Why most AI agent memory implementations break in production

Every team trying to give AI agents memory is solving the same three problems badly. After running production agent memory for several months across two codebases, here are the failure modes I keep hitting and the one pattern that actually works. Failure 1: Embed everything as vectors and call it memory The instinct is reasonable. You have a vector database, you have embeddings, you have a retrieval