PostHog Python Engineering Benchmarks
PostHog Python delivery benchmarks are based on 34 merged pull requests in the last 30 days (121 all-time), with 3.5 hours median cycle time, 0.3 hours median review time, and 9 active contributors. AI-related signals appear on 2.9% of recent work. PR volume is down -11% compared to the prior period.
Posthog Python merged 9 PRs in the past 30 days with 0% showing AI-related signals. Median cycle time is 13.07 hours.
Repo vs PostHog Analytics Average
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Cycle Time by AI-Related Signals
PR Breakdown
Top AI Tools
PR Type Breakdown
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| chore: add explicit type definitions to consumer arrays and… | mishrak5j | — |
| fix: no-op flag helpers on API errors | marandaneto | — |
| chore: Bump flags-project-board workflow pin to latest | haacked | — |
| chore: configure dependency minimum release age / cooldown | Piccirello | — |
| fix: no-op global client for blank api key | marandaneto | — |
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 17 hours, 31 minutes ago.
Updated daily from public GitHub pull requests.
See Your Team's Benchmarks