Announcing the Agent Development Kit for Go: Build Powerful AI Agents with Your Favorite Languages

Toni Klopfenstein

The Agent Development Kit (ADK), an open-source, code-first toolkit for building powerful and sophisticated AI agents, now supports Go. ADK moves LLM orchestration and agent behavior directly into your code, giving you robust debugging, versioning, and deployment freedom. ADK for Go is idiomatic and performant, leveraging Go's strengths, and includes support for over 30+ databases and the Agent-to-Agent (A2A) protocol for collaborative multi-agent systems. Start building today!

Google

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Toni Klopfenstein

•3 min read•advanced•

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•View Original

Google CloudJava

Overview

The article announces the addition of Go to the Agent Development Kit (ADK), an open-source toolkit for building AI agents. It highlights the flexibility, control, and robust features that Go developers can leverage to create sophisticated AI applications.

What You'll Learn

1

How to build AI agents using Go with the Agent Development Kit

2

Why using Go's concurrency and strong typing enhances agent performance

3

When to utilize the A2A protocol for multi-agent systems

Key Questions Answered

What is the Agent Development Kit (ADK)?

The Agent Development Kit (ADK) is an open-source, code-first toolkit designed for developers to build advanced AI agents with fine-grained control over orchestration, behavior, and tool use directly in their code. It allows for robust debugging, versioning, and deployment across various environments.

How does ADK for Go enhance agent development?

ADK for Go provides an idiomatic and performant way to build agents by leveraging Go's concurrency and strong typing. This results in robust and scalable applications, allowing developers to define agent logic and orchestration directly in Go, enhancing flexibility and control.

What are the key features of ADK for Go?

Key features of ADK for Go include a rich tool ecosystem, code-first development, modular multi-agent systems, and a built-in development UI. These features ensure a consistent development experience similar to that of Python and Java ADK, regardless of the programming language used.

What is A2A support in the Go ADK?

A2A support in the Go ADK allows for the creation of multi-agent systems where agents can collaborate to solve complex problems. It enables a primary agent to orchestrate and delegate tasks to specialized sub-agents, ensuring secure interactions without exposing internal logic.

Technologies & Tools

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Programming Language

Go

Used to build AI agents with the flexibility and control of the ADK.

Cloud Service

Google Cloud

Integrates with ADK for deploying AI agents.

Key Actionable Insights

1
Leverage the ADK for Go to build AI agents that can be deployed anywhere, from local machines to the cloud.
This flexibility allows developers to adapt their applications to various environments, enhancing scalability and accessibility.

2
Utilize the A2A protocol to create complex multi-agent systems that can efficiently solve problems through collaboration.
This approach is particularly useful in scenarios where tasks can be distributed among specialized agents, improving overall system efficiency.

3
Take advantage of the built-in development UI to streamline the testing and debugging of your agents.
This feature accelerates the development process by providing immediate feedback and visualization of agent behavior.

Common Pitfalls

1

Overlooking the importance of robust debugging when developing AI agents can lead to complex issues during deployment.

Without proper debugging, developers may struggle to identify and resolve problems, resulting in inefficient or faulty agent behavior.

Google has released version 1.0.0 of the Agent Development Kit (ADK) for Java, introducing powerful new features like Google Maps grounding, built-in URL fetching, and a standardized Agent2Agent protocol for cross-framework collaboration. The update enhances agent control through a new "App" and "Plugin" architecture, which allows for global logging, automated context window management via event compaction, and "Human-in-the-Loop" workflows for action confirmations. Additionally, the release provides robust session and memory services using Google Cloud integrations like Firestore and Vertex AI to manage long-term state and large data artifacts.

DockerJavaGoogle Cloud

11 min read

Includes Code

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Google

Advanced

How A2A is Building a World of Collaborative Agents

Celebrating the first anniversary of the Agent-to-Agent (A2A) protocol, this blog post highlights how the framework enables autonomous AI agents to securely collaborate and hand off tasks without the rigidity of traditional APIs. By delegating complex workflows to specialized peer agents, A2A prevents context pollution, ensures data privacy, and simplifies application design through modularity. To demonstrate this ecosystem in action, the post spotlights FoldRun—an agentic interface for life sciences that orchestrates complex protein structure predictions—alongside diverse A2A use cases spanning commerce, data streaming, DevOps, and telecommunications.

TypeScriptJavaScriptJava

6 min read

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