At I/O, Google launched Managed Agents in Gemini API. The core pitch is brutally simple: collapse weeks of agent engineering into a single API call. Paired with the new Antigravity CLI, Google is clearly gunning for end-to-end control at the agent execution layer.
This reflects an emerging architectural split: should agent management live in the model layer (Anthropic's way) or in the infrastructure layer (Google's way)?
Anthropic's Managed Agents embeds orchestration capability in the model layer — enterprises retain execution control while the model handles reasoning and planning. Google goes further, treating the model, harness, and sandbox as one integrated whole, all running inside Google's managed secure environment. Ramp's René Sultan put it directly: with this stack, developers can focus on polishing the domain behavior of their agent, and the iteration speed is in a different league.
Technically, this approach does address the biggest deployment pain point — the upfront "boring work" of standing up execution environments, configuring sandboxes, and wiring tool-call infrastructure. One customer said they "used to need two weeks of work, now it's done in a single call."
But handing the execution layer to the platform means handing over control as well. XYO founder Arie Trouw flags a real risk: developers end up swapping deterministic services for probabilistic ones, and when things break, data corruption or service degradation becomes much harder to trace and fix than with traditional stacks.
My take: Google's approach is highly attractive for enterprises that need to prototype fast, but for production use, the platform-lock-in and observability gaps can't be ignored. Teams choosing this path should think ahead about how much "black-boxing" they can tolerate in monitoring and incident response.