Mercor, a startup founded just three years ago, has rapidly grown into a $10 billion intermediary capitalizing on the booming demand for AI data. The firm serves as a bridge between leading AI developers such as OpenAI and Anthropic and professionals who previously worked at elite institutions like Goldman Sachs, McKinsey, and prestigious law firms. These experts can earn as much as $200 per hour to impart their specialized knowledge, helping to train the very AI systems that may one day streamline or replace functions at their former workplaces.

Recently, we had the opportunity to speak with CEO Brendan Foody at this year’s Disrupt conference. He detailed why AI labs increasingly prefer highly skilled contractors over general crowdsourced labor, how challenges faced by Scale AI contributed to Mercor’s ascent, and his vision of an economy increasingly focused on preparing AI agents. Tune into the complete episode to explore:

Foody’s journey from providing AWS credit consulting in high school to building a company valued at $10 billion.

How the most skilled 10–20% of contractors are responsible for the bulk of model enhancements, and Mercor’s strategy for identifying these top performers.

The nuanced boundary between an employee’s expertise and corporate confidential information—and whether firms like Goldman Sachs have cause for concern.

Foody’s perspective that, in the future, all knowledge-based work will essentially serve as training material for AI agents.

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