Champion-Challenger (A/B Model Testing)

Champion-challenger is a live model-testing pattern: the current production model, the champion, keeps serving the bulk of traffic while one or more candidate models, the challengers, receive a controlled slice. You compare them on real outcomes — conversion, resolution rate, revenue, complaints — and promote a challenger only when it convincingly beats the incumbent. It is A/B testing applied to models rather than button colors. The reason it exists: offline evaluation on a fixed dataset never fully predicts how a model behaves against messy live traffic. Champion-challenger measures actual business impact under real conditions. For AI SaaS this often means running two prompts or two model tiers side by side and watching which resolves more support tickets or drafts more accepted replies. Practical note: pick one guardrail metric that must never regress, wait for statistical significance before declaring a winner, and keep the traffic split small until a challenger proves it is safe.