A New Vision for Human Work After Automation

Thesis: 2027 is made possible by our founding partners, Lovable and Notion. Lovable is the fastest way to turn ideas into software people love: https://link.lovable.dev/every Notion is the collaborative AI workspace where teams and agents work side by side: https://www.notion.com/?utm_source=youtube&utm_campaign=thesis-2027&utm_content=every-261111-video What does great human work look like after automation? It’s a question we try to answer every day at Every, and the one we built our conference, Thesis, around. In his closing keynote, *Dan Shipper* argues that as AI makes intelligence cheap and widely available, what matters most is human perspective. It’s your “non-consensus” point of view, plus your responsibility for a particular corner of the world, that helps you spot the insight no one else would. On this week’s episode of The Every Podcast, we’re sharing Dan’s full talk at Thesis: 2027. Dan explains why benchmark charts make the future of work look bleaker than it is, why picking the right idea still takes a human, and how we should really measure AI models. Subscribe to Every (free for 14 days): https://every.to/youtube-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign= (https://every.to/youtube-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=companyagentepisode)thesistalkepisode Links to resources mentioned in the episode: • Thesis: https://every.to/thesis-2027 • Dan Shipper: https://x.com/danshipper • OpenAI’s GDPval benchmark: https://openai.com/index/gdpval/ Timestamps: 0:00 Introduction 1:51 Work after automation 5:00 1 person vs 5 jobs 10:18 Why perspective matters 17:55 Better AI, more valuable humans