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AI interview platforms are evolving beyond simple keyword-matching bots into layered architectural systems. Three primary models are examined: the basic protocol-matching bot that follows a fixed script, a smarter filter layer that incorporates organization-specific values and weighted scoring, and an advanced dual-agent adversarial system where one LLM conducts the interview while a second silently evaluates and triggers targeted follow-up probes in real time. Each model trades off cost and complexity against the ability to detect genuine cultural fit versus rehearsed answers.

Architecting the Score: The Tech Behind AI Interview Evaluation

1. The Simple Bot: Sticking to the Script

2. The Smart Filter: Baking in the Culture

3. The Adversarial Prober: The Ultimate Stress Test