Experiment Inflation
When producing variants gets cheap, the number of experiments rises, but traffic stays the same, so the sample and power per experiment fall; apparent experiment speed rises while real learning speed does not (this site's definition).
AI and GrowthTerm 81 / 81
In practice
AI made building free, not knowing: the sample-size formula has no term for who wrote the variant, only traffic, base rate and effect (our reading). Ten experiments a week on the same page means traffic that is enough for none of them; the result is more false positives and exaggerated winners. The right measure is not the number of experiments but the number of decisions changed per unit of traffic (our reading). Kohavi's low-power table and Georgiev's review of 1,001 tests (median effect 0.08 percent) show the two ends of this mechanism (our reading).