Rory Sutherland calls this the "doorman fallacy".<p>We look at a doorman and might naively think their function is to open doors so if we can replace their function, we can replace the person. Then we build an automation, fire the doorman and subsequently discover the doorman was responsible for a multitude of social tasks, like taking in the mail, co-ordinating services, providing small tasks for the residents etc. and that physically opening and closing doors was actually the least important part of their job.<p>Similarly, we think the purpose of code review must obviously be for reviewing code until we look deeper and understand the sociological purposes of code review.<p>Technologists have a bad habit of entering into a field they don't know, observing but not talking to any of the people they're trying to automate and assuming only the most legible parts of anyone's job are important to grok. It's important to understand that the value any job or function brings can often be totally opaque to an outsider and it requires actually talking to people and understanding total value chains to fully understand where technology can be used to improve things.
We use AI code review and it is genuinely helpful, but I agree it's mostly just making my life easier to review my own PR by pointing out salient points I would otherwise not really think about.<p>This obviously is not a replacement for another human looking at your code, and I would not do it in safety critical environments, but it really helps especially in small teams where time is precious and you ship fast.<p>My only issue is that I would love a dedicated UI where I get this review BEFORE another human looks at the code, so their feedback is not drowned by the AI noise
Interestingly, the bar for machine accuracy is often much higher than for humans for us to be willing to adopt its autonomy (baseball ABS systems or self-driving cars come to mind as examples).<p>I can imagine a future where even if an AI code reviewer that autonomously reviewed code resulted in a noticeable drop in some meaningful metrics, like DORA's MTTR or Deployment Frequency, an organization would flip out the very first time the AI made a mistake, even if a human reviewer would have resulted in 10x as many impactful errors.
I used AI code review tools but agree It would never replace human IMO.<p>Here is why because of 2 golden rules of Code Reviews in tech why AI can't understand or trained on:<p>- AI can't see always and remember it’s a human being on the other end of the code and review.
- AI could be brutal and will miss the good intent like a senior member who is helping the junior.<p>It goes without saying that the key benefit of doing code reviews is to make the code better and fix issues.
This well-thought article restricts the notion of code review to pull request assessment - diff file - on an existing code base, perhaps a mostly human-written legacy code base.<p>As a Java code generation researcher, I would appreciate any constructive comments regarding the automated code review of automated changes made to an entirely generated code base, whose live specifications and requirements have been modified in order to generate the code being reviewed.
AI won't replace humans at the moment, but it does make humans more productive. I've personally increased my productivity by many % after integrating AI into my workflow.