Side Projects

Purpose

• The purpose of Side Projects, including utilities to a degree, is to learn and develop experience using technologies useful in future Production App projects, and utilities.

Tech Stack

• Web Dev
  • Svelte, SvelteKit and related ecosystem
  • identify best AI tools for Web Dev
    • Canvas features in …
      • Gemini 2.5 Pro
      • …
• Python

Dev Process for Side Projects and Utilities

This process prioritizes speed, experimentation, and getting to a working result quickly. Documentation and formal planning are minimized.

Phase 1: Define & Prompt (Iterative)

• Quick Goal Outline: Write a short description (maybe just a few bullet points or sentences in a README.md or directly in the AI prompt) of what the utility/project should do. Include key inputs and expected outputs.
• AI Initial Generation: Prompt an AI agent with the outline. Ask it to:
  • Suggest a basic structure/approach.
  • Generate the initial code scaffold (e.g., main script file, basic functions).
  • Suggest necessary libraries/dependencies.
• Refine & Iterate:
  • Review the AI’s output. Tweak the prompt or directly edit the code. Ask the AI to implement specific functions or handle edge cases based on your immediate next step. This loop is tight and frequent.

Phase 2: Develop & Test (Incremental)

• Task Execution (AI or Human): For each small feature or function:
  • Prompt the AI to write the code, or write it yourself.
  • Ask the AI to generate simple Unit Tests or test cases for the code snippet just created.
• Manual Testing: Run the script/project frequently with sample inputs to ensure it behaves as expected.
• Version Control (Highly Recommended):
  • Use Git from the start (git init).
  • Make frequent, small commits after getting a piece working (git add ., git commit -m "Implemented feature X"). Branches are optional for solo projects but useful for experiments.
• Basic Logging: Add simple print statements or basic logging for debugging as needed.

Phase 3: Finalize (Minimal)

• Cleanup: Remove temporary code, add basic comments where logic isn’t obvious (AI can help with this).
• README Update: Ensure the README.md has:
  • A clear description of what the project does.
  • Instructions on how to install dependencies (e.g., pip install -r requirements.txt).
  • How to run it (basic usage examples). (AI can generate much of this based on the code).
• (Optional) Share: Push to GitHub/GitLab if desired.

Key Artifacts:

• README.md
• Source Code Files
• requirements.txt (or similar)
• Git History

AI Focus:

Code generation, suggesting approaches, generating tests, basic documentation/comments.