We Need to Think Bigger
In 2013, I pitched the CEO of the Singapore Stock Exchange a Myanmar e-commerce company. We thought too small and the product died. AI makes ambitious attempts cheap enough to explore.
In 2013, I was 21 or 22, sitting in Magnus's home in Singapore and trying to raise money from him.
Magnus was the CEO of Singapore Stock Exchange at the time.
I was starstruck and so nervous that my knees were shaking.
He asked me about my biggest dream for the company. I told him I wanted to build a really successful company in Myanmar.
"Think bigger," he said.
I didn't understand what he meant.
At the time, we were building something like Shopify, but designed entirely for mobile. Smartphone use was growing quickly in Myanmar, and we believed online shopping would follow.
To make it work, we built much of the underlying technology ourselves. We compiled Android apps on our own virtual machines on AWS and iOS apps on colocated Mac Minis.
This was long before cloud app builds became common.
The product eventually failed. The e-commerce behaviour we expected in Myanmar did not arrive quickly enough.
But the part that bothers me now is not that we were wrong.
It is that we only explored one version of the idea and gave it up.
We never seriously considered taking the product somewhere that already had strong e-commerce behaviour.
We never considered turning the infrastructure we had built into the company itself.
Maybe both would have failed too.
But we didn't even attempt them.
That is the real cost of thinking small. You don't just build a smaller company. You fail to see the other companies you could have built.
AI makes ambitious attempts cheaper
AI is not just making our existing plans cheaper to execute.
It is making entirely different plans cheaper to explore.
If we had today's tools back then, we could have explored the same product across different markets. We could have tested the infrastructure as its own business. We could have researched the demand, built different versions and challenged our original assumptions before betting everything on one path.
None of this would have guaranteed success.
But it would have made more futures possible to attempt.
That is what has changed.
In the past, exploring every direction required more people, more expertise, more time and more money. So we learned to narrow our ambitions early.
We started with what we knew and reduced the idea until it fit.
AI allows us to reverse that.
We can start with the biggest version of the idea. We can explore the markets, products and business models around it. Then we can let reality tell us where the limits are.
Thinking big does not mean doing everything.
It means refusing to shrink the idea before we have explored what it could become.
In 2013, I treated Myanmar as a fact. It was only an assumption based on the world I knew.
Today, our assumptions are based on what we think one person or a small team can achieve.
Those assumptions are changing quickly.
AI does not make every ambitious idea work.
It makes ambitious ideas cheap enough to attempt.
We need to think bigger.
Related reading: I wrote about my first company and what the founder role cost me in High Agency Burned Me Out, and about why I stepped away from founding in I Never Wanted to Be a Founder.