Coding Agents can plan, edit, and test code with limited supervision, but keeping their plans, decisions, and handoffs connected quickly becomes a coordination problem. This article covers how these agents work, where they help, where they fail, how to evaluate them, and how to integrate external APIs safely.

What are coding agents? Understanding AI coding agents

Coding agents are large language models wrapped in a runtime that can read a repository, call tools, run shell commands, and apply changes across multiple files. The runtime supplies the loop: it feeds tool output back into the model, tracks state between steps, and decides when the task is finished. The distinction that matters is scope of action, not model quality. An assistant suggests. An agent acts, then reports what it did.

That changes the unit of work. A developer no longer reviews a suggestion at the cursor, but a set of edits, a test run, and a short justification for the approach.…