Agentic Memory

Agentic memory refers to the mechanisms by which an AI agent retains and retrieves information across steps within a task or across multiple sessions.

It includes working memory (the active context window), short-term memory (task-scoped storage), and long-term memory (persistent vector stores or databases). What an agent remembers shapes what it does next, so stale or incorrect memory keeps producing errors long after the original mistake.

Closely related concepts include Short-Term Memory (Agent), Semantic Memory (Agent), Agent Memory, Episodic Memory (Agent). Each is defined in the Prefactor glossary.