Large language models are stateless by default. Each API call starts fresh. The model forgets your last message once the response returns. That is fine for a single question. It breaks the moment you build an agent.
Agents plan, call tools, and run across many steps. They need to remember. Memory is the infrastructure that fixes this. It turns a stateless model into a system that retains context. That system can learn from experience and act over time.
What is Agent Memory
Memory is any mechanism that carries information across a model’s reasoning. Some of it lives inside the context window. Some of it lives outside, in databases or model weights. Each type stores a different class of information for a different duration.
Memory varies by form and by time. Form means parametric, stored in weights, or non-parametric, stored as text. Time means short-term or long-term. The seven types below map onto those two axes.
