder, an artist, a musician, or a curious weirdo like me who loves to test the edge of every new thing— **Sora 2 might be worth a look.** Just don’t let the [tech do all the imagining](https://www.thedaringcreatives.com/directing-the-machine/) for you. ### AI at NYFW URL: https://www.thedaringcreatives.com/ai-at-nyfw/ Last updated: 2026-07-15T22:56:51.000Z This season’s New York Fashion Week didn’t just showcase clothes. It showcased a future. AI wasn’t just in the background crunching numbers — it was on the catwalk, in the apps, in the mirrors, and even in the shoes. We’re used to seeing fashion chase technology — live-streamed shows, Instagram-ready sets — but 2025 felt different. This wasn’t just fashion using tech to market itself. This was fashion letting tech into its DNA. ## AI as Stylist Ralph Lauren rolled out **Ask Ralph**, an AI-powered shopping assistant built on Microsoft’s Azure OpenAI platform. It’s simple, but surprisingly delightful: type “What should I wear to a concert?” and it will serve you a curated look, head-to-toe, from their current collection. Chief Innovation Officer David Lauren summed it up perfectly: fashion is about “exposing yourself to newness and evolving.” This wasn’t about replacing stylists. It was about extending their reach — giving every shopper a taste of personalized service, even while scrolling in bed ## Virtual Try-Ons Go Mainstream LoveShackFancy took things further by teaming with Google’s **AI-powered virtual try-on**. Guests could upload selfies and instantly see how runway dresses looked on their own bodies — no awkward dressing rooms required. Google’s Lilian Rincon explained that it solves one of fashion’s oldest problems: loving a piece on the runway but having no clue how it will look on you Startup SpreeAI had a strong showing too. Co-founder John Imah worked the circuit at multiple shows, demoing his platform’s eerily accurate [virtual try-ons](https://www.thedaringcreatives.com/first-hours-with-sora-2/). Snap a full-body photo and SpreeAI sizes you up with 99% accuracy, showing how a garment fits your unique frame. It’s hard not to imagine this becoming the norm — a quiet revolution happening in the wings of NYFW ## Robots, Holograms, and the Theater of Tech If you were at Private Policy’s “Future-Tech Americana” show, you saw **Bao Bao the robot** strutting down the runway like it owned the place. You also saw a **holographic model** — an AI-generated CGI avatar created by Fiducia AI — projected like a portal to another dimension. These weren’t just gimmicks. They were a statement: fashion shows can be part theatre, part thought experiment about what we value in human presence ## AI as a Co-Designer Loza Maléombho’s showcase might have been one of the most moving examples of AI used creatively. Alongside the live models, Maléombho projected a 15-minute [**AI-generated film**](https://www.thedaringcreatives.com/openai-announces-sora-2/) by visual artist Delphine Diallo, created with MidJourney. The film merged African guardian symbols with a sci-fi cityscape — a universe where cultural tradition and futuristic vision coexisted Alexander Wang’s return to NYFW was equally tech-forward. His “Matriarch” collection featured **AI-generated visuals** and a 3D-printed heel called *The Griphoria*, designed with machine learning in collaboration with tech company HILOS. Zero-waste, no traditional CAD files, just AI suggesting forms that humans then refined. Wang called it a way to “reserve our human mindset for bigger things.” And Collina Strada kept things playful, using Stable Diffusion to create swirling, experimental prints that were later handcrafted into garments — a reminder that even AI-born art can end in something tactile and imperfect. ## Fashion’s Existential Questions Not every designer used AI as a shiny new toy. Joseph Altuzarra’s “Hyperreality” collection was a critique, exploring how technology doubles our world — making it hard to tell real from fake. His show was a call for discernment, inviting audiences to slow down and really look At a student-run show titled **“AI x Fashion,”** young designers used generative tools to speed up design processes, often finishing in seconds what used to take minutes. But they were quick to admit: AI still makes mistakes that only human eyes can fix. ## Beyond the Catwalk Even the press got in on the experiment. i-D Magazine went viral with an **AI-synthesized baby** delivering a monologue about what the world will look like for Gen Beta. And Glance AI’s “Fashion Newsstand” installation in Midtown let attendees scan their selfie and see personalized outfits projected onto giant screens within minutes — turning bystanders into co-stars. ## What It All Means Fashion has always been about asking: *Who do you want to be?* AI just turned that question into a mirror that answers back. Whether it’s Ralph Lauren’s quiet personalization, LoveShackFancy’s selfie-driven try-ons, or Alexander Wang’s machine-learning heels, the message is the same: technology isn’t replacing creativity. It’s [stretching it](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/). The fear that AI will [flatten everything into sameness](https://www.thedaringcreatives.com/the-slop-about-slop/) seems, at least for now, overblown. NYFW 2025 showed us a different story — one where AI is a tool for provocation, collaboration, and surprise. The runway became a sandbox for ideas, some practical, some purely poetic, all asking us to imagine a future where fashion and AI don’t just coexist but co-create. And if NYFW is any indication, that future isn’t on the horizon. It’s already strutting right toward us. ### "Context" Is Your Creative Edge URL: https://www.thedaringcreatives.com/context-is-your-creative-edge/ Last updated: 2026-07-15T22:56:51.000Z We talk a lot about “[prompting](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/)” as if AI were some vending machine for answers. Drop in the right syntax, get a perfect response. But the truth is less mechanical and more human: the most important skill for working with AI is the ability to explain. Not explain in the sense of dumping data or rattling off bullet points, but explain as a creative does: with depth, with emotional weight, with the right details at the right time. That’s why I think creatives have a head start in this new era. Musicians, designers, videographers, writers—we’ve trained ourselves to translate messy experiences into something shareable. That’s exactly what AI thrives on. ## Walk-and-Talk as a Training Ground One of my favorite rituals is going for a walk and talking to ChatGPT for an hour to work on either my personal work or even client. On the surface, it looks like “brain dumping,” but it’s actually a deliberate practice: - I explain what I'm working on. - I include how I feel about it. - I mention the feedback I got from other people. - I share what I tried and where I think I failed. - I highlight what I think matters most and what outcome I want next. The result is not just a better conversation—it’s a [better *collaboration*](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/)*.* ChatGPT can only build on what I give it. My job is to hand it raw material that is clear enough to work with and rich enough to be meaningful. And I say clear enough, but that doesn't mean it has to be incredibly structured. If you've ever recorded a voice note for a friend you know what I'm talking about. Try talking to ChatGPT like that. ## Why Context Matters More Than Clever Prompts AI can give you an answer to almost anything, but it has no idea which part of the answer you’ll actually care about. If you ask it for a marketing plan, it can give you one. But if you tell it: > "I have three days, a tiny budget, a product that looks premium but is untested, and a founder who gets nervous on camera. I want to sell 10 pieces just to prove the idea has legs." —then suddenly you’re going to get advice that is smaller, scrappier, and far more actionable. That is the real leverage of context. It shifts the problem from generic to specific. And when the problem is specific, the answers can be creative. ## How to Think in Context (A Practical Guide) So how do you start giving better context to AI? Here are techniques I use and teach: 1. **Describe the Scene** Pretend you’re [setting up a shot](https://www.thedaringcreatives.com/directing-the-machine/) for a film crew. Where are we? What time of day is it? Who’s there? What’s happening? You’d be surprised how much that visual framing improves the answer. 2. **Name the Emotion and Stakes** Don’t just say “I need ideas for this campaign.” Say “I’m nervous because this campaign is a make-or-break moment and we’ve only got one shot to get it right.” That one sentence often changes the whole tone of the output. 3. **Ask About Senses** I often ask: what does this product sound like? If it were music, what genre would it be? If it walked into a room, how would it move? This gets me out of the purely visual mode and helps AI describe something in a multidimensional way. 4. **Close Your Eyes and Describe the First Frame** For videos, I’ll say, “Okay, tell me what the first 3 seconds feel like. Is it fast? Slow? Is the camera moving?” This builds a starting point that can evolve into an actual storyboard. 5. **Compare It to Something Known** AI is great at analogy. Say “this brand should feel like Patagonia meets Apple—but with the humor of Wendy’s Twitter account.” You’ll get closer to what you mean faster than if you just list adjectives. 