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Comment by ryanisnan | Hacker News Reader

I agree. What would age have to do with recalling syntactic idiosyncrasies, or being able to theorize about problems with a dry-erase marker and a whiteboard (or a pen and pencil, or a keyboard and a computer)?

Reading between the lines, you seem upset about having to answer questions about technical problems you perceive to be irrelevant, and that these technical problems are more likely to be solved successfully by those who have recently practiced them (e.g. graduates).

I too agree that, while abstract technical interview questions have little bearing on most day-to-day work, they do some things quite well:

1 - Define a well-bounded problem of sufficient difficulty 2 - Give the interviewee a good baseline for objective success 3 - Exercise a person's mind to think about complicated problems

While they are contrived and not entirely representative of daily work, they are not without value.

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I think most of the dislike comes from the tendency of typical whiteboard questions to favor someone who happens to have seen a very similar problem recently, the same way someone who comes up with the correct answer to a brain teaser very quickly is usually someone who's seen it before. Many rely on that, in fact, since otherwise they'd be asking people to come up with a publishable (once published, perhaps) finding, under pressure, on the spot, in maybe an hour.

This might be fine if the "very similar problem" is something you'd likely have encountered in your work, but often they questions are drawn from a pool that most people in this line of work see rarely if at all, and if they do it's likely to be some very small subset of the questions, so dedicated study of the remainder of the pool still puts one at a large advantage, regardless how useful it is in doing your actual work.

They're measures of "how bad you want it" (how much of your time you spent memorizing stuff you don't actually use to prep for the interviews) and/or how recently you took an algorithms course. And maybe those are things worth measuring, I dunno. Maybe the absence of strong enough signals on either of those is important enough that it makes sense to use them to reject people who are otherwise very capable of doing the actual work.

> Many rely on that, in fact, since otherwise they'd be asking people to come up with a publishable (once published, perhaps) finding, under pressure, on the spot, in maybe an hour.

In much of science the hard part is asking the right question rather than coming up with the solution, so figuring out these algorithms is not equivalent to making publishable research.

Fair criticisms. I tend to prefer asking/being asked system design questions, which in nature allow for a wide range of experiences to excel at.

What they aren't the best at, although more realistic, is coming up with an objective measurement of quality. Algorithms , at the cost of realism, do measure things quite nicely.

There is some value to it, yes. But what I've experienced so far is that whiteboard > individual project + culture + experience + whatever else. Thus my hunch that they are not there to show something more on top of other things but rather be the most decisive factor of all.

> individual project + culture + experience + whatever else

That gives you the interview and determines what level you get if you get hired, so it still matters more than the white-board. White-boarding is still necessary to check that you are top x% in terms or some mishmash of skill and intelligence. Having tech leads who are less talented than our juniors would be bad, so testing that they are better in every way is important.

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