Aiman Kulay

Most portfolios are a collection of projects, technologies and experience. Mine has those too, but they don't really explain why I build the things I build.

I enjoy solving problems, but I'm equally fascinated by how those solutions are experienced. To me, building software isn't just about making something work. It's about making it feel effortless, intentional and memorable.

This page isn't here to convince you to hire me. It's simply a glimpse into how I think, what I care about and why I spend so much time obsessing over details most people will never notice.

I've been around computers for as long as I can remember. Long before I understood what programming was, I was the kid clicking through every folder, changing desktop wallpapers, exploring settings I probably wasn't supposed to touch and wondering what every button actually did.

I wasn't interested in hardware. What fascinated me was the experience. How software responded, how interfaces behaved and how something as simple as clicking a button could make a machine feel almost alive.

That curiosity eventually turned into creating things of my own. HTML and CSS were my first canvas. They weren't just programming languages to me. They were tools that allowed me to take an empty page and slowly turn it into something visual, interactive and entirely my own.

People often expect a dramatic story when they ask why I chose Artificial Intelligence. The truth is far less cinematic. It simply felt like the most interesting direction at the time. Traditional software engineering already had well-established paths, but AI felt like unexplored territory. There were more questions than answers, and that uncertainty was exactly what attracted me.

I've never been interested in following a predefined roadmap just because everyone else was taking it. I enjoy stepping into areas where there's still room to experiment, question assumptions and learn something new every day. AI happened to offer that opportunity.

Over time, my perspective changed. I realised AI isn't impressive because it can generate images or hold conversations. Those are demonstrations. What interests me far more is solving problems that people or businesses genuinely face. Sometimes the best AI solution isn't the most complex model—it's the one that quietly removes friction without drawing attention to itself.

Imagine standing in a supermarket holding two biscuit packets. One looks thoughtfully designed, clean and premium. The other looks rushed together with little attention to detail. You don't know which one tastes better, yet almost everyone instinctively reaches for the first one.

That's what design really is.

Before a product proves itself, before someone experiences its features or understands the engineering behind it, design becomes the first conversation between the product and its user. It communicates trust, quality and confidence long before functionality gets a chance to speak.

I notice design everywhere. Door handles. Product packaging. Billboards. Mobile apps. Government websites. Laptop hinges. Even the radius of a button on a webpage. Most people don't consciously think about those details, but they influence how something feels to use. Great design often goes unnoticed because it simply feels right.

That's why I care about it so much. A technically brilliant product deserves an equally thoughtful experience. One without the other always feels incomplete.

For a long time, engineering and design were treated as two separate disciplines. One solved problems while the other made them look good. I've never really believed that distinction.

The products I admire most don't force users to think about either. They solve meaningful problems while feeling effortless to use. That's the balance I try to achieve whenever I build something.

I enjoy being involved from the earliest brainstorming sessions to the final deployment. Designing the experience, building the system, refining the tiny interactions and making sure every decision serves a purpose. Watching an idea slowly become a polished product is still one of the most satisfying parts of my work.

Not every problem needs generative AI. Not every business needs Retrieval-Augmented Generation. Sometimes the smartest solution is also the simplest one. My goal has never been to add AI for the sake of AI. It's to understand the problem first and then choose the right technology to solve it.

I spend an unreasonable amount of time thinking about things most people will never notice. Whether a divider should be lighter. Whether sixteen pixels of spacing feels better than twenty. Whether an animation is too fast. Whether a button deserves another iteration.

Some people might call that perfectionism. I think it's respect for the people using what I build.

There's a quote often associated with Steve Jobs that says people may not consciously notice the details, but they'll notice the absence of them. That idea has stayed with me for years. It's influenced not only how I design interfaces, but also how I approach engineering.

The goal isn't complexity. In fact, I actively avoid overcomplicating things. If a simpler solution exists, I'd rather spend more time finding it than hiding unnecessary complexity behind clever code.

During the early years of engineering, I genuinely believed I understood most of what there was to know. Looking back, that confidence came from not yet knowing how much I hadn't discovered.

The deeper I went into software, machine learning and product development, the more I realised how enormous the field really is. Instead of discouraging me, it changed how I approach learning.

These days I don't chase the feeling of knowing everything. I enjoy being proven wrong, discovering better approaches and slowly replacing certainty with curiosity. Progress isn't about reaching some finish line. It's about staying curious long enough to keep improving.

I wouldn't describe myself as someone obsessed with working harder than everyone else. If anything, I'm constantly looking for smarter ways to solve repetitive problems. Automation isn't about avoiding work—it's about making more time for the parts that actually require thinking.

AI has become part of that process. I use it every day, not as a replacement for learning, but as a tool to accelerate it. Asking better questions, validating ideas and exploring approaches faster has become just another part of how I work.

I'm also far more process-oriented than goal-oriented. Goals are useful, but they don't guarantee satisfaction. What I can control is showing up consistently, learning something new and making today's work slightly better than yesterday's. Everything else tends to follow.

Most of my time revolves around technology, but not all of it. When I'm away from work, you'll probably find me watching Modern Family for the hundredth time, reading about new developments in technology or spending time with cats. I currently have four of them, and somehow I've always preferred the older, calmer ones over energetic kittens.

I also find myself revisiting the philosophies of people like Steve Jobs. Not because I want to imitate them, but because I'm fascinated by the way they thought about products, craftsmanship and attention to detail. Those ideas continue to influence how I approach my own work today.

If someone remembers my work years from now, I hope it isn't because I used the latest framework or built the smartest AI model.

I hope it's because using it simply felt right.

Because the experience felt effortless. The interactions felt intentional. The design quietly earned their trust. The technology solved a real problem without demanding attention.

That's the kind of work I want to keep building.