Tobi Lütke: AI Agents, Better Decisions, and the Future of Work
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How does Tobi Lütke introduce the concept of an AI council for decision‑making?
Things need to be pruned. You cannot make things better and better by adding stuff. You can't. You must prune. You must rebuild. You must create an end for things.
Toby, welcome back. Shane, it's so good to be back. I'm glad we're doing this again.
How
are you using AI internally at Shopify? We find some uh ways for it to be supportive now. It's actually um uh look When have you recorded last time?
Oh, we recorded like two, three years ago.
Yeah, so a hundred years of internet. Uh yeah. Like a look, I'm I'm ten out of ten nerd. I uh cannot bear the idea of like um somehow not being at the forefront of a technology shift. I l live for these things. Anyone growing up reading sci-fi books wanted to uh live. Or I mean my my take from sci fi books I read was like I wanted to live in that world. Like how can I accelerate us there? Right. Like so um, you know, e even even in uh Whatever minor steps um we can get there. So inside of Shopify, the amount of people I know who really write code is like vanishingly small now. It's it it still exists in the at the limits of uh complexity for sure. And uh ob obviously in the reviews and so on, and then state management of all things, it seems to be uh remains to be the thing that's really the hardest to get right, which people do by hand and then sort of uh vibe the rest around it.
This is what things look like. Very, very, very few people are um writing code uh directly. Everyone who does does it deeply assisted by um many agents. Very often um t uh ten, twenty, thirty, forty, fifty instances of them, uh all uh through, you know, either sub agents or just different windows coordinating. We're pushing all sort of engineering infrastructure to its absolute limits. I'm a I'm a student of computing history really. Because I think it's actually mainline history, as it will be told a thousand years from now, looking backwards. But like the main accomplishments of these years are going to be uh clearly the emergence of AI and the technological breakthroughs and also the the interconnectedness of the internet and all these kind of infrastructure we created.
Those are the great works of our time. But where we started, um uh as a young industry, we tend to not um uh be seen. Deeped in tradition, or we mistrust the great lessons that have been found by the people uh by by by the grades of our industry. Right. In fact, we are the only industry in computing that doesn't even under know its heroes. Imagine um people in physics not knowing who are Richard Feynman or Richard Richard Feynman is actually like like he might even be too obscure, but like I mean Isaac Newton, Albert Einstein. But you go into computer science. And it's like, who's who's who's you, Newton? And no one uh knows Alan Key and or uh and Dennis Ritchie and uh Ken Thompson. Oh. This matters, I think, because we we we we discard great lessons and have to rediscover them over and over and over again.
For instance, like probably the best idea of all times in um the earliest, earliest moments of um operating this system design um was a file system. Like if you look at the Apollo guidance computers, we didn't have file systems, right? Like memory, in fact. Because of radiation in space, was actually encoded in as a rope with knots in it. Either a knot or no knot for ones and zeros, and you had to pull through a thing to rebootstrap the entire machine. So the entire machine was one piece of software that ran that was computing for a very, very long time. So until then, again, Dennis Ritchie really created the sort of Unix file system slash forward and um you know, bin user and these kind of things. Think about it.
A file system is something that we have in office building too, right? We have a uh uh you know has folders, they have files in it. This this makes intuitive sense to everyone. We come from a inheritance here of of of deep stoichomorphism. We we we we analogize the best parts of uh of how we organize ourselves um in the digital world. And then at some point we decided, okay, you know what's not something we need to do anymore?
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Chapters
8 chapters
1
How does Tobi Lütke introduce the concept of an AI council for decision‑making?
0:00–6:22
2
What is River and how does it function as an AI colleague inside Shopify?
6:22–14:45
3
How does Shopify use AI agents to evaluate complex strategic choices?
14:45–21:55
4
Why are intuition, taste, and judgment more valuable than raw AI capability?
21:55–29:08
5
Why does the optimal long‑term path often lack immediate feedback?
29:08–36:35
6
How do affirmations and the “yet” mindset reshape personal behavior?
36:35–42:43
7
What role does pruning, rebuilding, and refounding play in lasting products?
42:43–48:54
8
How does Tobi envision the future of work with super‑intelligence and AI agents?
48:54–1:04:40
Speakers
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