Y CombinatorHow Internships Seed Most of YC's Billion-Dollar Startups
Internships at Cohere and going undercover as a medical biller surface real problems; hackathon ideas miss these, but outsourced jobs signal the next wave.
Episode Details
EPISODE INFO
- Released
- February 7, 2025
- Duration
- 43m
- Channel
- Y Combinator
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Apply to AI Startup School in SF: https://events.ycombinator.com/ai-sus There’s never been a better time to launch an AI startup, but many prospective founders find themselves stuck when it comes to thinking of a good idea. In this episode, the Lightcone hosts look at different ways breakthroughs can be discovered. Apply to Y Combinator, applications for X25 are due Feb 11: https://ycombinator.com/apply Learn more about the startups mentioned in this episode: Salient: https://www.trysalient.com Diode: https://diode.computer Spur: https://www.spurtest.com Datacurve: https://datacurve.ai David AI: https://www.withdavid.ai Can of Soup: https://canofsoup.com Happenstance: https://happenstance.ai Ezdubs: https://www.ezdubs.ai Egress Health: https://tryegress.com HappyRobot: https://happyrobot.ai Abel Police: https://abelpolice.com Sweetspot: https://www.sweetspot.so Lilac Labs: https://www.drive-thru.ai Automat: https://www.runautomat.com ParadeDB: https://paradedb.com Reducto: https://reducto.ai Juicebox: https://juicebox.ai Giga ML: https://gigaml.com Zepto: https://www.zeptonow.com Chapters (Powered by https://bit.ly/chapterme-yc) - 00:00 - Intro 03:20 - First version 04:38 - Examples 10:55 - Pivoting 12:35 - Internships 22:20 - Going undercover 37:35 - Fundraising 41:45 - Product Market Fit
SPEAKERS
Garry Tan
hostHarj Taggar
hostJared Friedman
hostDiana Hu
host
EPISODE SUMMARY
In this episode of Y Combinator, featuring Garry Tan and Harj Taggar, How Internships Seed Most of YC's Billion-Dollar Startups explores from Hackathon Hacks To Billion-Dollar AI: Finding Real Ideas The hosts of the Lightcone Podcast explain how aspiring founders can systematically generate strong AI startup ideas by going beyond shallow, hackathon-style projects and instead pursuing hard, ambitious problems.
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