Production Eval

Design a slice-level eval strategy for an LLM system where mean score is insufficient

What is the key property that distinguishes shadow deployment from a standard A/B test for LLMs?

What is shadow deployment for LLMs and how does it enable safe evaluation?

How do you integrate LLM eval into a CI/CD pipeline so regressions block merges?

Order the stages of a production LLM quality assurance pipeline from development to release

How do you navigate the latency, cost, quality triangle when choosing an eval approach?

How do you detect quality drift in a production LLM system without ground-truth labels?

Which proxy signals are valid indicators of potential quality drift in a production LLM system?

Design a cost-efficient LLM-as-judge eval strategy for a system processing 1M queries/day

How do you set up an A/B test for an LLM system change, and what's different from standard A/B testing?