The outcome
Learn the interaction loop using a small task with a clear outcome.
Cursor is a AI code editor. Working with AI inside a real codebase: planning a change, editing files, reviewing diffs, and testing the result. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.
Before you begin
Set the boundary before the tool starts.
Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.
AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.
Step by step
A workflow you can repeat.
- 01
Download Cursor, run the installer, then complete onboarding for shortcuts, theme, and terminal settings.
- 02
Open one existing repository and let the editor understand that project before asking for a change.
- 03
Ask for a small, scoped plan tied to named files and acceptance checks.
- 04
Review the diff and run the relevant tests before accepting the edit.
Working standard
What good use looks like.
- State the outcome before the background.
- Provide the real source material.
- Review the result before expanding the task.
AI-generated code can appear plausible while breaking conventions, security assumptions, or tests. Keep changes small and make the test or verification step explicit.
Official references
Check the current product documentation.
Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.