I’m Not Edwin Chen. So What Can His $1 Billion AI Business Teach Me?

 HappyKay Lifegazing · Business & AI

I’m Not Edwin Chen. So What Can His $1 Billion AI Business Teach Me?

I came across a story about Edwin Chen, founder of Surge AI.

MIT
Mathematics.
Linguistics.
Machine learning.
Google.
Facebook.
Twitter.

And then there was me, reading the story.

I have never studied at an Ivy League school. I don’t know machine learning. I wouldn’t know what to do with a giant dataset if someone handed one to me.

So my first thought wasn’t,

How inspiring.

It was much more practical:

What does any of this have to do with someone like me?

I’m trying to build a small online business. I write a blog. I create content. I use AI. I’m learning Pinterest and Instagram. I’m trying to understand what people might actually find useful—and eventually, what could become a real source of income.

Surge AI operates in an entirely different universe.

So why should I care?

The more I looked at the company, though, the more I realized there was one idea worth taking home.

And it wasn’t mathematics.

It was judgment.

Surge AI, in ordinary-person language

AI needs enormous amounts of data, but having data isn’t enough.

Someone still has to help determine:

Is this answer good?

Is that answer better?

Does this make sense?

Is it accurate?

Would a human actually find this useful?

Surge AI built a business around helping AI companies obtain high-quality human feedback and evaluation.

That was the part that stopped me.

Because suddenly this wasn’t only an AI story.

It was a story about something much more familiar:

There is already too much information in the world. The valuable part may be knowing what to do with it.

Maybe my job isn’t to create more information

This made me think about my own little corner of the internet.

Take travel.

Search for “Paris travel” and there is almost too much information.

Hotels.
Metro maps.
Museum tickets.
Restaurants.
Travel insurance.
Airport transportation.
Neighborhood guides.

The problem isn’t finding information anymore.

The problem is standing in front of all of it and wondering:

Okay…but what should I actually do?

A mother traveling to Paris for the first time with her teenage daughter may not need another list of 50 hotels.

She may need someone to say:

I looked through all of this. Here are the few things I would pay attention to. Here’s what confused me. Here’s what I learned. And if I were planning this trip myself, this is where I would start.

That’s different.

That’s judgment.

And perhaps that’s where a small creator can still be useful in an AI-filled world.

But Edwin Chen has something I don’t have

This is also where I think we have to be careful with billionaire founder stories.

I cannot copy Edwin Chen’s education, technical expertise, Silicon Valley experience, professional network or circumstances.

And pretending otherwise wouldn’t teach me very much.

So instead of asking,

“How can I become like him?”

I’m learning to ask:

“What principle from his business can I borrow at my own scale?”

That’s a much more useful question.

From Surge AI, the principle I want to borrow is this:

Don’t compete by producing more.
Become better at recognizing what is useful.

That I can practice.

My tiny version of data doesn’t require a mathematics degree

I used to hear the word data and imagine enormous spreadsheets and complicated statistics.

But for a small creator, data can begin with something much simpler.

Which Pinterest post did people save?

Which blog article did people find through Google?

Which title received clicks?

Which subject received almost no response?

Which question keeps appearing?

Which post unexpectedly keeps bringing people back?

Those are data too.

And today I don’t necessarily have to become the analyst myself.

AI can help me organize the numbers and explain what they might mean.

Then I can do the part AI shouldn’t completely take away from me:

I decide what seems worth pursuing.

Platform → gives me signals.

AI → helps me organize and understand them.

Human → makes the judgment.

Suddenly “data-driven business” sounds much less frightening.

A five-question experiment for my own small business

I’m going to start looking at my content through five questions:

1. PROBLEM — What is someone struggling with?

Not, What do I feel like posting today?

But also:

What question is this helping someone answer?

2. INFORMATION — What can I find?

Research. Read. Compare. Ask AI. Check original sources.

3. JUDGMENT — What actually matters?

This may be where the human value begins.

Not everything I find deserves to be passed along.

4. TRANSLATION — Can I explain it to someone like me?

No industry jargon required.

If I can’t understand it, I probably can’t make it useful to someone else.

5. PRODUCT — Does this problem keep coming back?

Only then might a blog post become something more:

a printable,

a beginner’s guide,

an affiliate resource,

a travel checklist,

a small digital product,

or perhaps something I haven’t thought of yet.

I don’t need to monetize every idea.

I can watch first.

Maybe this is my version of an edge

This was the part of the Surge AI story I didn’t expect.

At first, Edwin Chen’s background made me wonder whether people like him simply possess an edge that ordinary people don’t.

In some ways, of course they do.

Expertise matters.

Education matters.

Experience matters.

But that doesn’t mean everyone needs the same edge.

Perhaps a small creator’s edge can be something else:

Curiosity + lived experience + taste + judgment + consistency + AI.

And perhaps another surprisingly valuable skill is translation.

Not translation from Korean to English.

Translation from:

“Here is everything happening in the world”

to:

“Here is why this might matter in your actual life.”

That’s something I would like HappyKay Lifegazing to become better at.

I don’t want to pretend to be an AI expert.

I don’t want to pretend to be a financial analyst.

I don’t need to become Edwin Chen.

But I can read about someone building a remarkable company and ask:

What did they notice that other people overlooked?

Why did people pay for it?

And is there one tiny piece of that thinking I can borrow for my own life?

That may be enough.

Because perhaps learning from extraordinary people doesn’t mean copying their lives.

Sometimes it simply means borrowing one useful lens—

and then looking at our own ordinary lives differently through it.

A question I’m taking with me

In a world where AI can produce more and more information, what kind of human judgment could become uniquely valuable from me?

I don’t know the full answer yet.

But I think that’s a much more interesting business question to explore.

— HappyKay