I think it reveals how many people were only familiar with LLMs as the generic AI tool for everything. It only took one ambitious marketing campaign for someone to come along and present a simpler technology as a new breakthrough to audiences that hadn't considered anything else.
The largest LLMs are really amazing for how much they can accomplish on unseen tasks. That is undeniably remarkable. The mistake that gets made everywhere is thinking that they're the best tool for every task, because LLMs are the only AI tool in most developer's AI toolbelt right now.
That’s exactly how the biggest vendors have been marketing them, it’s no wonder non-experts think of them that way. I’m not an expert myself but have a passing familiarity with theory as a SWE and grad student who did some research for machine translation and currently am in a computing-adjacent field. I use LLMs heavily for work and have never come across any coder-oriented tutorial, guide, etc. encouraging use of LLMs as decision models specifically, even if they are being used that way “beneath the hood.” Jev’s announcement seemed sort of new functionality to me but even in the first post about it on HN (where I heard about it), iirc people were pointing out that LLMs do the same thing, at least to some extent.
I don't know of any devs in real life who would loudly and publicly get excited about anything unless it was their own completed project to show off.
The tools are a footnote. It's precisely because it's so hard to get a project that far along that they would be familiar with many more tools than they would ever speak about. I suppose some people have a low bar. I wouldn't really call them "devs", especially now in this "AI era".