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Build an AI Agent with Gemini 3

#AI Tools
2025-11-24 10:1911 min read

Content Introduction
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The video introduces the newly launched Gemini 3 Pro, highlighting its advanced capabilities in high-level reasoning and following complex instructions, making it suitable for the development of AI agents. It outlines the process for creating a first AI agent using Gemini 3 Pro, including setting up a project folder, initializing it with necessary Python packages, and integrating Google's AI libraries. It explains how to access the Google AI Studio API key and details the steps for coding and deploying the AI agent. The tutorial guides viewers through the customization of the agent's functionality, enhancing its ability to generate detailed responses based on specified queries, such as finding horseback riding lessons in Toronto. The video emphasizes the powerful features of Gemini 3 Pro and encourages viewers to explore building more advanced agents, offering links for further resources.

Key Information

  • Gemini 3 Pro has been launched and comes with new and improved updates.
  • The model excels at advanced reasoning and complex instruction following, making it suitable for building AI agents.
  • A video tutorial demonstrates how to create an AI agent with Gemini 3 Pro and the agent development kit.
  • Initial setup requires creating a project folder and initializing it with a Python package manager (UV).
  • Two libraries, Google ADK and Google's JDI, need to be added for the project.
  • Obtaining and exporting a Google AI Studio API key is essential to proceed.
  • The tutorial guides users through setting up their Python environment and creating agent scaffolding with a simple command.
  • Instructions detail how to modify the template code to use Gemini 3 Pro and improve functional capabilities of the agent.
  • Specific search functions allow the agent to provide detailed responses, utilizing contextual searching for user queries.
  • The video ultimately demonstrates an agent's ability to assist users with inquiries such as locating horse riding lessons in Toronto.

Timeline Analysis

Content Keywords

Gemini 3 Pro

The launch of Gemini 3 Pro introduces improved updates, making it adept at advanced reasoning and following complex instructions, which is ideal for building AI agents.

AI agent development

The video provides a tutorial on how to create an AI agent using Gemini 3 Pro and the agent development kit, starting with setting up a project folder and using Python package manager UV.

Google ADK and JDI libraries

Instructions are provided for adding necessary libraries such as Google ADK and JDI for the development of the AI agent.

Google AI Studio API key

Viewers learn how to find and utilize their Google AI Studio API key for the project's configurations, enhancing the personalization of their AI agent.

Agent scaffolding

The video demonstrates how to create the scaffolding of an ADK agent using a simple command, which sets the foundation for building more complex functionalities.

Agent functionality

The tutorial highlights how to incorporate detailed, source-based responses into the agent's capabilities, including instructions to improve its performance.

Feedback and query handling

Viewers observe how the created agent responds to user queries, demonstrating its ability to provide detailed and categorized responses based on user prompts.

Chain of thought

The video explores the chain of thought employed by the AI model to arrive at responses, emphasizing how it searches and analyzes data effectively.

AI building opportunities

The video concludes by encouraging viewers to explore the vast opportunities for building agents using Gemini 3 Pro and the ADK, providing links for further learning.

Related questions&answers

What is Gemini 3 Pro?

Gemini 3 Pro is a newly launched AI model that provides advanced capabilities for building AI agents.

What are the key features of Gemini 3 Pro?

Gemini 3 Pro is great at advanced reasoning, handling complex instructions, and building efficient AI agents.

How do I start building my first AI agent with Gemini 3 Pro?

To start, create an empty project folder where your AI agent will reside and initialize it using a Python package manager.

What libraries need to be installed for the Gemini 3 Pro project?

You need to install Google ADK's library and Google's JDI library for this project.

How do I obtain the Google AI Studio API key?

You can obtain it by navigating to Google AI Studio and following the instructions to get your API key.

What should I modify in the sample code for my agent?

You'll want to modify the model name to Gemini 3 Pro and update the instruction set to provide more detailed guidance.

How does Gemini 3 Pro help with web search?

Gemini 3 Pro can execute web searches, categorize results, and provide detailed responses based on the search results.

Can I access my AI agent once it's deployed?

Yes, you can access your deployed AI agent using a provided link from the terminal.

What types of AI agents can I build with Gemini 3 Pro?

You can build various advanced AI agents focused on tasks like web searching, data sorting, and more with Gemini 3 Pro and ADK.

Where can I find additional resources for learning about Gemini 3 Pro?

You can check out the links provided in the description for detailed resources on building agents with Gemini 3 Pro.

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