I think that's what these leetcode type questions are good at. You're either naturally adept enough to do well, or internally motivated enough to memorize/learn them. Either way, it's a decent signal for a company that needs someone to learn their internal, proprietary techstack
> You're either naturally adept enough to do well, or ...
I'm personally very wary of using algorithms questions as a proxy for how "adept" someone is at software engineering. If I were running a business, I'd personally want to make sure people could manage technical debt and build decoupled systems.
I have had multiple positions at FAANG companies, and despite being "adept" according to these algorithms questions the systems built by these highly-paid (and, around me, generally experienced) people are pretty awful in terms of quality and maintenance.
Learning a proprietary stack also hampers effectiveness in future positions if wanting to opt-out of FAANG later on.
I have observed this problem and usually it’s not because the people are incapable but that the incentives are to ship things that move the needle to quickly get promoted. The financial rewards at these companies from promotions are huge.
Where the managers have incentivized quality and stability my team mates have moved mountains and I’ve seen some really good stuff but otherwise not.
Why do you suppose these hires aren’t good at learning engineering best practices? I see comments like yours here all the time. Is it some kind of arrogance, perhaps amplified by a false signal sent by getting hired off leet code questions in the first place?
It’s false based on what I’ve seen. Plenty of people passionate about good engineering where I am. But they are sometimes trapped in a system which doesn’t always incentivize it.
> Why do you suppose these hires aren’t good at learning engineering best practices?
I guess what I was trying to convey is different: being good at algorithms doesn't give much of a signal (positive or negative) about other things I think really matter more on the whole.
(Of course, having enough people being aware of algorithms subtleties is important ... everyone, not so much)
I partially agree but this point of view has become very polarizing and controversial and I get the other side of it too. People who have spent ages getting better at their craft feel undervalued. However the two need not be mutually exclusive. One needs to learn to do their job while also navigating the system. That is part of the job just like selling your work is also work.
But having worked at both FANG and non FANG you can see the rigor of the interview process reflected in the quality of your colleagues. That’s something that is hard to deny having experienced it.
