Prompt Versioning and A/B Testing (ANSWERED)
MLOps for prompts: semantic versioning, eval gates, traffic splitting, and rollback when prompt changes regress quality or cost.
TL;DR — Quick Answer
Treat prompts like code: store them in a registry with semantic versions, tie each deployment to eval benchmarks, and roll out via feature flags or traffic splits. Measure quality, latency, cost, and safety on held-out sets before full promotion, and keep rollback one config change away.
The Interview Question
How do you version prompts and run A/B tests safely in production LLM applications?
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VersioningA/B TestingMLOpsEvalsStripeShopifyOpenAI