Implement AI-powered recommendations in iOS app

Integrate AI recommendation engine for personalized content

Task

Build native iOS integration for AI-powered content recommendations

Requirements

• Native bridge to Python AI service
• Real-time recommendation updates
• Personalization based on user behavior
• A/B testing framework integration
• Cache recommendations locally
• Offline fallback recommendations

Integration Points

• Depends on ai-recommendation-engine Python service (ai-features&1)
• Use Redux for state management
• WebSocket connection for real-time updates

Implementation Progress

Phase 1: Core Integration

• Setup API client for recommendation service
• Implement authentication flow
• Create recommendation data models
• Add WebSocket connection handler

Phase 2: UI Integration

• Build recommendation UI components
• Implement swipe gestures for feedback
• Add loading states and error handling

Phase 3: Optimization

• Add local caching layer
• Implement offline fallback
• Add A/B testing hooks

Estimated effort

6-8 days

Cross-group dependencies:

• Requires mobile-section&4 (Infrastructure) for deployment
• Integrates with ai-features&1 (AI Services)
• Rolls up to mobile-section&2 > mobile-section&1 > acme-corp&4