B (3:07)

Well, I think it was our. Was it our first Claude Code camp that in June.

A (3:12)

That was one. I think, honestly, I think what. What happened was, um, in June we really had built this engine that was ready to get people to subscribe. So basically we had the newsletter and then we had. We had a couple different of our AI software apps in market. So I think we had launched Quora in June.

B (3:34)

I think Quora was June.

A (3:35)

That was in June. And then. And Quora is our. Our. Our AI email assistant. Yeah, we had Sparkle. We had a version of Spiral, which is our. Our AI ghostwriter. And. And then I don't think we had Monologue yet, but we had three. We had three products in market. And so it was. It was this really meaty subscription because you pay one price, you get access to everything you make. But we needed like, a couple moments to like, almost reintroduce ourselves to the business. And so we had that launch moment with cora. We did a cloud code camp, which is like. Basically that was like, when cloud code was breaking, it was starting to break out, and we sort of noticed it, and we started to do these live webinars called cloud code camps for subscribers. But the big thing was I went on Lenny's podcast and that was like in June. And that was one of those moments where it was like, oh, it res. I think it reset some of people's expectations about what every is and what you can get from it. And so we grew like 20% that month. And it has just basically been that way since then.

B (4:34)

We grew 22.63% that month after consistently growing between 1 and 5% for years.

A (4:41)

Well, here's. Here's what's really interesting. What people should know is we started growing like about 5% month over month, starting in like, maybe. Let me see. Let's look at this. It's like we started growing about like, a couple percent month over month between like 2 and 5% month over month starting in May of 2024. That's actually when the growth curve changed.

B (5:04)

What else happened?

A (5:06)

Brandon joined.

B (5:11)

You can really see, sort of see the day that I joined you.

A (5:14)

And so once Brandon joined it just the curve, like, started to consistently bend up. It was like starting to go up and then. And so I think the business at that point was starting to like, reconfigure around this whole thing that, that we started to start to build together and. And then it needed like a moment to catalyze it and like sort of light it on fire. And I think that was like the lending podcast moment.

B (5:38)

And what's been interesting after that is it has consistently delivered. So after the Lenny podcast, we've grown at least 10% each month. We've had a bunch of other launches since then. But I do think the biggest thing was a rejiggering in people's brains of what every actually is from a newsletter to a bundle. And we're not even there yet. Like, that's going to be what 2026 is really, really about.

A (6:03)

Totally. And I think, yeah, it sort of. It sort of became a real company too. So we were, I think at the. At the beginning of the year, we were like maybe five people or something like that. Five people full time. And now we're almost 20. And that has been that.

B (6:23)

It's honestly a huge consulting business.

A (6:25)

We have a huge consulting business that's not even counted in the mrr. And that's honestly been. It's been so fun.

B (6:32)

Yeah.

A (6:33)

Because I think we're really figuring out what it means to be an AI first business ourselves. And then we get to bring that to readers to like people who use our products because we build tools for ourselves that we can sell to, sell to subscribers and bring it to big companies in the consulting business. And it's just like, it's the most exciting thing I've ever done.

B (6:53)

What's one word to describe 2025?

A (6:58)

The word that came to my head was fire. I don't know.

B (7:01)

In a good way.

A (7:02)

Or is that like in a good way, good? Fire. We lit the engine. Right. And so like, the engines are lit. Liftoff. Yeah, let's say liftoff is the word.

B (7:11)

I don't even know. Yeah, I guess so. Yeah. I really think we've, like. I don't even think the engine is on. I think we've like, primed the engine and 2026 is going to be where we really, like, you know, in the grand scheme of every. We're just going to be putting it into first. We're going to think we're putting it into fifth.

A (7:28)

That's the thing about these curves is every time you hit a new inflection point, the old curve looks really, really small and shitty. And so I think right now the one we're on, we're like, this is amazing. But I Definitely agree. In 2026, the thing that we're going to do is every has been this very bottoms up place for a long time where we're doing the newsletter and we're sort of writing whatever we're interested in. We're building tools and we're just sort of building whatever tools come to our head that we kind of need ourselves. And I think we're starting to build a more, much more cohesive platform. So we brought in someone really talented, his name is Willie, who is building every platform where we have. We have single sign on so you can log into any one of our apps. We have now we have unified billing, so you don't have to enter your credit card information for each one of the apps. But that's sort of like the groundwork. And what we're doing next year is we're going to build this like unified memory and context layer where we have a bunch of. Basically we can collect everything that you care about and who you are into one place and all of the apps and all the content can take that into account as they work with you. So it's like a, it's a much more custom, personalized AI experience across all the different services.

B (8:40)

I think the biggest, one of the biggest challenges for us next year will be, I describe every as like the most genuine work environment that I know of.

A (8:51)

Yeah.

