A comprehensive, reusable documentation template that transforms how you build software. Developed using AI-assisted workflows, this framework provides structured guidance for software development with modular documentation that adapts to any project type.
- 📚 Complete Documentation Framework - Ready-to-use templates for planning, development, testing, and deployment
- 🤖 AI-Assisted Development - Optimized for AI collaboration with structured prompts and guidelines
- 🎯 Modular Architecture - Department-based approach mimicking software agencies for systematic development
- 🔧 Technology Agnostic - Adaptable templates for any programming language, framework, or project type
- 📖 Learning Resource - Educational examples showing best practices in software development
- 🚀 Quick Start - Fork and customize for your next project in minutes
| Department | Purpose | Key Deliverables |
|---|---|---|
| Requirements | Capture what to build | User stories, specifications, constraints |
| Architecture | Design the solution | System diagrams, tech stack decisions |
| Implementation | Build the system | Code guidelines, patterns, standards |
| Testing | Ensure quality | Test strategies, coverage requirements |
| Security | Protect the system | Threat modeling, security measures |
| Deployment | Release to production | CI/CD pipelines, infrastructure |
| Operations | Maintain in production | Monitoring, maintenance procedures |
| Standards | Quality baseline | Code style, processes, conventions |
| AI Guidelines | AI collaboration framework | System prompts, interaction patterns |
# Fork this repository
git clone https://github.com/kliewerdaniel/workflow.git my-awesome-project
cd my-awesome-project
# Replace placeholders with your project details
# Edit README.md, ai_guidelines.md, and customize the documentationExplore the News Synthesizer implementation as a reference:
- RSS feed processing with local LLM inference
- RAG synthesis for content generation
- Persona-based composition systems
- Text-to-speech audio output
- Real-time chat interface
This repository includes a fully documented example of a privacy-focused news processing application that demonstrates the workflow in action:
📥 RSS Feeds → 🔍 LLM Analysis → 🎯 RAG Synthesis → ✍️ Persona Composition → 🔊 Audio Output
Technology Stack:
- Backend: Python FastAPI + llama.cpp (local LLMs)
- Frontend: Next.js + TypeScript + Tailwind CSS
- Database: SQLite with semantic search
- AI: mlabonne_gemma-3-27b-it-abliterated-IQ4_XS.gguf (13B parameter model)
This workflow embodies a "department-first" approach, where development is organized around specialized domains:
- Requirements Analysis - Understand what to build
- Architecture Design - Plan how to build it
- Implementation - Write the actual code
- Testing - Verify it works correctly
- Security Review - Ensure it's secure
- Deployment - Get it to production
- Operations - Keep it running smoothly
- Local Models: Compatible with llama.cpp, GPT4All, Ollama
- Cloud Services: OpenAI, Anthropic, Google Vertex AI
- Hybrid Approach: Balance cost, privacy, and performance
- Structured Prompts: Each department includes optimized AI prompts
- Fork this repository
- Edit
ai_guidelines.mdwith your project details - Customize department files for your technology stack
- Add project-specific documentation sections
- Implement following the established workflow
- Web Apps: Modify for React/vue/Angular frameworks
- APIs: Focus on REST/GraphQL design patterns
- Data Science: Emphasize model validation and deployment
- Mobile Apps: Update for iOS/Android native development
- DevOps: Enhance deployment and operations sections
Each documentation file includes:
- ✅ Standards - Quality requirements and guidelines
- 📋 Checklists - Step-by-step procedures
- 🤖 AI Prompts - Optimized prompts for each department
- 🔗 Cross-references - Links between related sections
- System Prompts: Project-wide AI orchestration
- Department Prompts: Specialized guidance per domain
- Feedback Loops: Continuous improvement cycles
- Knowledge Transfer: Documentation that teaches best practices
Planning Phase → Design Phase → Build Phase → Test Phase → Deploy Phase → Operate Phase
│ │ │ │ │ │
Requirements Architecture Implementation Testing Security Deployment
Analysis Design Guidelines Strategy Review Strategy
📁 Project Root
├── 📄 ai_guidelines.md # Central control document
├── 📄 README.md # Project overview
├── 📄 requirements.md # What we're building
├── 📄 architecture.md # How it's structured
├── 📄 implementation.md # Code development
├── 📄 testing.md # Quality assurance
├── 📄 security.md # Security measures
├── 📄 deployment.md # Release process
├── 📄 sop.md # Operations procedures
└── 📄 [other-docs].md # Project-specific docs
We welcome contributions! This template is designed to evolve with the community:
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-addition - Customize documentation for your project type
- Test your workflow with a real project
- Submit a pull request with your improvements
- New Department Templates (accessibility, performance, etc.)
- Technology-Specific Guides (AWS, Kubernetes, React Native)
- Industry Examples (healthcare, finance, e-commerce)
- AI Integration Enhancements (new model support, prompt engineering)
- Tooling Automations (GitHub Actions, custom scripts)
v1.0 - Core departments documented, News Synthesizer example implemented
- v1.1 - Additional department templates (accessibility, SEO)
- v1.2 - Technology-specific guides and examples
- v2.0 - Interactive tooling and automation
- v2.1 - Community-contributed project examples
- 📊 Coverage: All major development departments
- 🔬 Examples: Complete working implementation
- 📖 Documentation: Comprehensive guides and standards
- 🤖 AI Ready: Optimized for AI-assisted development
- Cline - AI-powered code completion and refactoring
- GitHub Copilot - Intelligent code suggestions
- Continue.dev - Local model integration
- GitHub Gemini - Google's AI assistance
- Qwen 2.5 series - General purpose coding assistant
- Code Llama - Meta's coding-focused models
- Mistral - Efficient instruction-following models
- Custom GGUF - Quantized models for local inference
- VS Code - Primary IDE with AI extensions
- Hardware: GPU-accelerated workflows with CUDA support
- Version Control: Git with structured commit messages
MIT License - Fork, modify, and use commercially. Attribution appreciated but not required.
Copyright (c) 2024 kliewerdaniel
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
- AI Tools: Thanks to amazing AI technologies making this possible
- Open Source: Built on countless open source projects and communities
- Documentation Culture: Inspired by excellent OSS documentation practices
- Workflow Pioneers: Drawing from agile, lean, and DevOps methodologies
- GitHub Issues: Bug reports and feature requests welcome
- Discussions: Share your implementations and customizations
- Wiki: Community-contributed guides and examples
- GitHub: @kliewerdaniel
- LinkedIn: Let's connect for collaboration opportunities
- Portfolio: More projects and AI-assisted development content
Made with ❤️ using AI-assisted workflows | Built with documentation-first development