Guide
How to Use an AI IDE for a Real Feature Change
Use an AI IDE for a real feature change by starting with one issue, naming the relevant files, asking for a plan, making a narrow patch, running checks and reviewing the diff. Treat the AI IDE like a fast teammate whose work still needs proof.
What is the working pattern for AI IDE feature work?
- Move
- Start with a bounded task
- Use this when
- Developers moving beyond AI autocomplete into agent-assisted feature work.
- Proof to save
- Issue, files, checks and owner are named
- Move
- Give the agent context
- Use this when
- The repo has patterns the agent must follow
- Proof to save
- Prompt cites files, errors and constraints
- Move
- Review the diff
- Use this when
- The task changes production code
- Proof to save
- Changed files, test output and risks are visible
| Move | Use this when | Proof to save |
|---|---|---|
| Start with a bounded task | Developers moving beyond AI autocomplete into agent-assisted feature work. | Issue, files, checks and owner are named |
| Give the agent context | The repo has patterns the agent must follow | Prompt cites files, errors and constraints |
| Review the diff | The task changes production code | Changed files, test output and risks are visible |
A good AI coding workflow is specific enough to review and small enough to recover.
Interactive diagram. Use Tab to move through hotspots or use the step controls when shown.
Use this loop when the change is larger than autocomplete and smaller than a full project rewrite.

The public guide connects to lessons, recall and readiness checks inside Learn Cursor.
How should a team run AI IDE feature work?
- 1Pick one real backlog item with a clear owner and expected result.
- 2Add only the context the agent needs: files, failing output, constraints and done state.
- 3Ask for a plan before code when the task touches more than one file.
- 4Run checks that match the risk: unit test, typecheck, visual pass or review checklist.
- 5Capture the prompt, diff, result and reviewer note so the workflow can be repeated.
Task, context, constraints, done state and checks.
Open the diff, read changed files and rerun the check yourself.
The guide anchors the workflow to issue, plan, patch, tests and review.
What should you keep after the run?
- The prompt or plan that shaped the work.
- The files changed and the reason each file changed.
- The command, screenshot or review note that proved the result.
- The rule, checklist or template you would reuse next time.
Frequently asked questions
Who is How to Use an AI IDE for a Real Feature Change for?
Developers moving beyond AI autocomplete into agent-assisted feature work.
What makes this page credible?
The guide anchors the workflow to issue, plan, patch, tests and review.
What should I do next?
Start with one real repo task, capture the prompt and review the result before scaling the workflow.
Sources & last verified
- Cursor agent best practices
- Cursor Learn: working with agents
- Cursor Learn: context
- Cursor docs: prompting agents
Cursor ships frequently. Facts verified against primary sources on June 23, 2026.
