AI Code That Fixes Itself (An MCP You Can Try Now)
AI coding assistants (even the best ones like Claude Code) constantly make frustrating mistakes - wrong function names, incorrect syntax, endless debugging loops. Here I introduce a breakthrough solution that is still very experimental: indexing open source projects into knowledge graphs that enable AI to self-correct in real-time. Instead of guessing at APIs/SDK syntax and getting stuck in infinite debugging loops, AI coding assistants can now query exact syntax, validate its code against actual codebases, and heal itself automatically. I even give a live demonstration showing how this knowledge graph approach eliminates hallucinations and creates truly reliable AI coding. This isn't just incremental improvement - it's the foundation for taking AI coding assistants to the next level of reliability and usefulness. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Check out Director to easily create browser automations in real time with natural language (get started for free!): https://browserbase.plug.dev/h04lnzt Director and the open source Stagehand browser automation framework are both created by Browserbase: https://browserbase.plug.dev/JpoDwdP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Crawl4AI RAG MCP Server: https://github.com/coleam00/mcp-crawl4ai-rag Archon (V2 Overhaul Coming Soon): https://github.com/coleam00/Archon ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 00:00 - Fixing AI Coding Hallucinations with Knowledge Graphs?! 01:19 - What's in the Knowledge Graph? 02:44 - Detecting Hallucinations in Action 06:56 - When this Strategy is Useful (or not) 11:51 - Hallucination Detection in the Crawl4AI RAG MCP Server 15:38 - Knowledge Graphs + Claude Code = $$$ 20:04 - Results of One Shotting an AI Agent with Our Strategy 22:40 - Final Thoughts ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Join me as I push the limits of what is possible with AI. I'll be uploading videos weekly - Wednesdays at 7:00 PM CDT!
