[tomrod]

> It's tough to answer because you want to hedge for both an AI enthused employer and an AI hesitant employer with limited information about who they are and how they personally use these products.

I'm an old hat on both sides of this type of discussion from a post-grad view.

Recommendation: use it to own the conversation and to signal mutual fit. Yes, your idea of AI lover versus hesitant matters. I recommend reframing the question to pivot to your fit to the org (and org fit to you) question. Show/concisely explain how you consider whether LLMs are fit to a task and how to tell it improves outcomes.

An outcome focus and willingness to show thought process around a common use case will be a substantially strong response.

[AnotherGoodName]

Just in general these questions are probes on curiosity and ability to show depth too. I’m astounded by suggestions of stating flat out refusal to even try out LLMs or suggestions to over praise the merits as if the interviewers want to hear binary answers. A well thought out pros and cons story wins over binary yes/no answers at pro and anti ai companies alike.

[sdesol]

> A well thought out pros and cons story wins over binary yes/no answers at pro and anti ai companies alike.

The issue with this is, you need to know how to really program to be able to articulate the pros and cons, which a new grad would mostly likely not have.

For example, if you want to include how AI can onboard quickly, you really need to understand the pain points like, I tried asking people but really, everybody is busy. Or I've found coding agents help me speed up making code changes, but it some situations, they can help accelerate making mistakes.

I think the issue that a lot new grad are faced with is, you don't know, what you don't know.