Evals are emerging as a transformative approach for product optimization, moving beyond traditional A/B testing, particularly in the context of AI-driven products. Unlike A/B testing, which is limited by the need to create a few fixed variants, evals allow for dynamic, personalized experiences by letting AI adjust features in real-time based on user feedback. This shift enables rapid iteration, infinite variations, and continuous improvement, making it possible to optimize user experiences more efficiently. While A/B testing remains useful for certain scenarios, such as model selection or non-AI products, the adoption of evals allows teams to focus on setting the parameters for automated systems to enhance themselves. As companies begin to integrate evals into their processes, they are positioned to innovate and improve at a pace that could surpass traditional methods, ultimately leading to more personalized and effective user experiences.