Nathan Labenz: preference

Transcript context

…no mistake. Yeah. Yes. And I forgot it's first suggestion, but it was it was it was a reasonable suggestion if you did not understand OCI, and it was it was it was was not good, like, given given the constraints we're operating under. And so, like, the engineers chimed in. They're like, no. Actually, we can't do that. We started by that. They're like, ah, that's a fair point. So we went back and forth. And then and then together, we came up with, like, oh, yeah. Yeah. We should totally do that. Like, just go ahead and do it, please. A thesis that I've had for a while, and it may be too early to say, but you're definitely gonna have a perspective on it, is but, again, going back to what I've been wrong about, I expected a lot more transformation than we've seen in the economy. If you had showed me Fable in 2022 and said, what's the unemployment rate when this model is out? I would have said, I don't know, but something definitely higher than what we are currently experiencing. Yeah. So then why and this has been something I've been wrestling with for the intervening time. Like, why are we not seeing more? And one answer I've come to is people are stuck in their ways and not everybody's enthusiast like I am and it's gonna take time. But then also, when we get to the drop in knowledge worker, that'll be the time when it'll suddenly flip. Right? Because now I'll have a more parody kind of choice between I could try to go hire a human or I could plug in an AI, and that's gonna be easier in a lot of ways. Right? I don't have to go through a whole interview process. I kinda know what I'm getting blah blah blah blah. I don't need to tell you why an AI employee is a good form factor. Do you think we are starting to see this flip, and is it going to be something that incumbents will be able to adopt in time to avoid getting disrupted, or are there still gonna be bottlenecks or resistance points that I'm not anticipating? I expect more disruption as well. I think as long as the models are spiky, we're all going to need a lot of humans in the room because the holes in the model are very dangerous. Not not just like AI, existential dangerous. They'll just they'll just harmful. They're really harmful to the system. And so however expensive humans are, they're going to earn their keep by plugging these holes. Now regarding whether incumbents will be able to adopt this this this this this thing, I think as long as it is spiky, I think the the incumbents are going to be at a disadvantage. If you had a true drop in remote worker with no holes, then I think even the incumbents would be able to adopt it quite quickly because it's just like hiring an employee, and they have processes for that. And I actually think they would be south on on on on a lot of the of the innovation because it it would be skeuomorphic effectively. You would you would just have, like, AGIs, like, sitting in human seats effectively, and I don't think that's the best way you build an AGI organization, but it would work. The the smaller organizations are going to be at an advantage both because they are going to be able to to short term figure out this AI native organization while the human is filling the holes. And and long term, I think they are going to be to build, like, a less skeuomorphic AI organization. You know, economists are very fond of talking about that. I actually wrote a a blog post about this that's called the tough tomato principle on my blog in in 2018 or so. And it's it's about how, like, every time you have a technological revolution, you think of the new paradigm in the in the terms of the old paradigm. You know? And and and one tale that you're you're you're falling into that trap, which is very natural, is that you're you're you're calling the new paradigm after the old one. So, you know, the the first cars were called horse less carriages. Right now, self driving cars are called self driving cars. Right now, eventually, we're gonna have a a will for them. You know? That's not that's not in the terms of the old paradigm. It's almost like right now we're doing it with AI employee. Like, it's it's like AI employees is is as strong as as as a term. It's a very strong sign that you're doing something very wrong in how you're thinking about your product. And I think I think it's it's fine if you're doing it just to communicate about your product because, like, the nature of positioning is that you have to position against something that already exists in the market's mind. And so the the car exists, you know, the the the the the carriage exists. Sorry. The carriage exists. The the car exists and not the employee exists. So you can't really invent a new, like, wheel out of nowhere. The iPhone did that. You know? It's like the iPhone's obviously not a phone. It's it's so much more than that. Like, you know, what percentage of of your iPhones use is just like making phone calls, like 2%. You know? It's called an iPhone because it's it's an electronic thing you've got in your pocket. Right?…

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