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Hey Pal, Josh here. These two ends of the spectrum are wild, check it out.

The $3-Per-Hour Cashier and the Billion-Dollar AI Trainers: Two Sides of Work's Weird Future

Here's what's happening right now: A Filipino worker sits in their living room in Subic, greeting customers at a Manhattan chicken joint via Zoom for three dollars an hour. Meanwhile, three 22-year-old debate champions just became the world's youngest self-made billionaires by paying other people $85-$200 per hour to teach AI systems how to think.

These aren't random stories. They're the same story, just at opposite ends of the labor market—and they both end the same way.

The Arbitrage Game

Let's start with Happy Cashier, because it's beautifully dystopian. NYC restaurants mount iPads at the register, and suddenly your cashier is 8,500 miles away. The economics are brutally simple: New York minimum wage is $16/hour, Philippines minimum wage is $3.75, and Happy Cashier splits the difference at $3. Restaurant owners save money. The remote workers make 150% more than local cashier jobs. Everyone wins, right?

Except here's the thing: this model has maybe two years left before it's completely obsolete. If a human can take your order through a screen from the Philippines, an AI can take your order through that same screen from nowhere. The infrastructure they're building—the mounted tablets, the payment processing, the real-time interaction—that's all the setup work for voice AI. They're basically beta testing their own replacement.

The Billion-Dollar Scaffolding

Now zoom up the economic ladder to Mercor. Three kids drop out of Harvard and Georgetown with Thiel Fellowship money, and within two years they're running a company valued at $10 billion. What's the product? They connect 30,000 expert contractors—PhDs, lawyers, doctors—with AI labs that need human feedback to train their models.

The contractors make good money ($85-$200/hour). Mercor takes a cut. OpenAI, Anthropic, and DeepMind get smarter AI. The company's paying out $1.5 million daily to contractors and pulling nearly $500 million in annualized revenue.

But listen: these contractors aren't building the future. They're teaching their replacements. Every hour a lawyer spends explaining legal reasoning to Claude or GPT, that's one more hour the model learns to reason like a lawyer. The work is well-paid, skilled, and completely self-terminating.

The Pattern

Both companies occupy this bizarre transitional moment where:

• Geographic wage arbitrage still makes sense

• Humans are cheaper/better than AI (for now)

• The technology exists to coordinate remote labor at scale

• Nobody's quite ready to automate fully yet

Mercor's founders are transparent about this. CEO Brendan Foody basically admits they're unlocking proprietary knowledge that enterprises want to keep locked up—former Goldman Sachs employees sharing workflows, startup CTOs granting access to production codebases. All of it feeding AI models that will eventually automate those same jobs.

The $3/hour cashier and the $200/hour domain expert are both participating in the same process: training the systems that will make them unnecessary.

What Happens Next

The difference is what happens when the transition completes. Happy Cashier's workers are disposable by design—when voice AI gets good enough, they're gone, and they've built no lasting value. Mercor's founders, though? They own the platform. They've positioned themselves as the intermediary between human expertise and AI capability, and even when the humans become optional, they might still control the infrastructure.

This is the actual story of AI and work: not that robots are coming for jobs (they are, obviously), but that the most lucrative position is building the bridge between human labor and automation—then charging a toll on both sides until you can remove the humans entirely and just own the automated system.

The 22-year-old billionaires figured this out. The remote cashiers are living through it. And the rest of us are somewhere in between, wondering which end of this deal we're on.