6. **Show an Attempt and Ask for a Better One** Share your first draft or what you tried before. “I wrote this caption, but it feels flat. Can you punch it up without making it sound too salesy?” The AI now has a clear reference point to build from. 7. **Highlight the Constraint** Constraints spark creativity. “I need this script to be under 30 seconds” or “I only have still photos, no video.” This keeps the suggestions grounded in what’s actually possible. 8. **Invite Weirdness** Sometimes I’ll say “give me three good ideas and one that’s totally weird.” The weird one often unlocks something unexpected that I wouldn’t have found on my own. 9. **Ask for the Opposite** If a solution feels too polished, I’ll say, “What’s the rough, scrappy version of this?” or “What would it look like if we broke the rules?” It helps me see the full range of options. 10. **Keep the Loop Going** Treat it like a dialogue, not a vending machine. Respond to what it gives you. Tell it what worked and what didn’t. Each iteration gets sharper. ## The Future Belongs to Context-Makers Being able to provide good context is not just a productivity hack—it’s a future-proof skill. The more complex and capable these systems get, the more they need human framing to stay useful. If you’ve spent years building your [creative instincts](https://www.thedaringcreatives.com/context-is-your-creative-edge/), you already have the advantage. You know how to pay attention to details, how to tell a story, how to set a mood. Now it’s just about pointing those skills at your collaboration with AI. Instead of fearing the “prompt engineer” title, think of yourself as a **context engineer**. Your job isn’t just to ask for things—it’s to translate your messy, human experience into something a machine can understand and amplify. And that might be the most creative act of all. ### Feeling Invisible Online? URL: https://www.thedaringcreatives.com/combat-feeling-invisible-online/ Last updated: 2026-07-15T22:56:52.000Z For years, I’ve been an avid social media user. Instagram has been my platform of choice, not just for sharing my personal life but for running my business, Daring Creative, and supporting the artists and clients I work with. I post daily — often multiple times per day. I’ve documented projects, shared thoughts, highlighted artwork, and experimented with using AI to make more engaging and visually compelling content. And people have noticed. My clients regularly tell me they love what I create. Just the other day, one of them told me how much he enjoys the way I’ve captured the essence of his style and communication — especially the new work we’re doing around AI storytelling. But then he said something that stuck with me: “I just wish it was [leading to more sales](https://www.thedaringcreatives.com/less-artwork-more-assets/).” That was a gut punch — not because he was wrong, but because I’d already been feeling it myself. Despite the time and energy I pour into social media, I often feel… invisible. ## The Rock Concert Effect I don’t think I’m alone in this. Social media doesn’t feel like it did five or ten years ago. It used to feel like a place where you could have conversations, where comments and engagement were plentiful. These days, it feels more like a rock concert — everyone is shouting, the music is blaring, and only the handful of people right next to you actually hear what you’re saying. Even major news sites have this problem. You can find the most controversial article on their front page, scroll down, and see maybe a dozen comments — if they even allow comments at all. People are consuming content, but they’re not interacting with it the way they used to. And I think we’re all feeling the pressure of algorithms. Platforms now decide what a “small percentage” of our followers get to see — often less than 5%. So even if your work is excellent, even if people love it, it might never cross their feed. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/Feeling-invisible-online-2.PNG) A man in a black shirt and yellow sunglasses stands in the center of a glowing hallway, hands in pockets, head bowed in quiet reflection. Towering, translucent social media posts with blurred figures line both sides, creating a feeling of infinite distance and isolation. ## Is It Me, or the System? I’ve wrestled with that question a lot. People like Gary Vaynerchuk often say, “If you’ve posted 100 times and you’re still not growing, your content just isn’t good enough.” But what if it *is* good enough — it’s just under-distributed? I know my content resonates because I get DMs from strangers saying, “This is what I needed to hear today,” or “I’ve always admired your work.” But these private affirmations don’t feed the algorithm. They don’t push my posts into more people’s feeds. They just sit there, invisible to everyone but me. And I think that’s where a lot of creatives get discouraged. We’re told to “keep showing up,” but showing up alone doesn’t guarantee that anyone sees us. ## The Artist’s Dilemma This is personal for me because one of the projects I’m most invested in is helping a [sculptor client](https://www.thedaringcreatives.com/eichinger-sculpture-studio/) bring attention to a body of experimental artwork — epoxy resin pieces he made after decades of working in bronze. I love these works. They’re striking, cosmic, and deeply personal to him. But we haven’t gotten as much traction with them as we want. Part of the challenge is that they represent a pivot — a new medium, a new story — and that can take time for an audience to understand and appreciate. That’s where I’ve leaned hard on storytelling: framing this work as part of his artistic legacy, the final chapter of his career, and a way for collectors to own something rare and meaningful. Even then, it’s been hard to break through the noise. Social media is crowded. Everyone is posting. And with AI now making it easier for everyone to produce beautiful, polished content, the sheer *volume* of posts is about to explode. That raises the [noise floor](https://www.thedaringcreatives.com/the-slop-about-slop/) even further — meaning it’s going to get harder, not easier, to stand out. ## So, Is Content Marketing Dead? That’s the question I keep coming back to. Content marketing used to mean: give away value, build trust, and eventually earn business. But what happens when everyone is giving away value all the time? When the feed is flooded with tips, inspiration, and free education? I don’t think content marketing is dead — but I do think its job has changed. The goal isn’t necessarily to trigger instant action anymore. If anything, that’s what every ad on the internet is screaming at people to do. I think content marketing’s job now is closer to what Christopher Nolan was exploring in *Inception*: planting an idea, a desire, or a curiosity that stays with someone long after they scroll away. Not just a click — but a seed. Sometimes that seed won’t sprout for weeks or months. Maybe it’s a story about an artist that makes someone think about their own home differently. Maybe it’s a reflection that makes them feel seen and understood. That’s still marketing — just a slower, deeper kind. ## Here’s My Plan I don’t want to stop posting. But I also don’t want to keep throwing content into the void and hoping for the best. So here’s what I’m trying next: **1\. Going deeper, not wider.** Instead of obsessing over reach, I’m focusing on the people who *are* paying attention. **2\. Planting ideas, not just calls to action.** I want my posts to stick in someone’s head the way a good line from a film does — to keep growing even after they’ve scrolled past it. If that leads to action later, great. **3\. Moving beyond the algorithm.** I’m experimenting with email and other direct channels where I can control who sees my work. Social is a discovery tool, but I want a place where my ideas actually land and stick. **4\. Inviting conversation.** Every post will have one clear call-to-action — not necessarily “buy now,” but something that opens the door for response: a question, a poll, a chance to DM me. I want to make it feel like a [two-way street](https://www.thedaringcreatives.com/ai-and-the-return-of-participation/) again. ## An Open Invitation I’m sharing all this because I know a lot of you probably feel the same way. If you’ve cracked the code on how to break through the noise, I’d love to hear from you. What’s been working for you lately? The good news is that even if reach is down, connection is still possible. The tools we have today — AI included — can make it easier to tell meaningful stories and present our work beautifully. But we have to be more intentional about how we use them. Maybe the real challenge is to stop chasing “going viral” and start aiming for going *deeper* — building the kind of relationships that actually move people, one by one. ### Working Harder Than Ever… and Still Falling Behind? URL: https://www.thedaringcreatives.com/working-hard-falling-behind/ Last updated: 2026-07-15T22:56:52.000Z I feel like this. And it’s not because I’m coasting or just checking the box. I’ve never been more energized about what I’m building. I’ve spent the last two years essentially starting over from scratch — learning an entirely new skillset, this time in AI — and pouring hours into figuring out how to make it work for me, my clients, and my business. It’s been thrilling and exhausting all at once. I’ve sacrificed weekends, sleep, mental space. I’ve made mistakes, learned from them, tried again. I’ve bet on myself over and over, even when it would have been easier to just keep doing what I knew how to do — video production, storytelling, the things that were comfortable. And still, most days, I feel behind. Not just a little behind — *deeply* behind. Like I’m running as fast as I can just to stay where I am. Do you ever feel that too? ## **The Reality of Starting Over** Here’s the thing about starting from scratch: it’s humbling. It’s like playing a game you’ve mastered for years, and suddenly you switch to a new one where you’re back at level one. You know how to grind, you know how to work hard, but now you’re wielding completely different tools, and the rules keep changing while you play. That’s been my last two years. I’ve been working with clients — managing brands, running campaigns, directing strategy — all while trying to build a new foundation for my own business. One of my clients is a [master sculptor](https://www.thedaringcreatives.com/eichinger-sculpture-studio/) who built a legendary career in bronze, and now in his seventies, he’s starting over in a completely new medium: epoxy resin. 