It occurs to me that LLMs ("AI," if you like) are used pretty much exclusively in areas where quality is difficult to define.

Art, service, design, communication, writing...arenas full of ambiguity, where it's hard to quantify success or failure.

It strikes me that LLMs are deployed mainly here, rather than in less equivocal places, at least in part because this masks the terminal flaw of LLMs:

They are designed for generation, not for accuracy.

They are not at all truthful or reliable.

I think we're focused on the wrong thing when we look at what tech works for a company like Amazon or Facebook or Netflix.

We should be looking at what tech works when you *don't* have a small army of staff engineers optimizing it. I want to know what I can scale *without* paying someone a half million dollar salary to do it.

There should be more case studies on things that don't have a billion-dollar company propping them up, humming along quietly on a cheap-ass VPS somewhere.

I took this photo of my kid playing with his blocks the other day, and when I realized it reminded me of something, well...I had to make this.