What is an AI coding agent?

An AI coding agent is a coding tool that works in a loop: it reads your request, makes a plan, edits files across your project, runs commands or tests, reads the output, and keeps going until the task is done. Unlike plain autocomplete or a chat window, it takes real actions in your codebase instead of only suggesting text.

How is a coding agent different from autocomplete or chat?

Autocomplete finishes the line you're typing. A chat assistant answers a question in a side panel and waits for you to copy the code over. An agent does neither and stops there — it takes the goal and carries it out.

Give it 'add pagination to the users list,' and it will find the right files, write the changes, run the app or the tests, and fix what broke, deciding each next step from what it sees. The shift is from a tool that suggests to a tool that acts.

What can a coding agent do on its own?

Most agents share the same core abilities:

• Read your project — open files, search the repo, and pull in the context needed to understand your code.
• Edit multiple files — make coordinated changes across a task, not just a single snippet.
• Run commands — execute tests, build the project, install packages, or run a script and read the output.
• Loop and self-correct — check whether a change worked and try again when a test fails or the build breaks.
• Report back — summarize what it changed and why, so you can review before keeping it.

Where should you be careful?

Because the agent decides each step itself, it can take a wrong turn — edit the wrong file, misread an error, or loop on a fix that doesn't work. A small early mistake can spread across a long chain of edits. That's why the agent mode in modern coding tools usually asks before running risky commands, and why you should review the diff and run your own tests before merging.

Treat the agent as a fast junior developer whose work you always check.