OpenAI Reveals: Codex Users Open 70% More PRs — Productivity or Illusion?
Sherwin Wu, who leads engineering for OpenAI’s API platform, just shared a striking number: engineers at OpenAI who lean heavily on Codex open an average of 70% more pull requests than colleagues who don’t — and the gap keeps widening.
But is this really “productivity”?
Measuring the Unmeasurable
Measuring engineering productivity was already hard before AI. With AI, it’s approaching impossible. PR count up 70% — but are those quality PRs or “looks about right” PRs? Who reviews them? Does merge rate increase correspondingly?
u/OfficialLeadDev on Reddit noted: “Measuring engineering productivity has never been straightforward, and AI has made it harder.”
The Real Questions
OpenAI’s 70% figure raises three deeper questions:
- Quality vs. quantity: More PRs doesn’t mean better code. Someone has to review all those PRs — which may be the burnout engine already spreading through the industry
- The skills gap: Are junior devs using AI actually learning, or just copy-pasting more intelligently?
- The future of code review: When 70% of code is AI-generated, is human review still the right model?
Industry Perspectives
Engineering leaders are splitting into two camps:
- Optimists: “This is the biggest productivity boost since the Internet. Measure outcomes, not output.”
- Pragmatists: “We’re trading quality for speed, and the bill comes due in 6-12 months when technical debt compounds.”
Bottom Line
70% more PRs is an impressive headline — but it raises more questions than it answers. As AI becomes inseparable from the development workflow, the industry needs new metrics: not “how many lines” or “how many PRs,” but “how many problems solved” and “how many users satisfied.”
Sources: LeadDev, Reddit r/artificial, OpenAI