Getting Started with Google Antigravity

Google’s release of Antigravity signals the end of the chatbot-in-an-IDE era by replacing manual prompting with autonomous, multi-agent orchestration. You aren't just typing commands anymore; you’re managing a fleet of agents that plan, execute, and iterate across your entire codebase.

Installing and Configuring the Environment

Getting started with Google Antigravity requires strict adherence to versioning; you must install v1.23.2 or earlier to maintain compatibility with current codelab workflows. Newer builds, specifically v2.0.0 and above, introduce structural changes that break the environment setup documented here.

Download the installer from the official releases page and run the setup. During the initial configuration, you'll encounter the terminal, review, and JavaScript execution policies. Don't skip these. I recommend the "Review-driven development" setting. It forces the agent to pause and request human approval before executing destructive terminal commands or navigating to external URLs. You can always toggle these later via Cmd + , on Mac or Ctrl + , on Windows. Sign in with your personal Gmail account to unlock the preview quota and you're ready to initialize your first workspace.

Mastering the Agent Manager

Antigravity bifurcates the interface into an Editor and an Agent Manager, forcing you to stop thinking like a coder and start thinking like an engineering manager. The Agent Manager acts as your mission control dashboard where you spawn, monitor, and kill autonomous processes.

In a standard VS Code environment, you’re stuck in a linear, synchronous loop—ask a question, wait for an answer, repeat. Antigravity breaks this. You can dispatch five separate agents to handle five distinct bug tickets simultaneously. Each agent keeps its own artifact log, implementation plan, and status update. When you open a folder, the manager immediately prompts for a task. If you’re stuck on specific UI elements, markagent helps you bridge the gap by capturing precise DOM context and CSS selectors, ensuring your agent doesn't hallucinate which button you're trying to fix.

Navigating Agent Modes and Models

Choosing the right model and mode is the difference between a productive session and hitting your quota limit in ten minutes. The Model Selection dropdown is your primary lever for performance versus cost, while the mode toggle switches between Fast and Plan.

The Plan mode isn't just a marketing term; it forces the agent to generate a structured strategy before touching a single line of code. I’ve found that for complex refactors, starting in Plan mode prevents the agent from spiraling into a series of broken commits. For simple CSS tweaks or boilerplate generation, Fast mode is sufficient. Keep an eye on your usage; Gemini 3 Pro quotas are currently limited, and it’s easy to burn through them if you leave agents running in the background on long-lived tasks.

Bridging the Browser Subagent

When you need your agent to interact with live web content, it invokes a specialized browser subagent. This subagent doesn't use your main model; it uses a vision-optimized model to read console logs, capture screenshots, and parse the DOM.

To make this useful, you have to provide the agent with high-quality input. Don't just paste a URL and hope for the best. Use the Antigravity browser extension to permit the subagent to see what you see. If the subagent misses a specific interactive state—like a modal or a dropdown menu—it’s usually because the DOM context was too noisy. This is where capturing targeted screenshots and specific CSS selectors becomes vital. You need to feed the agent the exact state of the UI, not just a vague description of the page.

Orchestrating Parallel Workflows

The real power of Antigravity is the ability to run multiple agents in parallel. You can have one agent refactoring your src/components directory while another writes unit tests in src/tests and a third monitors your terminal for build errors.

This isn't just about speed; it's about context isolation. By giving each agent a narrow scope, you reduce the likelihood of cross-file contamination. When an agent requests a review, you see the diff in the Agent Manager, approve it, and move to the next task. It’s a shift from "writing code" to "validating AI output." If you find yourself constantly typing descriptions of UI bugs, stop. Use your tools to export the state directly to the agent.

Troubleshooting and Feedback

You will hit walls. The current preview is sensitive to local environment configurations, especially on Linux. If you encounter a bug, don't just restart the application. Use the "Report Issue" link under your profile icon in the editor.

For codelab-specific errors, use the "Report a mistake" button provided in the documentation UI. Antigravity relies heavily on user feedback to tune its planning capabilities. If you find the agent consistently misinterpreting your project structure, check your tsconfig.json or equivalent path mappings; the agent is only as good as the context you expose to it. Keep your workspaces clean and your agent tasks granular.

Stop fighting with your IDE's limitations and start managing your agents. The tools are here; you just have to learn how to delegate.