It’s genuinely depressing you’re so creatively stifled that you haven’t encountered a task that meets those conditions yourself and instead have to retreat to these middleschool-tier insults, but hey, if you’re gonna throw down a mitten in challenge, who am I to refuse?
Novel reporting across diverse data systems! That’s not even a mid developer task, that’s intern shit - and good luck getting an agent to deal with that one lmao.
The more i use it the clearer it becomes it can do much more than a human. One of my hobbies are electronics and embedded development. The llm designed the circuit and even the firmware in 5-6 prompts, that took me a week on a similar project. With clean requirements and scope it may do almost any task, it may struggle on huge projects and monoliths but looking back to each improved model i can guess that won’t take a long time to accomplish either. In less than 2 years we went from buggy gpt 3 to multi agents workflow that work almost autonomously.
That you’ve gone from “I bet you can’t name even one thing AI can’t do”, to being told something it can’t do, and now immediately you’re ignoring that interaction in favor of telling anecdotes about how great AI is? That says a great deal about your conviction to your own arguments.
I already replied that it may accomplish too, haven’t used it in such projects so I won’t claim any certainty.
Let’s say it couldn’t accomplish the specific task you mentioned (best scenario), how is the field safe ? Are we going to focus on that scope for our careers ? What if a future model manages to accomplish that too ? You focus on the tree and miss the forest.
Hey, that’s nice! you’re actually trying to engage, although you’re slightly undermining it with the whole “best scenario” casting my example as somehow doubtful instead of the more accurate “something we regularly test”… But that’s nitpicking I suppose. To answer your question with an example: Data management has proven pretty resilient to AI - we do use it, it’s a great way to fill out boilerplate code, but AI currently fundamentally lacks the ability to manage large complex architecture or databases, adhoc reporting or even middling novel applications (and holy shit it’s bad at dynamic SQL).
From your description of your job you’re not doing anything (and I swear this isn’t a value judgement on you personally) particularly interesting - and IDK if you’re devops or webdev or appdev or what (not that those are inherently boring (okay devops a little ( <3 ))) - but there are segments of software development that have been largely “solved problems” for many years; the humans mostly manage and direct tools, and are kept around to solve the interesting and challenging problems. Within those segments, AI has been extremely effective at integrating into, and with some caveats about how much it screws up in devops accelerating, workflows, in an ideal world freeing up the humans to focus even more of their time on the interesting problems (in practice this has led people to think they can lay off their devops team, with disaster not far behind).
In the rest, AI truly is not at the point it can live up to it’s promises, and the cost in tokens trying to integrate it is often astronomical. From how you approach this, I get the impression that you don’t have much experience outside your segment or role - it’s worth not being quite so pig-headed about this when Lemmy, which hosts a population of users heavy with non-mainstream disciplines, shares their own anecdotal experience about this subject; It’s not nearly as cut-and-dry as the massive propaganda engines would have you believe.
It’s genuinely depressing you’re so creatively stifled that you haven’t encountered a task that meets those conditions yourself and instead have to retreat to these middleschool-tier insults, but hey, if you’re gonna throw down a mitten in challenge, who am I to refuse?
Novel reporting across diverse data systems! That’s not even a mid developer task, that’s intern shit - and good luck getting an agent to deal with that one lmao.
The more i use it the clearer it becomes it can do much more than a human. One of my hobbies are electronics and embedded development. The llm designed the circuit and even the firmware in 5-6 prompts, that took me a week on a similar project. With clean requirements and scope it may do almost any task, it may struggle on huge projects and monoliths but looking back to each improved model i can guess that won’t take a long time to accomplish either. In less than 2 years we went from buggy gpt 3 to multi agents workflow that work almost autonomously.
That you’ve gone from “I bet you can’t name even one thing AI can’t do”, to being told something it can’t do, and now immediately you’re ignoring that interaction in favor of telling anecdotes about how great AI is? That says a great deal about your conviction to your own arguments.
I already replied that it may accomplish too, haven’t used it in such projects so I won’t claim any certainty. Let’s say it couldn’t accomplish the specific task you mentioned (best scenario), how is the field safe ? Are we going to focus on that scope for our careers ? What if a future model manages to accomplish that too ? You focus on the tree and miss the forest.
Hey, that’s nice! you’re actually trying to engage, although you’re slightly undermining it with the whole “best scenario” casting my example as somehow doubtful instead of the more accurate “something we regularly test”… But that’s nitpicking I suppose. To answer your question with an example: Data management has proven pretty resilient to AI - we do use it, it’s a great way to fill out boilerplate code, but AI currently fundamentally lacks the ability to manage large complex architecture or databases, adhoc reporting or even middling novel applications (and holy shit it’s bad at dynamic SQL).
From your description of your job you’re not doing anything (and I swear this isn’t a value judgement on you personally) particularly interesting - and IDK if you’re devops or webdev or appdev or what (not that those are inherently boring (okay devops a little ( <3 ))) - but there are segments of software development that have been largely “solved problems” for many years; the humans mostly manage and direct tools, and are kept around to solve the interesting and challenging problems. Within those segments, AI has been extremely effective at integrating into, and with some caveats about how much it screws up in devops accelerating, workflows, in an ideal world freeing up the humans to focus even more of their time on the interesting problems (in practice this has led people to think they can lay off their devops team, with disaster not far behind).
In the rest, AI truly is not at the point it can live up to it’s promises, and the cost in tokens trying to integrate it is often astronomical. From how you approach this, I get the impression that you don’t have much experience outside your segment or role - it’s worth not being quite so pig-headed about this when Lemmy, which hosts a population of users heavy with non-mainstream disciplines, shares their own anecdotal experience about this subject; It’s not nearly as cut-and-dry as the massive propaganda engines would have you believe.