I would do the opposite and would likely use the same framework that some AI companies are doing to evaluate candidates. By either not allowing them to use AI assistants in any part of the interview process (Anthropic and OpenAI does this.) or give candidates a strict token limit (100k tokens) until the candidate runs out of tokens.

They have to earn it, as the tokens are not free.

Given that deskilling and over-reliance in AI assistance will continue to happen, putting a hard token limit <100k tokens in the interview process serves as a great filter to prevent the vibe-coders and "tokenmaxxers" out and forces a higher bar for quality, with clean code and reasoning across well maintained software with less tokens rather than increasing the slop.

Do you want a candidate that knows when to use AI and carefully uses tokens with in their limits, or do you want a candidate generating incomprehensible AI slop to be tokenmaxxing out your company limits and then draining your company bank account?

I would start looking for a new job if I heard that my company hired someone who wasn't able to prove that they could write code without LLM assistance. A lot of people like that are legitimately illiterate.