Agentic AI goes beyond single-turn chat: it reasons toward a goal, decides when to use tools, and grounds answers in external evidence rather than guessing. You can apply agentic patterns with or without a formal “agent” construct.
In this hands-on lab, you’ll progress from model-only prompting in Vertex AI Studio to configuring your first Vertex AI Agent in Agent Builder. You’ll define agent scope and instructions, enable a basic built-in grounding capability (e.g., Google Search tool) to demonstrate Reason → Act → Observe, and use the Preview experience to see how tool use changes behavior.
Upon completion of this beginner-level course, you will be able to:
Explain how agentic AI differs from a traditional chatbot and single-turn LLM prompts, including the roles of reasoning, grounding, and action in intelligent systems.
Navigate the Vertex AI ecosystem (Vertex AI Studio, Agent Builder, and related capabilities) and describe how these components integrate within Google Cloud.
Create and configure a first agent using Vertex AI Agent Builder (Agent Designer), including defining agent identity, instructions, scope boundaries, and basic tool/grounding behavior.
Apply best practices for designing and scoping a first agent (clear purpose, bounded behavior, observable outcomes) and understand how templates/connectors accelerate future development.
Cloud Solution Architects
Platform / DevOps Engineers exploring AI capabilities on GCP
Developers and Technical Consultants new to Vertex AI
Innovation, R&D, and AI Enablement teams evaluating agentic approaches
Technical Program Managers supporting AI platform adoption
Basic familiarity with the Google Cloud Console (projects, navigation, permissions)
General understanding of what an LLM is (no ML training required)