Building Better Problem Solvers Since 2019
We started with a simple observation. Most people learning algorithms were memorizing patterns without understanding why they worked. That disconnect bothered us.
So we built something different. Not another bootcamp promising overnight transformations. Just honest education focused on how algorithms actually solve real problems.
Today, we work with students across Taiwan who want to genuinely understand computational thinking. Some are switching careers. Others are sharpening existing skills. All of them appreciate that we don't oversell what six months of study can accomplish.
The tech industry doesn't need more people who've memorized leetcode solutions. It needs people who can think through problems methodically and explain their reasoning clearly. That's what we teach.
Dragomir Solberg
Founder & Lead Instructor
I spent twelve years in software engineering before starting EvolvBeam. Most of that time, I watched talented people struggle not because they lacked intelligence, but because algorithm education was fundamentally broken.
The breakthrough came during a mentorship session in 2018. A junior developer asked me why we chose binary search for a particular problem. Not how to implement it—why it made sense for that situation. That question changed everything.
When I founded EvolvBeam in 2019, the goal wasn't to create the fastest path to a job offer. It was to teach people how to think about problems the way experienced developers do. To understand trade-offs. To evaluate options. To communicate technical decisions clearly.
We grow slowly and deliberately. Each cohort stays small because individual feedback matters more than scale. Our students don't always land jobs immediately after graduating. But when they do, they're ready for the actual work.
Six Years of Steady Growth
We've never chased rapid expansion. Each step forward came from listening to what students actually needed, not what sounded impressive in marketing.
Foundation Year
Started with eight students in a shared workspace. The curriculum was rough. We spent more time revising lessons than teaching them. But those first students helped us figure out what actually worked.
Curriculum Overhaul
After two years of feedback, we rebuilt everything. Out went the theoretical proofs nobody used. In came practical problem-solving frameworks and real-world case studies that connected concepts to actual development work.
Industry Partnerships
Local tech companies started reaching out. Not for recruitment pipelines, but for input on what junior developers actually needed to know. Those conversations shaped our advanced modules on system design and optimization patterns.
Sustainable Scale
We now run four cohorts annually with 15-20 students each. Still small by bootcamp standards. But our completion rate sits above 85%, and graduates consistently report feeling prepared for technical interviews and actual job responsibilities.
How We Actually Teach
Forget the buzzwords. Here's what happens when you study with us, explained without the usual education industry nonsense.
Problems Before Solutions
We don't start with algorithm definitions. We start with problems that need solving. You'll struggle with them first. Only after you've wrestled with the challenge do we introduce the algorithmic approach. This discomfort is intentional—it's how understanding actually develops.
Trade-Offs Over Perfection
Every algorithm choice involves compromise. Speed versus memory. Complexity versus maintainability. We spend considerable time on why you'd pick one approach over another in different contexts. The "it depends" answer is often the most honest one.
Communication Counts
Being able to explain your reasoning matters as much as getting the right answer. You'll practice articulating trade-offs, walking through your thought process, and justifying technical decisions. These skills transfer directly to code reviews and technical interviews.