The Journey
From curious autodidact to AI engineer, here's how I got here
I started coding in '95, teaching myself because I was curious about how things worked and how much could be automated. Thirty years later, I'm still asking questions — that's what keeps this interesting.
I spent over a decade in public administration building systems that actually helped people: platforms that automated tedious paperwork, helpdesk solutions that cut response times from 48 hours to 4, and tools that gave teams back their time. Real problems, practical solutions.
Then I went back to school—Bachelor's in Computer Science, then a Master's in AI. My theses? For my Bachelor's, I explored how blockchain technology could cut Public Administration storage costs by 85%. For my Master's, I used deep learning to detect traffic accidents from aerial imagery. Because sometimes the best view is from above.
Now I build full-stack systems for startups and established companies, working with everything from React and Angular to Spring Boot and ASP.NET. But I'm most excited about AI and machine learning: real-time computer vision systems, recommendation systems, crypto market analysis, and blockchain smart contracts.
My approach: understand the problem first, pick the right tool for the job, and share what I learn along the way. Technology should solve problems, not create them.