Comment by jrumbut

Well the essence of software engineering is taking this complex real world tasks and breaking them down into simpler parts until they can be done by simple (conceptually) digital circuits.

So it's not surprising that eventually autocomplete can reach up from those circuits and take on some tasks that have already been made simple enough.

I think what's so interesting is how uneven that reach is. Some tasks it is better than at least 90% of devs and maybe even superhuman (which, in this case, I mean better than any single human. I've never seen an LLM do something that a small team couldn't do better if given a reasonable amount of time). Other cases actual old school autocomplete might do a better job, the extra capabilities added up to negative value and its presence was a distraction.

Sometimes there is an obvious reason why (solving a problem with lots of example solution online vs working with poorly documented proprietary technologies), but other times there isn't. They certainly have raised the floor somewhat, but the peaks and valleys remain enormous which is interesting.

To me that implies there is both lots of untapped potential and challenges the LLM developers have not even begun to face.