The AI Agent Memory Stack: Building Blocks, Patterns, and Frameworks

This article explains how AI agent memory works, covering working, episodic, semantic, and procedural memory types along with design strategies for writing, retrieving, and maintaining memory reliably. It compares frameworks including Letta, Mem0, Graphiti, and Cognee on storage models, retrieval approaches, and handling of fact changes over time, and discusses multi-agent memory concerns and evaluation metrics such as retrieval recall, precision, faithfulness, and staleness.