Polar Engineering Benchmarks
Polar delivery benchmarks are based on 395 merged pull requests in the last 30 days (4,196 all-time), with 1.4 hours median cycle time, 0.1 hours median review time, and 12 active contributors. AI-related signals appear on 88.6% of recent work. PR volume is up 14% compared to the prior period.
polar merged 272 PRs in the past 30 days with 20.96% showing AI-related signals. Median cycle time is 0.22 hours.
Repo vs Polar.sh Average
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Top AI Coding Agents
Most active AI coding agents in the last 90 days.
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copilot-swe-agent
36 PRs (100.0%)
AI Signals vs Cycle Time
Correlation
Cycle Time by AI-Related Signals
PR Breakdown
Top AI Tools
PR Type Breakdown
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| CLI: Add "trigger" command for testing webhooks | sebastianekstrom | — |
| feat(checkout): enforce embed hosts through frame-ancestors | maximevast | AI |
| feat(scripts): audit command for the member model migration | maximevast | AI |
| feat(organization): gate frame-ancestors enforcement behind… | maximevast | AI |
| CLI: Backend support for triggering webhook events | sebastianekstrom | AI |
Methodology
Metrics are computed from merged pull request data synced daily from GitHub. AI-related metrics are directional signals inferred from pull request activity patterns and heuristics. Summary metrics use a 30-day rolling window; trends use a 90-day window. Last updated 2 hours, 3 minutes ago.
Updated daily from public GitHub pull requests.
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