Comment by kstenerud
2 months ago
You're quite right that the quality of the code is all that matters in a PR. My point is more historical.
AI is a very new tool, and as such the quality of the code it produces depends both on the quality of the tool, and how you've wielded it.
I want to be able to track how well I've been using the tool, to see what techniques produce better results, to see if I'm getting better. There's a lot more to AI coding than just the prompts, as we're quickly discovering.
Just curious, what metrics would you use to track how well your results are?
The tools are still in their infancy, but it would likely be a series of metrics such as complexity, repetition, test coverage issues (such as tests that cover nothing meaningful), architectural issues that remain unfixed far beyond the point where it would have been more beneficial to refactor, superfluous instructions and comments, etc.
Yep other people pointed this out as well, this makes sense to me.