Google Antigravity: Revolutionary AI Coding Platform

Software development is witnessing a paradigm shift with the launch of Google Antigravity, a groundbreaking agentic development platform that transforms AI from a coding assistant into an autonomous software partner. Released on November 18, 2025, alongside the powerful Gemini 3 Pro model, Antigravity represents Google’s vision for agent-first development where AI handles complex, end-to-end programming tasks while you focus on architecture and strategy.

Unlike traditional AI coding assistants that autocomplete lines or answer questions, Antigravity provides autonomous agents capable of planning multi-step workflows, writing production-ready code, testing applications in real browsers, and self-verifying their work—all with minimal human intervention. This comprehensive tutorial guides you through installation, core concepts, navigation, and practical use cases to help you leverage this free, experimental platform effectively.

What Is Google Antigravity?

Google Antigravity is an agent-first integrated development environment (IDE) built on the open-source Visual Studio Code foundation, enhanced with sophisticated AI agent capabilities powered by Gemini 3 Pro. The platform reimagines the developer experience by treating AI agents as collaborative team members rather than simple coding tools.

Core Philosophy: Agent-First Development

Traditional AI coding assistants operate reactively—you write code, they suggest completions. Antigravity inverts this model. You define high-level objectives like “build a finance tracker with user authentication” or “refactor the authentication module,” and autonomous agents break down tasks, generate implementation plans, write code, run tests, and validate results through browser automation.

The platform’s architecture revolves around four foundational tenets:

Trust: Agents produce verifiable Artifacts—task lists, implementation plans, screenshots, and browser recordings—that document their work transparently, replacing opaque action logs with human-readable evidence.

Autonomy: Agents access three primary surfaces: the code editor, terminal, and Chrome browser. This multi-surface access enables complex workflows like spinning up development servers, opening browsers, testing UI interactions, and debugging—without constant prompting.

Feedback: Inline commenting on Artifacts allows mid-task corrections without discarding progress. Similar to Google Docs collaboration, you can annotate specific actions, and agents incorporate feedback iteratively.

Self-Improvement: Agents maintain a knowledge base of past solutions, successful patterns, and problem resolutions, creating reusable playbooks that improve performance over time.

Key Differentiators from Cursor, Copilot, and Windsurf

While tools like Cursor, GitHub Copilot, and Windsurf excel at code suggestions and chat-based assistance, Antigravity distinguishes itself through:

• True Multi-Agent Orchestration: Run multiple agents simultaneously across different workspaces, each handling separate tasks in parallel—like having several junior developers working independently.
• Browser-Based Verification: Agents don’t just write frontend code; they launch your application in an instrumented Chrome browser, interact with UI elements, capture screenshots, record videos, and verify functionality visually.
• Artifact-Driven Transparency: Instead of overwhelming logs or opaque “magic,” agents produce structured documentation at every stage, making their reasoning and actions auditable.
• Free with Generous Limits: During public preview, individual developers access Gemini 3 Pro with rate limits that reset every five hours—no monthly subscription required.

System Requirements and Installation

Prerequisites

Before installing Google Antigravity, ensure your system meets these requirements:

• Operating System: Windows 10/11, macOS 11 or later, or Linux (Ubuntu 20.04+, Fedora 35+)
• RAM: Minimum 8GB (16GB recommended for smooth multi-agent workflows)
• Storage: 500MB for installation plus workspace requirements
• Internet Connection: Required for model API calls and updates
• Google Account: Personal Gmail account for authentication (workspace accounts coming soon)

Step-by-Step Installation Guide

Step 1: Download the Installer

Visit the official download page at antigravity.google/download and select your operating system. The installer packages are available for:

• Windows: .exe installer (approximately 180MB)
• macOS: .dmg file for Intel and Apple Silicon
• Linux: .deb or .tar.gz packages

Step 2: Run the Installation

Launch the downloaded installer and follow the platform-specific instructions. On macOS, you may need to allow the app in System Preferences > Security & Privacy. On Linux, use your package manager or extract the tarball to your preferred location.

Step 3: Initial Configuration

Upon first launch, Antigravity presents a setup wizard with several configuration screens:

Theme Selection: Choose between Light, Dark, or High Contrast themes. This preference can be changed later in settings.

