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What is agent memory?
Last reviewed July 16, 2026
Agent memory is persistent knowledge an AI agent keeps across conversations: facts you told it, preferences it inferred, decisions it made, and notes it wrote for itself. Unlike a context window (which resets per conversation), memory is written and recalled deliberately, so the hundredth session starts smarter than the first.
How memory actually works
Practical agent memory is notes, not neural weights: the agent writes structured entries ('the user prefers concise answers', 'the deploy target is staging first') and recalls relevant ones into context when they matter. Good implementations make this legible: you can read what the agent remembers, correct it, and delete it.
Memory, context, and files
Three layers with different lifetimes: context (this conversation), memory (what the agent carries across conversations), and files (the durable artifacts of work). Confusing them causes the classic failures: stuffing files into memory bloats recall; leaving decisions in context means re-litigating them next session.
Every idapt agent has its own memory it can write and recall in any chat; you can read and edit the entries, and the same memory serves the agent over the API, CLI, and MCP.
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