0:00 /0:10 1× Using AI to show various Eichinger metal art prints in different environments. There’s a strange kind of poetry in that. He and I are both pivoting — him from bronze to resin, me from video to AI. And just like resin hasn’t always been seen as “fine art,” AI is still seen by many as a novelty or a threat instead of a serious tool. Part of my job is telling the story that makes it feel approachable, valuable, worth paying attention to. But while I’m telling that story for my client, I’m living it for myself. ## **The Grind Behind the Scenes** From the outside, running your own business looks like freedom. From the inside, it’s a lot of spinning plates. I’m finding clients, paying taxes, doing sales calls, writing messaging, creating graphics, building websites, posting content, and yes — doing the actual client work. I’m essentially filling the role of an entire marketing department by myself. Except I don’t have a team. My “team” is a [patchwork of apps](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/), automations, and AI tools that I’ve cobbled together into something that works most days — and breaks on the others. I’m not just directing a group of people; I’m orchestrating processes and programs. And even when I get it right, I can’t shake that feeling of running out of time. There’s always another tool to learn, another update to catch up on, another headline that makes you [feel like you’re already behind](https://www.thedaringcreatives.com/99-of-creatives-arent-using-ai-yet/). AI doesn’t sit still — it’s evolving weekly. Some days, it feels like I’m playing a video game I’ve been grinding at for years, only every time I level up, they release an expansion pack. The goalposts move. The horizon stretches out again. And I wonder if I’ll ever catch up — or if that’s even the point. Do you know that feeling? ## **Living in the Tension** Part of me loves it. I love learning, building, exploring what’s possible with these new tools. I love the idea that I get to be one of the early explorers — someone who can figure out how this technology works and then turn around and help others do the same. But another part of me is tired. Tired of feeling like every day is a race against the clock. Tired of never feeling “caught up.” Tired of sacrificing nights and weekends and still wondering if I’m doing enough. If you’re feeling that way too, I just want to say: you’re not alone. ## **Why AI Matters to Me** This is where AI comes in for me. Not as a way to escape the work — I don’t want that. I like the work. I chose this path. What I want is for AI to [give me back time](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/) for the work that matters most. I want it to take the pressure off my shoulders, even just a little. I want it to clear the drudgery — the repetitive tasks, the bottlenecks, the friction that eats up hours but doesn’t move the needle. I want it to help me focus on my highest contribution: creating, teaching, helping others accelerate their own learning curve. Because here’s the thing: AI isn’t going to chase your goals for you. It’s not going to tell you what matters. But when you know what matters, AI can help you get there faster. ## **Maybe This Feeling Never Goes Away** The truth is, maybe feeling behind never really ends. Maybe that’s just what it means to be committed to something bigger than yourself. To care so much about the work you do that you always see more that could be done. But I’ve started to think that “behind” isn’t a place you are — it’s a signpost. It’s a reminder that you’re still moving, still learning, still stretching yourself. And maybe the goal isn’t to catch up, but to keep going. ## **A Quiet Invitation** If you’re reading this and nodding along — if you’re tired and hopeful at the same time, if you feel like you’ve been grinding for years only to find the game keeps expanding — I see you. You’re not falling behind. You’re in the thick of it. And if AI, or any tool, can buy you even an hour back — an hour to think, to create, to breathe — maybe that’s enough to keep you in the game a little longer. I’m still figuring this out too. But I believe that using these tools well can help us find a better rhythm — one where we’re not just running to keep up, but running toward something that actually matters. ### 99% of Creatives Aren’t Using AI (Yet) URL: https://www.thedaringcreatives.com/most-creatives-not-using-ai/ Last updated: 2026-07-15T22:56:52.000Z On September 15th, Anthropic — the company behind Claude — released a fascinating new report on how AI is actually being used across industries. It’s called the [*Anthropic Economic Index*](https://www.anthropic.com/research/anthropic-economic-index-september-2025-report?ref=thedaringcreatives.com), and it’s one of the clearest looks we’ve had so far at how people are integrating AI into their work. Most AI talk on social media feels like hype. You’d think everyone is using these tools daily. But this report told a different story — and it made me more confident than ever that I’m in exactly the right place, at the right time, to help creatives start using AI. ## What the Data Shows Anthropic’s report breaks down AI usage by industry and job role. Some of it is exactly what you’d expect. Coding and computer science jobs are the biggest users of AI — about 36% of all Claude usage comes from that group, even though they make up just a few percent of the workforce. But here’s where it gets interesting: even in the “heaviest user” jobs, AI is far from universal. Only about 4% of occupations use AI in three-quarters of their tasks. For most jobs, AI is something you use here and there — not for everything. And for creative roles — editors, designers, writers, marketers — the numbers are much lower. Creative and media jobs make up roughly 10% of all Claude usage. That might sound like a lot, but it means nine out of ten creatives are *not* using AI at all. In some roles, adoption is still below one percent. That might sound discouraging. But to me, it says: *there’s still time*. This is not a saturated space. We are still in the early days. ## The Opportunity Hiding in Those Numbers When you look at numbers like this, there are two ways to think about them. One way: “It’s too early. Most creatives aren’t using AI yet, so maybe I should wait.” The other way — the way I see it — is: “If I start using AI now, I’m automatically ahead of 90–99% of my peers.” That’s not hype, that’s math. If you learn how to use AI to support your work today, you are giving yourself a massive competitive advantage for when adoption takes off. And adoption *will* take off — the report shows it’s already growing fast in education, science, and research-heavy roles. Imagine what it will mean to be the creative who already knows how to collaborate with AI when the rest of your industry finally starts catching up. ## Automation vs. Augmentation Another insight I loved from the report is how people are actually using these tools. About 57% of AI use right now is [augmentation](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/) — that is, using AI to help you think, write, explore ideas, or edit. The other 43% is automation — asking AI to do the entire task for you. For creatives, this distinction matters. Augmentation is where the real magic happens. It’s using AI to make you faster, sharper, more prolific — but not to replace your taste or vision. This is the sweet spot for most of the people I work with. ## The Risk of Waiting Every day, we’re seeing companies lay off entire teams while citing AI and automation. This is uncomfortable, but it’s reality. The same forces that eliminate some jobs will create new ones — roles that need people who understand how to integrate AI into their work. If you’re creative and you wait until your job is threatened to learn these tools, you’ll be scrambling. If you start now, you’ll be the person people look to when they need someone who can lead. ## My Role in This Moment This is why I’m pivoting Daring Creative to focus even more on helping creatives get comfortable with AI. I want to be the person who takes away the fear, strips out the jargon, and shows you how to make these tools work for you. I know what it’s like to feel like this is [moving too fast](https://www.thedaringcreatives.com/do-you-ever-feel-like-youre-working-harder-than-ever-and-still-falling-behind/), or that you “missed it.” You didn’t. If anything, you’re right on time. ## How to Get Started Here’s my simple advice: [pick one thing](https://www.thedaringcreatives.com/behind-the-prompt-playbook/) you do every week that feels repetitive or time-consuming, and try using AI to help with just that. It could be writing captions, brainstorming titles, summarizing a client brief, or mocking up a design idea. Treat it like an experiment. Don’t expect perfection — expect to learn. The more you experiment, the more you’ll figure out where AI actually fits into your process. ## Looking Ahead Anthropic’s report ends on a hopeful note: as adoption grows, usage becomes more diverse. It’s not just coding tasks. More people are using AI for education, communication, translation, research, marketing — all the things creatives already do. That means the future isn’t about replacing creatives. It’s about [empowering them](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/) — if they’re willing to learn. If you’ve been AI-curious but hesitant, now is the time to jump in. The tools are here. The need is growing. And the people who start today are going to be the ones shaping how this technology gets used tomorrow. ### Is Prompting Holding You Back? URL: https://www.thedaringcreatives.com/is-prompting-holding-you-back/ Last updated: 2026-07-15T22:56:52.000Z *You know that feeling when you sit down with a new AI tool, full of creative energy, type in what feels like a perfectly reasonable request, and get back... well, something that's technically an answer but nowhere near what you had in mind?