Google has introduced new development toolkits aimed at simplifying the creation and deployment of intelligent AI agents for developers working in Python and Java.

Announced on May 20, the release includes version 1.0.0 of the Python Agent Development Kit (ADK) and an early preview (version 0.1.0) of the Java ADK. These open source frameworks provide the necessary infrastructure to help developers design and manage AI agents with a high level of control and flexibility.

According to Google, the Python ADK has reached a maturity milestone that makes it ready for use in production environments. Developers can now confidently build and deploy their agent-based applications in live systems using Python. In contrast, the Java version is still in its early stages but is intended to bring similar agent development functionality to the Java ecosystem.

Google positions the ADKs as modular, extensible platforms built for integrating AI agents into a wide range of use cases. While these tools are designed with compatibility for Gemini models and Google services, they are not limited to those and can be used with different AI models and platforms thanks to their framework-agnostic design.

The company highlights that one of the primary goals of the ADK is to make agent development feel as seamless and iterative as traditional software engineering. The kits allow developers to create, deploy, and orchestrate agents that can perform anything from straightforward tasks to advanced multi-step processes.

🔧 Notable Capabilities of the Python and Java ADKs:

• Tool-rich environment: Developers can tap into a wide selection of prebuilt tools, plug in custom functions, and use OpenAPI definitions. These capabilities allow agents to interact with various systems and services, particularly those in Google’s ecosystem.
• Code-driven architecture: Both toolkits emphasize a “code-first” approach, enabling developers to directly define agent behaviors and logic in Python or Java. This offers greater flexibility, easy testing, and better control over versions.
• Support for complex agent systems: The ADKs allow users to design scalable applications by composing multiple agents into structured hierarchies or collaborative systems—suitable for applications that demand parallelism or task delegation.

With these releases, Google aims to lower the barrier to entry for developers looking to adopt agent-based paradigms in their applications, offering solid tooling whether you’re building a small personal project or integrating agents into enterprise-scale systems.