Appendix: Machine Coding checklist

✅ Pre-Prompt Checklist: Define Your App Before the AI Builds It

Use this checklist to clarify your thinking before engaging the AI in coding your tool or app.

🧱 Data Design

• Have you defined your core tables or data structure?
• Do you know how your data flows through the app — from input to output?
• Have you considered how you’ll store, retrieve, and update records?

🛠️ Technical Foundations

• Will this be a CLI, Web App, or something else?
• What’s your preferred language and framework (e.g., Python + FastAPI)?
• Are you using an ORM (e.g., SQLAlchemy), or sticking with dataclasses + raw SQL?
• Will you manage schema with migrations, a .sql file, or something else?

🔐 Configuration & Secrets

• Do you want to use a .env file for secrets and environment variables?
• Is there a configuration wrapper class you plan to use?

🧠 Intelligence Layer

• Which model(s) will power your AI interactions? (e.g., qwen:2.5, mxbai-embed-large)
• Will you use local models (e.g., Ollama) or API-based models?

📦 Embeddings & Search

• Do you plan to use vector search (e.g., pgvector)?
• Have you chosen an embedding model, and do you know the expected dimension size?

📥 Input Handling

• What is the input format for your app? (e.g., Markdown file, CLI args, JSON payload)
• Do you want to support batch processing, or just single sessions?

📤 Output Handling

• What should your app output? (e.g., print to console, write to file, store in DB)
• Do you need to track results in a database or results log?