Built AI versions of 15 of my favorite creators over the last 3 months. Mostly for myself. Yesterday someone asked me how. Today a few more people did. So here's the entire blueprint, free. Pick any YouTube channel. Run Claude Code. Paste one message. Wait 30 minutes. You now have an AI tutor that's read every video on that channel and can answer questions like the creator would. Hormozi-bot for pricing. VanClief-bot for whatever you've been meaning to ask Jake at 2am(Spoiler Alert: this happens a LOT). Your favorite teacher, on tap. Repo: https://github.com/aaronb458/youtube-tutor-template Free version runs on your laptop. Paid version (~$5-10/mo, with $200 in free Deepgram credits to start) lives in the cloud and plugs into Claude.ai as a permanent tool. Both versions are walked through end-to-end by Claude itself — you don't need to know what an API key is, what a database is, or what "deploy" means. You click links. You paste things back. That's it. Posting it here because @Jake Van Clief's content rewired how I think about creative + business + software being one unified system. The only way I know how to repay that is to make sure people in this community can mainline it the same way. Try it. Break it. Tell me what's confusing. I'll fix it.

You built your first folder. Vote below, then drop a screenshot in the comments so we can see what you came up with.

This post has a video example. **TLDR:** Console injection. Anything running in a browser can print a control menu to the console. Claude reads it. Now it knows what it can do, and controls the site without an API. So, no back-end needed. Super simple. Want the full picture? Keep reading. Want your LLM to build this for you? Copy/paste this whole post. --- **THE PROBLEM** You want your LLM to control something in your browser. Your options aren't great: 1. Claude-in-Chrome's built-in tools. It doesn't know what your site does or how to use it. It takes screenshots and guesses. Slow and token-heavy. 2. Build an API server. Now you're managing keys, hosting, and paying per call. **THE SOLUTION: CONSOLE INJECTION** There's a third option. Whatever you're building loads in the browser. On load, it prints a list of controls the AI can use. The LLM reads the console, sees the control list, and runs JavaScript to call those controls directly. It's just a simple JavaScript control list sitting in the console. You can even add a workflow so the AI has an idea of what it can do with those controls. This works for anything that runs in a browser. A SaaS tool, an internal dashboard, a local dev environment, a canvas editor, a data pipeline UI - if it renders in a browser tab, you can give an LLM a control panel for it. Here's what it looks like in one of my tools (hit F12 to see your own console): ``` [AI-ACCESSIBLE] This app can be controlled via JavaScript. * Sidekick.help() - Complete tools reference (returns JS object) * Sidekick.teach() - Full teaching guide, 14 sections logged to console * Sidekick.tool(name, input) - Execute any tool directly * Sidekick.batchAutomap(mappings) - Smart batch mapping (recommended) help() + teach() contain everything needed. No need to fetch external files. ``` The LLM sees that, and it's immediately trained. It can read state, click buttons, type things, batch operations - whatever you've exposed. **IT GETS BETTER**