Measuring the impact of AI on experienced open-source developer productivity

It is 80/20 again - it gets you 80% of the way in 20% of the time and then you spend 80% of the time to get the rest of the 20% done. And since it always feels like it is almost there, sunk-cost fallacy comes into play as well and you just don't want to give up.

I think an approach that I tried recently is to use it as a friction remover instead of a solution provider. I do the programming but use it to remove pebbles such as that small bit of syntax I forgot, basically to keep up the velocity. However, I don't look at the wholesale code it offers. I think keeping the active thinking cap on results in code I actually understand while avoiding skill atrophy.

well we used to have a sort of inverse pareto where 80% of the work took 80% of the effort and the remaining 20% of the work also took 80% of the effort.

I do think you're onto something with getting pebbles out of the road inasmuch as once I know what I need to do AI coding makes the doing much faster. Just yesterday I was playing around with removing things from a List object using the Java streams API and I kept running into ConcurrentOperationsExceptions, which happen when multiple threads are mutating the list object at the same time because no thread can guarantee it has the latest copy of the list unaltered by other threads. I spent about an hour trying to write a method that deep copies the list, makes the change and then returns the copy and running into all sorts of problems til I asked AI to build me a thread-safe list mutation method and it was like "Sure, this is how I'd do it but also the API you're working with already has a method that just....does this." Cases like this are where AI is supremely useful - intricate but well-defined problems.