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FeatureFactory

Cursor Metrics

Measure what Cursor actually ships

Tag Cursor-assisted PRs automatically and track their real impact on quality, rework, and cycle time - not just authoring speed.

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Tag Cursor-assisted PRs

Automatically label pull requests that shipped with Cursor so you can compare AI-assisted work against the baseline without manual bookkeeping.

Cycle time by tool

Break coding, review, and merge time down by whether Cursor was in the loop, so you see where the AI actually moves the needle.

Quality signals, not vibes

Track revert rate, follow-up fixes, review churn, and defect escape rate on Cursor PRs to measure durability, not just speed.

Review effort analysis

Surface how much reviewer time Cursor PRs consume versus hand-written changes, catching cases where fast authoring shifts cost onto reviewers.

Trend lines over sprints

Watch Cursor adoption and its impact on throughput and quality trend week over week instead of guessing from a single standout demo.

Team-level rollups

Roll Cursor metrics up to squad, service, or org so leaders can decide where AI assistance pays off and where it needs guardrails.

Measure the impact of Cursor, not just its usage

Cursor makes writing code faster, but faster authoring is not the same as faster delivery or better software. A PR that took ten minutes to draft can still sit in review for two days, bounce back with rework, or ship a bug that escapes to production. Cursor metrics exist to close that gap between how it feels and what actually shipped.

FeatureFactory tags every Cursor-assisted pull request and measures it against your baseline across cycle time, review effort, rework, and defect escape. Instead of a demo-driven argument about AI productivity, you get a trend line your team can defend. Explore the full approach on Measure.

The point is not to grade Cursor for or against. It is to see where AI assistance genuinely accelerates delivery and where it quietly shifts cost onto reviewers or future maintainers, so you can adjust how and where you use it.

From authoring speed to delivery outcomes

Speed only counts when it survives contact with review and production. That is why Cursor metrics belong next to your delivery data, not in a separate silo. FeatureFactory connects Cursor attribution to DORA metrics and PR quality analytics so a single change in AI adoption is visible end to end.

When a squad ramps Cursor, you can watch whether lead time for changes drops, whether review churn spikes, and whether the change failure rate holds steady. If authoring gets faster but reverts climb, you catch it early instead of six months into a quality slide.

Ready to see it on your own repos? Take the tour or read how we measure AI-generated code across tools and teams.

Related tools & solutions

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Frequently asked questions

Cursor metrics are the engineering measurements that show the real impact of Cursor-assisted development: cycle time, review effort, revert and rework rates, and defect escape on the pull requests that shipped with Cursor. They let you compare AI-assisted work against your baseline instead of trusting anecdotes. See our guide to measuring AI coding tools.

From our design partners

“We finally have one number for whether the AI-written PRs are actually good. It changed how we staff reviews.”
SStaff EngineerSeries B fintech
“Plan from real signal, ship with agents, then see if the metric moved. That loop is the whole point.”
EEng ManagerDeveloper tools
“The measurement is transparent and the code is ours. That was the dealbreaker with the enterprise options.”
VVP EngineeringHealthcare SaaS

Measure what you ship.

Connect one repository and get your first delivery baseline.

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