How to Use Cursor's Agent Mode

Cursor agent mode is the part of the editor you reach for when a task is too big for a single inline suggestion. Instead of completing one line at a time, the Agent (driven through Cursor's Composer interface) plans the work, edits across multiple files, can run commands and tests, reads the results, and iterates toward a finished change. This guide explains what agent mode actually does, when to use it instead of inline edits or chat, how to give it the context it needs to succeed, and how to review its work so an autonomous change never surprises you. Where exact controls and command names change between releases, we point you to the official documentation rather than quote details that may already be stale.

What is Cursor agent mode?

Cursor is an AI-native code editor built on a fork of VS Code, and the Agent is its most autonomous surface. When you describe an outcome, the Agent breaks the request into steps, gathers the code it needs, proposes and applies edits across however many files the task touches, and can run terminal commands or tests to check its own work. It is closer to delegating to a teammate than to accepting a completion: you state the goal, it does the legwork, and you review the result.

In practice you will see the Agent and Composer mentioned together. Composer is the workspace where you describe multi-file changes and watch the model plan and edit; agent mode is the more autonomous behavior that can take actions like running commands and reacting to their output. The exact naming, modes, and toggles are refined often, so treat the Cursor docs as the source of truth for what each control does today.

Agent vs inline edits vs chat

Most of the skill in using Cursor is choosing the lightest tool that fits the job. Tab is for fast, in-flow edits while you type. Chat is for questions and small, well-scoped changes with attached context. The Agent is for larger work that spans files or benefits from running code. Reaching for the Agent when a one-line Tab completion would do is slower and noisier; reaching for Tab when you really need a multi-file refactor just creates a long chain of edits you have to babysit.

When to use agent mode

Agent mode pays off most when the task has real surface area or needs feedback from running the code. Good candidates share a few traits: they touch multiple files, they follow a pattern the model can generalize, and they have a clear definition of done you can check against.

• Implementing a feature that spans several files, such as adding an endpoint plus its types, tests, and a small UI.
• Refactors that repeat a mechanical change across a codebase, like renaming a concept or migrating an API call pattern.
• Wiring up boilerplate that follows existing conventions, where the model can learn the shape from nearby files.
• Tasks where running tests or a command tells you whether it worked, so the Agent can verify itself and iterate.

Conversely, lean away from the Agent for tasks that hinge on judgment you have not yet expressed, ambiguous requirements, or one-off tweaks. If you find yourself unsure what "done" looks like, write that down first; a vague request produces a vague, sprawling change that is harder to review than to make yourself.

How to give the Agent good context

The single biggest lever on output quality is context. The Agent reasons over the code and instructions you put in front of it, so the more precisely you scope the request, the better and faster the result. Cursor lets you attach specific files, folders, symbols, and selections, and project rules let you bake in conventions once so you are not repeating them every time.

1. State the goal, the constraints, and how you will know it worked, in plain language at the top of the request.
2. Attach only the files and symbols that matter so the model is not distracted by unrelated code.
3. Point to an existing example to follow ("match the pattern in this file") so new code fits your codebase.
4. Mention your tests or a command to run, so the Agent can verify its own work and fix what it breaks.
5. Use project rules to encode standing conventions (stack, naming, error handling) that apply to every task.

If you want more habits that compound over time, our companion piece on Cursor tips and tricks covers the small workflow choices that make every session smoother.

How to review the Agent's changes

Because agent mode can edit many files and run commands, review is not optional, it is the part of the workflow that keeps you in control. Treat every agent run like a teammate's pull request: read the diff, run the code, and ask for adjustments instead of redoing the task from scratch.

• Work on a clean branch with a committed starting point so you can always reset if a run goes sideways.
• Read the full diff before accepting; do not approve changes you have not looked at, especially in unfamiliar code.
• Run the tests or app yourself rather than trusting that the Agent's own check is sufficient.
• Reply with targeted feedback ("keep this, but handle the empty case") to iterate instead of starting over.
• Commit in small, reviewable chunks so the history stays clear and a bad change is easy to isolate.

Stay current with Cursor

Agent mode is one of the most actively developed parts of Cursor, so the best way to keep up with improvements is to watch the official changelog rather than memorize any single release. If you would rather get the highlights without combing through release notes, Cursor Drops summarizes new Cursor releases for you, and the in-app changelog keeps a running history of what shipped. You can grab the app on the App Store, then bookmark the documentation for the authoritative details whenever a feature changes. To go broader on the editor first, our guide to Cursor's best features puts agent mode in context alongside Tab, chat, rules, and MCP.