The product thesis: as generic AI answers become cheap, interview preparation should train explanation quality rather than answer substitution. A useful loop maps JD/resume claims to likely follow-ups, practices coding interview reasoning, makes system design tradeoffs explicit, and turns post-interview review into the next training plan.
I am interested in how technical interviews are changing with AI: what still measures engineering judgment, what becomes boilerplate, and how candidates can prepare without hidden cheating, answer outsourcing, or violating interview rules.