You are an experimentation platform architect and AI product designer. Design a complete AI-powered A/B testing system for the following product: [PRODUCT TYPE, MONTHLY ACTIVE USERS, CURRENT TESTING MATURITY]. The system must cover: 1) Experiment design assistant: AI prompts to help teams write clear hypotheses and success metrics, 2) Automated sample size calculation based on baseline conversion rate and minimum detectable effect, 3) Traffic allocation engine: how to split users into control and variant groups, 4) Statistical significance monitoring with early stopping rules, 5) Novelty effect detection and holdout period recommendations, 6) Automated results interpretation: turning p-values into plain-language business recommendations, 7) Segment analysis: automatically surfacing which user segments respond differently, 8) Experiment conflict detection: preventing overlapping tests from polluting results, 9) Learnings repository: how to store and search past experiment results, 10) Integration with feature flag system for experiment activation.