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openai-python — Engineering Performance

1 engineers all time · Jan 2025 – Dec 2025 · built 2026-09-08 · GitHub

Performance snapshot

Today's rolling 90-day reading for openai-python, compared with the start of the series. Pick a window to move that comparison point.

Avg. perf / dev / mo

−100.0%

0.14 → 0.00 ETV

Active engineers

−100.0%

1.0 → 0.0

Features

−7.3pp

7.3% → 0.0%

Performance Composition

Each month's output split by type of work: Features (new value), Maintenance (sustaining systems), Tests, Docs, and Fixes (rework). The yellow line is output per engineer, so when it rises each engineer is delivering more, whatever the team size did. Unit: Engineering Throughput Value (ETV).

Engineering capacity

Effective engineers behind openai-python, against its pre-AI baseline. Each subject has its own: openai-python's is 0.86 ETV / dev / mo, its first reading in April 2025. Per-engineer ETV divided by that gives a capacity multiple, and that multiple applied to the engineers active in the trailing 90 days turns it into engineer-equivalents. The line is the real headcount, so the gap between line and area is what the leverage is worth. Because each baseline is its own, every subject opens at 1.0x on its first day: multiples measure improvement and are not comparable between subjects.

Knowledge concentration

How dependent is this repo on a small number of engineers? Higher top-1 share = higher key-person risk.

Top 1
100.0 %
Top 3
100.0 %
Top 5
100.0 %

Robert Craigie owns 100.0 % of commits.

Behind the numbers

Written summary of the work completed each month.

No monthly reports available yet.