- In short
- A usable A/B test hypothesis names the treatment, the expected direction of the primary metric, a numeric threshold for what counts as a win, and any constraints on secondary metrics. "The new prompt is better" is not usable because it names no treatment, no metric, and no threshold. A well-formed hypothesis reads like: this specific change will increase task success rate by at least X% without degrading latency p95. Without a falsifiable hypothesis, any result can be reinterpreted as a win after the fact.
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