Being interviewed by an AI to get a job evaluating AI is disorienting the first time. It's also predictable once you know what the system measures.
What the AI interviewer scores
- Verifiable specifics. Named employers, credentials, years, tools. Vague seniority claims score poorly; concrete details cross-check against your CV.
- Communication structure. Evaluation work is written work — the interview is a proxy for your critique quality. Organized, complete answers win.
- Domain vocabulary used correctly. The systems are calibrated on real experts; precise terminology used naturally beats name-dropping.
- Depth under follow-up. The interviewer probes claims. A specialty you can't discuss in detail hurts more than a narrower, accurate profile.
The failure modes
- One-line answers — the system has nothing to score
- Reading prepared text — pacing mismatch with follow-ups is detectable
- Overclaiming breadth — follow-up questions find the edge fast
- Treating it casually — it's a real interview with a rubric
The preparation that works
Answer out loud, 60–90 seconds per question, one concrete example per answer. The format that scores well is claim → example → implication: what you know, when you used it, what it means for the work.
Every role page on this site includes practice questions prepared for that specific role. Run them out loud twice before your screen. Shortlisted candidates typically get project onboarding next, sometimes with a paid trial batch — trial batches are graded strictly, so read the rubric twice before starting.