Master Google Antigravity: A Complete Guide to the AI‑Powered IDE

Introduction

Google Antigravity is an advanced AI programming assistant developed by Google DeepMind. It uses Gemini 3 and other cutting‑edge models to act as a collaborative partner rather than a simple code‑completion tool. The assistant can understand whole project structures, plan and execute complex end‑to‑end tasks, and works across editors, terminals, and browsers.

Installation & Setup

Note: Antigravity typically runs as an IDE plugin (e.g., VS Code).

Install the plugin – search for “Antigravity” in your IDE’s extension marketplace and install it.

Log in / Activate – after installation, sign in with a Google account or provide an authorization token.

Open the sidebar – click the Antigravity icon in the IDE sidebar to open the chat window.

Index the codebase – on first project open, Antigravity builds a local index; wait briefly for it to finish.

Core Operations

Basic Conversation

Enter natural‑language queries directly in the chat window, such as “Explain what this code does” or “Write a Vue component with an input and submit button.”

Context References (@)

Use the @ symbol to tell the assistant which files or code blocks to focus on.

@Files – reference a specific file, e.g., @src/utils/index.js Please refactor this file. @Codebase – search the entire codebase, e.g., @Codebase Find all occurrences of gotoFaceCheck. @Docs – reference documentation files.

Agentic Mode

When you submit a complex request (e.g., “refactor the entire authentication flow”), Antigravity enters Agentic Mode and automatically creates the following artifacts: task.md – a task list that tracks progress step by step. implementation_plan.md – a detailed plan generated before any code is written; you review and approve it before the assistant proceeds. walkthrough.md – a verification document summarizing what was changed and how to test it.

Operation Modes

Planning Mode

The default Agentic mode for complex, multi‑file tasks. It performs deep codebase analysis, generates structured artifacts ( task.md, implementation_plan.md), asks for user confirmation before critical steps, and continuously self‑corrects errors.

When to trigger – requests that involve multiple files, complex logic, or explicit “create a plan” instructions automatically switch to this mode.

Fast Mode

A lightweight interaction mode for quick Q&A and simple code edits. The assistant replies immediately without generating any artifact files.

When to trigger – simple direct commands such as “explain this function” or “fix this typo” default to Fast Mode.

Mode Comparison

Speed – Planning Mode is slower due to planning; Fast Mode is instant.

Complexity – Planning Mode handles high‑complexity, multi‑file tasks; Fast Mode is suited for low‑complexity, single‑point issues.

Safety – Planning Mode offers high safety with plan review; Fast Mode relies on the user to verify output.

Artifacts – Planning Mode generates task.md, implementation_plan.md, and walkthrough.md; Fast Mode generates none.

Selection advice : Use Planning Mode for uncertain impact or core‑business changes; use Fast Mode for quick bug fixes or isolated code snippets.

Antigravity vs Cursor

Both are powerful AI coding tools but differ in design focus.

Positioning – Antigravity is an Agentic AI Assistant; Cursor is an AI‑first code editor.

Core strength – Antigravity excels at planning, multi‑file coordination, and self‑correction; Cursor shines at rapid code completion and inline editing.

Interaction – Antigravity uses a sidebar chat and generates planning artifacts; Cursor integrates directly into the editor with shortcuts like Cmd+K.

Thinking depth – Antigravity performs deliberate planning; Cursor favors speed and fluidity.

Pros & Cons

Antigravity

✅ Strong at handling complex, cross‑file refactoring and generating comprehensive plans.

✅ High reliability with self‑correction and deep context understanding.

❌ Slower due to planning overhead.

❌ Longer interaction flow because of plan review steps.

Cursor

✅ Extremely fast code completion and generation.

✅ Seamless editor integration, low learning curve.

❌ Lacks global planning; struggles with cascading changes across files.

❌ May produce “hallucinations” in complex logic, requiring careful manual review.

When to choose which

Use Cursor for new code writing, frequent auto‑completion, or quick single‑function edits.

Use Antigravity for large‑scale refactoring, multi‑file bug investigation, or designing new features that need a detailed plan.

Conclusion : The tools are complementary; employ Cursor for everyday fast coding and switch to Antigravity for challenging, high‑impact tasks.

Case Studies

Case 1 – Refactoring Legacy Code

Scenario : Replace all calls to gotoFaceCheck with a new H5 link redirect.

Enter the command:

@Codebase Help me refactor gotoFaceCheck to support H5 redirects and update all references.

Antigravity generates an implementation_plan.md listing affected files ( src/utils/index.js, related .vue pages). After reviewing, confirm the plan.

The assistant creates a task.md, opens each file, applies changes (using multi_replace_file_content), and attempts to fix any lint errors automatically.

Review the generated walkthrough.md to verify modified files and test steps.

Case 2 – Adding a New Feature Page

Scenario : Create a mock face-check page with three buttons (success, failure, exception) that call a callbackUrl.

Command:

@src/pages/ Add a new face-check directory with js, vue, html files. Include three buttons that trigger the callback URL.

Antigravity plans the file structure, then uses write_to_file to create src/pages/face-check/face-check.vue and related files, filling in Vue template, style, and logic.

Run the project and open /face-check.html to test the page.

Best Practices

Clear instructions – Describe requirements precisely, e.g., “change background color to #f0f0f0 and font size to 14px.”

Small steps – For very large tasks, split them into several smaller Task items.

Leverage @ references – Accurate context references dramatically improve answer quality.

Monitor artifacts – Keep an eye on task.md and implementation_plan.md to ensure the AI’s reasoning aligns with yours.