At Google I/O, the company unveiled Managed Agents in its Gemini API — a service that promises to collapse weeks of agent deployment work into a single API call. It's also a sign that Google believes its ecosystem, including the newly launched Antigravity CLI, is ready to own the execution layer end-to-end.

Before a single agent is written, teams are already spending days on the unglamorous work: standing up execution environments, managing sandboxes, wiring tool call infrastructure. Model providers like Anthropic have launched platforms to handle much of that work — but Google's approach is different.

Google said in a blog post that Managed Agents in the Gemini API abstracts “away the complexity so that you can focus on your product experience and agent behavior.” The service is available in preview via new custom templates in Google AI Studio.

The growth has introduced a real architectural question: should agent management live at the execution layer — embedded in the model or its harness — or at the infrastructure layer, as a separate runtime?

Comparing Google’s approach

Until recently, agent orchestration relied on frameworks that sat above the model, directing agents and letting teams control routing and execution separately. That layer is now being absorbed by the platforms themselves.

Recent platforms like Claude Managed Agents embed orchestration at the model layer rather than on a separate runtime platform. The idea is that the model owns the reasoning and orchestration layers, and enterprises have control over execution. 

AWS, through new capabilities on Bedrock AgentCore, adds managed harnesses that stitch together the upfront tasks for deploying agents. Google's approach goes further, optimizing the model, harness, and sandbox together and running everything in secure Google-managed environments.

René Sultan of Ramp, cited in Google's announcement, said the shift is concrete: "The real shift with Gemini Managed Agents is that the agent runtime moves into the platform. With the sandbox, infrastructure and execution loop managed for you, developers can focus on productizing the agent's domain-specific behavior and iterating at a completely different pace."

The new orchestration reality 

Enterprises starting fresh with agents could find the platform offerings from Anthropic and Google strong, especially since they remove much of the difficulty of deploying agents while still maintaining some control. Google, however, is pushing for a more vertically integrated system, while Anthropic is betting on the model layer as an orchestration plane, and AWS focuses on authorization. 

But this also brings some risks, according to XYO founder and chief executive Arie Trouw.

“An additional risk is that developers will switch out what previously were deterministic services for what will now be probabilistic services, which can introduce unpredictable outcomes for the users at best, or data corruption at worst,” Trouw told VentureBeat in an email. “This is the classic example of having an amazing hammer and everything starting to look like nails. I've seen this pattern repeatedly as a developer and business founder myself in the past few decades.”