The system by which AI agents store and retrieve information across interactions, encompassing short-term working memory (current conversation context), long-term memory (persistent knowledge from past interactions), and episodic memory (specific event recollections). Effective memory systems are critical for agents that need to maintain context across multi-step tasks or long-running relationships.
Related Terms
Semantic Memory
A knowledge storage system that allows AI agents to remember and recall information based on meaning rather than exact keywords. Semantic memory uses vector embeddings to store and retrieve contextually relevant information, enabling agents to maintain long-term context across conversations and channels.
Stateful Agent
An AI agent that maintains persistent state across interactions, remembering previous conversations, user preferences, and task context. Unlike stateless chatbots that treat each message independently, stateful agents build and maintain a model of the ongoing relationship — enabling continuity across sessions, channels, and time.
RAG (Retrieval-Augmented Generation)
A technique that enhances LLM responses by retrieving relevant information from external knowledge bases before generating an answer. RAG grounds AI responses in real, up-to-date data — reducing hallucinations and enabling agents to answer questions about proprietary or domain-specific content.