In this video, I’m talking about the future of coding interviews—and why we’re about to see a “new normal” with AI. I start with a very real story from my own journey: I once got pushed back in a Reddit interview because I used Python’s built-in sorted() instead of handwriting a sorting algorithm. That’s the old era of interviews: memorization-heavy, not very reflective of real work. Fast forward to today: Meta announced they’re piloting coding interviews where candidates can openly use AI assistants. That’s basically the “open-book test” version of interviews, and honestly, it’s long overdue. But here’s the nuance: letting you use AI doesn’t automatically make the interview easier—it changes what’s being evaluated. Companies will care less about whether you can recall quicksort from memory and more about whether you can reason, validate, debug, and iterate on AI-generated solutions. I also show how far agentic tools have come using Sphinx AI as an example—tools that can build and validate end-to-end ML workflows inside a notebook and even catch subtle logical mistakes. My three takeaways are simple: fundamentals still matter, memorization matters less, and your real advantage is knowing how to guide AI. AI isn’t a trend—it’s the new baseline, and interviewers are going to have to catch up to how work is actually done.