Your question is LLM Evaluation and Safety Guardrails. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
What strategies do you use for LLM evaluation, and how do you benchmark model hallucination against safety guardrails?
Explain a practical, eval-first approach suitable for a production LLM application. Cover offline test-set construction, automated and human evaluation, hallucination measurement, adversarial safety testing, prompt-injection resistance, and online monitoring. Describe how you would define pass or fail criteria, calibrate LLM-as-judge evaluations, and balance quality, latency, and cost. Include the structure of an evaluation harness or pseudocode for running tests and recording results.