As a hiring manager, I agree wholeheartedly with the root comment.

I love whiteboard interviews. Really. I do.

The problem is -- most start-ups are terrible at them. And most people interviewing at FAANG don't understand the reason those companies ask these types of questions.

Top tech companies ask hard interview questions for a few reasons.

They're not necessarily trying to hire the best people. They're trying to ensure the people that they do hire aren't incompetent. Hardly anyone incompetent is going to pass Google's interview process. Period.

Why are they so focused on not hiring incompetent people? It's not easy to fire people for being incompetent (or even worse -- toxic).

So if they're just trying to not hire incompetent people, why are the algorithms questions MUCH harder than the problems you face on an average day?

Two reasons. One, they have so many people interviewing, why would they not set the bar arbitrarily high? Two, the amount of people willing to cram and do almost anything for the job means they HAVE to set the bar high.

Now let's talk about the beef with start-up whiteboard interviews. Most of these interviewers have never been formally trained. They're just winging it. They ask questions that don't lend themselves well to a whiteboard. And they don't know what to look for during the interview!

A good whiteboard question does not rely on a trick or an obscure data structure. It doesn't have any gotchas that if you "get it" make it much easier.

A good question is slightly difficult to solve, but has many possible ways to solve it -- each with it's own trade offs. Ideally, none of them are much easier or harder than the others.

It's MUCH more impressive if a candidate can come up with 2-4 ways to solve a hard LeetCode easy problem or an easy LeetCode medium problem -- then for a candidate to happen to know the right combination of obscure knowledge to solve 1 LeetCode hard problem.

If you have 2-3 whiteboard interviews, and a candidate can come up with 2-4 totally different ways to solve the problem, and he materialize those thoughts into code -- there's a very slim chance s/he's bad.

The ideal candidate can discuss the tradeoffs of different solutions, and ask clarifying questions about the usage to figure out an optimal solution.

When you get to performance tweaks for edge cases, can the candidate weigh the pros and cons of adding the complexity for a certain gain.

Is it worth it to add some complexity to class to take an algorithm from 2n to n? Maybe. It depends on a lot of things...

I once worked with a guy who would ask a question that could be solved in O(N) time and O(N) space somewhat easily. But the question could also be solved in O(N) time and O(1) space IFF you knew some (discreet) discreet math. Almost everyone who didn't get the O(1) space solution he would say was a no hire.

Probably less than 10% of the engineers I've worked with have taken discreet math...

Another guy would ask a question that MOST candidates couldn't even comprehend, let alone come up with a solution. Most of the people that solved it would solve it O(n!) Or O(n^3). Occasionally, people would solve it O(n^2). But there is an O(n) solution. And that's what he was looking for. Literally NO ONE ever got it.

These are not good interview questions!