Learn
What is an AI agent?
Last reviewed July 16, 2026
An AI agent is a model given a goal, a set of tools, and permission to take multiple steps toward the goal: search the web, read and write files, run code, and evaluate its own intermediate results. The defining property is the loop: act, observe the outcome, decide the next action, repeat until done.
The anatomy of an agent
Four parts: instructions (what it is for and how it should behave), tools (what it may do: each tool is a capability with its own permissions), memory (what it retains across runs), and a stopping condition (budgets, step limits, or completion). Remove any one and behavior degrades in a predictable way: no memory means re-explaining, no budget means runaway loops.
What oversight looks like
Production agent systems bound autonomy explicitly: read-only modes that strip mutating tools, confirmation gates on consequential actions, per-run budgets, and complete action traces you can audit afterward. The measure of a serious platform is not how autonomous its agents can be, but how precisely you can set the level.
idapt agents carry instructions, memory, and tool permissions; they read and write Drive files, run code on cloud computers, and work on any of 200+ models, with an autonomy dial from read-only to full and a trace for every run.
Frequently asked
Related terms
See it in practice
The fastest way to understand it is to use it. Start free, no credit card.
Try idapt free