🌓 Dark Watcher

A learning-focused Zig implementation of a Windows 11 theme switching application, designed from the ground up for cross-platform expansion and AI-assisted collaborative development.

🎯 Project Vision

Dark Watcher is more than just a theme switching utility—it's a comprehensive learning journey into systems programming with Zig, designed to demonstrate modern development practices with AI assistance while building a genuinely useful application.

🌟 Why Dark Watcher?

• 🔧 Learning First: Every architectural decision optimizes for educational value and skill development
• 🤖 AI-Collaborative: Structured for effective partnership with AI coding assistants
• 🚀 Architecture Driven: Comprehensive planning and design before implementation
• 🌍 Cross-Platform Vision: Built for 65-70% code sharing across Windows, macOS, and Linux
• 📖 Open Learning: Documenting the entire learning process for the community

🏗️ Current Project Status

Phase: Comprehensive Architecture & Design

We're currently in the foundational design phase, with a complete architectural blueprint ready for implementation.

✅ Completed:
Comprehensive project architecture design
Cross-platform abstraction layer specification

Complete module breakdown and responsibility mapping
Build system configuration and dependency management
AI collaboration workflow optimization
24-week implementation roadmap with learning milestones

🚧 Next Phase: Core Implementation (Weeks 1-8)
Development environment setup and toolchain configuration
Platform abstraction layer implementation
Windows registry operations and theme switching
Global hotkey system with Win32 integration
Configuration management with YAML support
Background service architecture

🎓 Learning Journey Focus

Zig Mastery Progression

• Weeks 1-4: Memory management, error handling, C interop
• Weeks 5-8: Advanced patterns, comptime programming, interfaces
• Weeks 9-16: Performance optimization, testing, service architecture
• Weeks 17-24: Cross-platform development, release engineering

Systems Programming Skills

• Windows APIs: Registry manipulation, global hotkeys, service integration
• Cross-Platform Design: Platform abstraction, conditional compilation
• Service Architecture: Background services, IPC, system integration
• Performance Engineering: Memory management, resource optimization

AI-Assisted Development

• Structured collaboration sessions with clear learning objectives
• Implementation guided by AI with comprehensive code review
• Alternative approach exploration and best practice validation
• Documentation enhanced through AI partnership

🏛️ Architecture Overview

Platform Abstraction Design

┌─────────────────────────────────────────────┐
│              Application Core               │
│  (65-70% shared across all platforms)      │
├─────────────────────────────────────────────┤
│           Platform Interface Layer          │
├─────────────┬─────────────┬─────────────────┤
│   Windows   │    macOS    │     Linux       │
│ Implementation│ Implementation│ Implementation │
│             │   (Future)  │    (Future)     │
└─────────────┴─────────────┴─────────────────┘

Core Components

• 🎛️ Theme Manager: Central orchestration of theme switching operations
• ⚙️ Configuration System: YAML-based configuration with live updates
• ⌨️ Hotkey Manager: Cross-platform global hotkey registration and handling
• 🔧 Service Manager: Background service lifecycle and coordination
• 💬 IPC Server: External API for programmatic theme control
• 📊 State Management: Persistent application state with recovery

📖 Comprehensive Architecture Documentation

🤖 AI-Assisted Development

Modern Development Approach

Dark Watcher embraces AI-assisted development as a learning accelerator and collaboration enhancement tool, not a replacement for understanding.

🎯 AI Collaboration Strategy:

• Session-Based Learning: Structured 2-4 hour development sessions with clear objectives
• Code Review Partnership: AI-assisted code review focusing on Zig idioms and best practices
• Alternative Exploration: AI-guided exploration of different implementation approaches
• Documentation Enhancement: AI-assisted technical writing and explanation

📋 Implementation Templates:

• Context-setting protocols for maximum AI effectiveness
• Module-by-module implementation approach with learning checkpoints
• Quality assurance checklists combining AI validation with personal understanding
• Knowledge transfer patterns for long-term retention

🌍 Cross-Platform Vision

Progressive Platform Expansion

Phase 1: Windows 11 Foundation

• Native Win32 API integration
• Registry-based theme manipulation
• Windows Service architecture
• MSI installer and auto-update system

