Google Agent Platform: Build, Scale, and Govern Enterprise AI Agents
Google Cloud has launched Gemini Enterprise Agent Platform, a unified solution for building, scaling, and governing AI agents within an organization. The platform aims to simplify the complex engineering reality of agent deployment by handling underlying complexities, allowing technical teams to focus on business value. It supports various user personas from no-code business experts to high-code engineers and offers specific tools for different development needs, addressing questions about agent development, data connectivity, and interoperability.
- →Empowering Diverse User Personas in Agent Development
- →Accelerating Developer Productivity with Specialized AI Tools
- →Designing Agents for Human or Agent Interaction
- →Structured Approach to Agent Development with a Four-Rung Ladder
- →Introducing Gemini Enterprise Agent Platform for AI Agent Development
Features (4) ›
- Empowering Diverse User Personas in Agent Development
The platform supports a spectrum of personas, including no-code business experts, low-code developers, and high-code engineers, by offering flexible tools like Agent Studio and the Agent Development Kit (ADK).
- Accelerating Developer Productivity with Specialized AI Tools
Developers can leverage Google Antigravity as a primary engineering harness, integrated with the Agent Development Kit (ADK) and Agents CLI for managing the agent lifecycle, alongside specific extensions like the Google Cloud Data Agent Kit for data engineers.
- Designing Agents for Human or Agent Interaction
Teams can choose to build agents for direct human interaction, utilizing tools like the Gemini Enterprise app and the Agent-to-User Interface (A2UI) framework, or for inter-agent communication using the open Agent2Agent (A2A) protocol.
- Structured Approach to Agent Development with a Four-Rung Ladder
Agent development is presented as a four-rung ladder, from the low-code Agent Studio for rapid prototyping to the code-first Agent Development Kit (ADK 2.0) for highly custom multi-agent networks.
Enhancements (1) ›
- Connecting Enterprise Data and Context with Model Context Protocol (MCP)
Agents can access enterprise data and maintain business context through open standards like Model Context Protocol (MCP), enabling direct connections to live databases and business applications for accurate interpretation and decision-making.
Notes (1) ›
- Introducing Gemini Enterprise Agent Platform for AI Agent Development
Gemini Enterprise Agent Platform provides a unified destination for building, scaling, and governing customer-facing and internal AI agents, simplifying complex engineering challenges for IT leaders.
https://cloud.google.com/blog/products/ai-machine-learning/20-questions-for-the-agentic-enterprise/
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