What Is an AI Agent?
The term 'AI agent' is used loosely. The useful definition is narrow: a system that plans and acts across steps toward a goal, using tools and feedback along the way.
The short answer
An AI agent is a software system that uses a language model to pursue a goal over multiple steps — deciding actions, calling tools, observing results, and adjusting — rather than answering a single prompt. The defining trait is autonomy across a loop of decisions, not a one-shot response.
An AI agent is best understood by what separates it from a chatbot. A chatbot answers what you ask. An agent is given a goal and then decides, on its own, the sequence of steps to reach it — which tool to call, what the result means, and what to do next.
Concretely, an agent runs a loop: it observes the current state, chooses an action, executes it (often by calling an external tool or API), reads the outcome, and repeats until the goal is met or a limit is hit. The language model supplies the judgment at each step; the surrounding scaffolding supplies memory, tools, and guardrails.
This is why agents feel qualitatively different. Autonomy across a loop lets them handle open-ended tasks — research a question end to end, operate software, or keep a process running — but the same autonomy is why reliability, cost control, and safety limits matter far more than they do for a single prompt.
Key takeaways
- 01Goal-directed: given an objective, not just a question.
- 02Multi-step: runs a plan-act-observe loop rather than a single response.
- 03Tool-using: calls APIs, code, or software to affect the world.
- 04Stateful: carries memory across steps within a task.
Frequently asked
How is an AI agent different from ChatGPT?
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ChatGPT responds to a prompt; an agent pursues a goal across multiple autonomous steps, calling tools and reacting to results. Agents can be built on top of the same underlying models.
What are examples of AI agents?
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A research assistant that searches, reads and summarizes end to end; a coding agent that edits and tests code; or an ops agent that monitors a system and takes corrective action.
Are AI agents reliable?
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Reliability is the central challenge. Because agents act autonomously, small errors compound across steps, which is why guardrails, retries and human checkpoints are essential in production.
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