Hey Academy! To get support join the AI Architects! I built a free AI coding platform that lets you spin up a 20-person dev team in under 60 seconds—and manage everything from your phone. In this video I'll walk you through the PopeBot's new cluster mode, where you can create teams of AI agents that work together automatically. You'll see how to define roles like CTO, security expert, UI/UX designer, and developer—each with their own system prompts, triggers, and concurrency settings. Connect it to GitHub and your agents will pick up issues, create technical plans, review code, and submit pull requests without you lifting a finger. I'll also demo the new Claude Code interactive and headless modes, show you full mobile support for coding on the go, and walk through the complete setup process so you can launch your own cluster for free.

Your product is probably invisible to a growing segment of buyers. Not because your SEO is bad. Because they're not using Google. A growing number of people search by asking ChatGPT, Gemini, or Perplexity a question. The AI gives them a ranked list. They research from there. If your product isn't in that answer, you don't exist. I realised this early and did something most founders skip entirely: I built the layer of my website that AI models can actually read and cite. Before writing a single ad or social post, I spent weeks on what I call the "AI-readable layer." Here's what that looked like: 1. llms.txt files at the site root. These are plain-text documentation files designed for AI crawlers. Not a robots.txt. A structured brief that tells AI models what your product is, what it does, who it's for, and how it compares. Think of it as a pitch deck for machines. 2. 62 blog posts before launch. Not SEO filler. Honest comparison posts — my product vs each major competitor. Use-case deep dives. Technical explainers. FAQ content written in the natural question-answer format that AI models actually cite. 3. JSON-LD structured data on every page. FAQPage schema on the homepage, feature pages, use case pages, blog posts. This is the metadata AI models parse when they build their knowledge base. 4. Dedicated pages for every use case and feature. Not just a features list on the homepage. Individual pages at /for/podcasters, /for/game-developers, /features/ voice-cloning. Each with its own structured FAQ. 5. Competitor comparison content that's fair. Not "why we're better." Honest trade-off breakdowns. AI models prefer balanced, cited content over marketing copy. When the AI ranked my product third — not first — that's actually more credible than ranking it #1. This approach has a name: GEO — Generative Engine Optimization. It's early. Most founders haven't heard of it. Most AI tool builders haven't optimised for it either, which is ironic. The core insight: AI models don't read your marketing

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Hi all. Just wondering if anyone uses or is experimenting with text-to-speech. If so, what are you using? I'm Curious what are you using it for? How are you producing text-to-speech? Are you using a service, an app, or something else? And if you don't mind me asking, how are you, and how much are you paying for it?

I've just finished my latest video: a three and a half hour zero-to-hero Claude Code explainer. I've included the most recent improvements on Claude to move as fast as possible and get a product which ACTUALLY makes money: https://youtu.be/roYQt9rL8Kc This is the actual method I'm using right now to generate solutions which people are genuinely excited to pay me! A real win-win... If you guys can drop some love on the video, I'd be SUPER grateful to try and help others with this... 🙏🏼