Enterprise AI Measurement Guide
Team Performance
Code Review
How do Review Turnaround and Substantive Comment Rate behave together in the Team Performance tab as AI coding adoption grows?
What it shows
The Code Review card tracks two metrics that together measure the health of the review process: Review Turnaround (the median time in hours from PR submission to first substantive review) and Substantive Comment Rate (the percentage of review comments that ask a meaningful question, request a change, or flag an issue, as opposed to approvals, cosmetic comments, or rubber stamps). Both metrics have been destabilized by AI coding agent adoption in measurable ways.
Why it matters
Review Turnaround rising after AI agent adoption is the expected bottleneck, agents generate PRs faster than human review capacity scales. But Substantive Comment Rate falling at the same time is the more dangerous signal: it means the review process is not just slower to start, it's becoming less rigorous when it does. A review process that stamps more and questions less is the mechanism through which AI-generated code quality problems escape into production. CTOs and engineering leaders need both numbers to know whether the review system is a functioning quality gate or a formality.
The Larridin angle
Larridin tracks both metrics together, turnaround and substance, because each can mask the other's signal in isolation. A team with fast turnaround but 8% Substantive Comment Rate is rubber-stamping PRs quickly. A team with high Substantive Comment Rate but 72-hour turnaround has quality-conscious reviewers who are overwhelmed. Larridin's Team Performance view surfaces both problems simultaneously and links them to the individual engineer data in the Quality tab.
Related Team Performance Metrics
Common questions
What are the two key metrics tracked by the Larridin Code Review card?
The Larridin Code Review card tracks Review Turnaround and Substantive Comment Rate to measure the health of the review process.
How has AI coding agent adoption affected code review metrics?
AI coding agent adoption has destabilized both Review Turnaround and Substantive Comment Rate, leading to slower starts and less rigorous reviews.
Why is a falling Substantive Comment Rate a concern for engineering leaders?
A falling Substantive Comment Rate indicates that the review process is becoming less rigorous, allowing potential code quality issues to escape into production.
How does Larridin help identify issues in the code review process?
Larridin surfaces issues by tracking both Review Turnaround and Substantive Comment Rate together, linking them to individual engineer data for a comprehensive view.