Documentation
Everything you need to know about Google Antigravity
Getting Started
Installation guide and first steps
AI Agents
Master autonomous agent capabilities
Browser Extension
Browser integration guide
Core Concepts
Agent-First Architecture
Antigravity is built around the concept of autonomous agents that can independently handle complex development tasks. Unlike traditional IDEs where AI assists you, Antigravity allows you to delegate entire workflows to agents.
Key Benefits: Parallel task execution, automated testing, continuous learning
Artifacts & Verification
Every agent action generates artifacts - tangible deliverables like task lists, implementation plans, screenshots, and test results. This builds trust and provides transparency into what agents are doing.
Artifact Types: Task lists, screenshots, browser recordings, test reports, code diffs
Multi-Surface Integration
Agents operate across three surfaces: the editor (code), the terminal (commands), and the browser (UI testing). This comprehensive access enables end-to-end feature development.
Capabilities: File editing, command execution, web navigation, DOM inspection
Learning & Knowledge Base
Agents maintain a knowledge base of useful patterns, solutions, and context from past tasks. This allows them to improve over time and apply learned patterns to new situations.
What's Saved: Code snippets, architecture patterns, debugging solutions, API patterns
Key Features
๐ฏ Editor View
- โข AI-powered tab completions
- โข Inline refactoring commands
- โข Multi-file contextual editing
- โข Smart code suggestions
๐๏ธ Agent Manager
- โข Deploy multiple agents in parallel
- โข Monitor real-time progress
- โข Configure autonomy levels
- โข Review and approve actions
๐งช Testing & Validation
- โข Automated UI testing
- โข Unit test generation
- โข Visual regression detection
- โข Browser-based verification
๐ Multi-Model Support
- โข Gemini 3 Pro (default)
- โข Claude Sonnet 4.5
- โข OpenAI GPT models
- โข Switch models per task
Common Workflows
Feature Development Workflow
- 1.Plan: Describe the feature to an agent. It creates a task list and implementation plan.
- 2.Implement: Agent writes code across multiple files, installs dependencies, and sets up configuration.
- 3.Test: Agent launches the application in the browser and verifies functionality.
- 4.Review: Check artifacts (screenshots, test results) and provide feedback if needed.
Bug Fixing Workflow
- 1.Reproduce: Describe the bug. Agent reproduces it in the browser and captures evidence.
- 2.Investigate: Agent examines related code, logs, and stack traces to identify root cause.
- 3.Fix: Agent implements the fix and creates regression tests.
- 4.Verify: Agent runs tests and confirms the bug is resolved.
Best Practices
โ DO
- โ Provide clear, specific task descriptions
- โ Break complex features into smaller tasks
- โ Review artifacts regularly
- โ Start with lower autonomy, increase as you build trust
- โ Save useful patterns to agent knowledge base
- โ Provide feedback to improve agent performance
โ DON'T
- โ Give vague instructions like "make it better"
- โ Skip artifact review for critical changes
- โ Deploy agents with full autonomy on unfamiliar codebases
- โ Ignore agent questions or requests for clarification
- โ Forget to version control before major agent tasks
- โ Mix unrelated features in a single agent task
Additional Resources
Community Resources
๐ก Need Help?
This is a community resource for Google Antigravity. For official support and latest updates, visit the Google Developers Blog.