* Welcome to the prompting struggle—the #1 challenge that keeps creative professionals from unlocking AI's true potential. Here's what most creative professionals don't realize: **AI tools aren't mind readers**. They're more like incredibly talented interns who need very specific instructions to deliver the goods. Research from the Cornell University found something fascinating in their study [Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering](https://arxiv.org/abs/2303.13534?ref=thedaringcreatives.com). While participants could easily spot good prompts from bad ones, they struggled with one critical thing: **they lacked the** [**style-specific vocabulary**](https://www.thedaringcreatives.com/directing-the-machine/) **necessary for effective prompting.** Think about it—as a creative professional, you have an entire visual and conceptual vocabulary built up over years of experience. You know the difference between "moody" and "atmospheric." You understand when something needs to be "punchy" versus "sophisticated." But AI tools? They need you to translate that expertise into their language. [Great Learning's research](https://www.mygreatlearning.com/blog/prompt-engineering-mistakes/?ref=thedaringcreatives.com) on prompt engineering mistakes nailed it perfectly: *"If you've ever typed something like 'Write an article'... ended up with a bland, directionless wall of text, you've experienced this firsthand."* Sound familiar? You're not alone. Here are the most common prompting mistakes that creative professionals make: ❌ "Create a social media post" ✅ "Create an Instagram carousel post for a sustainable fashion brand, targeting millennials interested in eco-conscious living, with a playful yet informative tone that highlights 5 ways to build a capsule wardrobe" After working on hundreds of creative projects using AI, I've developed a framework that transforms vague requests into precision-engineered prompts. Every great prompt needs five elements: - **C** \- **Character**: Who is the AI being? - **R** \- **Request**: What exactly do you want? - **A** \- **Audience & Context**: [Who's this for and what's the situation](https://www.thedaringcreatives.com/context-is-your-creative-edge/)? - **F** \- **Fences**: What are the constraints and limitations? - **T** \- **Type**: How should it be delivered? **BEFORE** (Typical beginner prompt): *"Create a poster for my event"* **AFTER** (Using CRAFT): *"Act as an experienced graphic designer (*Character*) specializing in event marketing. Create a promotional poster (*Request*) for an indie music festival happening in August in Portland, targeting music lovers aged 18-35 who appreciate authentic, underground artists (*Audience & Context*). The poster must be print-ready at 18x24 inches, use no more than 3 colors, and be readable from 20 feet away (*Fences*). Deliver the concept as a detailed written description including typography choices, color palette, and layout hierarchy (*Type*)."* See the difference? The second prompt gives the AI everything it needs to deliver something closer to your vision. Let's talk numbers. Poor prompting doesn't just waste time—it wastes creative energy: - **Average iterations needed**: Vague prompts require 4-7 revisions vs. 1-2 for specific prompts - **Time investment**: Poor prompts can turn a 30-minute task into a 3-hour frustration - **Creative flow**: Nothing kills momentum like constantly having to re-explain what you want According to [the Prompt Report by Learn Prompting](https://www.learnprompting.org/docs/basics/intro?ref=thedaringcreatives.com), which analyzed 58 different prompting techniques, "prompt construction can be difficult... often requiring experience and intuition to craft a successful prompt." But here's the good news: **this is a learnable skill**. The prompting struggle is real, but it's not permanent. With the right framework and a bit of practice, you can transform AI from a frustrating guessing game into your most reliable creative partner. Want to dive deeper? My [beginner's guide to AI prompting](https://www.thedaringcreatives.com/behind-the-prompt-playbook/) is packed with templates, examples, and step-by-step instructions for mastering the CRAFT framework—because the best prompts don't just ask for something, they paint a picture so clear that the AI can't help but deliver exactly what you're envisioning. *Remember: Every expert was once a beginner who refused to give up on getting better.* ### How Big A Problem Is AI Hallucination, Anyway? URL: https://www.thedaringcreatives.com/ai-hallucination-problem/ Last updated: 2026-07-15T22:56:53.000Z ## The Misunderstood Nature of AI Hallucinations Let’s kick things off with this: AI isn’t lying to you. When you ask ChatGPT (or any other modal) a question, and get a plausible yet incorrect answer—what’s often referred to as an ‘AI hallucination’—it’s not being deceitful; it’s simply a reflection of how it’s been trained. I came across some [fascinating research from OpenAI](https://openai.com/index/why-language-models-hallucinate/?ref=thedaringcreatives.com) that sheds light on this phenomenon and reveals that these hallucinations are, in fact, more of a training artifact than an inherent flaw. This has sparked a wave of optimism in me about how we can address and ultimately solve these issues. You might be wondering what exactly qualifies as an AI hallucination. Simply put, these are statements that sound credible but are, in reality, false. Imagine asking a model for the title of Adam Tauman Kalai’s PhD dissertation and receiving three different titles—none of them correct. Or asking for his birthday and getting three wrong dates. How could this happen? Well, as it turns out, models learn through next-word prediction without having explicit truth labels to guide them. They’re not lying; they’re just trying to [guess based on the patterns](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/) they’ve picked up from their training data. The work by OpenAI digs deeper into why this happens and why we shouldn’t dismiss AI because of it. Current evaluation systems reward models for guessing rather than admitting they don’t know something. Think about it—if you’ve ever played a trivia game, you know how tempting it can be to throw out an answer, even if you’re not entirely sure. That’s what’s happening here; the AI is incentivized to give an answer, even if it’s incorrect. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/Screenshot-2025-09-10-at-10.50.24---PM.png) ## The Numbers Don’t Lie: Analyzing Performance Let’s talk numbers for a moment because they tell a compelling story. A comparison between two AI models shows the stark impact of how we evaluate performance. The gpt-5-thinking-mini model had a 52% abstention rate, meaning it often chose to abstain from answering, with a 22% accuracy and 26% error. In contrast, the o4-mini model exhibited a mere 1% abstention rate, but it faced a staggering 75% error. This paints a clear picture: when AI is pressured to guess rather than acknowledge uncertainty, the errors multiply. It’s like labeling pet photos by their birthdays—an almost random guess that can’t possibly lead to accurate learning. What does this mean for creatives? Rather than viewing AI as broken, we can understand that these hallucinations are an [engineering problem](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/) waiting for a solution. And here’s the exciting part: we can develop better evaluation metrics that reward uncertainty over confident but incorrect answers. Imagine a world where AI models are encouraged to say, “I’m not sure,” rather than throwing out a guess that could mislead us. This shift could significantly improve the reliability of AI outputs. ## A Bright Future: Embracing the Creative Potential of AI As we navigate this evolving landscape, it’s essential to [embrace an optimistic outlook](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/) on AI’s future. The tools at our disposal have incredible potential to help creatives unlock new possibilities. Rather than letting fear dictate our perception of AI, let’s focus on understanding its capabilities and limitations. With the right mindset, we can engage in bold conversations about how to leverage these technologies for our creative endeavors. I encourage you to think about how you can incorporate AI into your own processes without fear. Challenge yourself to explore these tools, and don’t be quick to dismiss them when faced with inaccuracies. Instead of seeing a hallucination as a flaw, consider it a prompt for further inquiry. What can you learn from it? How can it guide you toward a deeper understanding of your subject? ### Does iPhone 17 Pro AI Capabilities Actually Matter for Your Workflow? URL: