Hi, I'm Derek.

I've been self-taught in Python for a decade. I don't come from a Computer Science or engineering background — I graduated with a BBA and work in the logistics and manufacturing industry, not tech. But I was lucky enough to get opportunities to use Python on the job, and that opened the door for me to start building real tools.

Excel VBA the beginning

My coding journey began with Excel Macros. At first, I just wanted to automate a repetitive reporting task that pulled data from three different sheets. It used to take me almost an hour to restructure, clean, and calculate everything before I could produce a report. Frustrated with how inefficient the process was, I kept thinking there had to be a better way. So I started learning VBA. Eventually, I automated the whole task — and it ran in just a few seconds. That moment was a game-changer for me, and it's what sparked my interest in programming.

From there, I just kept learning and building. One of my early projects was a label-printing tool in Excel VBA. It could dynamically update data and print a full sheet of 8x8 (64) small labels, each with different product details. That little tool gave me a ton of flexibility and saved huge amounts of time during sales events. I also built a tool that collected and organized data from RFID devices using nothing more than email and Excel. With it, my team could check stock availability within minutes instead of spending hours on replenishment tasks. Seeing these tools make a real impact in day-to-day operations pushed me to keep going and keep improving.

Python: A New Lens on Problem-Solving

I started learning Python in 2014. Its simplicity and versatility drew me in immediately — it felt like the natural next step after VBA, but with far more possibilities. One of my first ideas was to read news articles from different newspapers at once, so I built a Python web scraper that pulled headlines and summaries from multiple sites into a single report. It wasn't a fully polished project, but it taught me how to scrape data from the web. The experience and skills I gained didn't just help me build personal projects — they eventually became tools I could apply to real work in the future.

The Future is Human + AI

Over the years, I've built a variety of tools in Python — automating data processing on customer portals, streamlining order-fulfillment workflows, and creating internal web pages that handle data collection, analysis, and reporting. Along the way, I picked up more tools beyond Python, like n8n and Node.js. Even this page was built with TypeScript, with help from GitHub Copilot. Each new tool expanded what I could create and how quickly I could bring ideas to life.

AI has completely changed how we create. With AI, we can spin up custom tools instantly. I'm not worried about AI replacing humans — just like I'm not the most intelligent person in the room, yet I can still find my place and contribute. In the same way, AI doesn't remove human value; it expands what we're capable of.

I actually feel excited about what people can build with AI — how we can create more, solve more, and extend our reach with AI as a partner. My experience taught me that problems will always exist, and so will solutions — but the real challenge is figuring out which questions actually matter.

Knowledge as Planets, Intelligence as Mass

To ask better questions, we need stronger general knowledge to guide our decisions. And by “general,” I really mean broad and wide-ranging. When I was learning about machine learning, deep learning, and AI, I started imagining knowledge as the mass of planets in the universe. If you go deep into one area, you become like a massive planet with strong gravity — everything seems to operate according to the rules of that world. But that doesn’t mean other planets don’t exist. Each has its own mass, its own environment, and its own way of operating.

In the end, everything is probability, shaped by where you stand and the environment around you. AI excels at going deep — it can become that massive planet in a single domain. But as humans, our value lies in extending the universe: connecting different worlds of knowledge, providing context, and defining the environment in which AI operates. That, to me, is what general knowledge means — not just depth in one area, but breadth across many, so we can ask better questions and guide AI toward meaningful answers.

My Guiding Habits

I would like to share my simple habits when approaching problems.

• ➜ First principles thinking — get to the core of the problem.
• ➜ Empathy — understand people so the solution actually fits for most humans.
• ➜ Non maleficence — avoid causing harm, even if the solution is technically correct.

Thank you for reading my story. I'd love to hear yours too.