It's been a year since I've actively given out take-homes for hiring, but I'm not sure I agree that everyone will use AI. I designed half the questions to be impossible for current-gen AI to answer without the candidate actually knowing what's going on [0], and only ~1% of candidates who responded did poorly on that half and not the other half (and, if we're worried about LLMs being better than I think, not all that many candidates passed most questions either).

[0] The most reliable strategy I've found for that is choosing questions where the wrong answer is the right answer for some much more common question. Actually spending a few seconds and solving the problem easily lets a human pass, but an LLM with insufficient weights or training data (all of them) doesn't stand a chance.

Thanks for clarifying - I kinda get the idea but would love to see an example for this.

I’ve mostly given up on all of the standard techniques for interviewing sadly, just because “using ai” makes a lot of them trivial, and have resorted to the good old fashioned interview, where I screen for drive, values and root cause seeking, and let people learn tech/frameworks/etc themselves.

But I was wondering, isn’t a take home question still good, if you give a more open ended and ambitious task, and let people vibe code the solution, review the result but ask for the prompt/session as well?

People will be doing that during normal work anyway, so why not test that directly?

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