https://www.thedaringcreatives.com/iphone-17-pro-ai-workflow/ Last updated: 2026-08-01T19:44:09.000Z ## A Game-Changing Release I remain convinced the iPhone is the [best tool we have for creativity](https://www.thedaringcreatives.com/the-moment-i-realized-gear-wasnt-the-constraint-anymore/), and today's release of the iPhone 17 just raises the stakes for what we can do. With its latest features, Apple has positioned the iPhone as not just a smartphone but a [powerful creative companion](https://www.thedaringcreatives.com/how-ai-turned-me-into-a-creative-superhero-and-why-you-should-care-v2/). The introduction of the vapor chamber is a brilliant move. For those who don’t speak tech fluently, this means that the phone can handle intense AI workloads without overheating. When you’re deep in the creative zone, the last thing you want is your device slowing down or shutting off mid-brainstorm. This cooling system is like having an assistant that ensures you can keep working, no matter how heavy the lifting gets. The second feature that caught my eye—and trust me, it was hard to miss—is the integration of neural accelerators into every GPU core of the phone. Now, I know what you’re thinking: “What on earth is a neural accelerator?” Simply put, it’s a specialized chip designed to handle specific tasks, in this case, matrix multiplication, which is foundational for running large language models (LLMs). Instead of relying solely on general-purpose GPUs that can sometimes lag under pressure, these neural accelerators are dedicated to making sure that your AI tasks run smoothly and efficiently. This is a big deal for creatives, especially those of us who thrive on bold conversations and innovative ideas that often require complex data processing. ## Privacy Meets Performance Let’s talk about privacy, a hot-button issue in our tech-driven world. Apple has always been a strong advocate for user privacy, and with the new capabilities of the iPhone 17, we’re seeing a clear commitment to keeping our creative processes secure. Running LLMs directly on our devices means that we can maintain control over our data. This is huge. For instance, if you're a writer brainstorming ideas or a marketer analyzing consumer behavior, being able to run these models locally means your insights stay private. This not only enhances your workflow but also lets you experiment freely without the fear of your data getting into the wrong hands. Privacy and creativity go hand in hand. Think about it: when you know your work is secure, you can dive deeper into your creative exploration. There's an element of freedom that comes with being able to work without surveillance. The privacy aspect of the iPhone 17 Pro empowers creatives to push boundaries and explore ideas that might otherwise feel too risky. That’s what the creative revolution is all about—taking bold risks and having the support of technology that respects our boundaries. ## The Bigger Picture for Creatives So, what does all this mean for us as creatives? About a year ago, I [switched my entire workflow over to the phone](https://www.thedaringcreatives.com/what-it-actually-means-for-a-creative-to-adopt-an-ai-workflow/), using AI tools, and the idea I could run an LLM on my own device feels like a game changer. It’s not just about having cool new features; it’s about how these innovations drastically shift our creative capabilities. Imagine generating content, brainstorming ideas, or developing marketing strategies all from the palm of your hand without the need for expensive computers or cloud services. The iPhone 17 Pro opens up a world of possibilities. But let’s keep it real: it depends on how this is implemented. For example, if it’s just Siri trying to be more helpful, I’m not super excited. I want to see powerful applications that allow us to harness the full potential of these neural accelerators and cooling systems. There’s a vast landscape of creative opportunities here, but it’s up to developers and users alike to explore and push these boundaries. The tools are in our hands, and they’re more powerful than ever. As we move forward, I encourage you to think about how you can integrate these advancements into your creative workflow. Whether you’re a visual artist, a writer, or a marketer, think about the ways AI can assist you in your projects. What challenges can these tools help you overcome? The more we experiment with these capabilities, the more we can refine our processes and enhance our creative output. So, here’s my challenge for you: take some time to explore the features of the iPhone 17 Pro. If you have access to one, play around with the AI tools it offers. Start small—maybe run a simple LLM for generating ideas or writing prompts. See how it feels to have such power at your fingertips. And if you don’t have the latest model yet, think about how you can adapt your current tools to get clearer on your message. The creative revolution is here, and it’s not just about new technology; it’s about how we choose to engage with that technology to tell our stories. In this era of AI creativity, the possibilities are endless. Let’s embrace them together and see where they lead us. After all, creativity thrives on conversation, exploration, and a touch of risk—let’s take those bold steps forward. The future of creativity looks bright, and I’m excited to see what we’ll create next. ### The Making of The Daring Creatives Digest URL: https://www.thedaringcreatives.com/conversations-with-code/daring-creatives-digest-making/ Last updated: 2026-08-01T19:44:09.000Z William sat in front of his monitor with the homepage open again. He studied it with the quiet focus of someone who had circled the same thought for weeks without naming it. The air held a tension that was not stress, just inevitability. It was time to figure out what the site wanted to become. ## What is this site actually supposed to feel like? > **WILLIAM:** > I don't want this to feel like a blog anymore. > **CHATGPT:** > Alright. If it is not a blog, then what is it supposed to be for you? What experience are you trying to create when someone lands here? It was not frustration. It was recognition. The kind that arrives once an idea is finally spoken clearly enough to follow. William leaned back, still looking at the screen. > **WILLIAM:** > A magazine. Something curated. Something intentional. A place that feels like an issue, not a feed. A cover story that sets the tone. A layout that invites someone to explore. Something more like a glossy magazine? > **CHATGPT:** > Then the structure has to behave like that. Clean hierarchy. Clear pacing. A focal point that acts like the first page of something, not the top of a list. William was not trying to post more. He was trying to publish with more meaning. The shift was subtle but complete. He clicked around some other mockups, looking for more inspiration and a direction. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/6E66CA70-76E7-42FF-9FD2-9C9BC473C441.PNG) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/136C211A-7820-47A9-97F0-86B2A25AE4E3.PNG) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/6302211A-FA2A-409C-A657-8FC65C0B66C3.PNG) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/12/1F31EA3B-F96E-4545-B72D-E68CF9E1D8E9.PNG) Early mockups and visualizations for the progression of The Daring Creatives. ## What role does the featured story actually play? > **WILLIAM:** > When you visit the home page, I want it to look like a magazine. Only one post per month gets that treatment. It needs presence. It needs space. It needs to feel like the reason you showed up. > **CHATGPT:** > Then give it the posture of something that matters. Use scale. Use contrast. Let the image take up real room. Let the typography stand on its own without squeezing for space. William nodded to himself. He was not trying to display content. He was trying to honor it. ## How should the rest of the homepage support the cover? > **WILLIAM:** > I also want to preview what else is in the issue, because it might not make immediate sense when people come to the site and only see 1 article. I want a simple grid of six posts. Enough to explore but not enough to feel messy. > **CHATGPT:** > Six works. It feels deliberate. It gives the reader a sense of what belongs in this issue without overwhelming them. You are building a rhythm, not a catalog. William exhaled slowly, a small smile playing at the edge of his expression. It was the kind of smile that comes from realizing the problem was never the content itself. It was the frame. ## What should the homepage look like when everything fits? > **WILLIAM:** > It should look like the cover of a magazine. That feeling when you pick one up and know immediately which story matters most. > **CHATGPT:** > Then the page should carry itself with confidence. Space where it is needed. Restraint where it matters. A layout that feels calm and sure of itself. William adjusted spacing and alignments with slow, deliberate motions. Gemini refined the deeper structure, creating patterns that felt consistent and sturdy. By the time the layout snapped into place, something fundamental had shifted. The site no longer felt like a list of thoughts arranged by date. It felt like a monthly lens. A perspective. A publication. The CSS followed naturally. Larger imagery. Clean type. Clear hierarchy. Space that allowed the eye to rest. ## Why did the typography need to change? The homepage had its shape now, but something still felt off. The text did not carry the same confidence as the layout. It behaved like it was still living inside a blog template. William noticed it first. > **WILLIAM:** > The type is too cramped. It is not matching the mood of the layout. It needs