AI is Writing More Of Our Code Than Ever So Why is Code Review Suddenly Breaking Down?

📰 Dev.to · Dhruv Joshi

AI-generated code is increasing, but code review processes are struggling to keep up, highlighting the need for adapted review strategies

intermediate Published 21 Apr 2026
Action Steps
  1. Assess your current code review process to identify bottlenecks and areas for improvement
  2. Implement automated code review tools to help detect errors and inconsistencies in AI-generated code
  3. Develop guidelines for reviewing AI-generated code, including criteria for acceptance and rejection
  4. Train your team on how to effectively review AI-generated code, focusing on understanding the code's intent and functionality
  5. Integrate AI-generated code review into your existing CI/CD pipeline to streamline the process
Who Needs to Know This

Developers, DevOps teams, and engineering managers can benefit from understanding the challenges of reviewing AI-generated code and adapting their review processes accordingly

Key Insight

💡 AI-generated code requires a different review approach, focusing on intent and functionality rather than traditional line-by-line review

Share This
🚨 AI-generated code is on the rise, but code review is breaking down! 🚨 Time to adapt your review strategies and tools to keep up with the change
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