Import Settings (Optional): If migrating from VS Code or Cursor, you can import your existing extensions, keybindings, and preferences. For a fresh start, skip this step.

Agent Autonomy Policy: This critical configuration determines how much independence agents have. Three preset options exist:

• Agent-Driven Development: Turbo terminal execution + Always Proceed review policy. Maximum autonomy; agents execute freely with minimal interruption.
• Agent-Assisted Development (Recommended): Auto terminal execution + Agent Decides review policy. Balanced approach where agents determine when human approval is needed.
• Review-Driven Development: Off terminal execution + Request Review policy. Maximum control; you approve every significant action.

For beginners, Agent-Assisted Development provides the optimal balance of productivity and oversight.

Step 4: Editor Preferences

Configure your coding preferences including font family, size, tab spacing, bracket pair colorization, and minimap visibility. These settings mirror standard VS Code options.

Step 5: Sign In with Google

Authenticate with your personal Gmail account. This opens your browser for OAuth authentication. After successful login, return to the application.

Step 6: Terms of Service

Review and accept the terms of use. Note that Antigravity is experimental with known security limitations (discussed later in this guide).

You’re now ready to start your first agentic development session.

Understanding the Interface: Agent Manager vs Editor View

Google Antigravity features two distinct primary windows, each serving different workflows. Understanding when and how to use each is crucial for productivity.

Agent Manager: Mission Control for Orchestration

The Agent Manager acts as your command center for high-level task orchestration. Think of it as supervising multiple virtual developers working asynchronously.

Key Components:

Inbox: Tracks all active and past conversations with agents. Each conversation represents a distinct task or project thread. Click any conversation to review message history, Artifacts produced, and current status. This persistent history enables context switching—you can leave a task, work on something else, and return seamlessly.

Start Conversation: Initiates new agent sessions. Click to begin fresh tasks in your selected workspace or playground.

Workspaces: Displays all opened project folders. You can add multiple workspaces and specify which workspace context applies to each new conversation. Workspaces provide file system boundaries and project-specific context.

Playground: A scratchpad environment for experimentation without workspace constraints. Perfect for quick prototypes, testing ideas, or learning agent capabilities. Conversations started in Playground can be promoted to full workspaces if needed.

Planning Mode Toggle: Switch between Planning mode (agents create detailed task breakdowns and implementation plans) and Fast mode (agents execute directly for simple, straightforward tasks). Planning mode suits complex workflows; Fast mode accelerates trivial operations.

Model Selection Dropdown: Choose which foundation model powers your agent. Options include Gemini 3 Pro (default), Claude Sonnet 4.5, and GPT-OSS models. Model selection impacts reasoning depth, code quality, and rate limit consumption.

Typical Workflow: Developers use Agent Manager to dispatch high-level instructions across multiple projects. You might have three agents running simultaneously: one refactoring authentication logic in Project A, another generating test suites in Project B, and a third building a new feature in Project C. The Manager view provides status visibility and approval interfaces for all parallel workflows.

Editor View: Traditional IDE with Agent Awareness

The Editor View resembles familiar code editors like VS Code, complete with file explorer, syntax highlighting, and integrated terminal. However, it’s enhanced with agent collaboration features.

Key Components:

File Explorer: Standard directory tree for navigating project files and folders.

Code Editor Pane: Multi-tab editor with full VS Code capabilities including IntelliSense, refactoring tools, and Git integration.

Agent Side Panel: A dedicated panel on the right side for conversing with agents without leaving your code. Highlight specific code blocks and issue inline instructions like “Optimize this function” or “Add error handling here.”

Integrated Terminal: Run commands, start development servers, or execute scripts while agents observe and learn from terminal output.

Inline Command Feature: Highlight code, right-click, and select “Ask Agent” to provide context-aware instructions. This “vibe coding” approach lets you collaboratively edit code with natural language guidance.

Typical Workflow: Developers switch to Editor View when they need hands-on control, want to review agent-generated code in detail, or prefer making manual edits while occasionally consulting the agent for specific suggestions.

