Brendan Foody on Teaching AI and the Future of Knowledge Work

2026-01-07

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At 22, Brendan Foody is both the youngest Conversations with Tyler guest ever and the youngest unicorn founder on record. His company Mercor hires the experts who train frontier AI models—from poets grading verse to economists building evaluation frameworks—and has become one of the fastest-growing startups in history. Tyler and Brendan discuss why Mercor pays poets $150 an hour, why AI labs need rubrics more than raw text, whether we should enshrine the aesthetic standards of past eras rather than current ones, how quickly models are improving at economically valuable tasks, how long until AI can stump Cass Sunstein, the coming shift toward knowledge workers building RL environments instead of ...

Tyler and Brendan discuss why Mercor pays poets $150 an hour, why AI labs need rubrics more than raw text, whether we should enshrine the aesthetic standards of past eras rather than current ones, how quickly models are improving at economically valuable tasks, how long until AI can stump Cass Sunstein, the coming shift toward knowledge workers building RL environments instead of doing repetitive analysis, how to interview without falling for vibes, why nepotism might make a comeback as AI optimizes everyone's cover letters, scaling the Thiel Fellowship 100,000X, what his 8th-grade donut empire taught him about driving out competition, the link between dyslexia and entrepreneurship, dining out and dating in San Francisco, Mercor's next steps, and more.

Read a full transcript enhanced with helpful links, or watch the full video on the new dedicated Conversations with Tyler channel.

Recorded October 16th, 2025.

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Timestamps

00:00:00 - Hiring poets to teach AI

00:05:29 - Measuring real-world AI progress

00:13:25 - Why rubrics are the new oil

00:18:44 - Enshrining taste in LLMs

00:22:38 - Turning society into one giant RL machine

00:26:37 - When AI will stump experts

00:30:46 - AI and employment

00:35:05 - Why vibes-based hiring fails

00:39:55 - Solving labor market matching problems

00:45:01 - Scaling the Thiel Fellowship

00:48:11 - A hypothetical gap year