This mirrors something we ran into building an AI pipeline for audio content. The problem with traditional RAG is that chunking destroys the structure that actually matters — you end up retrieving fragments that are semantically similar but contextually useless.

The filesystem metaphor works because it preserves heirarchy. Documents have sections, sections have relationships, and those relationships carry meaning that gets lost when you flatten everything into embeddings.

Curious how this handles versioning though. Docs change constantly and stale context fed to an LLM is arguably worse than no context at all.