AI agents are great at writing new code but then the human bottleneck slows everything down

Date:
Mon, 12 Oct 2026 15:20:00 +0000

Description:
While AI has boosted the amount of code we can now produce, it needs substantially more reviewing.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Lines of code, code commits and pull requests are all up 20-30% Comments per pull request are up 49% as human review becomes more crucial With reviewing up from 7 to 10 days on average, the new bottleneck is code review A new Harvard University research paper has confirmed that AI is indeed excellent at boosting coding productivity, but humans just end up slowing the process back down anyway.

Authors Fiona Chen and James Stratton found a 30% increase in the amount of code developers can produce when using AI, but they found no statistically significant improvement in completed software. With increases across lines of code produced (+30%), code commits (+20%) and pull requests (+23%), the Harvard-backed researchers went on to investigate why we're not seeing a 20-30% increase in end product. Latest Videos From TechRadar Watch full video here: AI has definitely sped up coding, but human delays negate much of those benefits At the same time, the researchers also found increases across the time taken to review and merge pull requests (+49%), the number of reviewer comments per pull request (+35%) and even the proportion of employees doing code reviews (+14%), all of which implying that vibe coding is ultimately shifting the bottleneck further down the road instead of removing it altogether.

The paper also questions whether, with AI shifting the workload, companies
are responding by allocating more workers to code review. Layoffs have become somewhat synonymous with AI founded or not and concerns about jobs
continue, however the paper proves that human workers are still vital, just
in other parts of the coding process. You may like Humans in the loop: how software teams are learning to trust AI The visibility gap that's smuggling risk into AI code The rise of comprehension debt in the age of AI coding

Some thought it also given to the next stages of AI adoption, and whether it can help downstream in the code review stages. While AI is already being employed to some degrees in this part, "humans are still heavily involved
with review."

There's also the consideration of added workload, with AI now capable of producing code much more quickly than humans ever could. The average review process has gone from taking 7.03 days to 10.48 days as a result of this shifted bottleneck. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners
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The researchers also argue that AI-generated code needs substantially more corrections, begging the question whether it's actually helping at all.

Still, with AI adoption not resulting in any significant job losses, it
seems, it's more a question about how companies can best use AI to support employees and reduce unnecessary workload, rather than how they can replace workers outright.

"The productivity gains are absorbed by downstream constraints in the production process," the paper concludes, adding that "code review becomes
the bottleneck." Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.



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