AI regularly hallucinates API endpoints that don't exist, functions that aren't part of that language, libraries that don't exist. There's no fucking way it did any of this bullshit. Like, yeah - it can probably do a mean autocomplete, but this is being pushed so hard because they want to drive wages down even harder. They want know-nothing middle-managers to point to this article and say "I can replace you with AI, get to work!"...that's the only purpose of this crap.

Thank you for writing this so I only have to ~~upvore~~ upvote you.

Edit: What the difference between one key can be

But they could replace CEOs from what I can tell.

So what you're saying is that 86.66% of the time, it works every time.

80% accuracy, that is trash

More than 80% of most codebases is boilerplate stuff: including the right files for dependencies, declaring functions with the right number of parameters using the right syntax, handling basic easily anticipated errors, etc. Sometimes there's even more boilerplate, like when you're iterating over a list, or waiting for input and handling it.

The rest of the stuff is why programming is a highly paid job. Even a junior developer is going to be much better than an LLM at this stuff because at least they understand it's hard, and at least often know when they should ask for help because they're in over their heads. An LLM will "confidently" just spew out plausible bullshit and declare the job done.

Because an LLM won't ask for help, won't ask for clarifications, and can't understand that it might have made a mistake, you're going to need your highly paid programmers to go in and figure out what the LLM did and why it's wrong.

Even perfecting self-driving is going to be easier than a truly complex software engineering project. At least with self-driving, the constraints are going to be limited because you're dealing with the real world. The job is also always the same -- navigate from A to B. In the software world you're only limited by the limits of math, and math isn't very limiting.

I have no doubt that LLMs and generative AI will change the job of being a software engineer / programmer. But, fundamentally programming comes down to actually understanding the problem, and while LLMs can pretend they understand things, they're really just like well-trained parrots who know what sounds to make in specific situations, but with no actual understanding behind it.

But did you hear that it uses more water than regular data centers?

LLMs are not capable of this kind of meaningful collaboration

Which is why they're a tool for professionals to amplify their workload, not a replacement for them.