Build an AI Agent with Gemini 3 Pro and ADK

Introduction to Gemini 3 Pro and ADK

• 🚀 Gemini 3 Pro is highlighted as a powerful model excelling in advanced reasoning and complex instruction following, making it ideal for building AI agents.
• 💡 The video demonstrates how to build an AI agent using Gemini 3 Pro and the Agent Development Kit (ADK).

Project Setup and Initialization

• 🛠️ The process begins by creating an empty project folder and initializing it using UV, a Python package manager.
• 📦 Necessary libraries, Google ADK's library and Google's JDI library, are then installed.
• 🔑 An API key from Google AI Studio is required and exported for authentication.

Agent Scaffolding and Tool Implementation

• 🏗️ The ADK create command is used to generate the basic structure for the agent, prompting the user to select a model, with Gemini 3 Pro being the chosen option.
• 🔍 The Google Search Tool is implemented by copying and modifying code from ADK's documentation.
• ✍️ Key code modifications include specifying Gemini 3 Pro as the model and refining the instruction set to guide the agent to cite sources implicitly based on search results.

Agent Deployment and Interaction

• 🌐 The agent is deployed to ADK Web, providing a link to access and interact with it via a web UI.
• 💬 An example interaction demonstrates asking the agent for horse riding lessons in a city, showcasing its ability to provide detailed, categorized responses.

Analyzing Agent's Thought Process

• 🧠 The thought signature of Gemini 3 Pro is explored, explaining how it helps the model understand conversation context.
• 🔍 The video details the chain of thought process, including the specific web search queries Gemini 3 Pro executed, starting broad and becoming increasingly specific.
• 📈 The agent's ability to refine searches, check for public transit accessibility, and verify stable operating status is highlighted as a demonstration of its advanced reasoning.