Meta now lets candidates use AI during their coding interviews, and other big companies are starting to do the same. If that becomes normal, a lot of interview prep is aimed at the wrong thing. The job isn't writing a clean function from memory anymore. It's running an AI at a hard problem and being able to say, afterward, exactly what it did and why.
That's what Nyrion is for. You solve problems with an AI coding partner. You decide the approach and what to try next. It does the typing. Then each stage ends with an interviewer (also AI) who asks you to walk through what you just built. It's looking at the actual code while you answer. If you're bluffing, it knows. That part is deliberate: explaining your own solution under questioning is where real interviews are won or lost, and it's what editorials and pass/fail judges skip entirely.
The problems:
- Exact problems. LeetCode-style, with full test harnesses, built around what Meta, Google, and Amazon actually ask.
- Optimization problems, where the score reflects how good your answer is, not just whether it passes. We design them by running a solver against an adversary over several rounds, so no single trick clears them.
- Multi-file problems where you debug or extend a small working codebase instead of a blank function. This one is modeled on Meta's AI-enabled interview format.
Problems are connected, so when the interviewer explains one it'll often point back to something you did earlier. The library is still growing, and every problem is hand-built.
It's for new grads heading into FAANG hiring, for engineers who've been somewhere a long time and need to get sharp again, and for anyone with an interview coming up that allows AI.
In beta now at nyrion.ai. Free to try.
