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https://github.com/jeffmelton/dark-watcher

A learning-focused Zig implementation of a Windows 11 theme switching application with AI-assisted development. Features comprehensive cross-platform architecture designed for 65-70% code sharing across Windows, macOS, and Linux. Currently in design phase with complete architectural blueprint ready for implementation.
https://github.com/jeffmelton/dark-watcher

ai-assisted-development architecture-first dark-mode learning-project light-mode systems-programming theme-switching win32-api windows-11 zig

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A learning-focused Zig implementation of a Windows 11 theme switching application with AI-assisted development. Features comprehensive cross-platform architecture designed for 65-70% code sharing across Windows, macOS, and Linux. Currently in design phase with complete architectural blueprint ready for implementation.

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README 

          
# 🌓 Dark Watcher



[![Project Status](https://img.shields.io/badge/Status-Design%20Phase-blue?style=flat-square)](#project-status)

[![Zig Version](https://img.shields.io/badge/Zig-0.15.1-orange?style=flat-square)](https://ziglang.org/)

[![Platform](https://img.shields.io/badge/Platform-Windows%2011%20x86-lightgrey?style=flat-square)](#platform-support)

[![Architecture](https://img.shields.io/badge/Architecture-Cross--Platform%20Ready-green?style=flat-square)](#cross-platform-vision)

[![License](https://img.shields.io/badge/License-MIT-yellow?style=flat-square)](#license)

[![AI Assisted](https://img.shields.io/badge/Development-AI%20Assisted-purple?style=flat-square)](#ai-assisted-development)



> **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:**

- [x] Comprehensive project architecture design

- [x] Cross-platform abstraction layer specification  

- [x] Complete module breakdown and responsibility mapping

- [x] Build system configuration and dependency management

- [x] AI collaboration workflow optimization

- [x] 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**](Zig-MVP-Project-Structure.md)



---



## 🤖 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](https://ziglang.org/)**: 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`](Zig-MVP-Project-Structure.md) for comprehensive design details



2. **🛠️ Setup Development Environment**:

   ```bash

   # 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](https://ziglang.org/documentation/master/)

- [Zig Guide](https://zig.guide/) - Community learning resource

- [Zig Standard Library](https://ziglang.org/documentation/master/std/) - API reference



### **Systems Programming**

- [Win32 API Documentation](https://docs.microsoft.com/en-us/windows/win32/api/) - Windows development

- [The Windows Programming Model](https://docs.microsoft.com/en-us/windows/win32/learnwin32/learn-to-program-for-windows) - 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`](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)**

| Week | Focus                                     | Learning Objectives                           |

| ---- | ----------------------------------------- | --------------------------------------------- |

| 1-2  | Project setup, error handling, logging    | Zig toolchain mastery, memory management      |

| 3-4  | Platform abstraction, registry operations | Comptime programming, Win32 APIs              |

| 5-6  | Theme management, configuration system    | Business logic architecture, YAML integration |

| 7-8  | Hotkey system, service integration        | Win32 message handling, service lifecycle     |



### **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**](Zig-MVP-Project-Structure.md#8-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



---






**Built with ❤️ using Zig and AI-assisted collaborative development**



[⭐ Star this repository](https://github.com/username/dark-watcher) • [📖 Read the docs](Zig-MVP-Project-Structure.md) • [🤝 Contribute](#contributing) • [📞 Get support](#community--support)