Course Overview
This course equips technical professionals and cloud architects with the specialized skills needed to deploy, manage, and optimize autonomous AI agents at scale within an enterprise environment. It covers the core taxonomy and operational lifecycle of agentic AI, multi-agent design patterns, enterprise governance and security frameworks, and advanced full-stack evaluation metrics.
Participants will learn how to leverage Google Cloud services, such as the Gemini Enterprise Agent Platform, Google Kubernetes Engine (GKE) Autopilot, and Spanner Graph, to construct secure, scalable, and cost-effective autonomous multi-agent systems that drive business value while mitigating operational, identity, and economic risks.
Who should attend
Solutions architects, lead AI engineers, and technology leaders with technical knowledge of cloud infrastructure who plan to build, scale, and govern autonomous multi-agent fleets within an enterprise setting.
Prerequisites
Familiarity with Google Cloud core services, AI foundational concepts, and standard model application programming interfaces (APIs).
Course Objectives
- Analyze an organization's operational landscape and determine its current position on the 5-level AI autonomy maturity model.
- Design scalable multi-agent architectures using design patterns.
- Apply the 12 non-negotiable governance capabilities for autonomous systems to mitigate autonomous risk.
- Evaluate agent performance using multi-step trajectory metrics and formulate a FinOps optimization strategy