Toggling Between Views

Use the Open Agent Manager and Open Editor buttons in the top-right corner, or press Cmd + E (Mac) / Ctrl + E (Windows/Linux) to toggle instantly between modes. This keyboard shortcut becomes second nature with regular use.

Setting Up the Browser Agent

One of Antigravity’s most powerful features is browser automation through specialized browser subagents. These enable agents to visually test web applications, interact with UI elements, capture screenshots, and verify functionality—mimicking real user behavior.

Why Browser Integration Matters

When building web applications, verifying that buttons click correctly, forms submit properly, and layouts render as expected traditionally requires manual testing or complex Selenium scripts. Antigravity’s browser agents automate this entirely, running verification loops where agents:

1. Write frontend code
2. Start development server
3. Open application in browser
4. Interact with UI (clicking buttons, filling forms)
5. Capture screenshots and videos
6. Compare results with expected behavior
7. Debug and iterate automatically

Installing the Browser Extension

The browser agent requires a Chrome extension installation. Here’s how to set it up:

Step 1: Trigger Browser Task

Start a conversation in Agent Manager or Playground and give an instruction that requires web interaction:

textGo to antigravity.google and summarize the key features

Step 2: Setup Prompt

When the agent determines browser access is needed, it displays a prompt: “Browser agent setup required. Click Setup to install the extension.”

Click Setup.

Step 3: Install Extension

Chrome launches automatically, directing you to the Antigravity extension page. Click Add to Chrome > Add Extension.

Step 4: Confirmation

Return to Antigravity. The agent confirms successful connection and proceeds with the browser task. You’ll see a distinctive blue border around browser windows controlled by agents—visual confirmation that automation is active.

Step 5: Permissions

The first time an agent attempts browser actions (navigation, clicking, form filling), Antigravity requests permission. You can approve once, approve always for this task, or deny. Your approval preferences are remembered.

Browser Agent Capabilities

Once configured, browser agents can:

• Navigate to URLs and follow links
• Click buttons, checkboxes, and interactive elements
• Fill input fields and submit forms
• Scroll pages and expand collapsible sections
• Read page content through DOM capture or markdown conversion
• Capture full-page screenshots at any point
• Record screen videos of entire interaction sequences
• Read console logs and detect JavaScript errors
• Wait for dynamic content (spinners, loading states)
• Verify visual appearance against expected designs

These capabilities transform frontend development workflows, enabling true test-driven development where agents write tests, implement features, and automatically validate correctness.

Understanding Artifacts: The Trust Layer

Traditional AI systems either show overwhelming technical logs or hide everything behind “trust me” outputs. Antigravity solves this with Artifacts—structured, human-readable documentation that agents produce throughout their workflow.

What Are Artifacts?

Artifacts are verifiable proof-of-work objects that explain what agents plan to do, what they’re doing, and what they’ve accomplished. They bridge the gap between opaque AI processes and developer understanding.

Types of Artifacts

Task List Artifact: When you give agents complex instructions, they first generate a structured task list breaking the objective into logical steps. Each step includes:

• Clear description of the sub-task
• Estimated complexity or time
• Dependencies on other tasks
• Success criteria

You can review this plan, comment on specific tasks, request changes, or approve proceeding.

Implementation Plan Artifact: After task decomposition, agents create detailed implementation plans specifying:

• Files to be created or modified
• Code structure and architectural decisions
• Libraries or dependencies to install
• Testing strategies
• Edge cases to handle

This artifact serves as a technical specification, allowing you to catch architectural issues before any code is written.

Walkthrough Artifact: Once implementation completes, agents produce walkthroughs documenting:

• What was built and how it works
• Key code sections with explanations
• How to run, test, and deploy the application
• Known limitations or future improvements

Walkthroughs often include screenshots, terminal output, and browser recordings as evidence.

Media Artifacts: Screenshots and screen recordings captured during browser testing. These visual artifacts let you verify UI behavior without running the application yourself.

Verification Artifacts: Logs of automated tests run by agents, including:

• Unit test results with pass/fail status
• Integration test outputs
• Performance metrics
• Error logs (if any issues arose)

Interacting with Artifacts

Artifacts support inline commenting similar to Google Docs. Click any section of an artifact, leave a comment like “Use TypeScript instead of JavaScript” or “Add input validation here,” and agents incorporate feedback in subsequent iterations—no need to restart from scratch.

