How It Started: Excel VBA
I hold a BBA and work in logistics and manufacturing—far outside the traditional tech world. My first real coding win was simple: using Excel macros to automate a daily report, turning nearly an hour of manual work into a process that took seconds.
That moment completely shifted my mindset. Code isn't just for software engineers; it’s a practical lever for solving everyday operational friction. With the right tools and guidance, anyone can leverage code to work smarter and build better processes.
From VBA to Python
My Python journey began in 2014 with a simple script that scraped news headlines from multiple sources into a single feed. It was a basic project, but it taught me data handling, web scraping, and—most importantly—how to translate curiosity into functional software.
Over time, those early experiments grew into practical, operational tools. I eventually moved on to building label-printing utilities, RFID data pipelines, and custom automations for customer portals and fulfillment processes.
Reading Regularly
Once you start building, you naturally begin to question how to build better. Refining that craft requires broader knowledge, which is why I continuously read across science, math, economics, and technology. Execution is great, but building becomes far more fulfilling when you understand the context—the "why" behind the "how."
Building and learning with AI
I still remember my first real interaction with AI on December 16, 2022, right after OpenAI released ChatGPT. I tested it on a coding task, and the results blew me away. I instantly made an IG Reel declaring it a complete game-changer.
Today, in 2026, it’s an essential part of my workflow. Beyond just answering questions, AI acts as a thought partner—helping me prototype ideas, test technical approaches, and build at speed.
I’ve never seen AI as a replacement for human talent. Instead, humans and AI act as mutual amplifiers—extending what either could accomplish alone. Imagine what becomes possible when we combine human imagination and expertise with AI's broad knowledge base.
My Thinking Framework
I view knowledge like a system of planets, each with its own gravitational pull. While deep expertise in one domain is powerful, breadth across disciplines allows us to ask better questions and connect richer answers—transforming isolated ideas into a full universe. As I build and learn, I rely on three core principles:
- First principles: find the real root of the problem.
- Empathy: design for real people, not only perfect assumptions.
- Non-maleficence: avoid harm even when a solution appears efficient.
Thank you for reading. I'd love to hear your story too.