A Beginner's Guide to Google's Antigravity IDE

Most AI coding tools still work like a smart autocomplete. You type, they suggest, you decide. Google’s Antigravity is built on a different premise entirely: what if the AI didn’t just suggest code, but actually managed the work?

This Antigravity IDE tutorial covers what the platform is, how its core pieces fit together, and what you need to know before writing your first prompt.

What Is the Google Antigravity Agentic Development Platform?

Antigravity is an agent-first IDE released by Google in 2025, currently available in public preview for personal Google accounts in approved regions. It’s designed to feel familiar to developers used to modern code editors—but the experience is fundamentally different.

Instead of a chat panel bolted onto a text editor, Antigravity gives you a Mission Control interface for orchestrating autonomous agents. These agents don’t just write a function when you ask. They plan tasks, generate implementation steps, write code across multiple files, run terminal commands, open a browser to verify results, and iterate based on your feedback.

Think of it less like a coding assistant and more like a junior engineer you can delegate entire tasks to. You can learn more about the platform and its concepts in the official Antigravity documentation.

The Two Sides of the Antigravity Development Workflow

The interface splits into two primary views that you’ll switch between constantly.

Agent Manager: Where You Direct the Work

This is the default view when you launch Antigravity. It’s designed for high-level task orchestration. You describe what you want built—“Create a REST API for user authentication”—and the agent breaks it into a structured plan before touching a single file.

You can run multiple agents in parallel across different workspaces. While one agent refactors your data layer, another can be writing tests. This parallel execution is one of the clearest separations between Antigravity and tools like Cursor or GitHub Copilot, which operate synchronously.

Editor: Where You Review and Refine

The editor view retains everything you’d expect from a modern IDE—file explorer, syntax highlighting, extensions, and an integrated terminal. The difference is the agent side panel, which lets you send highlighted code, terminal output, or error messages directly to the agent.

Artifacts: How the Agent Shows Its Work

One of the more practical features of this AI-agent coding IDE is how it communicates progress. Rather than silently generating code, Antigravity produces Artifacts at each stage:

• Implementation Plan — what the agent intends to build and how
• Task List — a concrete step-by-step breakdown
• Code Diffs — changes you can review before accepting
• Walkthrough — a post-task summary with screenshots or browser recordings

You can comment on any artifact using Google Docs-style inline comments. The agent reads your feedback and adjusts. This feedback loop is what makes the Antigravity development workflow feel collaborative rather than unpredictable.

Planning Mode vs. Fast Mode

Before submitting a task, you’ll choose between two execution modes:

Planning mode produces more artifacts and takes longer. Fast mode skips the planning phase and executes directly. For anything non-trivial, Planning mode is worth the extra time.

What Makes This Different From a Chatbot IDE

The distinction matters. A chatbot IDE responds to prompts one at a time. The Google Antigravity agentic development platform dispatches agents that work through a task end-to-end—including spinning up a browser to verify the UI actually works—without you needing to babysit each step.

It supports multiple AI models (not just Gemini), and the platform is evolving quickly. Settings, policies, and available models will change as it moves out of preview.

Getting Started

You’ll need a personal Google account, Chrome, and a local machine running Mac, Windows, or a supported Linux distribution. Download the installer from antigravity.google/download, run through the setup wizard, and choose Review-driven development as your initial agent policy—it’s the recommended starting point that keeps you in the loop without blocking every action.

Once you’re in, open a workspace folder, switch to Planning mode, and give the agent a focused, specific task. That’s the entire starting workflow.

Conclusion

Antigravity is still early, but the core idea—treating the AI as an autonomous actor rather than a suggestion engine—represents a meaningful shift in how development tools work. Rather than responding to one prompt at a time, it plans, executes, and verifies across multiple files and even a live browser. For developers willing to adapt their workflow around agent orchestration, it’s a platform worth exploring as it matures beyond public preview.

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