About Cursorship

Find out what your AI-written code is actually costing you in review, rework and incidents.

What we do

Measurement of downstream consequences rather than adoption. It links code provenance to what happens afterwards: review time and comment volume, revert and rework rates, defect density, incident linkage, and time from first commit to production, comparing AI-assisted changes to human-authored ones within the same codebase and team. It identifies where assistance genuinely accelerates work and where it produces code that costs more to review than it saved to write, and it does this without ranking individual developers, which is stated as policy.

Who we built it for

• VPs of Engineering and CTOs

  Leaders at 30 to 1,000 person companies where developers use AI coding assistants heavily and nobody can say whether it is helping.

• Platform leads

  Leads who need to know where AI assistance speeds work up and where it adds review time and rework.

The problem

AI assistants write a large share of code now, and organisations have no idea what that means.

Some teams ship faster, others have quietly traded authoring time for review time, rework and incidents, and leadership is making headcount and tooling decisions on anecdote.

The vendors report acceptance rates, which measure nothing anyone cares about.

Try it before anything else

The free AI code net-time calculator runs in your browser with no account. Put in your team and your estimates, and see whether AI-assisted changes save time once review and rework are counted. Open it.