I have, and it is surprisingly straightforward.

Find an easy to understand product, like a step above a todo list app. Share a spec and have them code it in their own IDE using LLM. Focus on speed. Then have them extended it, adding some features. Then ask them to show you where certain functionality exists in the code and to explain the architecture of how it is built. Ask them where it is weak and could be improved.

That's it, that's the interview. SWEs are getting quite good at the prompting, but fast navigation and understanding of the code is the key.

Anyone that can effectively translate a spec to code with minimal handholding shows product awareness. Anyone who can produce a working app can prompt AI reasonably. Anyone who can revise their design on the fly to support new features is someone with flexible thinking and some humility. Anyone who can navigate and explain what AI built is someone that understands how to build a mental map of a codebase. Anyone who can do all of this in an interview is someone who can handle pressure, work quickly and communicate.

You are welcome to keep trotting out linked list traversals and sliding window problems if you like, but leetcode is now (and maybe always has been) about culture fit more than an ability to build software.

The way you describe your ideal interview is how I conducted leet code style interviews. Ask a problem with a simple algorithm and then ask extensions until the time ran out. This worked pretty well.

For interviews where candidates are using AI I think you can supercharge this approach, but I do not think there is value in turning it into a code navigation puzzle as there is little value in that can be evaluated in the ~45 min you have for coding in a 1 hr interview slot. Ultimately in many software engineering jobs these days we need to understand how to build quality systems without looking into the underlying system except as necessary. I am not sure how to best evaluate this judgement in an AI assisted interview