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title: Can We Trust AI to Code Without Human Oversight? | daily.dev
description: Sam Newman examines whether human code review still makes sense when code is increasingly written and reviewed by AI. Citing Faros&#x27;s whiplash report, he notes...
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og:title: Can We Trust AI to Code Without Human Oversight? | daily.dev
og:description: Sam Newman examines whether human code review still makes sense when code is increasingly written and reviewed by AI. Citing Faros&#x27;s whiplash report, he notes...
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# Can We Trust AI to Code Without Human Oversight?

**[Continuous Delivery](https://daily.dev/sources/continuousdelivery)** · 12 min read · 0 upvotes · 0 comments

## Summary

Sam Newman examines whether human code review still makes sense when code is increasingly written and reviewed by AI. Citing Faros's whiplash report, he notes PR sizes are up over 50% and work-in-progress up 64% among high AI-adoption teams, yet throughput is falling, suggesting code review has become the new bottleneck. He revisits the traditional goals of code review (correctness, shared learning, strategic alignment, awareness) and argues most no longer hold up well in an AI-authored-code world. He highlights Chainguard's decision to drop human code review in favor of investing more in upfront design collaboration, likening this to 'dark factories' in industrial automation, and frames the decision as ultimately a matter of trust in one's AI workflow.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=6deDU-JeRuI>

## Questions this post answers

### Why did Chainguard stop doing human code review on AI-generated code?

Chainguard, a supply chain security firm, moved away from human code review and redirected that effort into upfront collaboration on design decisions and documentation. The idea is that design documents produced through team discussion then drive AI code generation directly, rather than the team spending time inspecting the AI's output afterward.

_Teams weighing whether to drop code review for AI-generated code can track how peers approach this shift on daily.dev._

### How much did average pull request size grow due to AI coding tool adoption according to the Faros AI whiplash report?

Faros's acceleration whiplash report from March found over a 50% increase in the average size of pull requests among teams with high AI tool adoption compared to the previous year. The same report showed a 64% increase in the number of PRs a developer has to touch daily, and a 225% increase in time tasks spend in progress.

_Developers tracking AI's real impact on PR volume and review load can follow ongoing coverage on daily.dev._

### Does using AI coding assistants actually reduce developer workload and stress?

No, early evidence suggests AI coding tools are increasing pressure and stress on developers rather than reducing it. A Harvard Business Review piece titled 'AI doesn't reduce work, it intensifies it' found workers report doing more at once and feeling more pressure than before adopting AI, even though the tools were expected to save time and ease workload.

_Engineers assessing whether AI tooling is helping or hurting their workload can dig deeper into these debates on daily.dev._

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#productivity](https://daily.dev/tags/productivity), [#code-review](https://daily.dev/tags/code-review), [#company-culture](https://daily.dev/tags/company-culture)

[View this post on daily.dev](https://daily.dev/posts/can-we-trust-ai-to-code-without-human-oversight--xlconnqm8)

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