Phase 2: macOS Integration

• Objective-C interop and Cocoa integration
• macOS defaults system integration
• LaunchAgent service architecture
• PKG installer with code signing

Phase 3: Linux Desktop Support

• GNOME, KDE, and XFCE theme system integration
• systemd service integration
• DEB/RPM packaging with distribution support
• Desktop environment auto-detection

Shared Architecture Benefits

• 65-70% code reuse across all platforms
• Consistent user experience and feature parity
• Unified configuration and state management
• Cross-platform build and release automation

🛠️ Technology Stack

Core Technologies

• Zig: Primary implementation language for performance and safety
• YAML: Human-readable configuration with schema validation
• Win32 API: Native Windows integration for optimal performance

Development Tools

• Zig Build System: Native build configuration with cross-compilation
• AI Coding Assistants: Claude, GPT-4, GitHub Copilot for collaborative development
• VS Code: Primary development environment with Zig language server

Cross-Platform Libraries

• Platform Abstraction Layer: Custom Zig interfaces for cross-platform compatibility
• Configuration Management: YAML parsing with validation and live updates
• Logging System: Structured logging with multiple output targets

🚀 Getting Started

Note: Dark Watcher is currently in the design phase. Implementation will begin with the core Windows functionality.

For Learning and Following Along

1. 📚 Study the Architecture: Review Zig-MVP-Project-Structure.md for comprehensive design details

2. 🛠️ Setup Development Environment:

   # Install Zig (when implementation begins)
   # Download from https://ziglang.org/download/
   
   # Clone repository
   git clone https://github.com/username/dark-watcher.git
   cd dark-watcher
   

3. 🎯 Follow the Learning Journey: Implementation will be documented week-by-week with learning objectives and AI collaboration insights

For Contributors

• Design Phase: Review architecture documentation and provide feedback
• Implementation Phase: Follow coding standards and AI collaboration guidelines
• Testing Phase: Multi-platform testing and validation

📚 Learning Resources

Zig Programming

• Official Zig Documentation
• Zig Guide - Community learning resource
• Zig Standard Library - API reference

Systems Programming

• Win32 API Documentation - Windows development
• The Windows Programming Model - Windows concepts

AI-Assisted Development

• Project-specific AI collaboration templates and patterns
• Weekly learning reviews and knowledge transfer sessions
• Implementation documentation with AI partnership insights

🤝 Contributing

Current Phase: Design & Architecture Review

We welcome feedback on the architectural design and learning approach:

• 📖 Architecture Review: Examine Zig-MVP-Project-Structure.md and suggest improvements
• 🎓 Learning Path Feedback: Suggest additional learning objectives or resources
• 🤖 AI Collaboration: Share experiences with AI-assisted development workflows

Future Contribution Areas

• Implementation: Module-by-module development following architectural guidelines
• Testing: Cross-platform testing and validation
• Documentation: Learning guides and technical documentation
• Platform Support: macOS and Linux platform implementations

📊 Development Roadmap

Phase 1: Windows MVP (Weeks 1-8)

Phase 2: Advanced Features (Weeks 9-16)

• IPC server and external API development
• Windows Service integration and auto-start
• Advanced state management and persistence
• Performance optimization and comprehensive testing

Phase 3: Cross-Platform Expansion (Weeks 17-24)

• macOS platform implementation and integration
• Linux desktop environment support
• Cross-platform build automation and release engineering
• Community documentation and contribution guidelines

📅 Detailed Implementation Roadmap

📞 Community & Support

Learning Community

• 📝 Development Blog: Weekly progress updates with learning insights
• 💬 Discussions: Architecture decisions and learning challenges
• 🎯 AI Collaboration Sharing: Templates and best practices for AI-assisted development

Technical Support

• 📖 Documentation: Comprehensive guides and troubleshooting
• 🐛 Issues: Bug reports and feature requests
• 🔧 Development: Implementation questions and code review

📜 License

MIT

🙏 Acknowledgments

• Zig Community: For creating an exceptional systems programming language
• AI Development Partners: Claude, GPT-4, and other AI assistants enabling collaborative learning
• Open Source Community: For inspiration and best practices in system utility development
• Learning-First Philosophy: Prioritizing education and skill development alongside practical outcomes