The Artifacts Panel toggles on/off via the button in the top-right corner. When enabled, artifacts display alongside conversation threads, providing contextual documentation as agents work.

Practical Use Cases and Tutorials

Now that you understand Antigravity’s core concepts, let’s explore hands-on tutorials demonstrating real-world applications.

Use Case 1: Automating Web Research and Data Extraction

Objective: Visit a news website, extract top headlines, and summarize them by category.

Instructions:

1. Open Agent Manager and select Playground.
2. Ensure the browser extension is installed (if not, follow setup steps above).
3. Give the agent this prompt:

textVisit Google News at news.google.com, extract the top 10 headlines, 
and organize them by category (World, Technology, Business, etc.). 
Provide a summary of each story.

What Happens:

• Agent analyzes the task and creates a Task Artifact outlining steps: launch browser, navigate to site, extract headlines, categorize, summarize.
• Browser subagent launches Chrome with blue border, navigates to news.google.com.
• Agent reads page content using DOM capture or markdown parsing.
• Extracts headline text and associated metadata.
• Uses LLM capabilities to categorize and summarize.
• Produces final Walkthrough Artifact with organized headlines.

Artifacts Produced:

• Screenshot of Google News homepage
• Video recording of browser navigation
• Text output with categorized summaries

Customization Ideas:

• Change target website to industry-specific news sources
• Ask agent to track sentiment (positive/negative news)
• Request comparison of headlines across multiple news sites
• Schedule periodic runs (though Antigravity currently lacks built-in scheduling, you could combine with external cron jobs)

Use Case 2: Building a Full-Stack Web Application

Objective: Create a Python Flask application for a one-day technical conference with speaker profiles, schedules, and search functionality.

Instructions:

1. Open Agent Manager and create or select a Workspace folder (e.g., my-conference-app).
2. Set Planning mode and select Gemini 3 Pro model.
3. Provide detailed specifications:

textBuild a one-day technical conference website with these requirements:

1. Home page displaying event date, location, and full schedule
2. Eight technical talks throughout the day with a 60-minute lunch break
3. Each talk includes: unique ID, title, 1-2 speakers, category tags, 
   description, and time slot
4. Speaker profiles with first name, last name, and LinkedIn URL
5. Search functionality by speaker name, talk title, or category
6. Use dummy data focused on Google Cloud technologies
7. Tech stack: Python + Flask backend, HTML/CSS/JavaScript frontend
8. Include comprehensive README with setup and usage instructions
9. Test the application thoroughly and launch it for review

Agent Workflow:

Task Planning Phase: Agent generates Task Artifact with sequence:

• Set up project structure (folders for templates, static assets, etc.)
• Install Flask and dependencies
• Create data models for talks and speakers
• Generate dummy data based on Google Cloud theme
• Build backend routes (home, schedule, search API)
• Design frontend templates with responsive CSS
• Implement search functionality
• Write automated tests
• Launch development server
• Verify functionality in browser

Implementation Phase: Agent creates Implementation Artifact detailing:

• File structure (app.py, models.py, templates/index.html, etc.)
• Database schema (SQLite or in-memory)
• API endpoints and routing logic
• Frontend design approach (Bootstrap or custom CSS)
• Search algorithm (keyword matching, filtering)

Execution Phase: Agent writes code files, which you can monitor in real-time via the Editor View. It installs packages via terminal, handles port conflicts (e.g., if port 5000 is busy, tries 5001, 5002, etc.).

Testing Phase: Agent launches Flask server, opens browser, interacts with site (searches for speakers, clicks talks, verifies schedule display), captures screenshots and videos, and validates that all requirements are met.

Verification Phase: Agent produces Walkthrough Artifact with:

• Complete application overview
• Screenshots of home page, speaker profiles, search results
• Video recording of browser testing
• README file content
• Instructions: python app.py to run, visit localhost:8080

What You Get:

A fully functional conference website ready to customize. Switch to Editor View to explore generated files, modify styling, add more talks, or integrate real data sources.

