Micromanaged Driven Development (MMDD)

A methodology for AI-assisted software development that emphasizes granular control and systematic documentation of the development process.

Yes, we said micromanaged - and this time makes sense.

Quick Start

Start here: Read dev_log/00_mmdd.md for the complete MMDD principles and implementation guide.

What is MMDD?

MMDD is a methodology for building software with AI assistance. Instead of giving broad, vague prompts like "build me a web app," MMDD focuses on breaking development into specific, well-defined tasks with systematic documentation of the entire process.

Key principles include granular task breakdown, controlled AI direction, and maintaining a chronological audit trail of how your system evolved.

Repository Structure

This repository demonstrates MMDD by using MMDD to build itself:

├── README.md                # This introduction file
└── dev_log/                 # Chronological development units
    ├── 00_mmdd.md           # MMDD methodology
    ├── 00_main.md           # This project's development plan
    ├── 01_repository.md     # Repository structure and templates unit
    ├── 02_content.md        # Content terminology and documentation unit
    ├── 02_content_analysis.md    # Content analysis subunit
    ├── 02_content_planning.md    # Content planning subunit
    ├── 02_content_replacement.md # Content implementation subunit
    ├── 03_templates.md      # Templates and adoption support unit
    └── 04_adoption.md       # Adoption guide and how-tos unit

How to Use

1. Learn the Principles: Read dev_log/00_mmdd.md
2. See it in Action: Check dev_log/00_main.md to see how this repository was planned using MMDD
3. Copy the MMDD Files: Copy 00_mmdd.md into your project's dev_log/ directory
4. Generate Your Plan: Use this prompt with your AI: "Using the template and methodology in dev_log/00_mmdd.md, generate a 00_main.md file for my project that [describe your project]"

Why MMDD?

MMDD provides several key benefits for AI-assisted development:

• 🎯 Predictable AI Results: Granular control leads to more reliable outputs
• 🔧 Maintainable Code: Systematic approach produces cleaner, understandable systems
• 📚 Knowledge Transfer: Detailed logs help other developers (and future you) understand the codebase
• ✅ Quality Assurance: Regular validation points catch issues early

Contributing

These principles evolve through real-world usage. Share your experiences, improve templates, or contribute examples of MMDD in action.

License

MIT License - Use freely in your own projects.

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Want to see MMDD in practice? This entire repository was built using these principles - explore the dev_log/ directory to see how.