Agent Memory
A mechanism by which an AI agent stores and retrieves information during operation. It is generally divided into short-term memory within a single session and long-term memory retained across runs. Common implementations include vector databases, key-value stores, or file systems.
Timeline (last 90 days)
The "recall" of agent memory usually corresponds in engineering to the retrieval-augmented generation (RAG) approach: historical interactions are segmented, vectorized, and stored in an index, and relevant fragments are retrieved by semantic similarity or hybrid retrieval.
Agent memory is more complex than document RAG because historical entries carry temporal order, task attribution, and causal associations, and pure vector similarity may recall outdated or already-overturned information.
All Facts (2)
The "recall" of agent memory usually corresponds in engineering to the retrieval-augmented generation (RAG) approach: historical interactions are segmented, vectorized, and stored in an index, and relevant fragments are retrieved by semantic similarity or hybrid retrieval.
50%UnverifiedAgent memory is more complex than document RAG because historical entries carry temporal order, task attribution, and causal associations, and pure vector similarity may recall outdated or already-overturned information.
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