PostHog Python Engineering Benchmarks
PostHog Python delivery benchmarks are based on 24 merged pull requests in the last 30 days (187 all-time), with 22.6 hours median cycle time, 0.5 hours median review time, and 13 active contributors. AI-related signals appear on 20.8% of recent work. PR volume is down -45% 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.
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 |
|---|---|---|
| fix(aio): never drop or leak multimodal content in ai captu… | carlos-marchal-ph | AI |
| feat(mcp): stateless and multi-pod server support | gesh | AI |
| feat(aio): dedicated AI capture lane and multimodal passthr… | carlos-marchal-ph | AI |
| feat(metrics): support metrics config via module-level sett… | DanielVisca | — |
| fix(metrics): harden attribute snapshots, retry backoff, an… | DanielVisca | — |
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 25 minutes ago.
Updated daily from public GitHub pull requests.
See Your Team's Benchmarks