B (8:51)

The things that we build are the things that like any one of us is like, this is interesting, I need it, it's cool. And then we build it. And that has like served us really well. We get to build cool things, but then write about it and, and we build things that we need and we're gonna like start to have like a real strategy next year which like, we haven't not had, but we've been doing it like based off of what's genuinely interesting.

A (9:17)

Yeah.

B (9:17)

And it's gonna be, I think one of the big challenges will be like continually being genuine and also like having a strategy and having Personas of the types of people that we want to like attract towards every and not losing that like genuine motivation that we have to just like make cool.

A (9:34)

I agree. What was like for you? Like, so this is actually this is the first time I've run a business with 20 people. But you've run a business. Your last business, you got to about, like, 100 employees, I think.

B (9:45)

100?

A (9:45)

Yeah. What was the transition like from, like, 20 to 50?

B (9:49)

You have to rebuild the business every time the number of people doubles. And we felt that. I mean, we've. We've done that a little bit from, like, 5 to 10, and now we're at 20, and, like, you know, we just went through and changed everything. So every time the business doubles, it changes. You have to rethink operationally how everything works and just sometimes the whole strategy. And then you just sort of need to have, like, people do their job really, really well. And when you're smaller, everybody's sort of doing everything because you have one person doing support and one person doing design. And then as you scale, like, what I mean by that is, like, sometimes you need the design person to also help with support. And then as you scale, people start to just do very specific things. And I found it that it's a real challenge to keep the culture going where everyone feels equally as excited about the company, and they play a very big role in it because you end up just hiring some people where they're just. I just do support for this company.

A (10:55)

Right.

B (10:55)

You know?

A (10:56)

Yeah, yeah.

B (10:58)

And so keeping that genuine interest in building stuff and exploring things is what makes us special and will be the big challenge as we scale.

A (11:09)

I totally agree, but I don't really

B (11:10)

think we're going to, like. I think we'll hire next year, but I don't think we're going to hire a ton. Like, the whole thing is like, keep it small.

A (11:16)

I hope so. Yeah, I hope so. Because I love just.

B (11:18)

It's amazing.

A (11:19)

I love all the people that we work with, and every time I go into a meeting, I'm like, wow, all these people are so cool and interesting and have interesting backgrounds and such to say, and I really don't want that to change.

B (11:28)

And I don't think you need to anymore because AI is allowing us to scale with the same number of people, essentially.

A (11:34)

Yeah. Speaking of which, let's get into our 2026 predictions. I know you have some doomer takes.

B (11:41)

I got a couple doomer takes, which

A (11:42)

is good because I'm. I'm usually, like, pretty sunny and optimistic, so it'll be a good, good balance. Rachel, our producer, said we're going to do a good cop, bad cop routine. So do you want to start?

B (11:51)

I don't only want to do. I'll. I'll start with a positive take is actually inspired by a conversation that we had, which is that agentic development will be maybe by the end of the year inside of the app that you're actually using. You said that to me and it, like, completely blew my mind. And we're already doing that. So what. What I mean by that is, like, inside of every. Right now, we build a product. If something isn't working, you can dm. Dan's building a tool that does this right now. You can DM this tool or mention it in a. In a Discord channel and say, hey, I want this feature. Or this bug is broken and it will write some code and then submit a PR for it. So it's sort of like working inside of Discord. But the next step of this is that I can do it inside of the app itself and then it can like, write the code in a way that doesn't break it and then actually, like, relaunch the app itself with a feature that I might specifically want. And it just feels really hard to do, but kind of inevitable.

A (13:00)

