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Agent memory lets an AI remember what happened before so it can make better decisions next time.
Systems that allow AI agents to store, retrieve, and use information from past interactions and experiences.
Agent memory encompasses short-term memory (conversation context within a session), long-term memory (persistent storage across sessions using vector databases or key-value stores), and episodic memory (records of past experiences and outcomes). Implementations often use embedding-based retrieval to surface relevant memories at inference time.