Feature gates and partial rollouts are crucial tools for managing risk and ensuring successful product launches by allowing product teams to test new features on a small percentage of users before a full rollout. This approach, similar to trying out a shirt with a friend before wearing it in public, enables teams to gather feedback and assess the impact of features without affecting the entire user base. The binary nature of feature gates allows for quick deactivation in case of negative outcomes, while partial rollouts facilitate A/B testing to generate insights on user experience and engagement. Statsig, for example, uses a structured rollout cadence to iteratively increase user exposure to new features, enabling data-driven decisions based on the impact observed in metrics. This methodology not only helps mitigate risk but also informs product strategy, drawing insights from industry leaders and past experiences, such as those of Optimizely and Facebook, to build a robust experimentation culture.