Earlier quoted context omitted.
You mean doing the work _again_. I had all the algorithm stuff down cold out of college and maybe for another 5 years after. Now after 20 years of rarely needing any of it and having it be a web search away when I did, I couldn't come up with any of it on demand. "Doing the work" meaning having to study to relearn a thing that I'll maybe use sparingly in my work means the interview process is broken, not anyone's mot…
>"Doing the work" meaning having to study to relearn a thing that I'll maybe use sparingly in my work means the interview process is broken, not anyone's motivation I used to think this too, but as a filter I think it's having the desired effect. From the outside looking in Life at a FAANG seems competitive in nature and they are optimizing for the people willing to push themselves that far to learn something. The ad…
Do they?
In my experience this was true in the early days of white board interviews where the only people that even thought about this stuff were people deeply interested in algorithms and computation.
But in the post-"Cracking the Coding interview" era (including the transition into the full leetcode era) people seem to be able to pass these interviews without really understanding anything in the same way college students can ace calculus while have literally zero intuition about derivatives.
I don't mind whiteboard interviews, they're a fun game you can train for and the practice is interesting. But the big tragedy now is that I feel almost nobody understands algorithms anymore since everything has been reduced white board coding drills and everyone believes they have an understanding of something they don't.
As a great example of this almost nobody today knows any heuristic optimization techniques (think the old ITA software puzzles), which used to be near and dear to anyone that cared about algorithms. But since you can't test for heuristics they same as you can established algorithmic solutions nobody studies them.