GoKawiilGoogle introduces AX, an open control plane for running AI agents at scale
Google has unveiled AX, a declarative orchestration system designed specifically for agentic AI workloads rather than conventional stateless or batch computing. The project grew out of agentic runtime research from Google DeepMind combined with Google's experience in isolation, resumption, and scheduling at scale, and builds on the existing Agent Substrate framework. AX treats tasks, workspaces, network policies, and models as core primitives so developers can operate large fleets of AI agents without building custom infrastructure.
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AI agents behave unlike typical cloud workloads—they run in bursts, sit idle waiting on model or tool responses, and can require human approval mid-task, which makes existing orchestration tools inefficient or costly to run at scale. By open-sourcing a purpose-built control plane, Google is positioning itself to shape the emerging standard for how enterprises deploy and manage autonomous agents in production, similar to how Kubernetes became foundational for container orchestration.
- AX is Google's new open, declarative orchestrator built specifically for agentic AI workloads.
- It addresses the unique demands of stateful, bursty, long-running agents that traditional orchestrators handle poorly.
- The system builds on Agent Substrate and Google DeepMind research into agentic runtimes.
Source: agentexecutor.io, 2026-09-20
Published there as: “Google's Open Agentic Orchestrator”
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