The AI Record
The team was roughly the same size throughout (39 unique contributors before, 43 after), but each developer went from merging 34 PRs per month to 96: a 2.9x increase in individual throughput with no headcount change.

OnaPublished by the organization itself (post), no named author

Post: How auto-approving low-risk PRs with AI cut our lead time by 74%, Ona blog, April 9, 2026, at The results.

  • 34 prs prs merged per developer per month before, 4 weeks to 2026-03-13. A person approves
  • 96 prs prs merged per developer per month after, 4 weeks from 2026-03-13. A person approves

Checked against the source [ Grade B ] Said in the last year Sells AI tools

Filed under

Ona sells AI or agent tools or services, so it has a reason to publish flattering numbers about AI. The passage stays in the archive; read it with that in mind.

How this was checked

Checked against the source by a first reader, then confirmed independently by a second reader who fetched the source without seeing the first reader's notes (Independent review agent (Claude Sonnet), blind second pass from passage text and citation only, no repository access, 2026-11-04).

Exact match in the Ona blog post, in the organization's own voice.

How to cite this passage

Ona, “How auto-approving low-risk PRs with AI cut our lead time by 74%”, Ona blog, 2026-04-09, at The results. https://ona.com/stories/auto-approving-low-risk-prs Archived at https://the-ai-record.com/passages/ona-each-developer-went-merging-34-prs-month-96-2026

More from the same source

We already had Ona's code review automation running on every PR. The agent reviewed diffs, ran the code in a full environment, cross-referenced tickets, and left inline comments with an 88% acceptance rate and a 50% reduction in time spent on pull requests.

OnaPublished by the organization itself (post), no named author

Post: How auto-approving low-risk PRs with AI cut our lead time by 74%, Ona blog, April 9, 2026, at The experiment.

  • 88% review comment acceptance rate, before auto-approval, 2026. AI assists a person
  • 50% time spent on pull requests reduction, before auto-approval, 2026. AI assists a person

Checked against the source [ Grade B ] Said in the last year Sells AI tools Passage page

Our engineers waited a median of 2 hours 49 minutes for their first PR approval. Four weeks after we let an AI agent approve low-risk PRs, that dropped to 3.8 minutes, lead time fell 74%, and deploys tripled, all with the same size team.

OnaPublished by the organization itself (post), no named author

Post: How auto-approving low-risk PRs with AI cut our lead time by 74%, Ona blog, April 9, 2026, at Opening.

  • 169 minutes median time to first pr approval before, before 2026-03-13
  • 3.8 minutes median time to first pr approval after, four weeks after the AI agent began approving low-risk PRs. A person approves
  • -74% lead time change, four weeks after vs before. A person approves

Checked against the source [ Grade B ] Said in the last year Sells AI tools Passage page

Our team averages 10.8 PRs per engineer per week, 2.5x the 90th percentile according to DX benchmarks. But every one of those PRs still needed a human to look at it, and the review queue became the constraint.

OnaPublished by the organization itself (post), no named author

Post: How auto-approving low-risk PRs with AI cut our lead time by 74%, Ona blog, April 9, 2026, at The problem: the review queue.

  • 10.8 prs prs per engineer per week, 2026. Level not stated

Checked against the source [ Grade B ] Said in the last year Sells AI tools Passage page

Something wrong? Report a correction. JSON: /api/v1/passages/ona-each-developer-went-merging-34-prs-month-96-2026.json