Building, Deploying, and Managing AI Agents at Scale on Google Cloud

The hype around Agentic AI is real, but so are the challenges. Creating a single agent is straightforward.. But how do you scale effectively? If you don't do it properly, critical issues will arise: spiraling costs, fragmented oversight, and major governance risks. Your agents need to be governed by a set of fundamental design principles. In other words, you need a platform. But what does a “platform” truly mean in practice? We will provide a pragmatic deep dive—no hype, no superficial demos—into the key pillars of this foundational platform: - Infrastructure & Serving: reliable serving patterns with Vertex AI Agent Engine. - State & Memory: Implementing session management and long-term memory for personalized interactions using Google Cloud's MemoryBank. - Orchestration: Using frameworks like Google's Agent-Development-Kit (ADK) - Integration: We will take a look into the different options to connect your agents with external services and data. - Security: Highlighting current authentication and authorization challenges for autonomous agents. - Governance & Cost Control: Establishing robust guardrails for cost, security, and compliance from day one. - Observability & Evaluation: Implementing rigorous monitoring and evaluation to prove business value and ensure reliability. This talk offers a pragmatic, engineering-focused approach to building a resilient, manageable, and impactful AI agent ecosystem on Google Cloud.