Agents don't need memory, they need documentation

Current memory plugins for AI agents use retrieval-augmented generation (RAG) to store conversation snippets in vector databases, but this approach fundamentally misses the actual problem: agents don't need to remember conversations, they need well-organized documentation of your project. These memory systems fail because they rely on similarity-based recall without context, can't distinguish between current and outdated information, and create unauditable stores that agents can't effectively search or validate.