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Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, and now founder of Eureka Labs) talks with Sequoia partner Stephanie Zhan at AI Ascent 2026 about what's changed in the year since he coined "vibe coding."

Stephanie ZhanhostAndrej Karpathyguest
Apr 29, 202629mWatch on YouTube

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Episode Details

EPISODE INFO

Released
April 29, 2026
Duration
29m
Channel
Sequoia Capital
Watch on YouTube
▶ Open ↗

EPISODE DESCRIPTION

Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, and now founder of Eureka Labs) talks with Sequoia partner Stephanie Zhan at AI Ascent 2026 about what's changed in the year since he coined "vibe coding." He explains why he's never felt more behind as a programmer, why agentic engineering is the more serious discipline taking shape on top of vibe coding, and why we should think of LLMs not as animals but as ghosts: jagged, statistical, summoned entities that require a new kind of taste and judgment to direct. He also touches on Software 3.0, the limits of verifiability, and why you can outsource your thinking but never your understanding. 00:00 Introduction 00:44 Feeling Behind as a Coder 02:28 Software 3.0 Explained 03:44 Agents as the Installer 04:49 Menu Gen vs Raw Prompts 07:37 What’s Obvious by 2026 09:41 Verifiability and Jagged Skills 13:39 Founder Advice and Automation 15:46 From Vibe Coding to Agent Engineering 25:17 Agents Everywhere and Learning

SPEAKERS

  • Stephanie Zhan

    host

    Partner at Sequoia Capital and host/interviewer for AI Ascent.

  • Andrej Karpathy

    guest

    AI researcher and engineer known for work on deep learning and large language models.

EPISODE SUMMARY

In this episode of Sequoia Capital, featuring Stephanie Zhan and Andrej Karpathy, Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan explores Why “Software 3.0” turns prompting into programming and engineering Andrej Karpathy describes a personal inflection point in December where agentic coding tools began producing reliably correct code, leading him to feel “behind as a programmer” while also enabling rapid side projects.

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