Orchestration Is The Wedge
- Google unveiled the Gemini Enterprise Agent Platform to develop, optimise, govern, and run agentic workflows. - The platform supports agent-to-agent orchestration and multiday workflows, raising needs for memory and observability. - Enterprise patterns are shifting to an orchestrator-plus-specialists model instead of one monolithic chatbot ( ).
Google used Cloud Next on April 22 to turn Vertex AI into Gemini Enterprise Agent Platform, a system for building and running fleets of business AI agents. (cloud.google.com) The company said the platform combines model selection, model building, agent building, orchestration, DevOps, security, governance, and optimization in one stack. Google also introduced Agent Studio as the low-code interface and an upgraded Agent Development Kit for code-first work. (cloud.google.com) An AI agent is software that can take a goal, call tools, and complete steps on its own; orchestration is the layer that assigns work across several agents instead of asking one chatbot to do everything. Google said the new platform supports agent integration, multistep workflows, and multiday execution. (cloud.google.com; docs.cloud.google.com) Google has been laying the plumbing for that model with Agent2Agent, or A2A, an open protocol it introduced in 2025 so agents can discover each other, exchange tasks, and work across vendors and clouds. Current Google Cloud documentation says A2A agents can communicate as peers without exposing their internal logic. (developers.googleblog.com; docs.cloud.google.com) The product shift tracks a broader enterprise pattern: one coordinator agent routes work to narrower specialists for research, coding, approvals, or retrieval from company systems. Google’s Gemini Enterprise app now says administrators can manage Google-built, third-party, and internal agents from one place. (cloud.google.com; docs.cloud.google.com) That creates new operational problems. If a workflow runs for hours or days, the system needs memory to carry context forward, identity controls to show which agent acted, and observability tools to trace failures, latency, and cost across handoffs. Google’s recent release notes added agent identity visibility in preview on April 21, and its runtime documentation highlights deploy, evaluate, publish, and observe as built-in lifecycle steps. (docs.cloud.google.com; docs.cloud.google.com) Google is also tying the platform to its broader workplace product. Gemini Enterprise, introduced in October 2025 as the “front door” for workplace AI, now presents itself as a place to discover, create, share, and run agents with connectors to apps including Confluence, Jira, Microsoft SharePoint, and ServiceNow. (cloud.google.com; docs.cloud.google.com) Partners are part of the pitch. On April 22, Google said agents from companies including Adobe and Atlassian would appear directly inside the Gemini Enterprise app through its Agent Gallery and Agent Marketplace. (cloud.google.com) Google’s bet is that the control plane becomes the product: not one all-purpose assistant, but the software that builds, connects, governs, and watches many specialized agents at once. (cloud.google.com; cloud.google.com)