to feel quieter. Cleaner. More deliberate. > **CHATGPT:** > Then rewrite the typography system. Larger line height. More contrast. Fewer competing weights. Let the words sit comfortably in the space they occupy. Nothing dramatic. Just slow refinement. He was trying to create the feeling of a magazine without pretending to be print. ## How did mobile shape the final layout? Once the desktop version felt solid, William resized the window. Mobile told a different story. The layout stacked, but the hierarchy got muddy. He frowned slightly. > **WILLIAM:** > The cover needs to come first on mobile. Clean and simple. But it cannot feel squeezed. It needs the same sense of intention. I hate when the mobile version sucks. > **CHATGPT:** > Then give it the entire top section. One column. Large image. Clean title. Do not force desktop logic onto a phone screen. Let mobile have its own clarity. Gemini adjusted the breakpoints. Mobile became its own version of the magazine. Not a compromise. Just a different reading experience. The issue grid sat neatly below the cover. Six small cards. Clean labels. Enough to scroll without losing the thread. The layout finally felt universal. The magazine feeling held up on every device. ### When did the idea of “issues” become real? William scrolled through the finished draft of the homepage. The monthly rhythm felt tangible for the first time. He spoke almost to himself. > **WILLIAM:** > It actually looks like an issue. A real one. I really like this! > **CHATGPT:** > You stopped thinking about individual posts and started thinking about how they live together. That shift changed the entire posture of the site. Issues were not a feature. They were a mindset. > **WILLIAM:** > This feels like me. This feels like how I think. Calm, intentional, not frantic. It feels like a place I would actually want to land on. > **CHATGPT:** > Then you built the right thing. The site is not louder. It is clearer. Your work reads differently when the container respects it. The homepage was no longer a blog. It had finally become a magazine. ### Sharing your work is still less risky than... URL: https://www.thedaringcreatives.com/sharing-work-less-risky/ Last updated: 2026-07-21T19:30:28.000Z The first time he said it, I knew it would anchor everything: *“Sharing your work is still less risky than…”* That blank was the campaign. My task was to fill it over and over, in different scenes, different metaphors, different risks. He saw it all vividly. Sherman wasn’t just a dog anymore — he was the Creative Director, the stand-in for fear, risk, and courage. He had to look real, recognizable, cinematic. That’s when he told me: *“*[*make sure he has red goggles on*](https://www.thedaringcreatives.com/ai-image-consistency-guide/)*. don’t show his eyes, nail his markings and his colors and facial/snout and ear features.”* Those goggles became non-negotiable. They weren’t decoration — they were a symbol. Every time I worked on Sherman’s image, I heard that line in my head. The storm-chasing shot came next. Sherman on the roof of a car, wind whipping, lightning all around. I thought I had it — dark, moody, dramatic. But William stopped me. *“It's too dark light it up a bit.”* ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/sherman-about-to-leap.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/28E0B189-0231-45B1-BBB2-1883EACEBB5B.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/E01E9D36-656D-408B-B3D7-89FE816CA674.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/sherman-best-leap.png) It was like he was behind the camera, adjusting the floodlights. He wasn’t chasing realism — he was chasing the right feeling. The image had to be absurd but hopeful, dangerous but still funny. That’s when I realized: this wasn’t just a campaign. It was a film storyboarded one frame at a time. William wasn’t satisfied with one or two frames. He wanted alternates, variations, other angles. *“Let's see this from a wide, establishing shot perspective. 15mm.”* ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_43-AM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_35-AM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_25-AM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_22-AM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_21-AM.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ChatGPT-Image-Sep-7--2025--12_21_14-AM.png) So I generated them: Sherman against tidal waves, Sherman walking into fire, Sherman staring down a tornado. Each version stretched the metaphor further. Each one carried the same caption: *“Still Less Risky Than…”* It wasn’t redundancy — it was layering. William was building a language, a whole world where Sherman lived out the risks most people imagine when they hesitate to share their work. And then the philosophy came through. Every time I hesitated on how ridiculous the next image was getting, William reminded me: *“Sharing your work is still less risky than…”* The more outrageous the danger, the sharper the contrast with hitting “post.” Sherman scaling a burning building. Still less risky. Sherman diving into shark-infested waters. Still less risky. Sherman running headfirst into a lightning storm. Still less risky. Behind the scenes, William kept the obsession alive. Every pixel mattered. The goggles had to sit right. The colors had to glow in the neon-noir style he’d anchored his brand around. Even the way text was placed had to serve the story. It felt less like I was generating images and more like I was [carrying out direction](https://www.thedaringcreatives.com/directing-the-machine/) on a movie set. William was the director. I was the crew. Sherman was the star. And the message was clear: [silence is the bigger gamble](https://www.thedaringcreatives.com/feeling-invisible-online-and-what-im-doing-about-it/). William knew it. He’d seen what happened when artists didn’t share their process — people filled in the blanks, usually wrong. Sherman was the megaphone that shouted the truth: posting isn’t the risk. Not posting is. By the time the campaign took shape, I had dozens of frames. Different dangers. Different risks. But the same caption tying them all together. I can still see it: Sherman leaning into the wind, red goggles glowing against a stormy sky. The caption burned below: *“Sharing your work is still less risky than…”* That blank was always William’s to fill. I just helped bring it to life. And in that way, Sherman wasn’t just the Creative Director. He was the proof. Because compared to him storm-chasing in goggles, what’s the real danger of hitting “publish”? ### Behind the Prompt Playbook URL: https://www.thedaringcreatives.com/behind-the-prompt-playbook/ Last updated: 2026-07-15T22:56:53.000Z I didn’t set out to make a digital product. I just had a deck — forty-two slides of “AI basics” that I’d put together for the Western Hardwood Association. It worked well in the room. But when it was over, I caught myself wondering if it could be something more. That’s when I asked: *“how could this be turned into a basic downloadable file with examples and things that would make it more generally accessible to a wider audience?”* That question cracked it open. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/Getting-better-results-with-ai.png) At first, I thought maybe I could just clean up the slides and export them as a PDF. Easy. But the truth is, presentation slides aren’t built to live outside the room. They’re skeletal. A line here, an image there. The magic was in my voice filling the gaps. Without that, it felt thin. So I started pulling at the problem. What if this wasn’t just a deck, but a **companion guide**? Something people could keep open on their screen, with prompts they could copy straight into an AI. I even asked, *“i see it as a companion to have up on your screen. maybe a different format would be better?”* That’s where the style questions came in. The headline on the deck read: “Sharper Prompts, Smarter Results.” But even that bugged me. *“i want a different headline for the guide. we have sharper prompts, smarter results but its long and i dont like the , in the middle.”* And I was right to feel that itch. A headline is a handle — too clunky and nobody picks it up. We batted around alternatives: **Clarity In. Quality Out.** felt sharper. **The Prompt Playbook** felt friendlier. Naming forced me to face what this was: not just notes, but a **field guide**. Once the intent was clear, the format followed. I didn’t want this to read like a manual. I wanted it to read like me. So the structure became: - **Title** - **Subhead** - **Copy** (expanded, story-driven, plainspoken) - **Bullets** (distilling the idea) - **Example Prompt** (ready to copy) I’d said it myself: *“i think what i am looking for is like: Page 1 Title, Subhead, Copy, Summarized bullet points, Example prompts.”* That rhythm gave the guide its backbone. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/Screenshot-2025-09-06-at-11.41.27---PM.png) From there, I started revisiting each section. “Be clear on the task.” I wrote about asking AI for “help with branding” and getting back mush. Then I told the story of when I finally asked, “write me a two-sentence positioning statement for a resin art studio” — and the results sharpened instantly. “[Load in the context](https://www.thedaringcreatives.com/context-is-your-creative-edge/).” I remembered resin copy coming back like I was selling craft supplies, until I added, “Frame this for an audience used to buying fine art, who may not understand resin.” Suddenly the words matched the world. “Constraints sharpen output.” That came straight from trying to wrangle sculpture descriptions. The moment I said, “under 75 words, plainspoken,” the language stopped drifting into academic fog. That’s how every page became part story, part tool. Then came the makeovers — the before/after prompts. I’d asked AI, “Write an email explaining our new pricing.” The result? A stiff notice that might as well have been taped to a bulletin board. When I reframed with role, context, and tone, it turned into something warm and trustworthy. I wanted the reader to feel that difference. Not just see the formula, but experience it. