Google Antigravity for Teams: Complete Collaboration & Workflow Guide (2025)

Google Antigravity transforms individual productivity, but the real magic happens when entire teams adopt it. This comprehensive guide covers everything you need to know about using Antigravity collaboratively—from shared configurations to enterprise deployment strategies.

Why Team Adoption Matters

Individual developers see 40-60% productivity gains with Antigravity. Teams that adopt standardized practices see even more:

• Consistent code quality across all contributors
• Faster onboarding for new team members
• Reduced code review friction with AI-enforced standards
• Knowledge sharing through shared AI configurations
• Parallel development with AI handling boilerplate

Setting Up Antigravity for Teams

Step 1: Establish a Team .antigravity File

Create a comprehensive .antigravity file that becomes your team's AI coding standard:

# Team: [Your Team Name]
# Last Updated: 2025-01-01
# Owner: [Tech Lead Email]

## Project Overview
[Brief description of your project and its purpose]

## Team Conventions

### Code Review Requirements
- All AI-generated code must pass human review
- PR descriptions must note which parts were AI-assisted
- Complex logic requires explanatory comments

### AI Usage Guidelines
- Use Agent Mode for boilerplate and CRUD operations
- Manual coding for core business logic
- Always verify AI suggestions for security-sensitive code

## Technical Standards
[Your language-specific rules here]

## Domain Knowledge
[Business logic and terminology AI should understand]

Step 2: Version Control Your AI Configuration

# Commit .antigravity to your repository
git add .antigravity
git commit -m "Add team Antigravity configuration"

# Consider a shared config repository for multi-repo teams
git submodule add https://github.com/yourorg/antigravity-configs

Step 3: Document AI Boundaries

Create clear guidelines for what AI should and shouldn't do:

## AI Boundaries Document

### AI CAN Handle:
✅ Boilerplate code generation
✅ Unit test creation
✅ Documentation generation
✅ Code formatting and refactoring
✅ Type definitions
✅ API endpoint scaffolding

### AI CANNOT Handle Without Review:
⚠️ Authentication/authorization logic
⚠️ Payment processing
⚠️ Data encryption
⚠️ User input validation
⚠️ Database migrations

### AI MUST NOT:
❌ Access production databases
❌ Deploy to production
❌ Modify security configurations
❌ Access external APIs with real credentials

Collaborative Workflows

Workflow 1: AI-Assisted Code Review

Reviewer Setup

# Add to .antigravity for code review context

## Code Review Standards

When reviewing code, check for:
1. Adherence to team style guide
2. Proper error handling
3. Test coverage (minimum 80%)
4. Security considerations
5. Performance implications
6. Documentation completeness

Provide feedback in this format:
- 🔴 BLOCKER: Must fix before merge
- 🟡 SUGGESTION: Recommended improvement
- 💬 COMMENT: Discussion point

Review Process

1. Author creates PR with AI assistance
2. Author notes AI-generated sections in PR description
3. Reviewer uses Antigravity to analyze the diff:

   @git:diff:main
   
   Review this PR against our team standards.
   Flag any concerns, especially in security-sensitive areas.
   

4. Reviewer focuses human attention on flagged areas
5. Author addresses feedback with AI assistance

Workflow 2: Pair Programming with AI

The "AI Sandwich" Pattern

Human → AI → Human

1. Human: Define the task and constraints
2. AI: Generate initial implementation
3. Human: Review, refine, and validate

Real-Time Collaboration

When pair programming:

# Add to .antigravity

## Pair Programming Mode

When generating code during pair sessions:
- Keep implementations simple and readable
- Explain your reasoning in comments
- Stop at logical checkpoints for human review
- Suggest alternatives when multiple approaches exist

Workflow 3: Onboarding New Developers

AI-Assisted Onboarding Checklist

## New Developer Onboarding with Antigravity

### Day 1: Environment Setup
1. Install Google Antigravity IDE
2. Clone team .antigravity configuration
3. Connect to team MCP servers
4. Run: `/codebase Explain the project architecture`

### Day 2: Codebase Orientation
Use these prompts to explore:
- "Explain the authentication flow"
- "How does data flow from API to UI?"
- "What are the main services and their responsibilities?"
- "Show me the database schema relationships"

### Day 3: First Contribution
1. Pick a starter issue
2. Ask Antigravity: "Guide me through fixing issue #123"
3. Follow team PR guidelines
4. Use AI for code review prep

