Your team's best knowledge is trapped in Slack threads, Google Docs, and people's heads. I build a structured, compounding knowledge base using the Karpathy LLM Wiki pattern — so your AI agents and engineers always have the right context, instantly.

Based on Rebar, my open-source framework already used by engineering teams in production.

What You Get 📚😍 Knowledge audit & structure design — map what you know and how it flows

Ingest pipelines for Notion, GitHub, Slack, PDFs, transcripts, and web content

Obsidian-compatible wiki with semantic search — find anything in seconds

Self-learning loop — promotes validated knowledge, discards stale content automatically

MCP server integration — Claude Code and Cursor can query your knowledge base directly

Handoff documentation and team training so your team can maintain it independently

Your team's collective knowledge stops living in people's heads and starts compounding over time. Every doc, decision, and conversation becomes a queryable asset for both your engineers and your AI tools.