A) they're only tangentially related to the work, meaning they include bad hires and exclude good hires
B) they put a huge workload on employees who must practice tens or hundreds of hours of underwater basket weaving, time which would be better spent doing almost anything else
C) they systemically exclude anyone who can't play the dumb game due to a lack of time, including but not limited to older people and poorer people
And that's the reason many companies have to set the standards so high in the first place: excluding false positives (bad hires) is so important in practice that this distorts the whole hiring process. Fine as far as that goes of course, but it does mean that people who practice their leetcode questions are basically stuck with very expensive (per B and C) lottery tickets.
I think everyone knows at this point that algorithmic puzzles are not desirable; the real question is whether one can do better, even at FAANG scale.
For coding, if a coding question boils down to implementing KMP string matching or something that's only realistically solvable by memorizing the entire algorithm and writing it out on a whiteboard, then it's not any different than any of the puzzle type questions like "why are manholes round?"
The proper way to evaluate coding questions, and what is mentioned in the article, is that one is evaluating general intelligence in the context of software programming. Is the candidate coming up with a reasonable solution? Are they asking questions to understand the problem better? If they get stumped by something, do they stay stuck on it, ask for help, or think through it? Can they find the issues with their code and improve on it?
I haven't heard of a better way to interview engineers, but if there is I'm definitely all ears.
Technical understanding of systems in general (networking, CAP, testing, writing maintainable code) are all overlooked in the interview process, though these are what actually make a developer productive.
The older you get the more specialized and optimized you are to learning what matters, which is why most of the older guys suck at these types of interviews.
Imagine interviewing Brendan Gregg by giving him some leetcode problems!
I went to CMU, enjoyed algorithms classes a lot. In the nearly 30-year career since, I've used that knowledge... never. Not once.
It's not about the interview bar being too high. It should be high, mine is. But interviews based on algorithm memorization have the bar in the wrong place, measuring something that has no real-world relevance.
If we’re out of the running no matter how much you practice, no matter how much job experience, and if there really is this mysterious value G, with the right combination of Ivy League CS program, then I can see how these discussions mirror the notion of ‘the bar’ - that is, a forgone conclusion.
What won't work though is hiring based on only past experience. The bullshitters will eat you alive. You really do need some kind of "underwater basket weaving" as a test.