Epoch Finds OpenAI's Codex Engineers Now Ship 4x More Superhuman Workdays
Epoch AI analyzed OpenAI's Codex repo and found 8% of engineer workdays in Q2 2026 exceeded 24 hours of estimated human effort, up from 2% a year ago.
- 4x jump in superhuman workdays: 8% of Codex contributor-days in Q2 2026 exceeded 24 hours of estimated unassisted effort, up from 2% in Q2 2025.
- LLM judge methodology: An ensemble of Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro estimated how long each merged PR would take a human engineer without any AI tools.
- 41 core contributors analyzed across 7,524 merged PRs in OpenAI's public Codex repository from April 2025 to June 2026.
- Upper bound caveat: The metric overstates true productivity gains because engineers choose bigger tasks when AI is available -- a phenomenon METR calls "task substitution."
- METR's framework distinguishes three uplift types (old tasks, new tasks, value) and shows new-task uplift always exceeds true value uplift.
- New measurement approach: Mining public commit histories with LLM judges offers a scalable, always-on alternative to controlled productivity studies.
A new analysis from Epoch AI offers a rare, data-grounded look at a question the industry has been debating in the abstract: how much is AI actually accelerating the engineers who build it? The answer, at least for the team shipping OpenAI's Codex, is: measurably, and growing fast.
The Setup: LLM Judges Rating Pull Requests
Epoch's researchers focused on 41 core contributors to OpenAI's public Codex repository on GitHub. The core question was simple but hard to answer: are these engineers merging more code than a human could physically produce in a day, without AI help?
To answer it, they adapted a methodology originally developed by METR. For each merged pull request, an ensemble of three frontier models (Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro) was asked to estimate how long a single experienced engineer, working alone and with zero AI tools, would need to reproduce that exact change. The models read the PR title, description, per-file line counts, branch commit messages, and a sampled slice of the diff, then emitted a single time estimate.
The three models agree closely on ordering, with pairwise log-scale correlations of 0.95 to 0.98, but less on scale: on the median PR, the highest of the three estimates is 2.5 times the lowest. To reduce that noise, Epoch takes the per-PR median and groups results into broad buckets: under 6 hours, 6-12 hours, 12-24 hours, 24-48 hours, and 48+ hours.
The Signal: 4x More "Superhuman" Workdays in a Year
In Q2 2026, 8% of contributor-days reflected work estimated at over 24 hours of unassisted effort -- more than a skilled engineer could do in a day, even working around the clock -- up from 2% in Q2 2025. That is a 4x increase in the share of workdays that look physically impossible without AI assistance.