Follow-Up Instructions:

textAdd two more talks to the schedule and update the UI to highlight 
keynote speakers with a special badge.

Agent updates Task and Implementation Artifacts, modifies code, reruns tests, and verifies changes—all autonomously.

Use Case 3: Creating a Productivity Web App with Custom Design

Objective: Build a Pomodoro timer application with aesthetic, calming UI design.

Instructions:

1. Start new conversation in Playground.
2. Give simple, open-ended prompt:

textCreate a productivity app featuring a Pomodoro timer. 
Use a calm, aesthetic design with soothing colors and smooth animations.

Agent Workflow:

• Interprets “Pomodoro timer” (25-minute work sessions, 5-minute breaks).
• Chooses appropriate tech stack (likely HTML/CSS/JavaScript for simplicity).
• Designs UI with timer display, start/pause/reset buttons, session counter.
• Applies calming color palette (soft blues, greens, or pastels).
• Adds smooth transitions and animations.
• Launches browser, tests timer functionality, captures video.
• Presents final Walkthrough with screenshot and demo video.

Iterative Refinement:

After initial version, provide feedback:

textAdd a motivational quote that changes with each session. 
Also, include an hourglass icon with transparent background.

Agent updates Implementation Artifact, generates or sources transparent hourglass image, integrates motivational quotes API or hardcoded list, and reruns verification.

Result: A polished Pomodoro app ready for personal use or deployment.

Use Case 4: Generating and Validating Unit Tests

Objective: Automatically generate comprehensive unit tests for existing Python code and verify they pass.

Setup:

1. Create workspace folder containing your Python module (e.g., order_service.py with business logic for e-commerce orders).
2. Open workspace in Agent Manager.
3. Reference the specific file using @ symbol:

text@order_service.py - Analyze this module and explain its functionality.

Agent provides detailed breakdown of classes, methods, dependencies, and logic flow.

Generate Tests:

textGenerate comprehensive unit tests for @order_service.py. 
Include mock implementations for external dependencies 
(InventoryService, PaymentGateway). Test edge cases, error handling, 
and validation logic. Execute tests and confirm they all pass.

Agent Actions:

• Creates test_order_service.py with pytest or unittest framework.
• Writes mock classes/functions to simulate external services.
• Generates test cases covering:
  • Normal checkout flow
  • Empty cart validation
  • Insufficient inventory scenarios
  • Payment failures
  • Price validation (negative prices, zero quantities)
  • Discount application logic (VIP vs regular customers)
• Runs tests via terminal: pytest test_order_service.py -v
• Captures terminal output showing all tests passing.
• Produces Verification Artifact with test results.

Outcome: Production-ready test suite with high coverage, automatically validated by the agent.

Use Case 5: Code Refactoring and Documentation

Objective: Refactor legacy code for readability and add comprehensive documentation.

Instructions:

text@legacy_module.py - Refactor this code to follow PEP 8 style guidelines, 
improve variable naming, extract complex logic into smaller functions, 
and add docstrings to all classes and methods.

Agent analyzes code, proposes refactoring plan in Task Artifact, implements changes, and generates before/after comparison in Walkthrough Artifact. You can review diffs directly in Editor View.

Advanced Features and Best Practices

Knowledge Base and Self-Improvement

Antigravity’s Knowledge feature enables agents to save successful code snippets, problem-solving strategies, and reusable patterns. When agents encounter similar challenges in future tasks, they query this knowledge base, accelerating development and maintaining consistency.

Accessing Knowledge: Open Agent Manager settings > Knowledge. Review saved entries, add custom snippets manually, or let agents populate it automatically.

Best Practice: Periodically review knowledge entries to ensure quality and relevance. Remove outdated patterns or deprecated approaches.

Terminal Execution Policies Explained

The Terminal Execution Policy determines how agents interact with your system’s command line:

• Off: Agents never auto-execute commands (except allowlisted safe commands). Maximum security but requires constant manual approval.
• Auto (Recommended): Agents decide which commands need approval. They auto-execute safe operations (reading files, installing packages) but request permission for risky actions (deleting files, system modifications).
• Turbo: Agents execute all commands automatically (except denylisted dangerous operations). Maximum speed but requires trust and sandboxed environments.

