Vector Similarity Isn't Memory: How Production AI Agents Are Solving an Unsolved Problem

Vector-based memory systems in AI agents retrieve information by semantic similarity, but similarity doesn't guarantee relevance to past successes or failures. This fundamental gap between current frameworks and production needs forces teams to build custom solutions—from simple file systems to specialized failure logs and post-mortems. Understanding these emerging patterns reveals where AI agent deployment is heading and highlights the importance of outcome-based memory over semantic similarity.