The AI Arbitrage Opportunity: Code Just Got Cheap

Writing code is becoming worthless.

But that’s not bad news. It’s an arbitrage opportunity.

The Barrier Is Collapsing

Building things in the digital world used to be hard.

Learn to code. Learn frameworks. Learn deployment. Without years of practice, nothing gets built.

Want a simple website? Learn HTML, CSS, JavaScript. Want an app? Learn React or Swift. Want a database? Learn SQL, APIs, backend frameworks.

Every layer is a barrier. Every layer takes time.

So most people stayed consumers. Scrolling phones, watching content, paying for products others built.

Now it’s different.

AI made code cheap.

What used to take years to learn can now be done in days—just explain what you want to the AI clearly.

That gap in barriers is the arbitrage space.

What Is Arbitrage?

Arbitrage is simple: something is expensive in one place, cheap in another. Buy where it’s cheap, sell where it’s expensive. The difference is profit.

Code is in that state right now.

In most people’s minds, “knowing how to code” is still a rare skill. Companies pay high salaries for engineers. Founders spend fortunes outsourcing development.

But in reality, AI already made this cheap.

You don’t need to actually “know how to code.” You need to know how to communicate with AI.

Being able to explain requirements clearly, understand AI’s output, iterate step by step—these skills don’t take years to develop.

This perception gap is the arbitrage window.

Digital Assets vs Platform Content

But knowing how to use AI to code isn’t enough.

The key question: what should this ability be used to build?

Many people’s first instinct is content creation. Writing articles, making videos, building social media presence.

These have value, but there’s a fundamental problem: traffic comes from the platform.

Platform changes algorithm, reach gets cut in half. Platform bans account, everything’s gone. Platform shuts down, content disappears with it.

Thinking you’re building assets, but actually working for the platform.

Real digital assets are different.

Think about a house.

Buy a house, rent it out, monthly income flows in. No need to manage it daily—it generates cash flow on its own.

Digital assets can work the same way.

A website on your own domain, continuously bringing traffic. A tool solving a specific problem, people willing to pay. A product with users, income coming in while you sleep.

These three things connected form a complete system:

Website brings traffic, traffic converts to users, users pay for the product.

Build once, it runs itself. That’s an asset.

And this is a long-term game.

Slow at first. No traffic, no users, no revenue.

But every article, every feature, every user compounds.

Time works in your favor.

People selling time—today’s effort resets to zero tomorrow. People building assets—today’s effort keeps stacking.

A year later, the gap becomes unbelievable.

Digital assets are even better than houses: marginal cost approaches zero.

A house can only be rented to one person. A digital product can serve unlimited people simultaneously.

Why Will the Window Close?

Arbitrage opportunities don’t last forever.

As more people realize AI can help them build things, this skill stops being rare.

Right now, building a product with AI still makes people think “wow, you can code.”

Three years from now? This might become a basic skill, like knowing Excel today.

The essence of arbitrage is information asymmetry. When the information gap closes, arbitrage ends.

So now is the best time.

Not because the barrier is lowest—it will only get lower.

Because most people haven’t caught on yet.

Where to Start?

Never used AI to code? Don’t worry.

The barrier is really lower than you’d think.

What’s needed isn’t learning programming languages—it’s learning to communicate with AI. Breaking vague ideas into concrete requirements. Understanding AI’s output, then iterating step by step.

These skills—anyone who’s done project management, written documents, communicated requirements—already has the foundation.

For tools, the most common choices now are Cursor, Claude Code, GitHub Copilot. Each has pros and cons, but the core logic is the same: describe requirements in natural language, AI generates code.

For a more complete comparison and real experience, see this post: 14 Years Away from Engineering, I Built a Complete Product with AI.

Closing

How long will this window stay open? Unknown.

But when everyone can build with AI, the arbitrage ends.

If there’s something you’ve always wanted to build, now is the best time to start.