Learning my way through Linux, IT security, and digital forensics — and thinking a lot about the impact of AI on society.

Over the past 10 years, I've used Linux on and off — mostly through VirtualBox, sometimes as my main OS. I’ve installed Arch Linux from scratch, got tiling window managers like Qtile and Awesome running, configured a GUI-less mp3 setup with moc, and fixed real issues like broken sound or printer configs.

I’m not a sysadmin, but I can find my way around. If I don’t know something, I’ll check the man pages or look it up. These days, I work with Linux mainly through WSL and VirtualBox on Windows.

I’ve explored basic CTFs in the past (HackTheBox-style challenges), mostly around SSH, FTP, and SQL exploitation. That was a couple of years ago, and while I don’t remember everything, the exposure helped shape my interest.

I’m just getting into digital forensics, but it’s something that really clicks with me. Since I’m naturally drawn to pattern recognition, analyzing browser artifacts and other digital traces feels like a natural extension of that. It’s early days, but I think this will be the direction I’m aiming for professionally.

Probably the topic I think about the most lately.

• Will AI be used mostly to cut costs and replace jobs?
• Will it create a new market for emotional dependency — like paywalled AI companions?
• Could it be meaningful in therapeutic settings?

I think we'll be impacted by this on a level we don’t fully understand yet. The only question is: for better or for worse?

I treat each project here as a self-directed tutorial. It always starts with a general idea — for example, in my town simulator, I knew I wanted a CLI-based text adventure with streets, buildings, NPCs, and shops. I first designed the skeleton: the streets, buildings, and a player character that could navigate the world. Once the basic structure worked, I added an in-game map using Pygame, then NPCs with schedules, homes, and workplaces. Each step required problem-solving and careful tweaking.. ChatGPT helped along the way, but these projects were never simple copy-paste exercises — they took hours or days of thinking, testing, and debugging to get right.

This approach applies to all my projects: I start with a vision, break it down, experiment, and refine. Even if the code isn’t perfect, the goal is to understand, learn, and build something meaningful. This has actually taught me more about programming — and Python in particular — than all the online tutorials I’ve done over the past years combined, because I didn’t just learn individual parts; I learned how to apply them and think ahead.

This profile is a snapshot of where I am right now — still learning, experimenting, and figuring out how I want to develop my skills.