Agentic AI reasons toward a goal and decides when to use tools available. It also may ground 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 use Vertex AI Studio to configure a Vertex AI Agent to perform Reasoning and Action in Agent Builder. The agent will ask follow-up questions to assist in reasoning and, using a set of tools, construct a query to fulfill your request. Sub-Agents will be used to run the tools.
Upon completion of this lab, you will be able to:
Understand how agentic AI differs from a traditional chatbot by including the roles of reasoning and action in intelligent systems.
Navigate the Vertex AI ecosystem (Vertex AI Studio, Agent Builder) 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, model 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)
The following content can be used to fulfill the prerequisites: