My journey.

What got me into building wasn't just writing code — it was the whole journey, from spotting a problem to seeing an actual solution in people's hands.

I got really into the whole process — understanding a problem, coming up with ideas, designing solutions, building products, shipping them, and then learning from how people actually use them. The best part isn't shipping a feature; it's finding out whether it actually fills a gap, solves a real problem, and makes a real difference.

Thinking like that pushed me to learn way more tech than what we cover in class. Every project became a chance to understand systems better, get better at engineering, and build better products.

These days I really enjoy building where software engineering, AI, and product thinking meet — where ideas turn into products, and products keep changing based on the people who use them.

Before I write a single line of code, I spend time really understanding the problem first.

I usually start with pen and paper — mapping out user flows, the system architecture, how features depend on each other, and what should and shouldn't be built. I like having clarity before I start implementing.

I try to picture the structure of the product long before it exists in code — how users will use it, how information moves through the system, and where things might get complicated later.

While I'm building, I keep reviewing, iterating, and refining. Features almost never come out great in the first version, so I keep improving them until they feel simple, easy to use, and solid.

When something breaks or I get stuck, I try to see it as part of the process instead of a setback. Every bug I fix, bottleneck I remove, and edge case I find makes both the product and my understanding of the system stronger.

I'm drawn to problems that sit somewhere between technology and human behaviour.

AI interests me because it changes what software can even do — it doesn't have to just follow instructions anymore; it can understand, adapt, reason, and help in ways that weren't possible before.

Startups interest me because they force you to be clear. You have limited resources, limited time, and no room to build stuff nobody needs. The hard part isn't writing more code — it's understanding the real problem well enough to build the right thing.

Research interests me for kind of the same reason. I like going past just using existing tools — actually understanding why systems work, where they fail, and what still hasn't been solved.

What keeps me building is one simple question:

If the answer is yes, I can honestly spend months thinking about it, building it, and improving it.

My long-term goal is to understand intelligence at a really fundamental level.

I want to study cognition and neuroscience deeply, look into how the brain learns and reasons, and eventually contribute to mathematical models of intelligence that could lead to more advanced AI systems.

Beyond AI, I'm just as fascinated by the universe itself — noticing patterns in nature, understanding physical laws, and exploring the principles behind how reality works.