Why Your A/B Testing Strategy is Broken (and How to Fix It)

Traditional A/B testing relies on fixed-horizon methods that delay decision-making. Safe testing, built on anytime-valid inference, allows experimenters to monitor and act on results in real time without increasing false positives. Compared to classical approaches and other AVI methods like mSPRT, safe testing detects significant effects with fewer samples. As data infrastructure evolves, this method could transform online experimentation at scale.