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Concept·Agents & Automation·Added 1 month ago

Memory Layer

Also known as: persistent memory, long-term memory, cross-session memory

A separate storage system that gives an AI agent the ability to remember information across sessions, beyond what fits in a single context window. The memory layer stores and retrieves facts, preferences, and prior work so the agent can pick up where it left off.

A context window resets with every new session. A memory layer doesn't. It's an external store, typically a vector database or key-value store, that the agent can read from and write to. When a user returns to the agent, it queries the memory layer for relevant prior context and injects it into the current session. From the user's perspective, the agent remembers them.

Different memory designs have different trade-offs. Episodic memory stores summaries of past conversations. Semantic memory stores facts and relationships as embeddings for fuzzy retrieval. Working memory is the current context window. Procedural memory encodes how to do things, closer to skills or fine-tuning. Most production agents use a combination.

For builders, implementing a memory layer is one of the most impactful UX improvements you can make to a multi-session AI product. A customer support agent that remembers your account history, a coding assistant that remembers your architectural preferences, or a research tool that remembers your prior findings all feel qualitatively different from stateless alternatives.

This definition is AI-generated and refreshed weekly. It may contain inaccuracies. Use your own judgment, especially for production decisions.
Related terms
Agent memoryRAGVector databaseContext windowClaude Projects