[dannyeei]

Unfortunately real life problems involve a lot of context and introducing that to interviews is hard. It either requires a long conversation where someone might lose track, or involve writing a large ish code base and getting them to work on that (which is a lot of work, and once again they don’t have context).

In my experience if a problem simple enough to be completed in an hour, it’s simple enough for AI.

[thot_experiment]

IMO if your interview question has a right answer that's like, a basic early screening tool to see if the person is paying the slightest bit of attention. The sorts of questions that really give you useful insight into who someone is as an engineer are the ones that don't have a right answer, and can't be reasonably solved in an interview. If your question has an achievable correct answer you're clipping the gamut of info you can glean from it.

I recently had a question where I was just given a bunch of tuples and told "let me know anything you can glean about this data in two hours". I think you learn much more by seeing how someone fails at a complex nebulous task than whether someone can implement a doubly linked list from memory or whatever.

Real life programming is like 80% failing at complex nebulous tasks, picking yourself up and trying again (by volume). Interviews should simulate that. If AI helps you, so be it.