BUILD AGENTS THAT NEVER FORGET

Summary from the TLDR AI newsletter

LLM agents fail without structured memory because stateless calls lose context, break multi-step tasks, and force repeated mistakes. Vector search alone cannot answer multi-hop questions, so Cognee combines relational, vector, and graph stores to preserve provenance, meaning, and relationships. The framework exposes four async calls to ingest, structure, refine, and retrieve memory, enabling agents to persist knowledge, link entities, and improve over time.