Creating a Team Knowledge Base

# Add domain knowledge to .antigravity

## Domain Glossary

### Users
- **Workspace**: A container for projects, owned by an organization
- **Member**: User with access to a workspace (roles: owner, admin, member, viewer)
- **Seat**: Billable user slot in a workspace

### Billing
- **Plan**: Subscription tier (Free, Pro, Enterprise)
- **Credits**: AI usage units (1 credit = 1 AI request)
- **Overage**: Usage beyond plan limits (billed at $0.01/credit)

### Technical Terms
- **Edge Function**: Serverless function running on Supabase
- **RLS**: Row Level Security (Postgres feature)
- **Webhook**: HTTP callback for event notifications

Workflow 4: Distributed Team Development

Async Collaboration Patterns

## Async Development Guidelines

### Handoff Documentation
When passing work to another timezone:

1. Update `.antigravity` with current context:
   ```markdown
   ## Current Sprint Context
   
   Working on: User authentication refactor
   Completed: OAuth integration
   In Progress: Session management
   Blocked: Waiting for security review
   
   Key decisions made:
   - Using JWT with 15-min expiry
   - Refresh tokens stored in httpOnly cookies

2. Create context snapshot:

   /save-context auth-refactor-handoff
   

3. Document in team channel: "Context saved as auth-refactor-handoff. Pick up from session management."

Receiving Handoff

1. Load context: /load-context auth-refactor-handoff
2. Ask: "Summarize where we left off and next steps"
3. Continue development

## Team Configuration Strategies

### Strategy 1: Monorepo Configuration

your-monorepo/ ├── .antigravity # Root rules (shared across all) ├── apps/ │ ├── web/ │ │ └── .antigravity # Web-specific overrides │ ├── mobile/ │ │ └── .antigravity # Mobile-specific rules │ └── api/ │ └── .antigravity # API-specific rules ├── packages/ │ ├── ui/ │ │ └── .antigravity # Component library rules │ └── shared/ │ └── .antigravity # Shared utilities rules

**Root .antigravity:**
```markdown
# Monorepo Root Configuration

## Shared Conventions
- TypeScript strict mode everywhere
- Consistent import aliases (@app/, @packages/)
- Shared prettier/eslint config
- Unified testing strategy

## Cross-Package Rules
- No circular dependencies between packages
- Shared types live in packages/shared
- UI components only in packages/ui

Strategy 2: Polyrepo Configuration

For multiple repositories, maintain a central config:

# Central config repository
antigravity-configs/
├── base.antigravity           # Common rules
├── frontend.antigravity       # Frontend projects
├── backend.antigravity        # Backend projects
├── mobile.antigravity         # Mobile projects
└── ml.antigravity             # ML/Data projects

Each project pulls from central:

# Project .antigravity

<!-- Include base configuration -->
@include https://github.com/yourorg/antigravity-configs/base.antigravity
@include https://github.com/yourorg/antigravity-configs/frontend.antigravity

## Project-Specific Overrides
[Your overrides here]

Strategy 3: Role-Based Configurations

Different roles need different AI behaviors:

# For Junior Developers
## AI Assistance Level: High

- Provide detailed explanations with code
- Include learning resources in responses
- Show multiple approaches when relevant
- Add extensive comments in generated code

# For Senior Developers  
## AI Assistance Level: Minimal

- Concise responses, minimal explanation
- Skip basic concepts
- Focus on edge cases and performance
- Assume knowledge of patterns

# For Tech Leads
## AI Assistance Level: Strategic

- Focus on architecture implications
- Include maintenance considerations
- Flag technical debt
- Suggest team documentation updates

Enterprise Deployment

Security Considerations

## Enterprise Security Configuration

### Data Handling
- No customer PII in AI prompts
- Mask sensitive values in examples
- Use placeholder data for demos

### Access Control
- AI cannot access production environments
- Staging credentials only
- Audit logging enabled

### Compliance
- SOC 2 compliant configuration
- GDPR data residency (EU servers)
- AI suggestion retention: 30 days

Centralized Management

For large organizations:

// antigravity-enterprise.json
{
  "organization": "YourCorp",
  "policies": {
    "allowedModels": ["gemini-3-pro"],
    "contextLogging": true,
    "auditRetention": "90days",
    "approvedMCPServers": [
      "supabase",
      "github",
      "sentry"
    ]
  },
  "teams": {
    "frontend": {
      "config": "./configs/frontend.antigravity",
      "members": ["team-frontend@yourcorp.com"]
    },
    "backend": {
      "config": "./configs/backend.antigravity",
      "members": ["team-backend@yourcorp.com"]
    }
  }
}

