I am painfully aware that I learned to write software over four decades ago, when it made sense to try and fit everything into 16K, but I'm really struggling with the attitude that it's a great idea to just throw more hardware at a problem.
LLM is being used, for the most part, as a sophisticated "more hardware", but it's far from the only place we do this.
And as a result, we've managed, as a society, to volunteer ourselves for a different kind of "Vime's boots" scenario, where most of our effort and expense goes into maintaining and patching, rather than clever solutions that make for lasting improvement.
Problems that could have been thought about, and addressed at dev time, or even at compile time, are now repeatedly addressed (and re-addressed, over and over) at run time.
It appears cheaper at launch, and impresses the bosses, but over time, it simply serves the purpose of funneling money into the AI service providers' pockets, for a possibly-small, but persistent, loss in performance.

@GossiTheDog I liked that.
Not a lot.
But I liked it.

@GossiTheDog "Chris Evans (not gay) and others hosted the station early on, but they weren't openly gay" - I love how much heavy lifting is being done in that sentence by "others".
In a very similar sense, I and others discovered fire, invented the wheel and built the pyramids.
I should put this on my CV, then the AI recruiter reviewing it will confirm it to be true.