red teaming

Jailbreaking is the adversarial sport of routing a model around its own safety training. The signal is naming the technique families and treating defense as a layered, never-finished arms race, not a one-time patch.

Shipping an LLM feature safely is an evaluation problem before it is a model problem. The signal is a layered eval-plus-guardrail design with honest, segmented metrics, not a single 'safety classifier.' Here is how to measure and defend each failure mode.

Red teaming is how you find an AI system's failures before users or attackers do. The signal is a structured program covering the real attack surface (jailbreaks, harmful content, leakage, bias) and feeding every finding back into defenses.

Safety is not one number. The candidates who pass name the axes, run benchmarks as a gate, and then explain why benchmarks alone certify nothing. Here is the framing interviewers score highest.

A request that would be refused in one message often succeeds when spread across ten. The signal is understanding that conversational state is part of the attack surface, and that turn-by-turn classifiers see only fragments.

Roleplay, obfuscation, optimization-based suffixes, and multi-turn escalation are different attack classes that need different defenses. The signal is organizing the space and pairing each class with a control instead of hoping one filter covers all.