"AI PMs" - cohort population + interview rigor

Everyone is now an "AI PM". Understandable because those roles pay a lot more and are typically open for cutting edge tech startups. I'm curious though; what percent of PMs do you guys are actual AI PMs. Meaning, they've actually built and shipped production level agentic products inclusive of harnesses, evals, and full observability? I'm trying to get a sense of how many PMs can actually have claimed to do that since there's such much noise and demand for it.

Also. It feels like the bar for PM interviews has gotten absurdly high for top startups and companies. I totally understand PMs need to be able to build with LLMs and prototype quickly. But it now feels like they legit need engineering skills -- enough to apply for and get an engineering job (system design stuff). This feels...off? Thoughts?

EDIT: I understand the fundamental need/value to understand how products work, how to work with data, the basic FE vs. BE vs. data layers. But I also feel like there's a core difference between product and engineering roles. That said, what do you guys think is the right "line" or scope of being technical as a PM.