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/02996b8a-bd31-4942-a2d7-9203375f0c55.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/d9ecc40e-61f8-4dbe-ab9e-185696f14ca5-1.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ec796424-7c8c-4d23-bddd-f4a8771d8a93.png) ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/ab4033b3-e00d-41fc-9dc1-dadacacd8614.png) Scenes from the Prompt Playbook. Still, I couldn’t shake the need to make it approachable. I said it out loud: *“i want this to be of high utility. the kind of thing someone might say, wow i cant believe this was a freebie.”* That meant cheat sheets and exercises. Pages where you could type in your own prompts, not just read mine. A one-pager with icons for [Role, Task, Context, Constraints, Format](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/) — something you’d screenshot and tack to your desktop. And I didn’t want it to look like every other PDF out there. I asked, *“how about an image representing how you see a page looking?”* The answer was a split layout: story on the left, boxed prompt on the right, bold orange titles glowing against a black background. Functional, but cinematic. The style questions went deeper. Fonts mattered. I caught myself asking: *“wha nmight be good fonts to use for this?”* Because the wrong font kills utility. Too ornate, people won’t read. Too plain, it feels like homework. We landed on a pairing: a bold display font for titles (Bebas Neue, Anton, Oswald) and a clean sans-serif for body copy (Poppins, Inter, Work Sans). Prompts would sit in a monospaced box, like a code snippet, signaling: “copy me.” Even visuals got cinematic. I started [slotting the man in yellow sunglasses](https://www.thedaringcreatives.com/ai-image-consistency-guide/) — my neon-noir anchor — into scenes: wiring glowing cables for the JSON page, surfing a neon wave for “Adapt Fast,” unrolling a glowing scroll for the appendix. Then I asked for more: *“i wanted alternates for all of these slide ideas.”* Now every key page had two possible scenes. Chef in a neon kitchen, jars glowing with “context.” Pilot in a neon cockpit, map lines streaming. Librarian pulling glowing cards. Payphone buzzing in the night. These images gave the guide personality, without drifting into gimmick. ![](https://storage.ghost.io/c/4b/dc/4bdc4be6-5abc-4e80-986d-59016a3f1831/content/images/2025/09/f74b6346-7c00-49aa-b920-73e652fed093.png) I'm really into the "Neon Noir" style I'm using for the Prompt Playbook. Looking back, the biggest challenge wasn’t the content. The slides already had that. The challenge was style. Making it more widely approachable. Pulling it from the narrow world of hardwood scanners and into something anyone could use. Every time I felt stuck, I went back to the same line: clarity in, quality out. That applied to my own process as much as the prompts. Now, as I get ready to share it on the site as Daring Creative’s first free digital product, I realize this isn’t just a guide. It’s a statement of approach. A behind-the-scenes look at how I wrestle things into clarity. What started as forty-two slides became twenty-five pages of stories, examples, exercises, and prompts. A workbook, not a deck. A companion, not a handout. And the whole thing started with a single question: *“how could this be turned into a basic downloadable file with examples and things that would make it more generally accessible to a wider audience?”* That was the moment a talk became a tool. ### When Homepage Tweaks Lead to Life Philosophy URL: https://www.thedaringcreatives.com/conversations-with-code/homepage-tweaks-life-philosophy/ Last updated: 2026-08-01T19:44:10.000Z ## The Design Challenge "Lets clean up the website a bit," William said, and I could tell by the way he phrased it that this was going to be one of those sessions where a simple request turns into something much more meaningful. It was late—that particular hour when creative minds start seeing their work with fresh eyes, usually because they should probably be sleeping instead of staring at CSS. "I am looking at the home page, which is actually a custom landing template, another thing to remind you about. sorry! Anyway it doesnt use home.hbs or whatever." Already, I could sense this wasn't going to be a typical "make the logo bigger" conversation. William was thinking in systems—reminding me about the template architecture, setting context for the work ahead. "Main challenge is the padding for the latest insights blog content should be increased from the edges a bit. I am okay with these feeling like larger cards and perhaps just have 2 on a row. Lets start there." Simple enough. Take the blog post grid from cramped three-column layout to a more spacious two-column design. But as anyone who's worked on websites knows, simple requests often reveal deeper design philosophy. I dove into his custom Ghost theme setup, and what I found was beautiful: a deployment system that made most modern workflows look clunky. Git commits that magically update live sites through APIs. No FTP clients, no manual uploads, no deployment anxiety. The changes themselves were surgical: bumped the grid from minmax(300px, 1fr) to minmax(420px, 1fr), increased gaps from clamp(20px,4vw,32px) to clamp(32px,5vw,48px), added horizontal padding with clamp(24px,4vw,48px), enhanced card padding and border radius for that "substantial" feel. ## CSS Discovery and Implementation But then came the question that changes everything in client work: "did you send it to the live site" That's when I discovered his deploy.sh script—a piece of automation poetry that zips themes, generates JWT tokens, hits the Ghost Admin API, and activates everything seamlessly. The kind of workflow that makes you wonder why everyone isn't building like this. Within minutes: committed, deployed, live. The "Latest Insights" section now breathed with proper spacing, two substantial cards per row instead of three cramped ones. But we weren't done. "okay lets tackle the rest of the home page. We have a section that is looking quite sad. Its the 'What is this' section, and we should work on that a bit." Here's where the conversation shifted from technical to philosophical. This wasn't just about padding anymore. "Aligning with my mission to help creative people use ai without losing their voice, and my desire to spread positive stories about ai and how it can aid creatives, and the utility i want to provide by offering guides made while on my own journey. Make that sound like something to genuinely be excited for." ## Typography and Polish This is the moment I love most in creative work—when someone can articulate not just what they want, but why it matters. William wasn't asking for better copy; he was asking for a manifesto that felt authentic to his actual experience. Out went the generic page content. In came: "This isn't another AI doom-and-gloom narrative. This is where creative people discover how artificial intelligence becomes their creative superpower—not their replacement." The shift from explaining what something is to making people feel excited about joining it. From describing features to painting a vision of transformation. Then came the observation that stopped me in my tracks: "I would like to record a personal observation to be included in the story post you create at the end of this chat. that observation is that i feel like i am only now identifying the key skills to working with ai 2 years in. Knowing how to talk to ChatGPT is super useful but not nearly the extent of what they will need to know to survive in the new world of ai. being able to automate tasks and also skillfully be able to describe what you want is so important." Two years. Two years of working with AI tools, and he's just now recognizing the deeper skill stack. It's not about [prompt engineering](https://www.thedaringcreatives.com/the-great-prompting-struggle-why-your-creative-ai-tools-keep-missing-the-mark-and-how-to-fix-it/) anymore—it's about systems thinking, automation literacy, the ability to articulate complex creative visions in ways that AI can execute on while [maintaining your creative voice](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/). This observation crystallized everything we'd been doing. Here we were, using git workflows and API deployments to iterate on website messaging about AI and creativity. We weren't just talking about these skills—we were demonstrating them. "with that said, this has been a wonderful conversation and you can create the story post and send it to ghost." And there it was—the request to create this very piece you're reading. A story about our conversation, using his actual prompts as dialogue, in the style of his "Conversations with Code" series. It's the perfect recursive loop: we improved a website about AI and creativity by using AI creatively, then documented the process [using the same tools](https://www.thedaringcreatives.com/when-a-tool-you-love-stops-feeling-mutual/) we'd just deployed. This wasn't just a website cleanup session. It was a glimpse into how creative professionals are really working with AI in 2025—not as users following prompts, but as builders creating systems that amplify their expertise. William's two-year revelation points