A New Vision for Human Work After Automation
Notas do episódio
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