AI didn’t remove the bottleneck, it just moved it from writing code to reviewing, validating, integrating, and deciding what actually deserves to ship.
We’re seeing much higher PR volume from AI-generated code, but review time hasn’t improved, so PR review has become the main bottleneck instead of coding.
I have a few strategies - which are all based on reciprocation.
If the code is reasonable and diligently created, be it with AI or not, I will provide a diligent and timely review.
If the code is totally unreadable AI slop that does not appear to have been read by the person who created the PR, I will use AI to review the code and share the output, without reading it.
If the code is of middling quality, I will find one or two token areas that could use improvement, and suggest a better alternative like "How about doing this with 2 syscalls instead of 4?" or "How about refactoring this duplicated code into a method, and calling the method?", or whatever. If the person responds intelligently, I will proceed to review the rest of the code and work together. If the person responds by sharing their AI's justification, I will politely disengage.
Occasionally, I will share remarks like "I'm noticing a lot of churn here - if this is a bugfix/patch for a prod issue, I'd expect to see a PR with the smallest delta that fixes the problem" or "I'm not clear on whether this approach is optimized for runtime efficiency, maintainability, resilience, or something else - could you share the outcome you're looking to achieve with this change?".
AI didn’t remove the bottleneck, it just moved it from writing code to reviewing, validating, integrating, and deciding what actually deserves to ship.
We’re seeing much higher PR volume from AI-generated code, but review time hasn’t improved, so PR review has become the main bottleneck instead of coding.
What are the strategies your team is doing to cope with it?
I have a few strategies - which are all based on reciprocation.
If the code is reasonable and diligently created, be it with AI or not, I will provide a diligent and timely review.
If the code is totally unreadable AI slop that does not appear to have been read by the person who created the PR, I will use AI to review the code and share the output, without reading it.
If the code is of middling quality, I will find one or two token areas that could use improvement, and suggest a better alternative like "How about doing this with 2 syscalls instead of 4?" or "How about refactoring this duplicated code into a method, and calling the method?", or whatever. If the person responds intelligently, I will proceed to review the rest of the code and work together. If the person responds by sharing their AI's justification, I will politely disengage.
Occasionally, I will share remarks like "I'm noticing a lot of churn here - if this is a bugfix/patch for a prod issue, I'd expect to see a PR with the smallest delta that fixes the problem" or "I'm not clear on whether this approach is optimized for runtime efficiency, maintainability, resilience, or something else - could you share the outcome you're looking to achieve with this change?".
Thanks for sharing. It’s smart to filter or prioritize it diligently or sometimes even turn it away
Skipping most reviews and waiting for disasters to happen.
Cut by half AI usage. Works wonders. Focus on the good stuff, ignore the rest
Can you expand on what strategy did you use? How are you deciding what to ignore?