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Appendix 12: Machine Coding: Pre-Prompt Checklist

A practical pre-prompt checklist for defining your app before engaging AI. Use this guide to clarify data design, technical foundations, configuration, intelligence layers, embeddings, and input/output handling—ensuring your AI partner has everything it needs to build effectively.

✅ 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.


    flowchart TD
    Start([💡 App Idea]) --> A[🧱 Data Design<br>Tables, flow, storage]
    A --> B[🛠️ Technical Foundations<br>CLI/Web, language, framework]
    B --> C[🔐 Configuration & Secrets<br>.env, config wrapper]
    C --> D[🧠 Intelligence Layer<br>Models, local/API]
    D --> E[📦 Embeddings & Search<br>Vector search, embedding model]
    E --> F[📥 Input Handling<br>Format, batch support]
    F --> G[📤 Output Handling<br>Console, file, DB]
    G --> H([✅ Ready to Prompt AI])

    style Start fill:#e1f5fe,stroke:#333
    style A fill:#fff3e0,stroke:#333
    style B fill:#e8f5e9,stroke:#333
    style C fill:#fce4ec,stroke:#333
    style D fill:#f3e5f5,stroke:#333
    style E fill:#fff9c4,stroke:#333
    style F fill:#e0f7fa,stroke:#333
    style G fill:#c8e6c9,stroke:#333
    style H fill:#4caf50,stroke:#333,color:#fff
  

🧱 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?
  • 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?