This conclusively tells us that the Leetcode grind has been (without any dispute) been gamed to the ground and is no longer an accurate measure of exceptional performance in the role. Even the interviewers would struggle with the questions themselves.
Why waste each other's time in the interview when I (if I was the interviewer) can just ask for relevant projects or commits on GitHub of a major open source project and that eliminates the 90% of candidates in the pool.
I don't need to test you if you have already made significant contributions in the open. Easy assumptions can be made with the very least:
* Has knowledge of Git.
* Knows how to code in X language in a large project.
* Has done code reviews on other people's code.
* Is able to maintain a sophisticated project with external contributors.
Everything else beyond that is secondary or optional and it's a very efficient evaluation and hard to fake.
When there are too many candidates in the pipeline, Leetcoding them all is a waste of everyone's time. Overall leetcode optimizes to be gamed and is now a solved problem by ChatGPT.
Why waste each other's time in the interview when I (if I was the interviewer) can just ask for relevant projects or commits on GitHub of a major open source project and that eliminates the 90% of candidates in the pool.
I don't need to test you if you have already made significant contributions in the open. Easy assumptions can be made with the very least:
* Has knowledge of Git.
* Knows how to code in X language in a large project.
* Has done code reviews on other people's code.
* Is able to maintain a sophisticated project with external contributors.
Everything else beyond that is secondary or optional and it's a very efficient evaluation and hard to fake.
When there are too many candidates in the pipeline, Leetcoding them all is a waste of everyone's time. Overall leetcode optimizes to be gamed and is now a solved problem by ChatGPT.