Most people who add "memory" to an AI agent do the same thing: embed every message, throw the vector into Pinecone or pgvector, and call similarity_search at query time. It works for a demo. It falls apart in production, because nothing ever updates or deletes anything — the store only grows, and it fills with contradictions. Say a user tells your agent "I live in Austin" in March and "I just moved to Denver" in July. A naive vector store keeps both. At retrieval time, both come back as...