Hi, I’m Ilias — I break things with AI and write about what happens.
I’ve always been curious about how things work — whether in sports, travel, or technology. Football taught me discipline, travel gave me perspective, and that curiosity eventually pulled me into AI — specifically, how it can make everyday work less painful.
How I got into AI
I’ve always been the kind of person who wants to understand how things work — and then figure out if they could work better. That curiosity has been with me as long as I can remember, whether it was in sports, travel, or just everyday life.
AI caught my attention because it matched that instinct perfectly. Not the hype around it — just the simple idea that you can teach a tool to handle the stuff you shouldn’t be spending your time on. Once I started experimenting, I couldn’t stop.
Why IBK Labs exists
I’ve always loved sharing what I learn with the people around me. Whenever I discover something useful — a tool, a shortcut, a new way of thinking about a problem — my first reflex is to tell someone about it. That’s just how I’m wired.
IBK Labs started from that same reflex. As I kept experimenting with AI and automation, I found myself explaining what I was doing to friends, colleagues, anyone who’d listen. At some point it made sense to put it all in one place — not as a polished course or a tech blog, but as an honest record of what I’m trying, what I’m learning, and what I think others could benefit from too.
It’s not about being the smartest person in the room. It’s about sharing the journey on my own scale, in my own words, and hoping some of it resonates with someone out there.
Background
I help teams figure out how to actually use their data — not just collect it.
In practice, that means:
- Building data products that turn scattered datasets into things people can actually act on.
- Prototyping AI workflows that shave hours off analysts' weeks.
- Working with business teams to measure what matters — time saved, decisions improved — not just model scores.
Six months learning data science and AI from the ground up — Python, machine learning, deep learning, the works.
This is where I went from "I understand the theory" to "I can actually build this." The program covered:
- Data analysis and visualization with Python, SQL, and Tableau.
- Machine learning and statistical modeling on real-world problems.
- Deep learning with TensorFlow and PyTorch.
- MLOps — deploying and scaling models with AWS, Docker, and Airflow.
- Generative AI — building with LLMs like GPT-4.
Studied at Auckland University of Technology and graduated magna cum laude.
One of the most eye-opening experiences of my life. Living so far from home taught me to adapt quickly, stay curious, and embrace new ways of thinking. I discovered a culture that values balance, authenticity, and respect for both people and nature — a mindset that still shapes how I approach work today.
Msc. in Business Engineering with a specialization in Data Science and Big Data.
What started as curiosity for numbers quickly became a genuine passion for analytics, technology, and the stories data can tell. This is where I learned to connect technical thinking with business strategy — predictive modeling, econometrics, and machine learning, all applied to real problems.
How I work
Most of my projects start the same way: I’m doing something tedious and I think "there has to be a better way." Then I spend an evening testing whether AI can do it. If it works, I write it up. If it fails, I write that up too.
Something feels repetitive, slow, or unnecessarily manual. That’s the signal.
I grab the simplest tool that might work — an LLM, Make.com, a quick script — and see what happens.
What worked, what broke, what I’d do differently. Everything goes on IBK Labs so you don’t start from scratch.