Yash Patil is the 23-year-old founder and CEO of Applied Compute, a $1.3 billion company helping businesses train custom AI models on their own data: smaller, cheaper, and purpose-built for the work they actually do. Before founding the company, Yash dropped out of Stanford and spent two years at OpenAI working on post-training infrastructure and Codex. He left with one core conviction: every company that runs its critical workflows on someone else’s model is building on shifting sand. Applied Compute is his answer to that problem, already serving customers including DoorDash, Cognition, and Mercor.

In our conversation, we explore:

• Why “own or be owned” is becoming existential for any company that relies on frontier AI models
• What it was like inside OpenAI the weekend the board fired, and then reinstated, its CEO
• Why post-training is where competitive advantage is now being built, and what reinforcement learning with verifiable rewards actually is
• Why evals have become the new production environment, and why companies will never share them with frontier providers
• How a specialized model built for DoorDash outperformed frontier models on a narrow, high-value task
• Why cost, not capability, is now the primary driver pushing companies toward custom models
• Why Yash believes AI’s transformation of the economy will unfold over decades, and why near-term fears about mass job displacement are misplaced

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Thank you to the partners who make this possible

Brex: The intelligent finance platform.

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Transcript: https://www.generalist.com/p/own-or-be-owned-why-every-company

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Timestamps

(00:00) Introduction

(03:50) Fable 5 and the case for owning your own models

(09:22) Why Applied Compute is betting on custom AI models

(12:30) Yash's early influences and first projects

(17:42) His brief time building at Stanford

(19:29) Leaving Stanford for OpenAI

(25:58) Inside OpenAI during Sam Altman's firing

(28:18) What Yash admires about Sam Altman

(29:43) Teaching models to reason

(35:39) The core insight behind Applied Compute

(39:40) How Applied Compute works with its customers

(45:55) Why model training never ends

(48:56) Why not every task needs a frontier model

(51:25) The culture and people of Applied Compute

(54:50) Applied Compute's training infrastructure

(58:43) The coming compute crunch and other predictions

(1:03:48) Final meditations

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Follow Yash Patil

X: https://x.com/ypatil125

Website: https://yashpatil.me

LinkedIn: https://www.linkedin.com/in/yash-s-patil

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Resources and episode mentions: https://www.generalist.com/p/own-or-be-owned-why-every-company⁠

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