Realtime Engineering Benchmarks
Realtime delivery benchmarks are based on 58 merged pull requests in the last 30 days (691 all-time), with 12.1 hours median cycle time, 1.1 hours median review time, and 10 active contributors. AI-related signals appear on 0.0% of recent work. PR volume is down -36% compared to the prior period.
Repo vs Supabase 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(tests): Wait longer on reconnect test | PragTob | — |
| chore(tests): Increase lenience in rate counter tests | PragTob | — |
| chore: Move flaky digest to notify channel | PragTob | — |
| fix: record Postgres Changes subscribers only after the sub… | hsusul | — |
| feat: add metric for join - sync latency | seangeo | — |
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, 46 minutes ago.
Updated daily from public GitHub pull requests.
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