The evidence suggests GenAI coding assistants offer tiny gains – real productivity lies elsewhere

GenAI coding assistants increase individual developer productivity by just 0.7% to 2.7%

How have I determined that? The best studies I’ve found on GenAI coding assistants suggest they improve coding productivity by around 5-10%.1see the following studies all published in 2024: The Impact of Generative AI on Software Developer Performance, DORA 2024 Report and The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers

However, also according to the best research I could find, developers spend only 1-2 hours a day on coding activity (reading/writing/reviewing code).2see Today was a Good Day: The Daily Life of Software Developers, Global Code Time Report 2022 by Software

In a 7.5-hour workday, that translates to an overall productivity gain of just 0.7% to 2.7%.

But even these figure aren’t particularly meaningful – most coding assistant studies rely on poor proxy metrics like PRs, commits, and merge requests. The ones including more meaningful metrics, such as code quality or overall delivery show the smallest, or even negative gains.

And as I regularly say typing isn’t the bottleneck anyway. The much bigger factors in developer productivity are things like:

  • being clear on priorities
  • understanding requirements
  • collaborating well with others
  • being able to ship frequently and reliably.

GenAI might slightly speed up coding activity, but that’s not where the biggest inefficiencies lie.

If you want to improve developer productivity, focus on what will actually make the most difference

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