Announced at Google I/O 2026, Managed Agents in the Gemini API is one of the more developer-consequential releases to come out of the event. Google is launching Managed Agents in the Gemini API, enabling developers to spin up an agent that reasons, uses tools, and executes code in an isolated, ephemeral Linux environment with a single call.
The underlying problem this solves is real. Building a production-grade agent previously meant managing complex infrastructure, scaffolding, and isolated sandboxes to serve customers at scale. With Gemini Managed Agents, Google is abstracting away that complexity so developers can focus on product experience and agent behavior.
As someone who covers the agent space daily, I can say this is one of the cleaner infrastructure abstractions I've seen from a major AI provider. The configuration-first approach, in particular, deserves a close look.
What the Antigravity Agent Actually Does
The Antigravity agent is a general-purpose managed agent on the Gemini API. A single API call gives you an agent that reasons, executes code, manages files, and browses the web inside your own secure Linux sandbox, hosted by Google.
The Antigravity agent (antigravity-preview-05-2026) is the general-purpose managed agent. It can execute code in Bash, Python, and Node.js, manage files, browse the web, and use Google Search.
Here's what a minimal invocation looks like via the Interactions API:
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
"agent": "antigravity-preview-05-2026",
"input": [{"type": "text", "text": "Write a Python script that generates the first 20 Fibonacci numbers."}],
"environment": "remote"
}'
Unlike a standard chat request that produces a single output, an Antigravity interaction is an agentic workflow. A single request triggers an autonomous loop of reasoning, tool execution, code running, and file management.
AGENTS.md and SKILL.md: Configuration as Code
The most interesting design choice here is how Google handles agent customization. Instead of requiring developers to write orchestration code, they opted for a filesystem-native, markdown-driven approach.
You can extend the Antigravity agent with your own instructions and skills. Instead of writing complex orchestration code, you can define everything in markdown files like AGENTS.md and SKILL.md and register them as a managed agent.
