Vertex AI has been Google Cloud's AI development platform since 2021. On April 22, 2026, at Google Cloud Next in Las Vegas, Google retired it — not with a deprecation notice, but with a full rebrand and architectural overhaul. Going forward, all Vertex AI services and roadmap evolutions will be delivered exclusively through Agent Platform. If you're building on Google Cloud's AI stack, the ground just shifted. Vertex AI was built for a different era. In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. Vertex handled that well — model selection, fine-tuning, deployment. But it was never designed for what enterprise AI has actually become: fleets of autonomous agents operating across dozens of systems simultaneously, often without proper security or governance guardrails. The gap is real. You can build a capable agent today without much trouble. Governing it — knowing what it's doing, what it has access to, whether it's behaving as intended — is a different problem entirely. Anthropic has Managed Agents, which cover runtime and memory but leave governance and observability to third parties. Google is betting that owning that full stack is the differentiator. The platform is organized around four pillars: Build, Scale, Govern, and Optimize. Each maps to a concrete set of tools, not just marketing categories. Build covers the development surface. Agent Studio provides a low-code visual canvas for designing, prototyping, and managing agent reasoning loops. The Agent Development Kit (ADK) handles code-first development of complex agents. Agent Garden gives developers a library of prebuilt agents and templates. And Model Garden provides access to over 200 foundation models — including Gemini 3.1 Pro, Gemma 4, and third-party models like Anthropic's Claude Opus, Sonnet, and Haiku. A significant ADK upgrade ships with this release. More than six trillion tokens are processed monthly through ADK. The new graph-based framework lets you organize agents into a network of sub-agents, defining clear, reliable logic for how they collaborate on complex problems. Scale is handled by Agent Runtime, which is rebuilt for a specific and important use case: long-running agents that maintain state for days at a time, backed by Memory Bank for persistent, long-term context. This is where Google draws a real line against stateless chat-based architectures. Payhawk is already using Memory Bank so their Financial Controller Agent recalls user habits and auto-submits expenses, cutting submission time by over 50%. Govern is where this platform separates from everything else on the market. Three components do the work: Agent Identity gives every agent a unique cryptographic ID, creating a clear auditable trail for every action it takes, mapped back to defined authorization policies. Think of it as IAM, but for agents rather than humans — SPIFFE-formatted, natively integrated. Agent Registry provides a single source of truth for the enterprise: it indexes every internal agent, tool, and skill, ensuring only governed and approved assets are available to your users. Agent Gateway acts as the air traffic control for your agent ecosystem — providing secure, unified connectivity between agents and tools across any environment, while enforcing consistent security policies and Model Armor protections to safeguard against prompt injection and data leakage. Optimize closes the loop with Agent Simulation, Agent Evaluation, and Agent Observability. Multi-Turn AutoRaters and Online Evaluation for live traffic give systematic quality assessment. The Unified Trace Viewer provides detailed visibility into agent reasoning and performance for debugging. The customer quotes in the announcement are more concrete than typical launch testimonials, which makes them worth citing. Comcast rebuilt the Xfinity Assistant using ADK — moving from scripted automation to conversational, generative troubleshooting. Color Health built a Virtual Cancer Clinic that uses Agent Runtime to check screening eligibility, connect patients to clinicians, and schedule appointments at scale. L'Oréal is arguably the most technically interesting case: their Beauty Tech Agentic Platform uses ADK for agent orchestration, and connects agents to their data sources via Model Context Protocol (MCP), securely linked to their core operational applications. PayPal is also live with Agent Payment Protocol (AP2), using it as the foundation for trusted agent-initiated payments. That's not a demo — that's commerce infrastructure. More than 85% of OpenAI's workforce uses Codex every week was one of GPT-5.5's big enterprise claims. Google's equivalent signal here is six trillion tokens per month through ADK alone. The scale is real. The headline is governance. Every serious enterprise blocker for production agentic AI comes back to the same questions: Who authorized this agent to do that? What did it actually do? Can we audit it? Can we revoke it? Until this week, the honest answer in almost every platform was "partially, with custom tooling." An IDC analyst framed Google's actual differentiation clearly: "Google has entrenched hardware, developer tools to build and manage agents, and an end-user AI app in Gemini — no one else has those three. That full lifecycle is what they're really hoping differentiates them." The MCP integration is also worth flagging for this audience specifically. Agent Gateway and Agent Registry natively support MCP servers — meaning any tool you've already built using the Model Context Protocol can be registered, governed, and exposed to agents through the same identity and policy system. That's a significant win for developers who've already built on MCP. Developers currently building on Vertex AI keep working in the same console, but the product has a different name and incorporates components that did not exist before: runtimes for long-running agents, persistent memories, registries with cryptographic IDs, security gateways, and simulation tools. The migration surface is low. The capability delta is not. Announced at Google Cloud Next on April 22, 2026, the platform brings together the Gemini Enterprise app, the Gemini Enterprise Agent Platform, and a partner marketplace that lets companies deploy third-party agents from vendors including Oracle, Salesforce, ServiceNow, Adobe, and Workday inside the same governed environment. You can access the platform directly at Agent Platform in the Google Cloud console. The ADK is available at docs.cloud.google.com. Full documentation for the governance layer — Agent Identity, Gateway, and Registry — is at the Agent Platform overview. Google says the new Gemini Enterprise features will roll out over the coming months. Not everything is GA today — build your evaluation timeline accordingly. The enterprise agentic AI race has moved past "which model is smartest" into "which platform can actually govern thousands of agents at once." Google just made the most complete argument yet that it has an answer. Whether the execution matches the architecture is what the next six months will show. Follow for more coverage on MCP, agentic AI, and AI infrastructure.