This has been my experience as well. The ones that have most heavily relied on GPT not only didn't really know what to ask, but couldn't reason about the outputs at all since it was frequently new information to them. Good candidates use it like a search engine - filling known gaps.
Yea I agree. I don't rely on the AI to generate code for me, I just use it as a glorified search engine. Sure I do some copypasta from time to time, but it almost always needs modification to work correctly... Man does AI get stuff wrong sometimes lol
I don't really can't imagine being it usefull in the way where it writes logical part of the code for you. If you are not being lousy you still need to think about all the edge cases when it generates the code which seems harder for me.
> you are not being lousy you still need to think about all the edge cases
This is honestly where I believe LLMs can really shine. I think we like to believe the problems we are solving are unique, but I strongly believe most of us are solving problems that have already been solved. What I've found is, if you provide the LLM with enough information, it will surface edge cases that you haven't thought of and implement logic in your code that you haven't thought of.
By chatting with the LLM, I created four user stories that I never thought of to improve user experience and security. I don't necessarily think it is about knowing the edge cases, but rather it is about knowing how to describe the problem and your solution. If you can do that, LLMs can really help you surface edge cases and help you write logic.
Obviously what I am working on, is really not novel, but I think a lot of the stuff we are doing isn't that novel, if we can properly break it down.
So for interviews that allow LLMs, I would honestly spend 5 minutes chatting with it to create a problem and solution statement. I'm sure if you can properly articulate the problem, the LLM can help you devise a solution and a plan.
