🎯 Summary

Implements PR#2: User Guide Prompt & Self-Updating Intelligence from the autopilot design documents. This adds sophisticated learning capabilities that automatically improve guide prompts based on user guidance patterns.

✨ Key Features

Guide Prompt Configuration

• Users can set custom guidance instructions via UI (accessible with 'G' key)
• Instructions are injected into LLM analysis for personalized autopilot behavior
• Persistent configuration stored in CCManager settings

Automatic Pattern Learning

• Tracks user guidance patterns in the background when learning is enabled
• LLM-based analysis extracts recurring themes across 5 categories:
  • Style: Code formatting, naming conventions, language features
  • Workflow: Testing approaches, development processes, tool usage
  • Architecture: Component structure, design patterns, organization
  • Testing: When/what to test, testing tools and frameworks
  • Communication: Level of detail, explanation preferences

Privacy-First Design

• Opt-in learning: Disabled by default, user must explicitly enable
• 30-day retention: User input patterns automatically deleted after 30 days
• Auto-approval: No manual review required - patterns with ≥70% confidence are automatically applied
• Transparent operation: Clear UI indicators and explanations

Quality Assurance

• Confidence thresholds: Only patterns with ≥70% LLM confidence are used
• Duplicate prevention: Smart deduplication prevents redundant patterns
• Safe evolution: Built-in validation ensures prompt updates are beneficial
• Error resilience: Graceful fallbacks when LLM analysis fails

🏗 Technical Implementation

New Services

• PatternTrackerService: Monitors user inputs with privacy controls
• PatternLearnerService: LLM-based extraction of guidance themes
• PromptEvolverService: Generates improved prompts from learned patterns
• LearningOrchestratorService: Coordinates all learning components

Enhanced Components

• ConfigureAutopilot: New learning configuration screen with retention/confidence controls
• LLMClient: Enhanced to inject user guidance into analysis prompts
• Type System: New interfaces for learning config, patterns, and orchestration

Architecture Highlights

• Event-driven: Reactive architecture using EventEmitter patterns
• Modular design: Each service has single responsibility with clean interfaces
• Extensible: Easy to add new pattern categories or learning strategies
• Performance-focused: Efficient analysis with minimal overhead

📊 Quality Metrics

Test Coverage

• 66+ new tests across 7 new test files
• Comprehensive coverage for all learning functionality
• Mock LLM interactions for reliable testing
• All 351 tests passing including existing functionality

Code Quality

• Type-safe: Full TypeScript support with proper interfaces
• Lint compliance: Passes all ESLint rules and Prettier formatting
• Documentation: Clear inline documentation and helpful UI text
• Error handling: Robust error handling with graceful degradation

🎮 User Experience

Simple Configuration

1. Navigate to Autopilot Configuration (press 'A' in main menu)
2. Set guide prompt with 'G' key - custom guidance instructions
3. Enable learning with 'L' key - automatic pattern improvement
4. Configure retention days and confidence threshold as needed

Automatic Operation

• Learning happens transparently in the background
• High-confidence patterns automatically improve guide prompt over time
• No user intervention required once enabled
• Privacy-respecting with automatic data cleanup

Example Learning Flow

Day 1: User frequently says "Always use TypeScript strict mode"
Day 5: User often corrects "Write tests first" 
Day 10: LLM detects patterns with 85% confidence
Day 10: Guide prompt automatically updated to include both preferences
Day 35: Old input data automatically deleted (privacy protection)

🔮 Foundation for Future

This implementation provides groundwork for:

• Cross-session learning across multiple projects
• Team pattern sharing and collaboration
• A/B testing of guidance effectiveness
• Advanced analytics and insights
• Plugin system for framework-specific patterns

📋 Test Plan

• All existing tests continue to pass (351/351)
• New learning services have comprehensive test coverage
• UI components render correctly with new configuration options
• LLM integration works with guide prompt injection
• Privacy controls function as expected (retention, cleanup)
• Error handling gracefully manages LLM failures
• TypeScript compilation succeeds with no errors
• Linting and formatting requirements met

🚀 Deployment

Ready for immediate deployment:

• No breaking changes to existing functionality
• Backward compatible configuration (learning disabled by default)
• Graceful degradation when LLM is unavailable
• Minimal performance impact on existing operations

Implements design specification from plans/outer-loop-ai-responder-20250802/03-pr2-guide-prompt.md

🤖 Generated with Claude Code