AI made code faster. Review is now the bottleneck.
Median time in code review went up 441% between each organization’s lowest and highest AI-adoption periods.
The numbers
- Median time in code review+441%
comparing each organization’s highest AI-adoption periods with its lowest.
Measured from tools, not a survey. Vendor data, and a correlation.
Source: Faros AI, AI Engineering Report 2026, 22,000 developers
- Same report
Output went up. So did the bugs.
Epics per developer+66%more work completedBugs per developer+54%lowest vs highest AI-adoption periodsSource: Faros AI, AI Engineering Report 2026
- Same report+31%
more pull requests merged with no review at all.
Source: Faros AI, AI Engineering Report 2026
- 8.1 million pull requests
AI PRs sit in the queue longer
Wait before review4.6xlonger than a manual PRReview once picked up2xfaster than a manual PROnce opened they move faster. Getting opened is the slow part.
Source: LinearB, 2026 Software Engineering Benchmarks (vendor data)
- A Google engineer, in Google’s own DORA research
“Reviewing [another’s] code is so much harder than writing it.”From 1,110 open-ended answers by Google engineers
Source: DORA, Balancing AI tensions, 10 Mar 2026
Fix the review, not the writing
- Let AI take the first review pass. I run an AI reviewer on every merge request, about 600 so far. People then review the design. GitHub says AI code review use grew 90%+ in a year.
- Track review time next to throughput. PR count shows what shipped. Wait time shows what it cost.
- Keep PRs small. An agent can write a thousand lines in a minute. Nobody reviews that well.
Sources
- Faros AI, AI Engineering Report 2026 (vendor telemetry, 22,000 developers), 12 Apr 2026
- LinearB, 2026 Software Engineering Benchmarks (vendor, 8.1M PRs), 2026
- DORA, Balancing AI tensions, 10 Mar 2026
- GitHub Octoverse 2026, 28 Oct 2026
Is review your bottleneck yet? Tell me on LinkedIn or Instagram.








