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> that is NOT what takes up most of the workday, implementation does - and if a tool saves some meaningful time on the implementation part Sorry no, completely untrue here, its about debugging and inter system complexity and getting stuff like debug artifacts together, using various tools, debugger, sniffers here, trace analyzers there, having clue and figuring out the bug, and then fixing it, but please not the surface quick fix, but understanding the root cause (though ChatGPT couldn't even do the first thing well even if guided to most of these I guess, unless trained on multiple 100k to million loc code bases, which would not happen for other reasons)... Pure implementation is the easy part (even if actually hard) and not taking up the workday, I'd wished it would more often.. It can help on those fun tasks like doing a visualization of some data for these things sometimes.. but there it is 50% great, other 50% I would have better used google skills and directly headed to docs or Stackoverflow where I can judge answers better, or transfer them to my problem more easy. I personally doubt even ChatGPT10 will be able to do all these various tasks and reason between them...and even if, how much computing power should be there for how many tech people world-wide? I wonder I never read about scaling and limits.. |