midLLMOps
How does evaluation work in LLMOps pipelines?
Updated May 16, 2026
Short answer
LLM evaluation measures output quality using automated metrics, human feedback, and LLM-as-a-judge systems.
Deep explanation
LLM evaluation is complex because outputs are probabilistic. Systems use BLEU/ROUGE for similarity, embedding-based metrics for semantic quality, and human evaluation for correctness. Advanced LLMOps uses LLM-as-judge to score outputs based on rubrics.
Real-world example
Customer support bots evaluated using satisfaction scores and human review.
Common mistakes
- Relying only on automated metrics.
Follow-up questions
- Why are BLEU scores insufficient?
- What is LLM-as-a-judge?