Predicting the Future
People are bad at exponentials. Not a little bad — really bad. And it's quietly shaping every conversation about what AI will do to your business.
The paper-folding problem
Here's a question I like to ask leaders: how many times do you need to fold a piece of paper to reach the moon?
I've heard guesses ranging from thousands to billions. The real answer? 32 times. That's 232 — give or take, depending on paper thickness.
Most people's jaws drop. And that reaction tells you everything about how we're wired. We're comfortable with addition. We memorized our multiplication tables. But our brains aren't built to feel exponentials.
We live in an exponential world
Right now, the technology shaping your business — AI, compute, connectivity — is improving exponentially. And most people are still planning linearly.
I saw this firsthand at Zscaler. My team worked with some of the largest enterprises in EMEA, helping them enable secure access to AI to drive business transformation. What we kept running into wasn't a technology problem. It was an adoption problem. Companies would buy the most sophisticated tools available, set up training sessions, and then watch adoption stall at 10–20%.
The teams that did succeed weren't the ones with the best technology budgets. They were the ones with leaders who understood that the game had changed — and had built systems to help their people change with it.
Those teams saw deals 50% larger. Churn dropped by 42%. The difference wasn't the tool. It was the behavior change around the tool. That's what exponential thinking looks like on the ground.
The problem with predicting the future
I studied economics in college, and I remember wrestling with the fundamental challenge of the discipline: how do you predict what will happen when it depends on billions of individual decisions, made by billions of different people, with different motivations, backgrounds, and goals?
It's impossible. That's why my favorite economist YouTuber opens every video with: "Nobody can predict the future — least of all economists."
But here's what is mostly universal: the more equipped a person is for their specific situation, the better their outcomes. That's why governments, NGOs, and companies invest billions in education. Not because one curriculum works for everyone — it doesn't — but because equipping people with the right tools and knowledge, in the right context, works.
The child growing up in a village in the Darién jungle in Panama needs different skills than I need as a founder in Madrid. The sales engineer at a Fortune 500 needs a different AI workflow than the ops manager at a 50-person logistics company. This has always been true. What's changed is that we now have the technology to actually act on it.
For the first time, we can meet people where they are
For the first time in history, we're building technology that can personalize at scale.
Not "personalize" in the sense of changing the color scheme of a dashboard. I mean genuinely meeting a person — or a business — where they are, understanding what they're trying to accomplish, and building the specific path that gets them there.
AI isn't good at deciding what needs to be done or why it matters. People are. AI is good at tireless iteration — finding ways to solve problems, executing on them, improving until it gets there. Humans define the destination; AI accelerates the journey.
Will every job look the same in 5 years? Almost certainly not. In 10 years? Definitely not.
But that's not the threat it feels like. There are more problems in the world than there are people solving them. Creative thinkers who know how to work alongside AI aren't going to run out of work. They're going to have more leverage than any previous generation of problem-solvers.
Why we built Lucy Labs
That's the foundation of what we're building at Lucy Labs.
We believe in people. We believe in a future where humans and AI work together toward human-defined goals — not because it's a nice idea, but because the alternative (AI for AI's sake, tool-first rollouts that ignore behavior) consistently fails.
I've watched it fail. I've also watched the alternative work — when you build systems that meet people where they are, that coach behavior rather than just train on features, that connect AI to the actual problems someone is trying to solve.
That's what Lucy Labs does. Not another AI tool. A platform for human–AI productivity — one that turns exponential change from a threat into an advantage, for the people and businesses willing to get ahead of it.
The future isn't coming at a pace we're used to. It's coming at 232.
The question is whether you'll be ready for it.