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title: AI broke code review. What about knowledge sharing?
description: AI-generated code has made traditional line-by-line code review impractical, since engineers can't carefully read the volume of diffs produced. Beyond...
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# AI broke code review. What about knowledge sharing?

**[The New Stack](https://daily.dev/sources/newstack)** · 6 min read · 0 upvotes · 0 comments

## Summary

AI-generated code has made traditional line-by-line code review impractical, since engineers can't carefully read the volume of diffs produced. Beyond bug-catching, review historically served a knowledge-sharing role, letting juniors learn from seniors and teams build shared mental models. Drawing on conversations with Vanitha Kumar (ThoughtWorks) and Margaret-Anne Storey, the piece introduces 'cognitive debt' - the erosion of shared understanding when AI writes code that nobody fully grasps. The proposed fix is 'intent-driven verification': capturing acceptance criteria, constraints, and architectural decisions before code is submitted, so reviewers evaluate intent rather than implementation. Aviator's Verify product is presented as a tool implementing this approach.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenewstack.io/ai-code-review-cognitive-debt>

## Questions this post answers

### What is cognitive debt in software engineering teams using AI-generated code?

Cognitive debt is a term coined by researcher Margaret-Anne Storey describing what happens when a team stops understanding the system it is building because AI generates most of the code. Unlike technical debt, which lives in the code itself, cognitive debt lives in people: it builds up silently, has no dashboard to detect it, and shows up when teams can no longer explain why features exist or make changes confidently.

_daily.dev surfaces practical takes on avoiding cognitive debt for teams scaling AI-assisted coding._

### What is intent-driven verification in code review?

Intent-driven verification is a code review approach where engineers capture the architectural decisions, tradeoffs, and scope calls made during a coding session with an AI agent, writing them as acceptance criteria before submitting the change. Reviewers then evaluate whether the right problem was solved with the right constraints, rather than reading every line of a diff, which Aviator's Verify tool is built to support.

_Developers rethinking code review workflows around AI can track approaches like this on daily.dev._

## Similar posts on daily.dev

- [AI Code Review Best Practices](https://daily.dev/posts/ai-code-review-best-practices-ii7hbaa3j) · Aviator Blog · 15 upvotes · 1 comments
- [How long before we stop reading the code?](https://daily.dev/posts/how-long-before-we-stop-reading-the-code--omchyubsd) · The New Stack · 1 upvotes · 0 comments
- [Code Review Has Changed. The Contract Needs to Change Too.](https://daily.dev/posts/code-review-has-changed-the-contract-needs-to-change-too--9t5wi90oo) · Kilo Blog · 1 upvotes · 0 comments

---

Tags: [#ai-coding](https://daily.dev/tags/ai-coding), [#code-review](https://daily.dev/tags/code-review), [#technical-debt](https://daily.dev/tags/technical-debt)

[View this post on daily.dev](https://daily.dev/posts/ai-broke-code-review-what-about-knowledge-sharing--hwpkhvgqt)

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