Learn how to optimize AI tool execution beyond basic discovery protocols in this conference talk that addresses the limitations of current approaches like MCP (Model Context Protocol). Discover why raw API exposure creates context pollution, prompt bloat, and performance degradation in enterprise AI deployments. Explore practical solutions for implementing a thin abstraction layer within tooling services that significantly improves accuracy, cost-effectiveness, and performance based on real-world experience from Fortune 100 technology company implementations. Gain insights into advanced context engineering techniques that move beyond tool discovery to focus on efficient tool execution in production AI systems. The presentation draws from extensive enterprise-scale deployment experience and provides actionable strategies for organizations looking to enhance their AI tooling infrastructure while maintaining optimal model performance.