
AI coding agents generate more code, but not more software
A recent study by Harvard researchers indicates that while AI coding agents significantly increase the volume of code generated, they do not lead to a corresponding increase in overall software output. The efficiency gains from automated coding are largely absorbed by a bottleneck in the human review process, which becomes longer and more intensive. Consequently, firms using these tools show no significant changes in software feature completion rates or employment levels.
- ▪The introduction of AI coding agents results in a 30 percent increase in total lines of code and a 23 percent rise in pull requests.
- ▪Average code review times increase by 49 percent after AI agents are introduced, with the share of pull requests requiring changes nearly doubling.
- ▪Researchers found no statistically significant change in the resolution rate of software features or overall employment levels at firms using AI tools.
- ▪The study analyzed 300 million work events from over 700,000 employees across more than 700 software development firms between 2021 and March 2026.
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| Original publisher | Ars Technica |
| Canonical URL | https://arstechnica.com/ai/2026/10/ai-coding-agents-generate-more-code-but-not-more-software/ |
| Publication time | Mon, 12 Oct 2026 02:10:20 +0000 |
| Retrieval time | 2026-10-12T02:27:58.524Z |
| Last seen | 2026-10-12T02:27:58.524Z |
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Quantity, not quality AI coding agents generate more code, but not more software Study finds coding efficiency gains get “absorbed” by human review “bottleneck.” Kyle Orland – Oct 9, 2026 3:43 pm | 232 Here, let me just... yeah, can I lend you a hand here? Credit: Getty Images Here, let me just... yeah, can I lend you a hand here? Credit: Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Anyone who has even tangentially associated with computer programming knows that modern AI coding assistants and agents can be incredibly efficient at generating huge amounts of functional code.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ars Technica.