Eval playgrounds provide a powerful editor UI that significantly accelerates the iteration loop for evaluating AI systems, allowing users to run full evaluations directly and refine parameters quickly. These platforms embed tasks, scorers, and datasets into an intuitive UI, enabling users to define and refine tasks, adjust scoring functions, and curate and expand datasets, while maintaining state and running underlying Eval capabilities as formal experiments. UX-first design is crucial for eval playgrounds, providing a cohesive toolkit that reduces evaluation time by 50%, triples dataset size capabilities, and leverages collaborative real-time prompts and trace comparisons, enabling AI teams to handle larger datasets, replace subjective assessments with objective metrics, and integrate evaluation results into organizational workflows.