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You sit down with Claude Code. You've got a plan. Three hours in, the context window is full, the conversation is tangled, and you've built half of the wrong thing. That's not a Claude problem. It's a workflow problem — and it's exactly what Matt Pocock designed his open-source skills library to fix. Pocock, best known as the creator of Total TypeScript, published these skills straight from his own .claude directory with a clear pitch: "Skills for Real Engineers." No bloated process frameworks. No opinionated orchestration. Just small, composable slash commands you can hack and extend. In June 2026, the mattpocock/skills repo has 150,773 GitHub stars and 13,032 forks — accumulated in under 5 months since its February 2026 release. That's the kind of adoption that tells you developers are hitting the same walls and finding the same fixes. This post covers the three productivity skills: grill-me , handoff , and teach . Key Takeaways As of June 2026, th...

Key Takeaways What you'll take away from this Cloud AI models can disappear overnight — a government letter, policy update, or pricing shift is all it takes Local models are now good enough for roughly 80% of everyday AI tasks Ollama and LM Studio make setup fast, even without a technical background Qwen 3, DeepSeek, Gemma, and Llama are the four models worth knowing right now Privacy, zero marginal cost, and always-on availability are the three core advantages of going local Five concrete startup opportunities open up the moment intelligence runs free on your desk The weekend was supposed to be spent building. The plan was locked in, the idea was sitting right there — and then, on a Friday evening, a government letter arrived at an AI lab. By Friday night, one of the most powerful models on the planet was gone. Disabled for everyone. No warning. No appeal window. That moment clarifies something...

  Watched a video by DSquaredLabs on " No more re-explaining: Give your AI agent a memory graph " — here's what stuck with me and why I think this three-tool system is worth your attention If you work on a large codebase with AI coding tools, you already know the ritual. Open a new chat, paste your file structure, explain your stack, describe how the modules connect — and repeat the whole thing tomorrow. It is not a minor inconvenience. It is a compounding productivity tax that gets worse as your project grows. This article breaks down a three-tool system designed to fix exactly that. If you want the full walkthrough with a live demo on a real monorepo, the video at the bottom covers everything in depth — but the core concepts are worth understanding before you dive in. The Problem With How Most Developers Use AI Today Most AI-assisted coding workflows are missing three things that every good engineering team actually has: A map of the codebase A process for how w...