Frontier labs like OpenAI and Anthropic need vast amounts of data in the race to achieve AGI. This comes at a pretty penny — billions of dollars — and little-known companies like Mercor and Handshake are cleaning up in this AI hype cycle.

When he was 19 years old, Brendan Foody started Mercor with two of his high school friends as a way for his other friends, who also had startups, to hire software engineers overseas. It launched in 2023 as essentially a staffing agency, albeit a highly automated one. Language models reviewed resumes and did the interviewing. Within months, Mercor was bringing in $1 million in annualized revenue and turning a modest profit.

Then, in early 2024, the company Scale AI approached Mercor with a big request: They needed 1,200 software engineers. At the time, Scale was one of the only well-known names in the historically back-of-house business of producing AI training data. It had grown to a valuation of nearly $14 billion by orchestrating hundreds of thousands of people around the world to label data for self-driving cars, e-commerce algorithms, and language-model-powered chatbots. Now that OpenAI, Anthropic, and other companies were trying to teach their chatbots to code, Scale needed software engineers to produce the training data.

This, Foody sensed, could herald a larger change in the AI industry. He’d heard about growing demand for specialized data work, and now here was Scale asking for a thousand coders. When the engineers he recruited started complaining about missed pay (Scale has a reputation among data workers for chaotic platform management and is being sued in California over wage theft, among other infractions), Foody decided to cut out the middleman.

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