[throwbadubadu]

4 and full agree and still confusedly wondering.. I know I will be shouted down, but what are all you "tech guys" doing in your daily biz, just glueing hyperdocumented boilerplate together and spitting out the same textbook examples, I don't get it.

[lm28469]

That's my impression too, for every engineer with master or more you have 10 developers who just got out of a 3 weeks Javascript boot camp

Of course they think Chatgpt is a revolution and will replace developers, that's because they don't see the bigger picture.

If you work on anything remotely hard you already know coding is like 10% of the job and out of this only 10% is trivial and this is the only part got will get right

[polalavik]

straight up don't understand the dialogue around chatGPT replacing tech jobs lmao.

Ok can chatgpt understand the super ambiguous requirement demanded by the customer, translate it into something meaningful to implement, anticipate what the customer actually wants (or will need in the future) and make sure the implementation meets that nuanced complexity? doubt it.

are you all writing hello world for a living?

[PeterisP]

Parts of our job that require skill and parts of our job that require time are not the same.

"understand the super ambiguous requirement demanded by the customer, translate it into something meaningful to implement, anticipate what the customer actually wants (or will need in the future) and make sure the implementation meets that nuanced complexity" takes skill, but that is NOT what takes up most of the workday, implementation does - and if a tool saves some meaningful time on the implementation part, then the same project can be done in the same time with less people, i.e. replacing some jobs.

[throwbadubadu]

> 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..

[876978095789789]

I simply asked whether they were using 3 or 4. I don't have access to 4 yet.

[waboremo]

Yes that's exactly what I do, except they're not really all that well documented.

What are you doing in your daily biz? Could you provide some specific examples I'd like to see how chatgpt reacts to them.