Glossary / Agentic AI

Agent Loop

The repeat cycle where an agent decides, uses a tool, reads the result, and chooses the next step.

Updated July 2, 2026

The agent loop is the basic rhythm behind most agentic work: an agent decides on a step, makes a tool call, reads the result, and chooses what comes next. A healthy loop keeps going because the job is unfinished; a stuck one keeps going because it’s confused. The difference is a task, boundaries, and a clear stopping point: check my email every fifteen minutes until the deck arrives, then notify me and turn it into slides.

Picture an assistant working through an inbox. They open an item, decide what it needs, act, look at what happened, and decide whether it’s done or needs another pass. Then they move to the next one. They’re checking, acting, and adjusting until the inbox is empty.

Why you care

Guardrails keep a loop from spinning: wasting time, hitting rate limits, or retrying a broken assumption. Design the loop like delegation. What’s the task, what’s the standard, which tools can it use, and when does it stop or ask you? Real work rarely finishes in one pass; the loop lets the agent take the rest.