1. Introduction

• AI has evolved from simple chatbots to autonomous agents.

• Agentic AI enables systems that can plan, reason, act and use tools.

• Google ADK (Agent Development Kit) makes it easy for developers to build such agents using Python.

• This article explains the fundamentals of agentic AI, agents, LLMs, tools, and how to use Google ADK.

2. What is Agentic AI?

• Agentic AI refers to AI systems that can think, decide, plan, and take actions.

• Instead of only responding, agents perform multi-step tasks.

• They can call APIs, connect to databases, run workflows, and coordinate multiple actions.

• Agentic AI focuses on autonomy, reasoning, and tool-use abilities.

3. Why Agentic AI Is Important

• Many real-world tasks require multiple steps (ex: checking order status, summarizing a document, sending email).

• Traditional LLMs cannot execute actions; they only generate text.

• Agentic AI bridges this gap by combining LLM reasoning + tool execution.

• Reduces manual effort and automates workflows end-to-end.

4. What is Google ADK (Agent Development Kit)?

• Google ADK is an open-source toolkit to build AI agents.

• Designed for developers: code-first, modular, production-ready.

• Supports Python, Go, Java.

• Integrates easily with Gemini, open-source models, APIs.

• Helps create, orchestrate, test and deploy agents.

5. Main Components of Google ADK

5.1 Agents

• Core entities that think and act.

• Types of agents:

  • LLM Agents (powered by LLMs)

  • Workflow Agents (deterministic task agents)

  • Multi-Agent Systems (multiple agents working together)

5.2 LLM (Large Language Model)

• Brain of the agent.

• Understands language, reasons, plans tasks.

• Google ADK supports Gemini models + other LLMs.

5.3 Tools

• Functions that allow agents to take actions. Example:

  • Call REST API

  • Fetch data from database

  • Read files

  • Run Python logic

• Tools extend the capability of LLMs.

5.4 Orchestration

• You can combine multiple agents to form workflows.

• Supports:

  • Delegation

  • Routing

  • Multi-step planning

6. How Google ADK Works (Step-by-Step)

1. Define an Agent.

2. Add Tools to the Agent.

3. Configure LLM model (Gemini / open-source).

4. Write instructions (role, goals).

5. Run the agent locally.

6. Deploy the agent using ADK CLI or container.