Training & Certification

Team Training Program

Week 1: Fundamentals

• Antigravity installation and setup
• Basic AI chat and completions
• .antigravity file basics

Week 2: Productivity

• Agent Mode introduction
• Keyboard shortcuts mastery
• Context management

Week 3: Advanced

• Multi-file refactoring
• Custom MCP servers
• Team workflows

Week 4: Best Practices

• Security considerations
• Code review with AI
• Troubleshooting common issues

Certification Checklist

## Antigravity Team Certification

### Basic (Required for all devs)
- [ ] Complete environment setup
- [ ] Successfully use inline AI assistance
- [ ] Create a component with Agent Mode
- [ ] Pass AI-generated code review

### Advanced (For senior devs)
- [ ] Configure custom .antigravity rules
- [ ] Set up team MCP servers
- [ ] Lead an AI-assisted code review
- [ ] Onboard a new team member

### Admin (For tech leads)
- [ ] Manage team configurations
- [ ] Set up enterprise policies
- [ ] Monitor AI usage metrics
- [ ] Conduct AI training sessions

Measuring Team Success

Key Metrics to Track

## AI Productivity Metrics

### Velocity Metrics
- Story points per sprint (before/after)
- Time to first commit for new features
- PR review turnaround time

### Quality Metrics
- Bug rate in AI-assisted vs manual code
- Test coverage changes
- Security vulnerability count

### Adoption Metrics
- % of commits with AI assistance
- Agent Mode usage frequency
- MCP server utilization

### Satisfaction Metrics
- Developer experience surveys
- AI suggestion acceptance rate
- Time saved estimates

ROI Calculation

Monthly AI Cost: $20/developer × 10 developers = $200

Time Saved: 10 hours/developer/month × 10 developers = 100 hours
Hourly Rate: $75/hour (loaded cost)
Value of Time Saved: 100 × $75 = $7,500

Monthly ROI: ($7,500 - $200) / $200 = 3,650%

Common Team Challenges & Solutions

Challenge 1: Inconsistent AI Usage

Problem: Some devs use AI constantly, others never.

Solution:

• Mandatory AI training for all
• Pair juniors with AI-proficient seniors
• Track and share success stories
• Set team AI usage goals

Challenge 2: Over-Reliance on AI

Problem: Developers accepting code without understanding.

Solution:

• Require explanation comments for AI code
• Code review specifically checks AI understanding
• Quiz developers on their AI-generated code
• Rotate "AI-free" sprints for skill maintenance

Challenge 3: Configuration Drift

Problem: .antigravity files diverge across projects.

Solution:

• Central config repository
• Automated config validation in CI
• Quarterly config reviews
• Config change requires tech lead approval

Challenge 4: Security Concerns

Problem: Sensitive data leaking to AI.

Solution:

• Pre-commit hooks checking for secrets
• .antigravityignore for sensitive files
• Regular security audits of AI prompts
• Enterprise data residency options

Quick Start Checklist

## Team Antigravity Setup Checklist

### Week 1
- [ ] Install Antigravity for all team members
- [ ] Create initial team .antigravity file
- [ ] Commit configuration to repository
- [ ] Schedule team training session

### Week 2
- [ ] Connect essential MCP servers (GitHub, DB)
- [ ] Document AI usage guidelines
- [ ] Set up code review process
- [ ] Create onboarding documentation

### Week 3
- [ ] Run first AI-assisted sprint
- [ ] Collect feedback from team
- [ ] Refine .antigravity configuration
- [ ] Address security concerns

### Week 4
- [ ] Establish metrics tracking
- [ ] Plan advanced training
- [ ] Document lessons learned
- [ ] Share success stories

Conclusion

Adopting Google Antigravity as a team multiplies the benefits exponentially. With shared configurations, standardized workflows, and clear guidelines, your entire organization can code faster, more consistently, and with higher quality.

Start with the basics—a shared .antigravity file and team training—then progressively add advanced workflows as your team gains confidence.

Ready to get started? Check out our .antigravity templates for team configurations, or explore MCP servers to connect your team's tools to Antigravity.

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Last updated: December 2024 Have team adoption tips to share? Join our community!