This session introduces the AI Gateway pattern—a central control plane for enterprise AI ecosystems. Explore how AI gateways solve real-world challenges through unified API abstraction, intelligent failover mechanisms, semantic caching, centralized guardrails, and granular cost controls. You'll learn practical architectural patterns for building high-availability gateways that handle thousands of concurrent requests while maintaining sub-millisecond decision-making through in-memory operations. The session covers separation of control and data planes, asynchronous logging patterns, and horizontal scaling strategies, with a look ahead to Model Context Protocol (MCP) integration for managing not just model access but entire tool ecosystems, enabling natural language automation across enterprise software.

Overview of the AI Gateway pattern as a central control plane for enterprise AI ecosystems, including API abstraction, failover, semantic caching, centralized guardrails, and cost controls. Discuss practical architectural patterns for high-availability gateways that handle thousands of concurrent requests with sub-millisecond in-memory decision-making, separation of control and data planes, asynchronous logging, horizontal scaling, and future MCP integration for tool ecosystems and natural language automation across enterprise software.