Build Sophisticated AI Agents in Java with Google's ADK

Java developers, it's time to level up your AI game. While Python often dominates the AI agent conversation, there's a new toolkit that brings sophisticated, production-ready agent development right into the Java ecosystem.

Google just dropped the Agent Development Kit for Java (ADK-Java), and it's a serious piece of kit for anyone wanting to build, orchestrate, and deploy AI agents using the language that powers countless enterprise systems. If you've been eyeing the agent trend but wanted a stack that integrates with your existing Java services, this is worth your attention.

What It Does

The ADK-Java provides a framework for building AI agents that can reason, use tools, and maintain state. Think of it as a structured way to create those "AI employees" you keep hearing about—agents that can perform multi-step tasks, make decisions, and interact with external systems. It handles the orchestration layer, letting you focus on defining the agent's capabilities and logic.

It's built on top of Vertex AI, Google's machine learning platform, and is designed to work seamlessly within the Google Cloud ecosystem, though the patterns it introduces are useful for any Java-based AI agent system.

Why It's Cool

First, it's Java. For teams with massive investments in Java microservices, Spring Boot applications, or legacy systems that need AI augmentation, this is a direct path forward. No context-switching to Python or building awkward inter-service bridges.

The toolkit embraces a modular architecture. You define Tools (functions the agent can call), Memories (for maintaining context), and Steps (the building blocks of agent reasoning). This separation of concerns makes agents testable and maintainable—something crucial for production deployments.

It also includes features for evaluation and safety. You can set up evaluation pipelines to test your agents' performance before deployment, which is often the missing piece in hackier agent prototypes. The framework encourages building agents that are reliable, not just clever.

How to Try It

The quickest way to get a feel is to check out the GitHub repository. The README has a clear getting started guide.

You'll need Java 17 or later and Maven. Clone the repo and explore the samples/ directory. There's a basic "Plan and Execute" agent sample that shows the core concepts. You can run it locally by setting up your Google Cloud credentials (it uses Vertex AI's Gemini models under the hood).

The code is structured and well-commented. Start by looking at how a Tool is defined and registered, then see how the agent's reasoning loop is orchestrated. It's the kind of codebase where you can understand the flow within an hour.

Final Thoughts

This isn't a toy library. It's an opinionated, production-focused framework from Google. If you're building AI features that need to slot into existing Java infrastructure, or if you simply prefer Java's type safety and tooling for complex logic, ADK-Java is a compelling option.

It acknowledges that real-world agents need more than just a clever prompt—they need state management, tool use, safety checks, and evaluation. This toolkit gives you the scaffolding for all of that. It might have a steeper initial curve than gluing together some Python scripts, but the payoff is in building agents you can actually deploy and maintain.

Give the samples a run. Even if you don't use the full ADK, the architectural patterns are a solid blueprint for agent design in any language.

Follow for more interesting projects: @githubprojects