A new benchmark comes out, it's designed so nothing does well at it, the models max it out, and the cycle repeats. This could either describe massive growth of LLM coding abilities or a disconnect between what the new benchmarks are measuring & why new models are scoring well after enough time. In the former assumption there is no limit to the growth of scores... but there is also not very much actual growth (if any at all). In the latter the growth matches, but the reality of using the tools does not seem to say they've actually gotten >10x better at writing code for me in the last year.

Whether an individual human could do well across all tasks in a benchmark is probably not the right question to be asking a benchmark to measure. It's quite easy to construct benchmark tasks a human can't do well in that you don't even need AI to do better.