LLM developers track metrics like factual accuracy, latency and cost when testing new prompts or model versions. Automated tests compare responses against ground truth, while manual review checks reasoning quality and safety.
Benchmarks such as BLEU, Rouge and human preference scores reveal regression or improvement across iterations. Clear metrics help teams experiment confidently and maintain reliability in production.