Agent Memory
Also known as: Memory System, Agent State Persistence
Definition
Mechanisms that allow an agent to retain and access information beyond the current context window. Memory enables agents to learn from past interactions, maintain state across sessions, and reference earlier observations. Memory systems range from simple conversation history to sophisticated retrieval- augmented stores.
What this is NOT
- Not the same as context window (memory is external storage, context is active prompt)
- Not just chat history (memory systems can be selective, summarized, or structured)
- Not the model's weights (those are frozen after training)
Alternative Interpretations
Different communities use this term differently:
llm-practitioners
External storage that an agent can read from and write to, enabling persistence beyond the LLM's context window. Implementations include vector databases, key-value stores, and structured databases accessed via retrieval.
Sources: LangChain Memory documentation, MemGPT paper (2023), Letta documentation
cognitive-science
The cognitive systems that encode, store, and retrieve information. Distinctions include: working memory (active, limited), episodic memory (events), semantic memory (facts), procedural memory (skills).
Sources: Cognitive psychology literature, Baddeley's working memory model
Examples
- MemGPT managing a virtual context with memory pagination
- A customer service agent remembering past support tickets for a user
- A coding agent that remembers project structure and past decisions
- A personal assistant that builds up knowledge about user preferences
Counterexamples
Things that might seem like Agent Memory but are not:
- A stateless API that treats each request independently
- Including the full conversation in each prompt (that's context, not memory)
- The model's training data (that's parametric knowledge, not memory)
Relations
- overlapsWith agent-state (Memory is a form of persistent state)
- overlapsWith retrieval-augmented-generation (RAG techniques often power memory retrieval)
- requires agent (Memory serves agents)
- overlapsWith context-window (Memory extends beyond context window limits)
Implementations
Tools and frameworks that implement this concept:
- AutoGPT secondary
- LangChain secondary
- Letta (MemGPT) primary
- Semantic Kernel secondary
- Zep primary