My first GitHub repo was a static article website. Pure HTML, CSS inline in some places, JavaScript only for a navbar toggle. Embarrassing? A little. But that’s where it started.
The Messy Timeline
Early 2024: HTML, CSS, building static websites for college assignments. Every new website = copy paste the old template, change the content.
Mid 2024: Discovered PHP. Built information systems for a village, a temple, even an ERP for an eyewear shop. All native PHP. No framework. No proper version control. Push directly to production. shudder.
Late 2024: Started teaching at DigiKidz. This was a plot twist I didn’t expect. Teaching kids to code made me realize how many fundamentals I had skipped.
2025: Python became everything. Pandas, Scikit-learn, data analysis, ML. Shifted from “building websites” to “building things from data.”
2026: Astro for my portfolio, FastAPI for backends, Docker for deployment, and now tinkering with AI agents for automation. Wild.
What’s Not Linear
From the outside, it might look like a neat path: web → backend → data → ML → AI. Reality? Messy.
I once got stuck for 3 weeks on a PHP bug that turned out to be a missing semicolon. Once submitted a college project that “worked” on my laptop but crashed on the professor’s. Once built an ML model with 99% accuracy and was so proud, until I realized the model was just memorizing the training data.
Every “level up” always started from an embarrassing failure.
The DigiKidz Effect
Teaching kids was a game changer I didn’t expect.
When you have to explain loops to an 8-year-old, you’re forced to truly understand loops. Not just the syntax, but the concept. Why it exists. When to use it, when not to. What analogy fits best.
And kids are honest. They don’t pretend to understand. If your explanation is bad, they immediately look bored or confused. No polite “oh yeah, I get it.”
That’s the fastest feedback loop I’ve ever experienced.
Now and Next
My target: Data/AI Engineer. Not because the buzzword sounds cool, but because I found that digging stories out of data is genuinely exciting.
But I don’t want to leave web development behind. Because data without an interface is just a spreadsheet. And spreadsheets can’t change people’s decisions if they’re not presented properly.
So my ideal position: someone who can take raw data, clean it, analyze it, and present the results through something people can actually use. End to end.
From static HTML to data pipelines. Not linear, not perfect, but at least I keep moving.