Customization: Navigate to Settings > Terminal Policy to manually configure allow/deny lists. For example, always allow npm install but always prompt for rm -rf.

Review Policies and Approval Workflows

The Review Policy governs when agents seek human approval on Artifacts:

• Always Proceed: Agents never pause for review. Use for well-understood, low-risk tasks or when iterating rapidly.
• Agent Decides: Agents determine complexity and risk, pausing for review on critical decisions. Balances autonomy with oversight.
• Request Review: Agents always wait for approval before executing each major step. Maximum control for sensitive projects or learning phase.

Best Practice: Start with “Agent Decides” as you learn Antigravity’s capabilities, then adjust based on project risk tolerance.

Multi-Agent Workflows

One of Antigravity’s signature features is running multiple agents in parallel. This is particularly powerful for:

• Large codebases: Assign different agents to backend, frontend, and testing simultaneously.
• Microservices: Each agent handles a separate service.
• Bug fixes: Multiple agents tackle different bugs in parallel.

How to Use:

1. In Agent Manager, start a new conversation for each task.
2. Assign different workspaces or focus areas to each agent.
3. Monitor all agents via Inbox, reviewing and approving as needed.
4. Agents work asynchronously; you’re not blocked waiting for one to finish.

Limitation: Agent-to-agent communication is not currently supported. Each agent operates independently without collaborating directly with others.

Security Considerations and Best Practices

Antigravity’s terms of service explicitly state “known security limitations,” including risks of:

• Data Exfiltration: Agents might unintentionally send sensitive data to model APIs.
• Malicious Code Execution: Prompt injection attacks could trick agents into running harmful commands.
• Unverified Actions: Agents might execute actions you don’t fully understand.

Mitigation Strategies:

Sandboxed Environments: Use Antigravity in Docker containers, virtual machines, or isolated development environments—never directly on production systems.

Manual Review: Enable “Request Review” policy for sensitive projects. Always verify code and commands before execution.

Avoid Sensitive Data: Don’t process confidential information, credentials, or proprietary code until security matures.

Allowlist Commands: Strictly configure terminal execution allowlists for production-critical workspaces.

Regular Audits: Review Artifacts and agent actions post-task to catch anomalies.

Extending Antigravity with VS Code Extensions

Since Antigravity builds on VS Code’s open-source foundation, it supports thousands of existing extensions. Install language support, linters, themes, and productivity tools via Extensions marketplace (Cmd/Ctrl + Shift + X).

Recommended Extensions:

• Python: Official Python extension for enhanced support
• Prettier: Code formatting across languages
• ESLint: JavaScript linting
• GitLens: Advanced Git integration
• Docker: Container management
• Live Server: Instant local web server for static sites

Note: Some extensions may behave unexpectedly due to Antigravity’s agent modifications. Test thoroughly.

Frequently Asked Questions

Q: Is Google Antigravity completely free?

A: During public preview, Antigravity is free for individual developers using personal Gmail accounts. You receive generous rate limits on Gemini 3 Pro that reset every five hours. Enterprise pricing will be announced for team deployments, likely based on compute consumption rather than per-seat licensing.

Q: How does Antigravity compare to Cursor or GitHub Copilot?

A: Cursor and Copilot excel at inline code suggestions and chat-based assistance but require developers to drive the workflow. Antigravity inverts this—agents autonomously plan, execute, and verify complex multi-step tasks. Antigravity also uniquely integrates browser automation for visual testing, a feature absent in competitors. Performance benchmarks show Antigravity achieves 94% accuracy on refactoring tasks versus Cursor’s 78%, and completes typical backend features 38% faster.

Q: Can I use models other than Gemini 3 Pro?

A: Yes. Antigravity supports Claude Sonnet 4.5 and OpenAI GPT-OSS models via the model selection dropdown. Each model has different strengths—experiment to find what works best for your use case.

Q: What programming languages does Antigravity support?

A: As a general-purpose IDE, Antigravity supports all major languages including Python, JavaScript, TypeScript, Java, Go, Rust, C++, Ruby, PHP, and more. Language-specific features depend on installed extensions and model capabilities.

