Courses Production Hey everyone! 👋✨ Full transparency: we’re building this engine while flying it, and we are loving every second of doing it with you! 🚀 Big love and appreciation for all your feedback, ideas, and collaborative energy—this community is truly shaping what this space becomes, and we couldn’t be more hyped to build it together. 🤝💡 While we’re hard at work crafting the ultimate experience behind the scenes, we want to make sure you get exactly what you need right now. Here is where you can dive in depending on what you're looking for: 🎓 Want the Official Basics? If you're looking for the official setup straight from the source, check out: 👉 Anthropic’s Official Claude 101 Course 🔥 Prepping for Exams & Building Together? If you want focused exam prep and want to learn, practice, and build alongside the rest of the crew, drop into our unofficial community hub: 👉 Skool Exam Prep Classroom 🎬 Watch & Review the Videos in Canva All course videos are hosted inside Canva, and we need your input directly in the Canva comments section! We’re using a multimedia learning framework designed to spark self-driven learning. When you analyze the videos from both an operational (process, mechanics, execution) and artistic (flow, visual impact, engagement) perspective, you help shape the content. Dive into the comments and let's hit these learning objectives together! 💡🎨 Keep the feedback coming, jump into the discussions, and let’s keep building! 🙌 🎉

In RAG, how you split a document into chunks directly determines the quality of the system, but there's no clear answer to "which strategy is best," it's usually chosen by intuition. So I built a tool that makes this measurable. Grain splits the same document with 6 different chunking strategies, tests each one with real embeddings, and shows which one is both the most accurate and the most efficient (fewest tokens). 🔗 Live: https://grain-cdw.pages.dev What I learned along the way, the part I most want to share with you: - My first measurement method turned out to unfairly favor small chunks without me realizing it. I tried 4 different approaches to fix it, moving to the next one whenever one didn't work. In the end, the root cause wasn't in the metric itself, it was in the retrieval protocol. - I kept challenging myself with "does this actually work?" Something that passed with synthetic test data failed a few times on the first real API run. Every failure was a real engineering lesson. - Managing a project at this scale with Claude Code end-to-end (from architectural decisions to production deploy) gave me a real chance to apply the discipline I've been learning here: typed error handling, avoiding the "right concept, wrong layer" trap, never deciding without evidence. If you want to try the product, it's at the link, you can upload your own document and see the real result. Always open to feedback. 🙏

We all know the struggle isn't finding information—it's following through on what we set out to do. Delivery Pilot Community is a safe, supportive space for anyone looking to bridge the AI skills gap, build gentle discipline, and take control of their path one day at a time. We choose a standard, practice honest reflection, and share our journeys alongside a community walking the same road. hand-in-hand. 🤝 What We Offer: 🔥 Start Here: The Delivery Pilot Standard 🎯 The 90-Day Challenge ⚡ Discipline & Execution guidance 📅 Daily accountability & weekly check-ins 🎙️ Weekly Live 1-on-1 Workshops (a safe, unrecorded space to learn & share) 📚 AI Course Library that unlocks as you grow 🏆 High Performer: 10x Productivity System unlocks at Level 3. Earn points simply by sharing and encouraging others and become a VIP! 👇 DROP YOUR PROMISE BELOW 👇 Share ONE simple promise in the comments that you are prepared to keep today. Just one day at a time.

🧠 Second Brain & Graph-RAG Setup - 📺 Second Brain Video Overview: Watch on YouTube - 📖 Second Brain Installation Guide: SecondBrain_install_guide.pdf - 📑 Architecture Report: Second Brain Graph-RAG Architecture Report.pdf - 📝 Notes App: Download Obsidian 🤖 AI Agents & Tools - ⚙️ AI Agents & Usage: Overview & Workflows - 💻 Local/Host AI Setup: grok_cli_install.pdf (Host AI Grok Installation) 🛠️ Infrastructure & Data Sync - 🔄 Data Synchronization: Rclone (Sync data sources) - 🌐 Free App Hosting: Cloudflare Worker Skool Post

A while back I posted about turning my Claude chat history into a living, self-organizing knowledge base instead of letting good conversations die in scrollback. Now it has a home: https://second-sight.sudedev.workers.dev/ What's changed since that post: It updates itself. Every day my pinned Claude chats get scanned, and anything new or changed gets categorized, cross-linked, and pushed to the site automatically, no manual exporting. TR/EN, one toggle. No more searching the same concept twice in two languages and finding neither. It reminds me before I forget. Spaced-repetition surfaces old notes right when they're about to fade, instead of me re-learning the same thing a third time. Still rough in places, but real now instead of a plan I keep describing. If you're doing something similar with your own chat history, I'd love to compare notes, especially on the "make it update itself" part.