Nikita Yasenkov

I wasn't supposed to end up here.

I studied petroleum engineering at Heriot-Watt University — reservoir models, well planning, subsurface analysis. It's a discipline that demands rigorous systems thinking, and I loved it. But somewhere between the geology lectures and the fluid dynamics problem sets, I discovered something that changed everything: software could solve the same problems faster, cheaper, and at a scale no engineer working alone ever could.

By the time I graduated, I wasn't just an engineer with a laptop. I was someone who couldn't stop building.

My first role out of university was at a software company shaping geomodeling tools for the oil and gas industry — translating the complex world of subsurface data into software that real engineers could use on real wells. It was the perfect collision of my two worlds. From there I continued building software solutions inside larger organizations, working at the enterprise scale where the stakes are high, the systems are complex, and the margin for error is thin.

But the corporate world could only contain so much of it. Alongside everything else, I built over 100 personal projects — spanning budget and trip planning, web-scraping, e-commerce stores, personal websites, workflow automations, data pipelines, dashboards, and things that probably didn't have a name yet. Not because I had to. Because every problem I encountered, my first instinct was: I can write something for that.

That instinct eventually led me to pursue a Master's in Technology Commercialization at the University of Texas at Austin. Here I learned something important: building great software isn't enough. You have to understand the business it serves, the market it enters, and the people who have to trust it. The degree wasn't about learning to code differently — it was about turning project into products.

AI was developing rapidly alongside with my academic journey and everything I'd spent years building expertise in — systems thinking, data engineering, software architecture, domain knowledge across oil & gas, SaaS, and e-commerce — suddenly became exponentially more valuable. I don't just use AI tools. I understand how they work at the model level, which means I can build with them in ways that most teams are still figuring out. My capabilities didn't change. They got multiplied.

Today I want to help startups and founders who need someone who has seen both sides — the technical depth of a career engineer and the commercial clarity of someone who has studied what it takes to bring a product to market. I've led engineering teams, built products from zero to one, scaled systems under pressure, and founded ventures of my own.

I'm not a consultant who talks about technology. I'm someone who has spent the better part of a decade in it — and I bring all of that to every engagement.