I'm not sure how to make this come through but I'm rather sympathetic. I think practical experience & can-do coder know-how count for most of the marbles. But I also think it's impressively hard to assess by, that most of what we do is just taste & path dependence on the specific techs we've seen that happened to leave good impressions on us: not science, not knowledge, not truth: most coding, most practice is almost entirely happenstance.
But again I want to empathize. Because I think it's cruel to disregard engineers that have seen so much. But I also think you're hyperbolizing overmuch & discrediting the discourse when you make your argument so sharply pointedly. Because there's some truth, absolutely, but it's also no-where near as lopsided. For example, you talk about fresh/current undergrads at Stanford. But this is a pretty regular, basic CS path that any university student should be familiar with. I only had two undergrad classes that really talked to algorithms (Algorithms and then Data structures; OS kind of somewhat), albeit there was some computational thinking already in play at that point. Understanding complexity & algorithms is understanding the basics, it really is. If you can't see time flowing, don't know the tally & impact of the work you're asking for, you're lacking knowledge to avoid a lot of bad decisions. This isn't made up fake shit taught only to the elite.
What's alluring about this system is that it has some hard facts & theory underneath it. It's not just opinion & engineering pop-culture. The answers don't change, the rules don't change, the material stays the same, and it's all rooted in being able to analyze and understand problems, rooted in comprehension. Being able to see & understand & analyze, being able to apply some basic principles: this is a pretty sure way to find people who will be able to Not Mess It Up, who are capable of looking, assessing, & navigating through scenarios computationally.
And last and perhaps most key to me: it's also material that someone with even a modest bit of aptitude can cram for. Pick up a book like "Cracking the Coding Interview" and you can semi-accurately reproduce the output of four years of undergrad in two or three months of occasional light practice & trying. Projects like Leetcode can get you the experience. You may feel bad that what you want yourself to be measured on doesn't count here, but to people trying to go get hired, it's enormously helpful to them to have well defined expectations, to have specific kinds of tests to expect & be able to prepare & study for. I see so many protests that it's not fair, that it favors only those with the luxury of time, but those views to me massively undermine how wonderfully vastly accessible it is that there's a known, well-described, well-supported subject-area we can study. The industry overflows with things to learn, study, & know, but here's something concrete & specific, which undergirds it all, which alone might not determine your coding skill, but which does indicate you at least have some raw basic intellectual capacity to go understand problems put before you & apply some sensible computational thinking to tackling them.
There's tons of things not tested for, but by having a well defined, technology-neutral set of computational thinking tests, based on actual science with objective, factual answers, rather a much wider corpus of future/current/legacy pop-engineering-of-the-day built on nothing but wishy-washy subjective opinion, I think we achieve one of the best possible wins we can against an enemy we both hate: class-based discrimination, cruel tests that reject outgroups.
