He Hit Every Goal on His List and Felt Nothing. That's When He Started Writing About AI's Next Class System.

Kunal Gupta remembers the exact moment, about a decade ago, running his company out of a Toronto office. Everything on his list was done. The business was profitable. No client was complaining. No staff had quit. By every external measure, he'd arrived. "I expected to feel successful and satisfied and happy and content," he says. "And I realised I just feel the same."

He doesn't dress up what that was. "I got to a place of curiosity from a place of burnout," he says, "and a place of fatigue, and a place of dissatisfaction after working like a dog and continually striving, striving, striving."

Building the thing before there was a word for it

Gupta was twenty when he started his first company, Polar, early enough in the smartphone era that he claims a share of the very first wave of iPhone apps — by his count, the ninth, twelfth and eighteenth ever approved. "Guaranteed, every person listening to this podcast has used an app that was built by me," he says, not quite boasting, more stating a strange fact about how early he got there. What pulled him out of the flatness that followed wasn't a pivot or an exit. It was meditation, journaling and yoga — habits he's kept for roughly a decade since, including a personal-reflection newsletter, How to Live, he's published every single Sunday for ten years straight.

AI literacy as the new reading and writing

Gupta's current argument is that AI fluency is heading toward becoming as foundational as literacy itself — not a specialist skill, but a baseline one society will eventually assume everyone has, the way it now assumes everyone can read. He sorts people into three rough camps: AI curious, AI confident, and AI confused, and argues the gap between the last group and the first two is where real inequality is forming.

His sharpest example is close to home. "My parents are getting old," he says, "and it's the same UI for somebody who's seventy years old and somebody who's seventeen. That makes no sense." Consumer software, in his telling, has always been built one-size-fits-all and left the user to adapt to the product, not the other way around. "The first one that builds an AI chatbot for seniors," he says, "is going to win."

The digital aristocracy

That framework is also the premise of his book, 2034: How AI Changed Humanity Forever, written roughly two years before this conversation, with every dollar of proceeds going to AI-literacy charities. It imagines a near-future class system built not on money or schooling but on who actually knows how to direct AI well. "Learning how to AI," he says, "is going to create a new species — not biologically, but from a socioeconomic standpoint, a quality-of-life standpoint, an access-to-healthcare, education, networks, services standpoint." He doesn't treat this as speculative fiction so much as a trajectory already underway. "Extrapolate that even two years," he says, "and society gets pretty bifurcated."

He's more optimistic about the flip side than the framing suggests. He points to how mobile banking reached parts of Africa and Southeast Asia a decade ahead of the West, by skipping landlines, dial-up and home computers entirely and going straight to phones. "I could see the same leapfrog opportunity," he says, "for parts of society" currently locked out by age, language or geography — provided AI literacy gets deliberately spread rather than left to concentrate wherever money already is.

The great humbling

Asked what he thinks is coming that most people aren't bracing for, Gupta reaches past the usual job-displacement talking points for something closer to a cultural reckoning. "I think there's going to be a moment," he says, "when we realise that we're not as unique, we're not as skilled as we think we are, and there'll be a real humbling. I call it the great humbling of humanity. That moment hasn't happened yet, and I think it's coming." Coming from someone who already lived through his own smaller version of it — arriving at everything he thought he wanted, and finding out that wasn't the point — it reads less like a prediction than a pattern he recognises.