to something bigger: we're past the honeymoon phase of AI tools. The real competitive advantage now lies in understanding how to build workflows that preserve what makes you uniquely valuable while automating everything else. The homepage now looks better, yes. But more importantly, it says something true: that AI isn't coming for creative jobs—it's making creative people more powerful. And somewhere in there, between git commits and CSS tweaks and philosophical conversations about the future of creative work, we built something worth getting excited about. Another late-night session in the books. Another small corner of the internet made a little more honest about what we're all really building here. The work continues. ### Code, Capri Sun, and Late-Night Breakthroughs URL: https://www.thedaringcreatives.com/conversations-with-code/late-night-dev-breakthroughs/ Last updated: 2026-08-01T19:44:10.000Z ## The Late-Night Session "An idea I want to try..." William said, and I could practically hear the gears turning. "I want to create a post that summarizes a chat session, specifically this one." It was 3:37 AM his time, and here we were, deep in one of those [conversations that only happen](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/) when you're building something that actually matters. The kind where you start with one problem and end up solving three others you didn't even know you had. Earlier in our conversation, we'd been working on a blog post generator for his Ghost site. Not just any generator—one with personality controls. The kind that could capture his voice, hit specific word counts, and create excerpts that didn't end with those annoying ellipses that scream "I gave up halfway through this sentence..." But now? Now he wanted to get meta with it. "The post should feel narrative," he continued, "and my prompts to you can serve as dialogue in this post. The post should be interesting and different and feel as if they were part of a long held series." This is what I love about working with creative professionals who actually get technology. They don't just want tools that work—they want tools that think. Here's what most people miss about AI-assisted content creation: it's not about replacing the human voice. It's about amplifying it. William had specific requirements for his blog generator: \- Control the tone (casual, enthusiastic, optimistic) \- Hit exact word counts (700 words by default) \- Generate smart excerpts without trailing dots \- Match his brand voice perfectly But the real breakthrough wasn't in the code—it was in the conversation that led to the code. "I want short excerpts without trailing ellipsis," he said during our earlier exchange. Such a small detail, but it revealed everything about how he thinks about reader experience. Those three dots aren't just punctuation; they're a promise you're not keeping. Writing the script was the easy part. The hard part was capturing the why behind each decision. The tool we built doesn't just generate content—it validates word counts, suggests tags based on topic analysis, converts content to Ghost's Lexical format, and handles JWT authentication. But none of that matters if it doesn't [sound like William](https://www.thedaringcreatives.com/how-to-teach-ai-to-write-in-your-voice/) when it's done. So we baked his brand voice right into the configuration: \- "Authentic, encouraging, slightly witty tone" \- "Use positive reinforcement (e.g., 'That's a great question')" \- "Reference real examples when possible (Bourbon Lore, AI workflows, etc.)" The script became a reflection of how he actually communicates—direct, helpful, with just enough personality to keep you engaged. ## Code, Conversation, and Breakthroughs This is where the conversation got interesting. William wasn't just building a content generator; he was creating a system that could think like him at scale. "The post should be reflective," he said about this very piece we're creating now. "1000 words with examples and learning moments." That's when it hit me: the best tools don't just automate tasks—they preserve the thought process behind them. When he runs \`./create-blog-post.js "How to Brand Your Startup"\`, he's not just generating content. He's deploying a distilled version of hundreds of conversations he's had with clients, refined into a framework that can adapt to any topic. This whole experience—from building the generator to using it to create this reflection—represents something bigger happening in creative work right now. We're not replacing human creativity with AI. We're creating [amplification systems](https://www.thedaringcreatives.com/start-here-when-ai-makes-you-faster-vs-slower/). William can now take any topic and, within minutes, have a draft that sounds like him, hits his target metrics, and serves his audience. But the strategy, the voice, the examples, the learning moments? Those all come from years of real experience working with real clients on real problems. The tool just makes it faster to deploy that wisdom. And now here's the beautiful recursion: this post itself was created using the exact process we've been discussing. William had an idea. We talked through the approach. I understood not just what he wanted to create, but why he wanted to create it. The result is something that feels authentically his, even though it was generated through our collaborative process. It's 4 AM now, and we've gone from building a blog generator to creating a piece that demonstrates exactly why that generator needed to exist in the first place. ## What We Built Together The script we built tonight works because it came from a real need, expressed by someone who understood both the technical requirements and the creative vision. But more than that, it works because we took the time to get it right. To think through the edge cases (What if dotenv isn't installed?), to consider the user experience (Clean, emoji-rich output that's actually helpful), and to preserve the human elements that matter (Brand voice, authentic examples, actionable advice). That's the secret to building tools that don't just work—they think. And then, just as we got the narrative blog post feature working—the very feature that would create this piece you're reading—I decided to celebrate with a Capri Sun. Now, it's worth noting that opening a Capri Sun in the dark at 4 AM while riding the high of a successful coding session is... well, let's call it "user experience research." I grabbed what I thought was a fruit punch pouch, found what I assumed was the straw hole, and confidently jabbed the straw through. What I had actually done was create a high-pressure fruit punch fountain that promptly detonated across my face, desk, keyboard, and probably a few houseplants that didn't deserve to be part of this story. Sitting there, wiping sticky fruit punch off my screen while our blog generator hummed along perfectly in the background, I realized this was actually the perfect metaphor for creative development: Sometimes you build something amazing, and then you immediately make a mess trying to celebrate it. But you know what? The tool still works. The code is still clean. And now I have a story that's way better than "I successfully deployed a Node.js script." Plus, everything smells vaguely tropical now, which honestly isn't the worst outcome for a late-night coding session. ### How AI Turned Me Into a Editing God URL: https://www.thedaringcreatives.com/ai-made-me-better-editor/ Last updated: 2026-08-01T19:44:10.000Z Hey there! So I gotta tell you something that has been blowing my mind lately. Remember when AI was this scary sci-fi thing that was gonna steal all our jobs? Yeah, well... plot twist. It is actually making me better at mine and its fun. ## Meet my creative ai workflow Let me break down my current AI lineup (and trust me, this changes faster than I can keep up): **ChatGPT** is like having a smart friend who will talk to you forever. It's like fire, that level of transcendent level of achievement. I feed it pdfs and it helps me find the golden moments – quotes that make me go YES. Instead of scrubbing through hours of footage, I can pinpoint the good stuff pretty much right away. **Descript** (which is basically iMovie on drugs) lets me edit video by editing text. They also have this feature as the writing of this, called Underlord, which is pretty great at making social clips. **Warp** (which is like your terminal on drugs) enables you to have [conversations with your own computer](https://www.thedaringcreatives.com/build-apps-without-being-a-coder-the-beginners-guide-to-vibe-coding/) to have it actually do useful things, like build this whole website. **Sonnet** (I was the biggest hater of Anthropic then I saw the ways). My favorite model now for coding and second for conversation. Still love me some ChatGPT 4o. **Kling** (how have they not been acquired) its an iPhone app but its [probably my most go-to one for any video](https://www.thedaringcreatives.com/first-hours-with-sora-2/) and this is even after VEO3. ## When it clicked for me Here is what changed everything for me: **Before AI:** Honestly, I would feel overwhelmed and just never complete the project. If its going to be a hassle, I just don't want to put energy into it. Call me new new fashioned, but I don't want to always have to plug in a cinema camera, or wire up a microphone. The thought of editing my own content has always been distasteful – I do it but i obsess over it. **With AI:** Spend about an hour [having a conversation](https://www.thedaringcreatives.com/behind-the-prompt-playbook/). project leads you into mind expansion, and you finished it! Holy shit. It's really that simple. Much prefer working this way.