About
I came to engineering from economics, wanting to build real systems rather than model them. I taught myself in — starting with Linux at Engeto in Prague, intensive study, and stepping straight into 24/7 production operations.
The first job was support and incident response at a global content delivery network. I stayed because I loved the analytical challenge: something broke in production, and you have to work out the root cause under real pressure.
Everything since has been that instinct at a larger scale. Keep systems up. Then build them so they stay up alone. Now shape what should be built at all — and build that too.
The economics never went away. It is still how I judge whether a piece of work was worth doing: hours returned, operating costs saved, and leverage created.
Today I am Founding Product Engineer and fourth on the team at Glow, shaping the product vision for real-time multiplayer automation and building the core platform alongside the team.
I have never stopped studying. Eight years in, I am still deepening my technical craft every week across distributed systems, product design, and compiler/runtime architectures.
Based in Prague. I work in English and Czech, applying economic principles of incentives, leverage, and efficiency to software systems.
Education
Certifications passed
Earned and passed during active enterprise engagements across AWS and HashiCorp infrastructure.
Languages
Also
I have presented this work in Switzerland and at EPH headquarters (see Work)
Now
- Building Glow: approvals that expire, a canvas that stays fast on large workflows, a Chat trigger — all shipped this month.
- Rebuilt this site from a blank page; published live canvas walkthroughs.
- Reading economics for fun, as ever; watching ByteByteGo and Domain of Science.
What I learn from
Not a course catalogue. The people, books and habits that shaped how I think — and what each one gave me.
A classroom in Prague, evenings, before anyone would hire me. This is where IT caught me and did not let go.
Where the operations years got their vocabulary — containers, pipelines, Kubernetes explained by someone who had run them.
The diagrams behind the systems everyone uses — how they scale, where they break. The reference I go back to before I decide how something should be built.
How large systems are shaped and why they fail — the thinking behind a platform serving many companies from one place.
Where the AI I put into workflows stops being a black box. Short courses, done properly, on the parts I actually ship.
Studied end to end. You cannot decide what to build better without having used what exists.
Grant Sanderson explaining linear algebra and neural networks by drawing them. Not for work — for the feeling of finally seeing why something is true.
Dominic Walliman’s maps of whole fields — physics, mathematics, computer science — on one sheet each. The habit of asking where a thing sits before learning it.
The degree, and everything I have read since. Still how I judge whether a piece of work was worth doing.