Updated README to reflect rebranding of Vertex AI to Gemini Enterprise Agent Platform.
Google Gemini Enterprise: Vertex AI Rebrand at Cloud Next 26 | AI Automation Global
Google rebranded Vertex AI as Gemini Enterprise Agent Platform at Cloud Next 26. A2A protocol v1.0, Workspace Studio, 200+ models, 150 deployments.
Google expands Gemini Enterprise, consolidates Vertex AI services to simplify agent deployment
Gemini Enterprise Agent Platform aims to help organizations to build, scale, govern, and optimize AI agents
Google Gemini Enterprise Agent Platform: Build and Deploy A2A Agents
Vertex AI is now the Gemini Enterprise Agent Platform. Learn ADK v1.0, A2A protocol, Agent Studio, and how to migrate before the June 2026 SDK deadline.
Introducing Gemini Enterprise Agent Platform | Google Cloud Blog
Gemini Enterprise Agent Platform is our new platform to build, scale, govern, and optimize agents. It integrates the model selection, model building, and agent building capabilities of Vertex AI, with new features for agent integration, DevOps, and orchestration, and security.
Google Sunsets Vertex AI, Launches Agent Control Plane | Awesome Agents
Google replaced Vertex AI with the Gemini Enterprise Agent Platform at Cloud Next 2026 - a full-stack control plane that assigns every agent a cryptographic ID and routes all tool calls through a central policy gateway.
Gemini Enterprise Agent Platform release notes | Google Cloud Documentation
You can see the latest product updates for all of Google Cloud on the Google Cloud page, browse and filter all release notes in the Google Cloud console, or programmatically access release notes in BigQuery.
Google introduces Gemini Spark, a 24/7 agentic assistant with Gmail integration, at IO 2026 | TechCrunch
At the Google I/O developer conference, the company announced a new agentic personal assistant called Gemini Spark, built from Gemini's base models and an agentic harness from Google Antigravity.
Building Managed Agents | Gemini API | Google AI for Developers
How to create and use custom agents with managed agents in the Gemini API.
Google Gemini to run AI services for all the phones
During his Google Cloud Next 26 keynote CEO Thomas Kurian said: “We’re collaborating with Apple as their preferred cloud provider to develop the next generation of Apple Foundation Models based on Gemini technology. These models will now power future Apple Intelligence features including a more personalized Siri coming later this year.” This is a big
Google Cloud Next 2026: The End Of The AI Pilot Era
Google Cloud Next 2026 opened with Thomas Kurian declaring the end of the AI pilot era and Sundar Pichai comparing the enterprise refrain of last year (“Can we build an agent?”) to today’s: “How do we manage thousands of them?” Google Cloud Next ’26 answers the second question with a single product story: Gemini Enterprise […]
generative-ai/gemini/agents/always-on-memory-agent at main · GoogleCloudPlatform/generative-ai
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform - GoogleCloudPlatform/generative-ai
With Gemini 3.5 Flash, Google bets its next AI wave on agents, not chatbots | TechCrunch
Google launched Gemini 3.5 Flash, its most powerful coding and agentic AI model yet, at the company's annual developer conference. It is capable of autonomously executing complex tasks and building software from scratch.
Expanding Managed Agents in Gemini API: background tasks, remote MCP and more
We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.
Environments in Managed Agents | Gemini API | Google AI for Developers
Learn about persistent execution environments for managed agents in the Gemini API, including pre-installed software, snapshots, and configuration options.
Gemini CLI: your open-source AI agent
Free and open source, Gemini CLI brings Gemini directly into developers’ terminals — with unmatched access for individuals.
Agent Gateway overview | Gemini Enterprise Agent Platform | Google Cloud Documentation
Secure and govern AI agent connectivity with Agent Gateway. Centralize access policies, mTLS, and Model Context Protocol (MCP) security for agent-to-agent and agent-to-tool interactions across diverse runtimes.