Anthropic Just Dropped a Masterclass on Building Agent Harnesses (for Large Codebases)

Anthropic published a playbook for making Claude Code work in a large codebase, and the core finding is blunt: the harness around the model - the AI context, config, and tooling in your repo - matters more than the model itself. It's a great post! But it's high-level - "add hooks for self-improvement," "use scoped skills," "build an MCP" - and never shows you one. So I built the whole thing. I took an example codebase with none of it and built the entire harness, component by component: a CLAUDE.md hierarchy, self-improving hooks, skills, LSP, an MCP, subagents, and the plugin that bundles it all. I call that harness the AI Layer. The harness beats the model. Here's how to build it! ~~~~~~~~~~~~~~~~~~~~~~~~~~ Check out JetBrains Academy's AWS Skill Paths for applied AI and LLM engineering - hands-on, project-based learning inside PyCharm with AWS sandbox labs where you actually build and deploy real AI projects: https://jb.gg/academy/aws-skill-paths ~~~~~~~~~~~~~~~~~~~~~~~~~~ If you're interested in building your own AI second brain to save yourself hours every week, check out the Dynamous community and the new second brain course: https://dynamous.ai/second-brain-boot... The example codebase (every component, built + validated): https://github.com/coleam00/helpline Anthropic - "How Claude Code works in large codebases": https://claude.com/blog/how-claude-co... ~~~~~~~~~~~~~~~~~~~~~~~~~~ 0:00 AI Coding in Large Codebases 1:04 What We're Covering 1:57 How Claude Code Navigates Today 3:00 The AI Layer 4:19 Lean & Layered Global Rules 8:40 Sponsor: JetBrains Academy 10:31 Self-Improving Hooks 15:22 Path-Scoped Skills 18:16 LSP & MCP for Symbol Search 21:57 Subagents for Exploration 23:56 Claude Plugin & Getting Started 26:19 AI Layer Ownership ~~~~~~~~~~~~~~~~~~~~~~~~~~ Join me as I push the limits of what is possible with AI. I'll be uploading videos weekly - at least every Wednesday at 7:00 PM CDT!