AI Agent Memory Explained in 3 Levels of Difficulty

AI agents built on stateless LLMs face a fundamental memory problem: every API call starts from scratch. This explainer covers three levels of agent memory — from the core problem of stateless systems, through the main memory types (in-context/working memory, external memory via RAG), to full-scale architectural patterns including episodic, semantic, and procedural memory stores. It also covers memory writing strategies (end-of-session summarization, event-triggered writes), retrieval approaches (vector similarity, structured queries, hybrid), memory decay and versioning, multi-agent memory consistency, and evaluation metrics like retrieval recall, precision, faithfulness, and staleness rate.