A Year in the Woodshed: A Development Practice in the Age of AI
Traditionally, a woodshed was more than just a storage space - it was a dedicated space for practice and growth. Like yoga, which transforms from physical movement to a mindful way of being, development can transcend mere coding to become a thoughtful practice. For the past twelve months, I've maintained my own practice in a "woodshed," exploring how to write software in an AI-transformed landscape.
Establishing the Practice
Creating a well-organized space is essential for any meaningful practice. I created a monorepo not just as a collection of experiments, but as a structured environment for daily exploration. Each session building upon the last, each challenge offering new insights into how AI is reshaping our approach to code.
Elements of Practice
Foundation Work
The foundation of any practice starts with understanding the basics:
- Understanding how to structure projects that integrate with AI services
- Developing patterns for testing code that interacts with probabilistic systems
- Finding balance between traditional development and AI-assisted approaches
Daily Practice
My experiments became daily exercises in understanding:
- Using Streamlit to prototype and test AI integrations
- Building SQL interfaces to bridge traditional and AI-enhanced development
- Exploring how state management and testing evolve with AI in the stack
Creating Space
Just as important as the practice itself was creating the right environment:
- Establishing Git workflows that support AI-assisted development while maintaining code quality
- Developing testing approaches that work with both traditional code and AI components
- Maintaining environments that balance familiar tools with new AI frameworks
Technical Foundation
The practice is supported by a balanced technical stack:
- Python as the foundational language
- Traditional development tools, adapted for new challenges
- Integration patterns for AI services
- Modern UI tools for rapid prototyping
- Experimental spaces for learning and testing
Key Learnings
1. Structure Creates Freedom
The monorepo's organization created space for growth and experimentation while maintaining stability. This structure provided a framework for consistent progress without constraining creativity.
2. Adaptation is Essential
Traditional development patterns needed mindful adaptation to work with new technologies. What worked before didn't always translate directly to AI-enhanced development.
3. Environment Matters
A practice needs the right space and tools. Managing the development environment proved crucial for maintaining consistency and growth, especially when working with both traditional and AI-powered tools.
Moving Forward
This year in the woodshed has established a foundation for growth in the AI era. Like any meaningful practice, it's not about reaching a final destination but about continuing to learn and adapt. Each day brings new opportunities to deepen understanding and refine techniques.
The woodshed-ai project remains active and growing. It's become a space for regular practice, experimentation, and learning. Feel free to explore the project and perhaps begin your own practice in AI-era development. The most valuable lesson has been that regular, mindful practice creates the space for genuine growth and understanding.