Compiled Knowledge for Agentic APIs: Why Your Agents Need a Wiki, Not Just RAG
summary
Argues that RAG causes semantic gaps and retrieval drift because agents retrieve fragments not synthesized entities, and proposes a precompiled AI-maintained wiki (entity pages, topic pages, KB-summary.md, Obsidian + Claude + MCP demo) that orients agents before they call APIs. Shows a working demo: drop a URL, vault updates, an agent answers from compiled context; contradictions are flagged for a human in the loop. Claims huge token savings (example 4,000 vs 2.8M tokens) and says the pattern is provider-agnostic and auditable.
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chapters (11)
- 0:00Compiled knowledge for agents
- 2:36RAG fails with semantic gaps
- 5:50Limitations of retrieval-augmented generation
- 7:14Compiled knowledge layer
- 10:02Industry recognition
- 11:23Live demo: AI compilation
- 15:13Key takeaways
- 17:44Enterprise implementation
- 18:26Q&A: Conflict resolution
- 21:37Managing large knowledge bases
- 23:52Q&A: IDP and agent KBs
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