I have coworkers with varying degrees of proficiency with AI. The ones that are better with it rein it in when it goes haywire. I have less of an issue with this. It still does awkward stuff here and there. The ones that are bad with it just commit the code for review and annoy me. When 60-80% or so of your PR can be refactored away then it’s a crap PR and honestly never should have been one. Don’t make me read through 2000 lines that should have been 400. It’s a waste of time. This mostly is it doing brain dead things like instead of passing a parameter into a method it makes 4 nearly identical methods.
I mostly use AI to implement a solution, not come up with the solution. I don’t care how fast you can type…AI can type faster. That also means I understand what it’s trying to build and how it should be going about it. That does mean you still have to use your brain and not offload your critical thinking to the machine which is what I see a lot of people doing with it.
In that regard I like AI but it’s still a love/hate relationship for sure. It both saves and costs me time just in different ways.
When 60-80% or so of your PR can be refactored away then it’s a crap PR and honestly never should have been one.
So their time savings in getting AI help to write their code means that you spend more of your presumably more expensive time doing reviews and educating them about slop removal instead of some higher-value activity. Sounds like you’re veering into negative ROI for the AI use if that’s true.
Luckily, I don’t review PRs very often, I have people to do that. But the general principle is that the content of a PR is the responsibility of the submitter, regardless of its source. Wrong algorithm? Their fault. No-good UTs? Their fault. Inappropriate or unsafe dependencies? Their fault. Slop? Their fault.
Luckily, with the work we do, there’s often nothing someone could train an LLM on, so we don’t see all that many PRs with AI-generated content, unless we’re using some well-known commodity library or framework in a common way. And that was always the easy stuff anyway.
A slop PR should be the submitter’s responsibility, but if they’re trying to push out unreviewed slop, you know they’re just going to ask an LLM to refactor it instead of looking at it themselves. The best response is just to reject it outright and have someone else work on a new solution.
I have had a fair amount of success getting AI to do those refactorings, reducing 2000 lines of code to 400, and generating 3000 lines of documentation (including flowcharts) explaining how the 400 lines work, adding 1200 lines of automated testing to prevent regressions, etc. etc.
I have coworkers with varying degrees of proficiency with AI. The ones that are better with it rein it in when it goes haywire. I have less of an issue with this. It still does awkward stuff here and there. The ones that are bad with it just commit the code for review and annoy me. When 60-80% or so of your PR can be refactored away then it’s a crap PR and honestly never should have been one. Don’t make me read through 2000 lines that should have been 400. It’s a waste of time. This mostly is it doing brain dead things like instead of passing a parameter into a method it makes 4 nearly identical methods.
I mostly use AI to implement a solution, not come up with the solution. I don’t care how fast you can type…AI can type faster. That also means I understand what it’s trying to build and how it should be going about it. That does mean you still have to use your brain and not offload your critical thinking to the machine which is what I see a lot of people doing with it.
In that regard I like AI but it’s still a love/hate relationship for sure. It both saves and costs me time just in different ways.
So their time savings in getting AI help to write their code means that you spend more of your presumably more expensive time doing reviews and educating them about slop removal instead of some higher-value activity. Sounds like you’re veering into negative ROI for the AI use if that’s true.
Luckily, I don’t review PRs very often, I have people to do that. But the general principle is that the content of a PR is the responsibility of the submitter, regardless of its source. Wrong algorithm? Their fault. No-good UTs? Their fault. Inappropriate or unsafe dependencies? Their fault. Slop? Their fault.
Luckily, with the work we do, there’s often nothing someone could train an LLM on, so we don’t see all that many PRs with AI-generated content, unless we’re using some well-known commodity library or framework in a common way. And that was always the easy stuff anyway.
A slop PR should be the submitter’s responsibility, but if they’re trying to push out unreviewed slop, you know they’re just going to ask an LLM to refactor it instead of looking at it themselves. The best response is just to reject it outright and have someone else work on a new solution.
I have had a fair amount of success getting AI to do those refactorings, reducing 2000 lines of code to 400, and generating 3000 lines of documentation (including flowcharts) explaining how the 400 lines work, adding 1200 lines of automated testing to prevent regressions, etc. etc.