AI agent
Given a goal, tools and rules, this kind of AI takes several steps on its own, such as looking things up, editing or handing over, rather than replying once.
Updated October 2026 · with examples from our own builds
What does AI agent mean in practice?
An agent combines a model with tools it can use and rules about when to use them. A support agent might search a knowledge base, collect a lead's details and escalate to a person; an editing agent might change a storyboard through a fixed set of allowed operations.
Agents promise automation of whole tasks, and their risk grows with their reach. The safe pattern is to give an agent the same narrow, typed operations a person would use, so every change it makes can be checked, logged and undone.
Limits on turns, time and cost belong in the design, along with a clear exit to a person.
AI agent at a glance
- Made of
- A model, tools and rules for using them
- Safe pattern
- Only typed, reversible operations
- Needs limits on
- Turns, time, cost and reach
Where has AI agent come up in our builds?
The AI agent answers from the business's knowledge inside set guardrails and hands over on sentiment, confidence, turn count or time, passing the full transcript and any lead details.
Reelberg, a director chat inside the studio, edits a storyboard only through a kit of typed operations, the same ones the inspector's buttons and the MCP server use, so every change can be checked and undone.
Common questions about AI agent
How much should an AI agent be allowed to do on its own?
Start with actions that are reversible and low-risk, through the same operations a person uses, and widen its reach only as the records show it gets them right.
How do I know what an agent actually did?
Log every operation it performs, as you would for a staff member. If it can only act through typed operations, the log reads as a list of exact changes.
Related terms
Planning a product and not sure where AI agent fits? Ask us, or browse all 116 terms in the glossary.