A Love-Hate Relationship with Economics

As I entered IIT Kanpur, I found myself drawn to the intellectual allure of economics. While most of my peers were diving into computer science or electrical engineering, I was captivated by models that promised to explain human behavior at scale. Little did I know this fascination would evolve into something more complicated: a relationship that would shape my career in unexpected ways.

The Initial Infatuation

My first economics class felt like a revelation. Here was a discipline that claimed to decode the mysteries of markets, predict consumer behavior, and optimize resource allocation. The mathematical rigor appealed to my analytical side, while the human element kept it from feeling sterile.

I dove deep into microeconomics, marveling at how supply and demand curves could explain everything from coffee prices to labor markets. Macroeconomics opened my eyes to the machinery of nations: GDP, inflation, monetary policy. Game theory introduced me to strategic thinking that would later prove invaluable in business.

The Cracks Appear

But as I progressed, doubts crept in. The models that had seemed elegant started to feel disconnected from reality. The assumptions required to make the math work (rational actors, perfect information, frictionless markets) seemed increasingly removed from how people actually behave.

The shift happened during an internship. What we modeled in class bore little resemblance to what I observed in industry. The clean equations couldn't capture the messiness of real decisions. It wasn't that economics was wrong. It was that the gap between theory and application was wider than I'd expected.

That gap ultimately took me away from an applied economics career.

The Computer Science Escape

This disillusionment coincided with my discovery of computer science. Unlike economic models that could only describe the world, code could actually change it. When you write a program, it does what you tell it to do. The feedback loop is immediate, the results tangible.

I found myself spending more time in the CS labs, working on AI problems and building systems. The minor in CS became as important to me as my major in economics.

The Unexpected Synthesis

What I didn't realize then was that I wasn't abandoning economics. I was finding a new way to apply it. When I later founded Balance, a micro-savings fintech, every design decision was informed by behavioral economics.

One thing we learned: nudges work best when they're contextual, even if the context seems random. Saving prompts tied to meeting a fitness goal of 10,000 steps, or even something as whimsical as the International Space Station passing overhead: these performed better than generic reminders. People don't respond to logic alone; they respond to moments.

At Paytm, leading product for millions of users, economic thinking helped me understand incentive structures and market dynamics at scale. Now, building AI tools for healthcare, I constantly draw on both disciplines: using AI to augment human decision-making in domains where the stakes are high.

The Reconciliation

Looking back, my love-hate relationship with economics was really a journey toward integration. Economics gave me frameworks for thinking about incentives, trade-offs, and system dynamics. Computer science gave me the tools to build things. The combination proved more powerful than either alone.

To any student feeling torn between disciplines: embrace the tension. The most interesting work often happens at the intersections.

Economics didn't give me the answers I thought it would. But it taught me how to ask better questions. In the end, that might be more valuable.