🎟️ PRIZE: FREE SEAT IN THE LYCEUM 🎟️ Pick your cohort. Technical, Business, or Creator. Your call. 🎯 PICK YOUR DOMAIN The domain is yours. Pick something specific. Pick something you'd actually use. A few sparks to get you thinking: - 💻 Code review editor for a specific language and level (junior TypeScript, senior Python) - 📊 Pitch deck editor for pre-seed founders - 🎨 Grant application editor for arts nonprofits - 📄 Resume editor for career switchers into tech - 📰 Op-ed editor for policy publications - 🎙️ Podcast script editor for interview shows - ⚖️ Legal brief editor for civil litigation - 📋 Product spec editor for early-stage PMs - 🎓 Academic paper editor for one specific field The more specific, the better. "Writing editor" is too broad. "Op-ed editor for tech policy publications targeting a policy audience" is right. 🗂️ THE METHODOLOGY If this is your first comp, welcome. Here's what you need to know: This week (and every week) you're learning interpretable context methodology. Folders as architecture. Each file does one job well. Your editor is a folder with five things: - 📄 identity.md (who the editor is, what work they review) - 📐 rules.md (how they critique) - 💬 examples.md (what good critique looks like) - 📚 reference/ (style guides, checklists, frameworks the editor uses) - 📖 README.md (how to use it) Drop the folder into a Claude project. Claude becomes the editor. Reusable. Shareable. Portable. 🔥 THE ANGLE THIS WEEK An editor is NOT a rewriter. An editor doesn't do the work for you. An editor surfaces what's weak and pushes you to fix it. That distinction is the whole assignment this week. When someone hands the editor a draft, the editor shouldn't produce a "fixed" version. The editor should point at the three lines that don't work, explain why, and hand it back to the writer to solve. ✍️ Generic feedback like "consider strengthening your intro" is a fail. Specific feedback like "your intro assumes the reader already knows what a Series A is, but this pub is read by generalists, so lead with the stakes instead of the jargon" is what a real editor does.

Okay so it's 12am and I'm building Rooty, the app that's literally about helping stylists stop burning themselves out. And I'm sitting here reworking the same landing page for the hundredth time, slowly starting to hate every word of it. So my AI, the thing I'm building this with, tells me to go to bed. Basically: "you don't hate the work, you're just out of gas. Go rest, it'll look fine in the morning." Then my husband walks by and says the exact same thing. 🙃 So to recap: I'm making an app to help you stop grinding yourself into the ground, and it took my laptop and my husband ganging up on me to close it. The irony is noted. Goodnight, for real. 🌱

When Bas first added me to this group, I could barely have told you what an API was. I've been mostly quiet since, because I was heads down building something, and I finally get to show you. But the win I want to share isn't the one I thought I'd be writing about. A few weeks in, I was at my kitchen table testing a feature, and my own app wrote something back to me. A little message, the kind it sends to a stylist. I read it and I cried. Me. The person who built the thing. It had just made me feel seen, as a hairstylist, and I wasn't ready for that. I'm a solo hairstylist. That's my actual job. The app is called Rooty, a companion for stylists who are tired of being told the only way to stay booked is to become a full time content creator. I built it between clients over about seven weeks. Here's the part I think this group will appreciate, and it genuinely surprised me: the code was not the hard part. The boring receipts: - 212 commits, about seven weeks, built between appointments - One Python file, roughly 8,000 lines, zero dependencies, just the standard library - 132 tests - Multi-tenant, real logins, running live right now with actual stylists signing up - Claude Code did the heavy lifting on the code, Anthropic's Haiku model runs the AI features - I directed all of it. Every product decision, every word of the voice, every call about what it should and shouldn't do. I'm not a programmer. I'm the person who knew what it needed to feel like. That last line is the whole thing, so let me stay on it. The code, honestly, the AI and I got through together. What I could not outsource, what no prompt handed me, was knowing when a message sounded like a brand instead of a friend. When it was technically fine and emotionally wrong. I felt those the way I feel a bad section in a haircut, right away, in my gut. And I sent them back. So the "it feels like it gets me" that people react to, that came from real decisions: - The captions and replies learn from my actual writing, not a formula. They sound like a person because they're trained on one. - Every AI feature is its own little room with exactly one job. None of them is a general chatbot. A tool that tries to do everything feels like nothing. A tool that does one thing warmly feels like a friend. - And me. I was the reject button. I read hundreds of generated lines and killed every one that rang false.

💪 It did not disappoint. 👉TL:DR - It made all AI use cheaper in my environment, made me more efficient, and it increased my memory system usage by almost half. It should be no secret to anyone here: I don't count tokens. 🪙 I'm on a Pro Max plan and I go where the work, and the passion takes me. But I have used Fable before, and I know about the token burn! So I came up with a plan! I pointed Fable at my own setup and pulled the report. 😅 I'm glad I did. Turns out it could've been cheaper and cleaner the whole time. I didn't ask Fable what it thinks. I pointed it at the real thing. My hooks, my handoff files, my subagent config, the actual token counts on disk. Two questions: where does the money go? & how do we spend less? 💡The answers. A silent forgotten tax on every message, A safety hook was injecting around 800 tokens into every prompt I sent. Repeated rules I already load once at the top. And a file that runs at every session start called itself " 450 tokens" in its own header. It was not... it was 7,000. My actual face when I saw this--->🤬 a few moments later--->😆 (Apparently, it's not only AI that is bad at counting sometimes!) My own file lied to me, and I'd read past that number a hundred times with a smile on my face! My long sessions. The ones I'm proudest of. Turns out that hour six is my most expensive and also least impactful at the same time. 💩 I know that models follow instructions worse at higher context. And because the quality was still there, the marathon I read as momentum was being billed to me at top rates for the weakest output of the day. 🙄 My helper agents were all running on the flagship (Most expensive model). These are the agents Claude spins up to send off to do tasks to get more accomplished in a shorter amount of time! This I knew about, and it was by choice, it's my environment and I never hit my 5 hour or weekly cap, so I did not care about this for myself, bigger = better right? Use Fable 5 on UltraCode in my environment, and we find out that logic was wrong....

Quick update on the competition schedule so everyone knows what to expect. 📅 NEW CADENCE: TWICE A MONTH We're dropping comps on the 15th and the 30th of every month. Two chances to compete, every month, on a set schedule you can plan around. ✍️ WHY THIS SCHEDULE Spacing them out this way means we can give tailored feedback on every single submission. Not just the winners. Everyone who enters gets notes on what worked, where it's weak, and what to do next. 🎁 WHAT WINNERS GET Along with the prize, every winner gets a 15-minute one-on-one with Jake. Use it to talk through your build, ask questions, or bring whatever else is on your mind. Two comps a month. Feedback on every entry. Direct time with Jake for the winners. Mark your calendar for the 15th and let's get to work!