AI coding agents generate more code, but not more software
Study finds coding efficiency gains get "absorbed" by human review "bottleneck.".
Study finds coding efficiency gains get "absorbed" by human review "bottleneck."
The short version
- But coders making use of those tools also know better than to trust the accuracy of that code , meaning substantial effort needs to be spent reviewing any AI-generated output.
- To come to these conclusions, Harvard University researchers Fiona Chen and James Stratton made use of aggregated analytics data from Jellyfish , which measures the granular output of engineering teams.
- That data encompasses 300 million individual “work events” (e.g., commits and pull requests) and issue management software data across more than 700,000 employees at over 700 relevant software development firms from 2021 through March of 2026.
What happened
In response to this change, the researchers found a 14 percent increase in the share of workers performing code reviews after AI agents’ introduction. They also write that they “cannot attribute significant employment changes to AI” after looking at total active workers across Jellyfish and cross-referencing with LinkedIn data at those firms.
Why it matters
While AI could also theoretically help with this review process, the researchers found that, so far, that impact has been marginal.
Summary by Nerd News Network. Read the full article at Ars Technica via the links above and below.