The Exchanges

Q I like optimistic takes about AI, so this is great. And like to your point, I want TBD if this is good for other countries, but good for the US. What else, what else you got? What other hot takes?

A Another, another big hot take. And this is, this is less like contrarian and more just like, I think people are truly sleeping on it. I think people are truly sleeping on how good cloud code is for non-coders. And I'll extend this to not just cloud code, but Google just came out with the Gemini CLI command line interface. Um, so things like that. And I'll tell you about, um, for people who are listening that don't know what cloud code is, cloud code is just the command line interface. So it's, you know, those black terminals that programmers use. Um, it's a command line interface that you can boot up. Uh, it has access to your file system. It knows how to use any kind of terminal command and it knows how to like browse the web, all that kind of stuff. You can give it something to do and it will go off and it will run for like. 20 or 30 minutes and complete a task like autonomously agentically. It's a, uh, especially with Claude Opus four that just came out. It's like this gigantic leap forward in AI's ability to, um, work by itself. And, and Claude code can even spawn multiple sub agents that do a bunch of tasks in parallel. And it's incredibly useful for programmers. Like, everybody inside of every is using it all day, every day. Like, everyone's agent-pilled. They've got, like, 15 agents doing all this kind of stuff. It's crazy. But non-programmers don't use it. Because it's …

AI assessment note: “I think people are truly sleeping on how good cloud code is for non-coders.”

Q okay, the job apocalypse, not gonna, people are not gonna be all fired. There's gonna be human jobs remaining for quite a while. It may be almost too comforting because you may, you probably have to change the way you operate to still Have a job in the future. Do you have any sense of just like, here's what you need to do to not be one of these layoffs?

A Yes. And I think that is actually super important. Um, the only thing you need to do is ride the models. And that means use them for whatever it is that you do. You know, we've talked about how codecs and co-work are becoming the sort of standard operating system for work. If you're just doing that, and when new models come out, you're trying them and figuring out, okay, how can I, now there are new powers. How can I use them instead of just being like, I'm going to like try to ignore it. Cause it like makes me afraid, which I think is honestly, it's rational. It's a reasonable response. And also Uh, if you ride on top of them, they ex extend your powers in a way that doesn't leave you behind. Like you, you're, you're, you're part of the future and part of the way work happens. And I think that, uh, we're going to need people doing that for a very, very long time.

AI assessment note: “The only thing you need to do is ride the models.”

Q That is a super cool. What is her background? This AI operations person?

A She, her name is Katie Parrott. Um, she does a lot. She actually does a lot of, um, ghostwriting for us. So she also, when, um, when people inside of every who are builders, um, often they just write themselves, but like sometimes they want help and she'll help, um, help them write about like whatever they're, whatever they're working on. So that's, that's how she started with us. She still does that, but she also spends a lot of time doing the AI operation stuff. Um, Um, and then before that she was, she worked at animals, which is a content marketing agency, like one of the top content marketing agencies, and they're very process oriented. And I think the reason Katie is so good is because she's, she's incredibly good at, at that kind of process stuff or like thinking about that. Um, but she's also a great writer and she's also, um, just incredibly, uh, Excited by AI. She just like wants to tinker and wants to use it. And like, that was the thing that got me to be like, okay, you should just come and do that. Instead of just ghostwriting, we should add this to your plate. And it's, it's been really fantastic. So I think that's a, at minimum, you really just want someone who's just like, I want to tinker. I want to build stuff. Um, there's also people who have a little bit more of that process orientation. I think that is important. Um, and to the extent they understand the cr…

AI assessment note: “before that she was, she worked at animals, which is a content marketing agency”

Q Yeah. Incredible. Okay. Do you have a favorite life motto that you often come back to find useful in work or in life?

A So basically, like I use chat to be all the time and it has memory. So I was like, you know, I'm going on Lenny's podcast. What would my life motto be? And it said, your life motto is witness deeply, build bravely. Um, you, you prize slow, attentive seeing, whether it's reading Tolstoy, tracking meditation themes, or x-raying a David Milch paragraph. So like we're, we're, it's hitting all the stuff I just mentioned, which is really funny. Um, Um, and then build bravely. You turn those insights into concrete things like every and Cora and long form essays and all that kind of stuff. So I think there's, I think there's something about that. Actually, this reminds me, this actually reminds me of the actual motto, which is, and I didn't come up with this. I think it's like Pliny the Younger, um, uh, said, um, do things worth writing about and write things worth reading. It seems like a pretty good summation.

AI assessment note: “do things worth writing about and write things worth reading.”

Q Oh man. Okay. So the second, uh, category of predictions is around just the shape of the work that we're going to be doing is going to change. Uh, what do you predict?

A There's all this interesting stuff in terms of, in terms of the shape of work. Like once you're in this land where you've got, you know, these, you've got async, uh, async agents off that you delegate work to, then you've got your like codex, cloud code, like work surface that, that starts to happen. So One thing that we see a lot internally, and you also see this in the big model companies, is the number of pull requests that you get is like skyrockets. You know, we have people, you know, in consulting, or in ops roles, or whatever, who are, or, or editors just, like, making pull requests, um, and A, that's really cool, and it's a very different shape of work, where you should, you can expect that a higher percentage of your company or your users are going to be doing things that previously only technical users can do. And what that does is it creates all this pressure on the other end for the people who have to deal with all of the new code for how to deal with that. And so I think there's a lot of, there's a lot of interesting things that happen with that. Like, so for example, um, Uh, like Open Claw. I mentioned that earlier. Pete gets like thousands of pull requests a day on Open Claw, and then he has like, and then he just spins up like 50,000 codex instances, and then sorts through them, and then merges like a thousand of them. It's really crazy. I actually think that th…

AI assessment note: “you can expect that a higher percentage of your company or your users are going to”

Q Okay. I love this. Okay. So let's dive in. Uh, what are some predictions for how the way we work is going to change in the coming year?

A One of my favorite questions, because I think if you look at the benchmarks, you're just looking at, okay, like, yeah, AI is going to just take all of our jobs, basically, you know, um, meter has this really cool benchmark where it's like, it measures how long it can, like, uh, the newest models can do tasks autonomously. And it's like, oh, it's like, It can, uh, uh, what's it called? Oh, myth, like mythos preview, the, like, big anthropic model that everyone's, like, so worried about. It can do tasks of 17 hours at 50% accuracy. It's like, holy shit, that's crazy. And I think it is real. It's true. And, and, and the, the progress, like, model progress is, um, going up exponentially. And my experience and my feeling is that we will look back in a year and, um, say, We actually have a lot more work to do. Humans have a lot more work to do. Um, even as models get better at doing work. And there's like a really interesting paradox there. And my, uh, prediction for the, uh, like how, how work, or my, my big prediction of how worker changer or how you will be doing work in a year is it's going to bifurcate in this, in two main ways, how you, how you use agents. One is you're going to be doing, I think like what we figured you would be doing like five years ago when we thought about how work with AI works, which is everyone's going to have at least in their company, at least one agen…

AI assessment note: “my big prediction of how worker changer or how you will be doing work”