A Black-Box Framework for Evaluating Trust in AI Agents

FIRST Why Not Just Use LLM-as-Judge? Many teams default to using another LLM to evaluate their agent. It's easy. No labels needed. But it has a critical flaw: you're trusting an LLM to judge an LLM. If both models share the same biases (and they often do, since they're trained on similar data), the judge will approve wrong answers confidently. Conformal prediction avoids this entirely. It uses your ground truth labels — answers you know are correct — and builds a mathematical guarantee from...