How Sam Altman Uses Dots to Take Back His Time

Dan Shipper (0:00)

Do you do all your prompting on Ultrafast?

Sam Altman (0:02)

I do.

Dan Shipper (0:03)

That's sick.

Sam Altman (0:04)

Yeah.

Dan Shipper (0:04)

That's crazy.

Sam Altman (0:06)

You know, seven people's dots can, working together, create something new that kind of existed in all of our heads to some degree, but was like an emergent thing.

Dan Shipper (0:25)

This is the second episode of Ultrafast. This is Dan Shipper. You might be wondering what happened to Ai and I. This is the same show we are just re-branding it to The Every Podcast. I'm really excited for our first episode with Sam Altman.

Here it is. Sam, welcome to the show.

Sam Altman (0:37)

Thanks for having me.

Dan Shipper (0:38)

It's psyched to have you here. So we're here at DevDay. I think if you had told me four years ago that the coding models were at this level of capability, I would have been like, wow, I don't know if there would be a lot of developers at DevDay, but there's more developers than ever, it seems like, and more work to do than ever. So what has the like riding the increasing capabilities of coding models and seeing the impact on engineering taught you about the future of engineering and more broadly, like the future of work with AI?

Sam Altman (1:06)

I think people just want so much more stuff. People's expectations are so high, and I think that's a wonderful thing. I think this is why we'll all have this incredible future in front of us to explore. But developers, they've never been able to do more, but there's never been a higher bar either, and I think that's great. I think it's like a nice thing about society.

Dan Shipper (1:23)

Is that something that surprised you? Did you expect that to happen?

Sam Altman (1:26)

I think I was never like as do-merry about the job stuff as other people, but it still has surprised me somewhat on the upside of just how much latent demand existed in the world, and also how much like people have remained the center of everything that is happening with AI.

Dan Shipper (1:44)

Do you think there's a limit to that, or do you think that translates pretty cleanly to other areas of work?

Sam Altman (1:50)

I think there will be some areas of work where there's actually not much creativity required, and we don't care about the person doing it, and many of those tasks or jobs will be done by AI. But I think there's so much other stuff people want in the world, there's going to be no shortage of new things to go do. I think that's been one of the lessons of recent time.

Dan Shipper (2:09)

Why do you think it's so human-centered, even though we talk a lot about automation?

Sam Altman (2:14)

I mean, one observation is we don't care that much about what the machines do, and in some sense, we never have.

We're just obsessed with other people. We want to know about the person behind the art, or the person behind the company, or the idea, or the product. I think this is a wonderful positive surprise that we probably should have all known before.

Dan Shipper (2:35)

I agree. I've been thinking, if an agent solves an obvious stokes in a data center, but no one finds out, did it really solve it?

Sam Altman (2:43)

I think that was a great example where 10,000 agents worked super hard for four days in perfect coordination with each other and did this amazing thing. Almost none of the public reaction was about that actually, the problem being solved. A lot of talk about the interpretation, a lot of talk about the people involved in it in different ways, but that was a good thing.

Dan Shipper (3:05)

So it's DevDay, you launched by my account, 22 new things today, which I've been at all four DevDays, and I think last year was like nine, and the year before that was like four or five. So it's a lot more than usual.

Sam Altman (3:19)

Just wait for next year.

Dan Shipper (3:20)

Okay. I'm tired.

Sam Altman (3:24)

We cut a bunch of things that we were going to launch today just because you have to fit it in 50 minutes. But we try to practice what we preach, and if we are saying these tools can make people much more productive and build more and that people want more stuff, we better build more ourselves.

Dan Shipper (3:41)

What are the new bottlenecks and best practices for doing that? Because I can see for myself, and I assume you guys are seeing this too. Now that you can build everything, you're like, what should we build, and how do we make it all coherent? How do you think about that?