Traditional chatbots wait for a prompt and generate an answer. AI agents can go further: they can search for information, use tools, reason across multiple sources, and execute multi-step research workflows.

In this session, we’ll build a practical AI research agent using Google’s open-source Agent Development Kit (ADK). Starting with a research question, our agent will determine what information it needs, invoke search and other tools, analyze the retrieved information with Gemini, and synthesize the findings into a useful, grounded response.

We’ll explore the core building blocks of agentic applications—agents, models, tools, sessions, orchestration, and grounding—without introducing unnecessary architectural complexity. The completed agent will then be containerized so the same project can run locally or as a cloud-native workload.

**What You’ll Learn:**

* Understand LLMs vs chatbots vs agents
* Build an agent with Google ADK
* Connect agents to search and external tools
* Create multi-step research workflows
* Ground AI responses with retrieved information
* Containerize an ADK application