Las Vegas hosted Google Cloud Next 2026 this week, and the central theme was unmistakable: enterprise AI isn’t about chatbots anymore. It’s about agents — and Google wants to be the foundation they run on.

The headline announcement: Vertex AI is being rebranded as the Gemini Enterprise Agent Platform (GEAP), a unified full-stack hub designed to let enterprises build, scale, govern, and optimize AI agents at production scale. The rebrand signals more than a name change — it’s Google’s clearest statement yet that the agentic era requires a different kind of infrastructure.

What Changed and Why It Matters

Vertex AI was already a powerful MLOps and model deployment platform. But as the industry shifted from “models that answer questions” to “agents that execute multi-step workflows over hours or days,” the brand no longer captured what Google was building.

GEAP is positioned as an end-to-end system for that agentic era. According to the official Google Cloud blog, the platform now includes:

  • Agent Designer — No-code/low-code builder for constructing agents and workflows through natural language or a visual interface, with support for reusable Skills
  • Long-running agent support — Agents that independently solve complex problems for up to days at a time, managed through a unified Inbox command center
  • Projects — Shared workspace for teams and agents to collaborate in real-time
  • Canvas editor — Integrated interface for human-AI collaborative work

The platform supports major multi-agent frameworks out of the box: LangGraph, CrewAI, and Google’s own Agent Development Kit (ADK).

A2A Protocol: From Spec to Production

One of the most significant data points from Cloud Next 2026: the Agent-to-Agent (A2A) protocol v1.2 is now live in production at 150+ enterprise organizations, operating under the Linux Foundation’s newly formed Agentic AI Foundation.

A2A is the open interoperability standard Google championed earlier this year, designed to let agents built on different platforms discover each other, delegate tasks, and exchange context. The 150-organization milestone confirms it’s moved beyond a design document.

For developers building multi-agent systems, A2A v1.2 means you’re no longer locked into a single vendor’s coordination layer. An agent on GEAP can, in principle, hand off work to an agent running on another platform — as long as both implement the protocol.

Agent Identity: Every Agent Gets a Cryptographic ID

A notable new capability tucked into the GEAP announcement: Agent Identity. Every agent deployed on the platform receives a unique cryptographic identity along with auditable authorization policies.

This matters enormously for enterprise governance. When an autonomous agent sends an email, approves a purchase order, or modifies a database, organizations need to know which agent did it and what it was authorized to do. Agent Identity provides the primitives for that accountability layer.

Agentic Data Cloud and 8th-Gen TPUs

GEAP also introduces the concept of an Agentic Data Cloud — positioning databases not just as storage, but as foundation for agent context. Agents need persistent, structured access to organizational knowledge to operate effectively across multi-day workflows. Google is betting that tight integration between their data infrastructure and their agent platform is a moat.

On the infrastructure side, 8th-generation TPUs were announced, though specific performance benchmarks weren’t fully detailed at time of writing.

The Salesforce Angle

Also announced: Salesforce Agentforce cross-platform interoperability with GEAP. This is significant because it suggests the two largest enterprise SaaS platforms are beginning to bridge their agent ecosystems rather than wall them off. Details on the scope of this integration remain limited, but the signal is clear: the era of vendor-locked enterprise agents may be shorter than the incumbents hoped.

Sundar’s Number: 75% of New Google Code Is AI-Generated

Google CEO Sundar Pichai confirmed at Cloud Next that 75% of new Google code is now AI-generated. The figure is striking and will likely be debated for accuracy and methodology, but even if directionally true, it dramatically changes what “AI-assisted development” means at scale. It’s no longer a productivity supplement — it’s the primary production path.

$240B Cloud Backlog

Google Cloud cited a $240B contracted backlog as context for the platform’s investment. That number tells you something about how enterprise buyers are thinking about long-term AI infrastructure commitments — this isn’t exploratory anymore.

What It Means for Agentic AI Builders

If you’re building multi-agent workflows today, the GEAP announcement has two direct implications:

  1. A2A is real now. With 150+ enterprise organizations running v1.2, it’s worth re-evaluating whether your agents should implement the protocol for future interoperability. Early adoption while the standard is still settling means you can shape how it’s implemented in your stack.

  2. No-code agent builders are getting serious. Agent Designer’s natural language construction approach directly competes with developer-first tools. If you’re building for non-technical business users, you’ll be competing on UX — not just capability.

Sources

  1. Google Cloud — What’s New in Gemini Enterprise
  2. Google Cloud — Introducing Gemini Enterprise Agent Platform
  3. Google Cloud Next 2026 Blog
  4. TheNextWeb — Google Cloud Next: AI Agents and the Agentic Era
  5. TechTarget — Gemini Enterprise Agent Platform adds connective tissue to Vertex AI
  6. iTWire — Introducing Gemini Enterprise Agent Platform

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260423-2000

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