Debugging LLM-as-a-Judge Failures in Production
TL;DR
LLM-as-a-judge has become essential for evaluating AI applications at scale, but production deployments reveal critical failure modes. This guide examines how judges fail in production, from hallucinating scores to missing domain-specific issues, and provides systematic debugging approaches. Key strategies include implementing distributed tracing, establishing
