ModelRefs / Long-Term Memory (Agents) — AI Glossary
Long-Term Memory (Agents) — AI Glossary
Persistent storage of information an agent accumulates across sessions, retrievable in future interactions.
Overview
Long-term agent memory persists beyond context window limits using vector or key-value stores. Agents write important facts, user preferences, and past task outcomes to long-term memory and retrieve relevant entries at the start of new sessions. Enables personalization, user preference learning, and continuity across multi-session workflows.
Reference details
| Topic | agents |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
The counterpart to working memory: this is what persists once the context window is gone. It is not RAG — a RAG corpus is documents you supplied, while this accumulates from the agent's own interactions, which means nobody curated it and stale entries stay retrievable until something removes them. Episodic and semantic memory are the two forms it usually takes.
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Frequently asked questions
What is Long-Term Memory (Agents)?
Persistent storage of information an agent accumulates across sessions, retrievable in future interactions.
What concepts are related to Long-Term Memory (Agents)?
Closely related concepts include memory store, working memory, retrieval pipeline.