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Sam Pasupalak

Sam Pasupalak

Oct 1, 2026

MatanHOST
19:40
I know the movie.
19:40
Yeah, it'll come to me as well.
19:42
But it's kind of like you're simulating the different future aspects of what the futures are going to be, and you select what future you want.
19:51
That's how we, even when I'm talking to you right now, I have to simulate the different futures I could talk about, but then I make the prediction of this is the policy decision or whatever I'm going to take before I speak to you.
20:05
So I think As human beings, we try to do very long-term rollouts.
20:09
Like as a CEO, I have to do, let's say, many things in the company, but one of the things I have to do is like a big round of fundraising sometime in like, let's say later this year, early next year, whatever it is, right? So there's so many steps, there are hundreds of thousands of steps involved in order to get there.
20:24
Okay, we have to work on all these demos, all these projects, who's working on what, we have to talk to all these people, what is the go-to-market pipeline, what is the sales pipeline, blah, blah, blah.
MatanHOST
22:11
I'm like, man, oh, God, what have we done? What have we unleashed on this world, you know? I love Reddit moderators.
1:53
Can you talk a bit about that? What are you trying to build? What are you trying to hope to achieve by utilizing AI in this regard, in this capacity at Skyfall?
2:03
Claude's doing amazing, and so is Codex and so many other companies.
2:08
The software is offered by these companies that are basically trying to replicate what an AI software engineer is supposed to do.
2:15
But if you think about it, software engineering tasks are much more logical and programmatic.
2:20
So they're much more deterministic in nature.
2:23
Whereas the CEO's tasks is so much more complex because it's much more probabilistic in nature.
2:30
And the CEO's tasks, like for me, for example, I have so many different tasks.

7 MINS LATER

9:06
it's so interesting to see that AI is now like if we have the ability to plan it would be fantastic for organizations as well because to your point like I don't think the human part can be replaced either and then managers CEOs can double down on the human part as well but on those you mentioned the three pillars initially here which one are you closest or which ones do you feel realistically that we're we figure this out or we're on the verge of figuring this out or are there any differences between the three or what's the status there
13:56
So
13:57
I think let's take a step back, okay? In the pre-L&M era, okay, so we had, I think, before Google, let's say, you had to go to, like, the New York Library or something like that to find the right information for your needs, right? Or you have to go, like, manually search for information to different sources.
14:18
And Google indexed the entire web, and you could do...
14:21
They did a whole web crawl and they made information accessible to everyone.
14:25
So I think Google was the pioneer in this whole AI revolution that we see as we see now.
14:31
I mean, people can say maybe it's like the browsers that came, like Mark Anderson's previous company, the first one in 1995. or people can say maybe it's Yahoo, but I'd say Google is the company that actually redefined modern internet search.
14:49
And I think post that era, there's not much... going on in the information retrieval search space, so as to speak.

14 MINS LATER

28:57
Yeah, for sure.
PrakashHOST
87:41
How can that be addressed?
87:43
Yeah, I think maybe we can take a step back about what we have seen the overall success in the last three and a half years is first and then go from there.
87:53
So I think if you think about what has succeeded since, let's say, November 2022, I think LLMs have succeeded in, I'd say, three broad categories.
88:02
The first one would be text generation and information retrieval.
88:06
So you have obviously the chat GPTs and then Gemini's and such.
88:11
The second would be the code generation where we have cloud code and cursor just got acquired with SpaceX and whatnot.
88:20
And the third to a smaller extent would be in the video generation paradigm.

5 MINS LATER

NathanHOST
93:28
When you make this new prediction, how broad is that scope? How do you think about how far out in the ripple effects of a decision AI can go, should go, will ultimately be able to go?

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