Affine Engineering Benchmarks

AFFiNE · GitHub · Updated October 26, 2026

Affine delivery benchmarks are based on 12 merged pull requests in the last 30 days (559 all-time), with 6.1 hours median cycle time, 0.2 hours median review time, and 2 active contributors. AI-related signals appear on 100.0% of recent work. PR volume is down -54% compared to the prior period.

Median Cycle Time
6.1h
PR open to merge
Median Review Time
0.2h
first review to approval
AI-Related Signals
100.0%
directional signal across recent PRs
Best Signal AI Adoption
100%
100% of PRs are AI-assisted
Watch Out Declining Cadence
-54%
PR volume down 54% vs prior period

Repo vs AFFiNE Average

+4.5pp
AI Signals
+2.2h
Cycle Time
+0.0h
Review Time

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

moderate negative
r = -0.59 (12 weeks)

Cycle Time by AI-Related Signals

14.1h
with signals

PR Breakdown

12 with signals / 12 total PRs

Top AI Tools

coderabbit 12
ai_generic 4

PR Type Breakdown

test 7
unknown 4
feature 1

Recent Pull Requests

View PR Explorer
Title Author AI
fix(server): data migration darkskygit AI
chore: bump deps darkskygit AI
fix(server): blob sync timing darkskygit AI
feat(server): handle m4a slice darkskygit AI
feat: bump deps darkskygit 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 21 hours, 29 minutes ago.

Updated daily from public GitHub pull requests.

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