AI Agent Memory

AI agent memory enables AI agents to retain and recall information about users across multiple conversations. Without memory, every conversation starts from scratch. With memory, the agent remembers who you are, what you've discussed before, your preferences, and relevant details from past interactions.

There are several types of AI memory: short-term memory (within a single conversation, managed by the context window), long-term memory (persisted across conversations, stored in databases), episodic memory (specific past events and interactions), semantic memory (general knowledge about the user — preferences, facts, relationships), and working memory (active information being used for the current task).

Memory systems typically involve: extraction (identifying memorable information from conversations), storage (persisting memories in a structured format), retrieval (finding relevant memories when needed), and management (updating outdated memories, resolving contradictions, and managing staleness).

For example, if a user tells an AI agent "I'm allergic to shellfish" in one conversation, the agent should remember this in future conversations when recommending restaurants or recipes — without the user having to repeat it.

The challenge is balancing memory usefulness with privacy. Users should control what the agent remembers, and memory systems should handle sensitive information carefully.