Agent memory is an AI agent's ability to retain and reuse information across turns and conversations, so it remembers context, history, and prior outcomes instead of starting fresh each time. It typically combines short-term memory within a session and longer-term memory stored and retrieved across sessions.
It matters because resolution depends on context. An agent that remembers a customer's plan, prior tickets, and recent order can resolve an issue in one pass instead of asking the customer to repeat themselves. Memory is what makes an agent feel continuous rather than amnesiac.
Agent memory is a general AI concept, not an Aide-owned term. In Aide, the agentic AI platform for customer experience, the relevant context is supplied by the Customer Context Engine, which pulls history and signals from connected systems such as Shopify, WooCommerce, and Salesforce. The aim is durable, accurate context, not a black box of accumulated state.
What the agent recalls and acts on stays traceable rather than hidden, and the same context is surfaced to people, so the team's shared understanding of the customer stays complete instead of being locked inside the agent.
Frequently asked questions
- What is the difference between short-term and long-term agent memory?
- Short-term memory holds context within a single conversation. Long-term memory persists across sessions, so an agent can recall a customer's history and prior outcomes in future interactions.
- How is agent memory different from a context window?
- A context window is the fixed span of text a model can read at once. Agent memory is the broader system that decides what to store, retrieve, and place into that window across many conversations.