> I don't get how AI fits in here. Software already had massive scale. You aren't replacing a massive data entry team with AI, you're replacing a reliable piece

> I don't get how AI fits in here. Software already had massive scale. You aren't replacing a massive data entry team with AI, you're replacing a reliable piece of software written by a human with a reliable (?) piece of software written by AI controlled by a human. There's no increase in scale. Until the reliability issues are fixed a very noticeable decrease in reliability (sure, some software was bad already, but now the good developers are also writing bad code). > This doesn't seem like a natural step to me at all. The best explanation I can come up with is AI is just being used as an excuse for destructive penny pinching. I think a big part of the explanation is business leaders aren't actually as smart or thoughtful as they're made out to be. They may have an inaccurate and unrealistic view of LLMs, and making policy and decisions based on that view. Also business leaders and management are often extremely tolerate and even seem to encourage bad code. The code is a black box that they usually don't even have to use, bugginess and unreliability are often hard to quantify and can be swept under the run. "Saving" $5,000 by not fixing a bug could over time lead to say $10,000 in unquantified costs, but it looks like the "smart" decision on a budget spreadsheet. They only really pay attention once quality is disaster level, or there's some unusually high-profile problem.