Team Collaboration with AI: Scaling AI Development

/company-patterns/
  api-endpoint-template.md
  react-component-template.md
  database-migration-template.md
  testing-template.md
  
/coding-standards/
  naming-conventions.md
  error-handling-patterns.md
  security-requirements.md
  performance-guidelines.md

# API Endpoint Template

Use this prompt for all new API endpoints:

"Create a REST API endpoint that:
- Follows our company REST conventions (see docs/api-standards.md)
- Uses our standard authentication middleware
- Implements proper error handling with our custom error classes
- Includes input validation using Joi schemas
- Has comprehensive logging with Winston
- Returns responses in our standard format: {success, data, message, error}
- Includes rate limiting (100 requests/minute)
- Has complete JSDoc documentation"

# Create prompts repository
git init company-ai-prompts
cd company-ai-prompts

# Structure
mkdir -p {frontend,backend,database,testing,deployment}
mkdir -p {patterns,standards,templates}

# Add prompts with versioning
git add .
git commit -m "Add initial prompt collection v1.0"
git tag v1.0

# Prompt Version History

## v1.2 - API Endpoint Template
- Added rate limiting requirement
- Enhanced error handling patterns
- Improved documentation standards

## v1.1 - React Component Template  
- Added TypeScript strict mode
- Enhanced accessibility requirements
- Updated testing patterns

{
  "ai": {
    "model": "claude-3.5-sonnet",
    "temperature": 0.1,
    "maxTokens": 2000,
    "contextLength": 8000
  },
  "codeStyle": {
    "formatter": "prettier",
    "linter": "eslint",
    "typescript": true
  },
  "prompts": {
    "repository": "https://github.com/company/ai-prompts",
    "version": "v1.2"
  }
}

{
  "cascade": {
    "teamMode": true,
    "sharedContext": "company-standards",
    "collaborativeEditing": true
  },
  "templates": {
    "source": "team-repository",
    "autoUpdate": true
  }
}

#!/bin/bash
# AI Development Environment Setup

echo "Setting up team AI development environment..."

# Install AI IDE
if [[ "$OSTYPE" == "darwin"* ]]; then
    # macOS
    curl -O https://windsurf.com/download/mac
    sudo installer -pkg windsurf.pkg -target /
elif [[ "$OSTYPE" == "linux-gnu"* ]]; then
    # Linux
    wget https://windsurf.com/download/linux
    sudo dpkg -i windsurf.deb
fi

# Clone prompt library
git clone https://github.com/company/ai-prompts.git ~/ai-prompts

# Install extensions
windsurf --install-extension company.ai-templates
windsurf --install-extension company.code-standards

# Apply team settings
cp ~/ai-prompts/config/windsurf-settings.json ~/.windsurf/settings.json

echo "Team AI environment ready! 🚀"

Review this code for our team standards:
- Follows naming conventions (camelCase for functions, PascalCase for components)
- Has proper error handling
- Includes TypeScript types
- Has unit tests
- Meets accessibility requirements
- Follows security best practices
- Has appropriate comments/documentation

Analyze this code change for architectural consistency:
- Follows our MVC pattern
- Uses established data layer patterns  
- Maintains separation of concerns
- Integrates properly with existing systems
- Doesn't introduce breaking changes

#!/bin/bash
# .git/hooks/pre-commit

echo "Running AI code validation..."

# Get staged files
staged_files=$(git diff --cached --name-only --diff-filter=ACM | grep -E "\.(js|ts|jsx|tsx)$")

for file in $staged_files; do
  # Check if file follows team standards
  ai_check=$(cursor-ai validate --file "$file" --standards team-standards.json)
  
  if [[ $ai_check == *"FAIL"* ]]; then
    echo "❌ $file failed team standards check"
    echo "$ai_check"
    exit 1
  fi
done

echo "✅ All files pass team standards"

Estimate development time for this user story:
"As a user, I want to upload and manage my profile photos"

Consider our tech stack:
- React + TypeScript frontend
- Node.js + Express backend  
- PostgreSQL database
- AWS S3 for storage

Include time for:
- UI components
- API endpoints
- Database changes
- Testing
- Code review

Analyze our codebase for technical debt:
- Identify outdated patterns
- Find duplicated code
- Suggest refactoring priorities
- Estimate effort for improvements
Consider our current sprint capacity and team skills.

feat: Add user authentication (AI-generated with custom prompts)

Generated using:
- Prompt: "Secure JWT auth with refresh tokens"
- Templates: auth-flow-template-v1.2
- Manual modifications: Error handling, validation

AI-Generated: 85%
Manual: 15%

ai/feature/user-dashboard-v2
ai/refactor/api-optimization
ai/bugfix/memory-leak-components

/**
 * User Authentication Service
 * 
 * @generated AI-assisted development
 * @prompt "Create secure authentication service with JWT"
 * @template auth-service-template-v1.3
 * @model claude-3.5-sonnet
 * @human_modifications Added rate limiting, custom validation
 * @review_status Approved by senior engineer
 */
class AuthService {
  // Implementation
}

Team Session: Building Payment Integration

Person A: "Let's create the Stripe integration"
Person B: "What about error handling for failed payments?"
Person C: "Include webhook processing for status updates"

Combined Prompt:
"Create a complete Stripe payment integration that:
- Processes one-time and subscription payments
- Handles all error scenarios gracefully
- Includes webhook handlers for payment status
- Has comprehensive logging and monitoring
- Follows PCI compliance requirements
- Includes unit and integration tests"

Company Policy for AI IDE Usage:
- Never include real customer data in prompts
- Use anonymized/mock data for examples
- Regular security reviews of AI-generated code
- Audit trails for AI assistance usage

Legal Framework:
- AI-generated code belongs to company
- Developers must review all AI output
- Document AI usage for compliance
- Regular training on AI ethics