AI agents are creating new security challenges for enterprises by generating uncontrolled outbound API traffic, which current infrastructure fails to effectively manage. As these agents evolve from simple text generators to autonomous entities capable of planning tasks and fetching data, they bypass traditional monitoring systems, leading to unpredictable costs and security vulnerabilities. This scenario mirrors past shifts in software architecture that required the introduction of API gateways and service meshes to manage new traffic patterns. Recognizing the need for a similar solution, Gartner has introduced "AI Gateways" in their 2024 Hype Cycle for APIs, aiming to manage AI-driven outbound traffic. These gateways act as middleware, enforcing policies and providing visibility over agent actions, thus addressing risks such as excessive permissions and unexpected behaviors. Emerging protocols like Anthropic’s Model Context Protocol and Google’s Agent2Agent highlight the urgent need for a governance layer to manage complex agent interactions, ensuring security and compliance while preventing potential system failures. As the agentic AI landscape develops, establishing robust foundational infrastructure and governance is essential for organizations to safely scale AI capabilities, drawing on familiar patterns of proxies, gateways, and monitoring.