Interview and hiring techniques are a perennial favourite on HN. I just have a couple of comments (disclaimer: I work for Google).

I personally detest abstract puzzles like "why are manhole covers round?" or (worse) "How do you move Mount Fuji?" AFAIK these types of questions are not and have never been used in engineering hiring at Google (sales, etc I know nothing about). WSJ and other sources have made this (AFAIK inaccurate) claim. It's possible individual interviewers do this.

My own philosophy is that a simple whiteboard coding problem is an incredibly useful litmus test. I don't mean anything incredibly complicated either. If you can't write a function that gives me a row of Pascall's triangle, that's a problem. Note: I don't expect you to know what Pascall's Triangle is, merely implement it when explained.

Some of you may think such a test is a waste of time but I assure you it is not. It's astonishing how many people can't do this (and even more astonishing how many that do make it through resume and even phone screens).

The key here is "simple". One problem is that interviewers fall into the trap of thinking these problems are too simple and make the problems increasingly harder. Worse, they may get in a situation of asking someone a problem that is either something they know (because they've covered it before) or they don't (where it's not something you can simply nut out). This is a useless indicator in my experience.

Just because you can create a function to return a row of Pascal's triangle doesn't mean you're a great programmer but if you can't, it almost certainly means you aren't. It's a negative signal filter, nothing more, but an incredibly quick and useful one.

API pop quizzes I'm not a big fan of either, generally speaking, but on the other hand if you've used a language sufficiently long, basic questions about commonly used libraries aren't unreasonable either.

Interviewing is a numbers game. Your goal is to come up with a process that balances time spent by the interviewer with finding a suitable candidate. Note that I didn't say accurately assessing each and every candidate. It's sufficient for the employer to simply find one qualified candidate even if you falsely determine someone who is qualified isn't.

A certain error rate is to be expected. It reaches a point where the time investment to reduce it outweighs the benefit of higher accuracy.

One final note: I detest (both as an interviewer and an interviewee) any kind of "take home" test (other comments have mentioned this).

As an interviewer, it's extra work to assess, people cheat, good candidates won't bother and so on.

As an interviewee, I'm not going to spend hours on you without speaking to someone first to find out how likely it is that you're a good match for me and the likelihood that you believe I'm a good match for you.

I would argue that a take home test is significantly more effort than a simple coding problem that doesn't have a significant increase in accuracy.

The one exception to this is automated testing where the problems themselves are relatively interesting. Some of the Facebook Puzzles fell into this category (and some don't). People may do those anyway for kicks. But again, there's nothing stopping someone going to Github and copying and pasting someone else's solution so what value is the filter, really?

EDIT: clarified my Pascall's Triangle comment. This isn't a trivia problem. I don't expect people to know what it is, merely implement it when explained.