They’re not saying “AI can replace some menial white collar tasks”, they’re saying AI can replace all white-collar work.

Yes, if you fuck up some white collar work, people will die. It’s irresponsible.

So AI systems are not reliable enough to power fully autonomous weapons but they are reliable enough to end all white-collar work in the next 12 months?

Odd.

I'll bite, because it does seem like something that should be quick in a well-architected codebase. What was the situation? Was there something in this codebase that was especially suited to AI-development? Large amounts of duplication perhaps?

The key part of my comment is "correctly".

Does it write maintainable code? Does it write extensible code? Does it write secure code? Does it write performant code?

My experience has been it failing most of these. The code might "work", but it's not good for anything more than trivial, well defined functions (that probably appeared in it's training data written by humans). LLMs have a fundamental lack of understanding of what they're doing, and it's obvious when you look at the finer points of the outcomes.

That said, I'm sure you could write detailed enough specs and provide enough examples to resolve these issues, but that's the point of my original comment - if you're just writing specs instead of code you're not gaining anything.

I want to be clear, I'm not against any use of AI. It's hugely useful to save a couple of minutes of "write this specific function to do this specific thing that I could write and know exactly what it would look like". That's a great use, and I use it all the time! It's better autocomplete. Anything beyond that is pushing it - at the moment! We'll see, but spending all day writing specs and double-checking AI output is not more productive than just writing correct code yourself the first time, even if you're AI-autocompleting some of it.