1 min lesson
The autonomy spectrum
Take this situation: "A developer says 'an agent is just a smarter autocomplete that edits files.' What single distinction would you teach to correct that and why does it matter?" Lead with your decision, then add the reason.
Step 1 of 2
The autonomy spectrum
Cursor's surfaces are not three names for the same thing. They sit at different points on how much the agent decides versus how much you steer and teaching developers to pick the right one for the task is pure DX.
- Surface
- Tab
- Autonomy
- Lowest - predicts your next edit as you type
- Best for
- Staying in flow on code you're actively writing
- Surface
- Agent / ComposerCursor's own fast coding model, tuned for the editor and priced well below frontier models; the recommended day-to-day model for executing a plan. Press Enter for the full definition.
- Autonomy
- High - plans, edits across files, runs the loop
- Best for
- Multi-file changes where you describe the goal, not the keystrokes
- Surface
- Background / Cloud Agent
- Autonomy
- Highest - runs a task to completion off your machine
- Best for
- Longer tasks you hand off and review as a diff or PR later
| Surface | Autonomy | Best for |
|---|---|---|
| Tab | Lowest - predicts your next edit as you type | Staying in flow on code you're actively writing |
| Agent / ComposerCursor's own fast coding model, tuned for the editor and priced well below frontier models; the recommended day-to-day model for executing a plan. Press Enter for the full definition. | High - plans, edits across files, runs the loop | Multi-file changes where you describe the goal, not the keystrokes |
| Background / Cloud Agent | Highest - runs a task to completion off your machine | Longer tasks you hand off and review as a diff or PR later |
Same underlying ideas, different leashes. Match the surface to how much you want to stay in the loop.
If a screen asks you to explain how Cursor works, resist the urge to dive into model internals. Draw the loop - assemble, decide, act, observe, revise - then place Tab, Agent and a cloud agent on an autonomy axis. That shows you can teach the mental model, which is the actual job, not just that you've read a model card.