Study Lab Core is a comprehensive monorepo designed to document my journey from a programming beginner to a Computer Engineering student. It serves as a central hub for my learning modules (Python, NodeJS, AI), professional devlogs, and real-world…
Study Lab Core is a comprehensive monorepo designed to document my journey from a programming beginner to a Computer Engineering student. It serves as a central hub for my learning modules (Python, NodeJS, AI), professional devlogs, and real-world automation projects like ‘Faceless Video Automation’. Maintained solely by me (@EngThi), the project focuses on applying professional software engineering standards from day one. Next steps include finalizing the video automation MVP and deep-diving into AI fundamentals.
It also serves as a kind of guide for beginners studying these areas. I try to organize and show how learning works in this field and how/which tools to use to learn.
I use AI (Perplexity, Gemini CLI) as a “senior mentor” to guide my learning, review my code architecture, and explain complex concepts. I use AI strictly to accelerate my learning—never to generate code I don’t understand. Specifically, I use it to:
Plan the project architecture and directory structure (like this monorepo).
Debug specific errors in my Python/Node.js scripts.
Generate documentation templates (READMEs, Devlogs) to maintain professional standards.
Acting as a partner programmer to refactor code according to PEP 8 standards. This speeds up my debugging and understanding. Perplexity is very good for web searches; it finds documentation, can see my public repo, that sort of thing.
