Optimizing the cost-to-outcome frontier in real world context means using the right model for each task, and optimizing the context, skills, tools, and agent harness around it. It's possible to take saturated frontier capabilities and deliver them at scale and at lower cost through models optimized for high-usage products, while continuing to use frontier models for frontier needs. The model is only one part of the hill-climbing system. Harness, memory, context, tools, skills, and user interactions all shape the evals and performance of these agentic systems.