idk what you’re talking about because i’m an amateur, i’ve never pushed anything to prod. sounds like AI slop is especially bad when you write code for a living, but me…idk i just dick around on my computer all day so it’s like the wild west over here, lmaooooo (i can’t work because i had a TBI)
yes, that’s exactly the point of everything I’ve said:
to an inexperienced user/developer/admin the output LLMs produce look perfectly valid, and for relatively trivial tasks they might even work out…but when it gets more specialized it fails spectacularly and it gets extremely obvious just how limited of a system it really is.
which is why there is so much pushback from professionals. actually that’s pretty much all professionals, not just in IT.
well i got a bacon number app with django and a .db that was like 2 gigs to work and i vibe coded it. i guess that’s the most complicated thing i’ve put together. i mostly use LLMs for instruction, debugging, and (sadly) writing my code for me when i’m too lazy to read the documentation
sure, and that works at small scales and as long as no change is required.
when either of those two change (large projects where interdependent components become inevitable and frequent updates are necessary) it becomes impossible to use AI for basically anything.
any change you make then has to be carefully considered and weighed against it’s consequences, which AIs can’t do, because they can’t absorb the context of the entire project.
look, I’m not saying you can’t use AI, or that AI is entirely useless.
I’m saying that using AI is the same as any other tool; use it deliberately and for the right job at the right time.
the big problem, especially in commercial contexts, is people using AI without realizing these limitations, thinking it’s some magical genie that can everything.
idk what you’re talking about because i’m an amateur, i’ve never pushed anything to prod. sounds like AI slop is especially bad when you write code for a living, but me…idk i just dick around on my computer all day so it’s like the wild west over here, lmaooooo (i can’t work because i had a TBI)
yes, that’s exactly the point of everything I’ve said:
to an inexperienced user/developer/admin the output LLMs produce look perfectly valid, and for relatively trivial tasks they might even work out…but when it gets more specialized it fails spectacularly and it gets extremely obvious just how limited of a system it really is.
which is why there is so much pushback from professionals. actually that’s pretty much all professionals, not just in IT.
well i got a bacon number app with django and a .db that was like 2 gigs to work and i vibe coded it. i guess that’s the most complicated thing i’ve put together. i mostly use LLMs for instruction, debugging, and (sadly) writing my code for me when i’m too lazy to read the documentation
sure, and that works at small scales and as long as no change is required.
when either of those two change (large projects where interdependent components become inevitable and frequent updates are necessary) it becomes impossible to use AI for basically anything.
any change you make then has to be carefully considered and weighed against it’s consequences, which AIs can’t do, because they can’t absorb the context of the entire project.
look, I’m not saying you can’t use AI, or that AI is entirely useless.
I’m saying that using AI is the same as any other tool; use it deliberately and for the right job at the right time.
the big problem, especially in commercial contexts, is people using AI without realizing these limitations, thinking it’s some magical genie that can everything.