More about ... Me

The real me

Long time ago, somewhere in the previous century, a little boy was born in a small country called Belgium. And yes, this was me …
Born and raised in Belgium, I had a magnificent childhood, growing up with 2 brothers in a decade where everything was possible and allowed. No computers, no internet, black and white television, …
So, I grew up in an analog world :- )
And believe me, I enjoyed every second of it. I can't imagaine growing up in another era than my youth. But I think every generation says the same 'growing up in my time was so much better than now'.

From little kid on, I loved reading and I still do.
You can call me old fashioned, but I still love reading physical books (no Kindle for me), I love the smell of old books, even touching books in my library, …
Besides reading, I love cycling (but I hate uphill, I'm more the cobblestones type of cycling) and playing tennis. Not that I am good at it, but I enjoy it a lot. As they say 'mens sana in corpore sano' (a healthy mind in a healthy body).
I am not a person who falls for hypes and trends but since a few years, I became passionate about padel. And I try to play at least 2 times a week. Not the best there is, but let's say I'm above average level. And that's how I try to keep in shape nowadays.

But how did I become such an IT-nerd?

I've always been fascinated by computers and automation, from the moment I got my hands on a Commodore 64 as a kid, I was hooked. It was amazing to see what a few lines of code could do.

Decades later, I became intrigued by AI long before 95% of the world ever heard of it. When I first encountered the concept, it felt like science fiction. But the deeper I dove into it, the more convinced I became that this wasn't just the future of IT, it was the future itself.

In December 2021, I completed my first course on building convolutional neural networks (CNNs). I was immediately hooked. I spent the following weeks consuming everything I could find on GANs, unsupervised learning, and natural language processing. For the first time I felt like I wasn't just building another system, I was architecting intelligence. And I got good at it. So good that I started getting ambitious ideas. What if I could reverse-engineer image generation by combining everything together? Instead of just classifying images, what if I could describe a scene and have the model create it? I built a prototype that could take a prompt like "draw me a blue cat next to a labrador in the style of Hieronymus Bosch" and, believe it or not, it did deliver surprisingly decent results. Then Midjourney launched. They were doing what I was building but much better, faster, harder and more beautifully than I had imagined possible. My first instinct? Frustration. I put my project aside.

Next brilliant idea (sometimes I have such moments): leverage my NLP knowledge to build a conversational app, like a "WhatsApp for people with no friends." A few months into development, ChatGPT exploded onto the scene. Same story, different ending.

At this point, I could have given up. And to be honest, I almost did. It took me a while to realize something crucial: every "failed" project was actually market validation. The problems I was identifying were real, valuable, and inevitable. The ideas were real, the problems were valuable, the timing was just simply off.

I have been working for 15+ years as a system administrator for a big US company, where I learned everything about data protection, intellectual property, workflow optimization, and audit compliance. And a few years later, all my work experience and knowledge about IT and AI came together: I understood something most automation builders miss: the real money isn't in flashy demos. It's in systems that actually work when your business depends on them.

I started building automations for myself: it was so cool to push a button and watch my computer handle tedious tasks in seconds that would take me 10-15 minutes to complete manually. No errors. Better results. Pure efficiency. Why not offer this to businesses that actually need it?

That's the moment I decided to launch my AI Automation Agency (AAA). And yes, once again, I was like a tiny sardine in a suddenly crowded ocean. The internet was flooded with new entrepreneurs using no-code tools to build impressive-looking automations. And some were making serious money.

My vision

And here's what initially frustrated me: they had no background in Python, JavaScript, React, enterprise security protocols, or compliance frameworks. How were they succeeding while I was struggling to gain traction? The answer was embarrassingly simple: they were using the tools I was trying to build from scratch, and they were infinitely better at marketing than I was.

But here's what they aren't doing: building systems that scale. Systems that integrate with existing enterprise infrastructure. Systems that pass security audits. Systems that don't break when you actually need them most.

So, focus on what you're good at and for me (and Aistralis) this is delivering quality. Not only quality but also on-time delivery and an open communication.