Cursor activity breakdown

See detailed Cursor activity patterns across teams and modes

Available at AI impact / Activity / Cursor

If you're looking for a productivity boost from Cursor, it's not enough to enable the tool for your teams and then forget it. People need to pick up the new habit and invest the time to learn how to use it effectively. To support that, you need proper visibility into the current activity patterns.

With the Cursor activity breakdown, you can:

• Understand where Cursor is gaining traction and where extra support may be needed.

• Know if people are just trying it out or actively relying on it in their work.

• Notice patterns in how suggestions are used across tab completions, agent, chat, and cmd+k.

Read more in our full guide:

Measure the productivity impact of AI tools

To track Cursor adoption and licenses, see:

AI adoption metrics

Setup

Enabling Cursor metrics:

AI coding tool integrations

Definitions

• Active users = There's no exact definition of an active user, but presumably it includes users who have opened the Cursor editor or interacted with the Cursor agent.

• Engaged users = accepted a suggestion or tab completion on a given day.

• Code suggestions = The number of Cursor code suggestions (excluding tab completions)

• Code acceptances = The number of Cursor code suggestions (excluding tab completions) accepted by users

• Acceptance rate (suggestions) = Code acceptances / Code suggestions

• Chat requests:

  • Agent = Requests in the chat using the "Agent" mode

  • Ask = Requests in the chat using the "Ask" mode

  • CMD+K = "Quick Edit" inline edits (⌘K on Mac)

  • Composer = (Discontinued) Cursor's legacy multi-file edit feature

  

Not all accepted code ends up in the codebase. An engineer could accept 200 Cursor-generated lines over the course of creating a 10-line pull request.

You can't use these metrics to get an accurate number of the share of your code that's AI-generated.