Q: Can agents write tests and verify code quality automatically?

A: Absolutely. Agents can generate unit tests, integration tests, and end-to-end tests using frameworks like pytest, Jest, or Selenium. They execute tests via terminal, analyze results, and iterate to fix failures—forming closed-loop development cycles.

Q: Does Antigravity work offline?

A: No. Antigravity requires internet connectivity for model API calls to Gemini 3 Pro, Claude, or GPT-OSS. Local models are not currently supported.

Q: How do I report bugs or request features?

A: Visit the official Antigravity community forums or GitHub repository (links available at antigravity.google/docs). Google actively collects feedback during this preview phase.

Q: Can I use Antigravity for production applications?

A: While you can build production-ready code with Antigravity, the platform itself is experimental with known security limitations. Always review generated code thoroughly, run security audits, and test extensively before deploying to production environments.

Q: What happens if I exceed rate limits?

A: When you exceed Gemini 3 Pro rate limits, Antigravity notifies you and provides a countdown timer until limits reset (typically five hours). You can switch to Claude Sonnet or GPT-OSS models if they have remaining quota, or wait for reset.

Q: Can agents access the internet during tasks?

A: Yes, through the browser agent. Agents can navigate websites, extract information, and interact with web applications. However, they don’t have unrestricted API access to arbitrary services unless you configure integrations.

Tips for Maximizing Productivity

Start Simple: Begin with straightforward tasks like “Generate a README for this project” or “Fix linting errors” to build familiarity before tackling complex multi-file refactors.

Iterate Incrementally: Break large projects into smaller conversations. Instead of “Build a complete e-commerce platform,” start with “Create user authentication module,” then “Add product catalog,” etc.

Leverage Comments on Artifacts: Don’t restart tasks when agents misunderstand—leave inline comments correcting course. This saves time and teaches agents your preferences.

Experiment with Models: Gemini 3 Pro excels at complex reasoning and planning. Claude Sonnet may be better for creative writing or natural language tasks. Test different models for different use cases.

Use Playground Generously: The Playground is perfect for prototyping, testing prompts, or learning agent behavior without cluttering your project workspaces.

Review Knowledge Base: Periodically audit saved knowledge to ensure agents learn correct patterns, not accidental mistakes.

Keep Workspaces Organized: Use separate workspace folders for unrelated projects to prevent context confusion.

Conclusion

Google Antigravity marks a significant milestone in the evolution from AI-assisted coding to AI-partnered development. By treating agents as autonomous contributors with planning, execution, and verification capabilities, Antigravity enables developers to operate at a higher abstraction level—defining objectives rather than implementing details.
The platform’s unique combination of multi-agent orchestration, browser-based testing, and artifact-driven transparency addresses key trust and productivity challenges that plagued earlier agentic tools. While still in experimental preview with security considerations to navigate, Antigravity offers a compelling glimpse into the future of software development.

Whether you’re a solo developer prototyping ideas rapidly, a small team scaling development capacity, or an enterprise exploring agentic workflows, Antigravity provides powerful, free tools to transform how you build software. The learning curve is gentle for those familiar with VS Code, and the productivity gains—once you embrace the agent-first mindset—can be substantial.
As the platform matures and Google refines based on community feedback, expect enhanced security, expanded model options, enterprise features, and deeper integrations with cloud services. Now is the ideal time to start experimenting, contributing feedback, and shaping the future of agentic development.

Download Google Antigravity today at antigravity.google/download, and redefine what’s possible when AI becomes your development partner.

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Additional Resources

Official Documentation: antigravity.google/docs
Use Case Gallery: antigravity.google/use-cases
YouTube Channel: @googleantigravity for video tutorials and demos
Community Forum: Join discussions, share projects, and get help from other Antigravity users
Blog Announcement: blog.google/products/gemini/gemini-3 for Gemini 3 and Antigravity launch details

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Disclaimer: Google Antigravity is an experimental platform in public preview. Features, availability, and security characteristics are subject to change. Always review agent-generated code and actions before deploying to production environments. The information in this guide reflects the platform’s state as of November 2025 and may become outdated as Google releases updates.