Comment by JohnBooty

    But let’s not forget the METR study that 
    found a 20% increase in self-reported productivity 
    but a 19% decrease in actual measured productivity.

Counting "time per PR" is as useless as counting lines of code.

An industry I think we spend ~10% of our time writing code and ~90% of our time maintaining it and building upon it.

The real metric is not "how long did that PR take" but "how much additional work will this PR create or save in the long run." -- ie did this create tech debt? Or did it actually save us a bunch of effort in the long run?

My experience with ChatGPT these last few years is that if used "conscientiously" it allows me to ship much higher quality code because it has been very good at finding edge cases and suggesting optimizations. I am quite certain that when viewed over the long haul it has been at least a 2X productivity gain, possibly even much more, because all those edge cases and perf issues it solved for me in the initial PR represent many hours of work that will never have to be performed in the future.

It is of course possible to use AI coding assistants in other ways, producing AI slop that passes tests but is poorly structured and understood.