I have spent the past three months in the company of a man who used to design algorithms for machines and now designs frameworks for living. Mo Gawdat, former Chief Business Officer of Google X, wrote four books that I’ve devoured in succession: “Scary Smart”, “Unstressable”, “Solve for Happy” and “That Little Voice In Your Head: Adjust the Code That Runs Your Brain”.

On paper, he’s an engineer. In spirit, he’s a philosopher. And somewhere between those two identities lies a way of thinking about the human condition that I’ve come to love deeply. For someone like me, who has always found comfort in the precision of mathematics, his approach to human experience is strangely satisfying.

Mo Gawdat treats emotions like systems, stress like input overload and happiness like an equation. His hypothesis is disarmingly simple:

Happiness is equal to or greater than the difference between the way we perceive events and our expectations of how those events should be.

When I first read that, my inner mathematician smiled. Here was someone articulating an emotional truth in the language of logic, assigning structure to something most of us experience as uncertainty.

It sounded overly tidy. But the more I observed my own life, the more the math revealed itself. The moments that unsettled me weren’t objectively bad. They were the ones that didn’t fit my mental model of how life should unfold. That gap (between “is” and “should”) is where suffering tends to hide.

Decoding Grief

What makes Mo Gawdat’s perspective remarkable is the context it comes from. He lost his son, Ali, at twenty-one and yet he didn’t let grief immobilize him. Instead, he treated it like a problem to analyze, a system to understand. Out of that unimaginable loss came a framework for returning to clarity, a map that doesn’t erase pain but shows how to navigate it.

Reading him felt like watching someone reverse-engineer what it means to be human. Happiness, he suggests, isn’t something we stumble into, it’s something we can approach with curiosity, logic and care.

Patterns in Feeling

It’s easy to think emotions are unpredictable. But the more I read Mo Gawdat, the more I saw patterns in my own mind. Stress is predictable. Unhappiness is predictable. Both arise when life fails to match our internal model of how it should be.

Engineers debug malfunctioning systems. What if we applied the same patience to our minds? Observing emotions without judgment, questioning assumptions, recalibrating expectations. Suddenly, we aren’t at their mercy. We’re learning their language.

I think that’s why I love reading psychology through an engineering lens. It replaces quick assumptions with curiosity. It says, “Hey, maybe your brain is just running a slightly outdated code, let’s debug it”. There’s precision in that, but also compassion.

The Equation I Return To

Since reading Solve for Happy, I catch myself mid-spiral and ask:

“Is it the event or my expectation of it?”

Almost always, it’s the expectation. The delay didn’t frustrate me; my anticipation that it would be faster did. The criticism didn’t sting; my assumption that it shouldn’t exist did. Separating reality from my story about it has recently saved me from countless unnecessary storms.

The Ongoing Calculation

I’ve loved mathematics since I was a child, drawn to its clarity and order. But now I see its deeper beauty in its adaptability, in the way errors can be corrected, systems recalibrated and equilibrium restored.

Mo Gawdat taught me that happiness works the same way. It isn’t a final destination or a fleeting emotion. It’s something we keep solving for, patiently and intelligently, over and over, until the balance returns and life feels aligned again.