Google AI Developers
@googleaidevs
Build powerful production-ready agents from a single API call! Learn more about managed agents in the Gemini API 🧵↓ https://t.co/fwq77I5fdP
3retweets42likes
View on XGoogle Launches Managed Agents in Gemini API for Production Workflows
Google· Updated
Google introduced managed agents for the Gemini API, allowing developers to deploy autonomous workflows through a single API call. By handling the underlying orchestration and infrastructure, Google is lowering the technical barrier for moving agentic prototypes into production environments.
Google launched managed agents in the Gemini API, enabling production-ready autonomous agents via a single API call. This update includes custom agent templates in the Google AI Studio Playground for rapid visual prototyping. These agents handle complex tasks without requiring developers to build the underlying orchestration logic from scratch.
This move mirrors the industry-wide shift toward managed infrastructure seen in Anthropic's managed agents. The release follows the launch of Google's Gemini 3.5 Flash, providing the high-speed model backbone required for low-latency agentic loops. It also extends the ecosystem alongside Chrome DevTools for agents to assist with runtime debugging.
You can start building by accessing the new templates in the Google AI Studio Playground or by integrating the managed-agents endpoint into your codebase. The feature works alongside high-speed models to reduce latency in agentic loops. Detailed implementation guides and API references are now available in the official Gemini developer documentation.
Still wondering? A few quick answers below.
Managed agents are a new feature in the Gemini API that allows developers to build and deploy production-ready autonomous AI systems using a single API call. These agents handle multi-step reasoning and task execution autonomously, removing the need for developers to manually build the complex orchestration logic typically required for agentic workflows.
You can quickly prototype these autonomous systems using new custom agent templates available in the Google AI Studio Playground. This visual environment allows you to test agent behaviors and configurations before implementing them in your code. Once satisfied with the prototype, you can transition to production by calling the managed agents endpoint via the API.
Google has published a dedicated documentation section for managed agents on its official developer portal. The guides cover how to initialize agents, manage sessions, and integrate them into existing applications. These resources provide the technical specifications and API references needed to move from initial experimentation in the playground to full production deployments.
Yes, Google has specifically designed this API feature to be production-ready from launch. By providing a managed infrastructure layer, the system handles the reliability and scaling challenges of autonomous agent loops. This allows developers to focus on defining agent goals and skills rather than managing the underlying sandboxing and state management infrastructure.
Every HeadsUpAI update is written based on its original source and reviewed before it's published. Read our editorial standards →
