Building

I asked ChatGPT a question millions of job seekers now ask it: what’s the best AI tool to practice for interviews? It gave me a confident, well-formatted list. Then I did the thing the chatbot never does — I opened every link. Otavo, Zilta, Prepra, VocalHyre — polished landing pages, the right keywords, “AI mock interview, real-time feedback, STAR method.” No company behind them. No founder. No reviews anywhere a stranger left them. Zilta even turned up on a marketplace for selling unfinished side projects. Yoodli, the tool it recommended most confidently, had quietly pivoted to enterprise sales coaching; interviews are now one line on its homepage. Google’s Interview Warmup — the “best free option” — was shut down months ago. The old URL redirects to an article. ...

The hardest engineering problem in building Revarta wasn’t making the AI smart enough to evaluate an interview answer. The models are already good at that. It was making the AI willing to tell someone their answer was bad. Ask a stock model to grade an interview answer and it will tell you almost anything is “a strong response.” A vague, rambling story with no result lands a cheerful 4.5 out of 5. This isn’t a capability gap — the same model can dissect exactly why the answer is weak if you ask it to critique a stranger’s. It’s a disposition. These models are trained, through human feedback, to be agreeable, and that training has gravity. It’s the same instinct that makes a coding agent say “you’re absolutely right” the moment you push back on its design — it would rather agree than hold a line. ...