The gold standard in hiring qualification is work-sample testing. It works fine. You do not need to "make hiring a profit center" or "provisionally hire" or do internships. Work samples done correctly demand less time from candidates than interviews and scale better than interviews. They are standardizable and iterable.
What I feel like I'm reading here is someone who has been poisoned by FAANG hiring practices --- and they are terrible --- and has missed most of the work that's been done (outside of Google's admirable work in debunking their own processes).
I appreciate the "kitchen confidential" here, but with respect to Yegge, I think he's been working at the Olive Garden this whole time. Go stage at Gramercy Tavern! They're working at a different scale, yes, but you'll at least get a different perspective on the "gold standard".
The problem with work-sample testing (which is commonly administered as a take-home problem for the developer candidate to solve) is two-fold:
a) it discriminates against people who cannot spare 4+ hours of focused time on evenings/weekends to work on the problem. People with multiple jobs, single parents, etc.
b) in the age of AI it is no longer a reliable measure of someone's skill, for obvious reasons
Unlike Yegge, I haven't worked at FAANG, but the companies I have worked at all followed the same hiring practices and suffered from the same problems as he describes.
Provisional employment (or, if that's not possible, then well-paid internships) solve all of those issues. The candidate gets 3-6 months of stable employment, you as the employer get a large number of work-sample tests, and you can see how they use AI and how much.