I keep hitting the same wall with Claude Code and Codex: they’re great at reasoning, but every session starts from whatever context I manually feed them. If I spent three hours yesterday mapping out architecture decisions, today I’m explaining it again. So I built a small open-source tool called llm-wiki-compiler that acts like a knowledge compiler for your agent workflows:
- Ingest docs, URLs, and project notes
- The LLM compiles them into an interlinked markdown wiki with [[wikilinks]]
- Your agent reads it because it’s just markdown on disk
- Query outputs can be saved back in, so the base compounds over time It’s not a chat wrapper or a vector store. It’s a persistent artifact: plain markdown, Obsidian-compatible, fully inspectable, no opaque database lock-in. This feels like the missing layer between stateless coding agents and the long-running project memory we actually need. Curious if other agent builders are solving this with local knowledge bases too. submitted by /u/riddlemewhat2
Originally posted by u/riddlemewhat2 on r/ArtificialInteligence
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