Yeah, no, I agree. I think, like, the way that I've been. I've been talking about it and thinking about it is we reached this place at the end of 2025 where coding agents are really good and mostly the code they write works, which is. Was not the case last year. It was. You could. You could get pretty far, but eventually you get stuck into a bunch of errors and bugs. And so if you're not a professional developer, it would, like, just break. And now you can kind of. With Opus, especially the Opus 4.5, you can kind of like keep going forever almost. Especially if you're using stuff like our compound engineering plugin and you're. You're actually like, having it plan and think and all that kind of stuff. It's like, it's really good. So I think that that fundamentally changes software engineering and it also fundamentally changes how apps are built and who they are built by. And so I've been kind of playing with this new idea for how software is architected that is very inspired by cloud code that I've been calling agent native architectures and an agent native architecture. The first level of an agent native architecture is anything inside of an app that the user can do, the agent can do. So in cloud code, anything you can do in cloud code, where you're like, oh, I want to please go, you know, or in cloud code, it's anything you can do on your computer, Claude can do. So like, if you want to Change files or, you know, write, write a file or run a server or whatever. Claude can do all those things. And mostly, most of the agents that we use right now, that's not the case. So if you go into, for example, one of our apps, Quora, the agent that you can talk to, there's many things you can do inside of the Quora app that the agent can't do itself. And same thing with a lot of other, like, sort of chat agent, like chat apps, basically. And so I think the first step of agent data development is anything you can do, the agent can do. And that gives this, like, power and flexibility to the application because you can just tell the agent to go do stuff. So, like, you know, oh, I want to change my settings, right? I've been doing that all the time now with, with the Atlas browser. It makes, kind of makes every app a little bit agent native. So if I. I get requests all the time where people are like, oh, my God, like, can you update this, like, setting or like, add me to this team or whatever? And I'm like, I don't want to figure out this interface. And I just asked Atlas to do it. I think every app, like every agent aided app will have that first level. Second level is anything that the code in the app can do, because there's many pieces of code that the user cannot trigger themselves. Any piece of code that the app can do, the agent can do. So that's a lot of like. So for example, in Quora, users can't really, like, generate their briefs, and briefs are the summaries of their emails. Eventually what should happen is the agent should have the ability to, like, regenerate and redo an entire, entire brief, an entire summary in whatever way, in whatever way they want. Maybe triggered by the user, maybe triggered by the developer. The third one is, yeah, anything a developer can do, the user, the agent can do. So the user can be like, I want to customize my software in this way. The agent's going to go submit it, and maybe, maybe it's a bug fix that goes out to everyone, or maybe there's. Maybe there's some system by which you can. You can just have your own custom version of any app. And we're already starting to do this inside of every. And it seems like it's sort of starting to work. And I just, I think that that's going to be broadly distributed. Like, especially that first level is going to be a broadly distributed paradigm in a year that no one's really talking about right now, except for except for Anthropic. I think Anthropic has nailed this, but everyone else is going to be doing it.

B (16:33)

I think Notion is doing that pretty well too. Yeah, I mean you can, you can use the notion AI to like do. To create almost anything that you would create in Notion.

A (16:41)

Yes, there are, I think they also get it. They're like really thinking about this in the right way, where it's not just software that's made for humans to collaborate, that they've like pasted agents into. It's like actually agents and humans are like first class citizens in the app. Yeah, let's keep going. What's my prediction? Let me see. I have a note file. Okay. Oh, this is a good one. I think that designers are the next big superheroes of the AI age. Like they have been uniquely enabled in this world because forever designers have, what they're good at is they have lots of taste and they have like a vision for how they want an app to work. And, and they've just bumped up against like, well, I have to convince this developer to do this for me for a long time. And I just see. So a good example is Lucas, our creative, our creative director inside of every. He has turned into this machine where he's not only like this incredibly creative designer, art director kind of person, he's also like Vibe coding little apps that let him do his work better. And I just think there's like, there's a whole class of people that are sort of like Lucas, where there are these highly creative, highly visual people who have been held back from making full experiences because they can't code that now are going to be able to code and the stuff they can make because code is cheap. Being able to make a really beautiful, really evocative, well thought through experience is going to be a huge deal. And I think all these designers are just going to like start going crazy and it's going to become this new archetype of, of like really interesting builder.

B (18:30)

Cursor, I mean, I think is already inching towards that. You can do, you can, you can do front end updates inside of Cursor with like a visual medium. I, I sort of think I get a little bit worried that like, so I, I used to be afraid of the terminal and like a lot of people are afraid of the terminal. Like it sounds like a scary word and I kind of wonder if like doing design inside of Cursor, a lot of designers will be like, no, I like that's scary to me. I can't touch the code. I don't want to mess anything up. So I wonder how that will play out next year. So that, like, you know, the best designers in the world will be doing this. But, like, you need to build a product that, like, every designer can, you know, can access. So I wonder how they'll abstract it. The cursor, you know, if they want to expand their market away from just engineers to designers, like, they might need to abstract it away from the code so that, like, the average person doesn't get scared going near code.

A (19:32)

What's next? I know.

B (19:34)

Okay, I have one.

A (19:35)

You have a hot take.

B (19:35)

I have a bit of a doomer take, which is that I am really worried that. Okay, I. So, like, I just have a bunch of friends. My mom, let's say my mom, who's also my friend, if she sees something on Instagram and it's. I'll tell you the exact story I'm thinking of. She sent me a video of some gorillas that were taking care of their children. And the point of the video was like, wow, gorillas. They're so human. Like, look at the way they're taking care of their kids. And it looked totally real. My mom sent it to me and was like, this is so cute. And I was like, mom, that's just not real. That's AI. And she refused to believe me. She was like, that's. You know. What are you talking about? This is real.

A (20:23)

Y.

B (20:24)

And I just think it's really scary that a lot of these social media companies, all of them which are heavily invested in AI working.

A (20:30)

Yeah.

B (20:31)

Aren't putting Made by AI, you know, as a thing. And I just think that that is going to be something that will have to happen, if not by the midterms, then by the next election year, presidential election. But, yeah, I think midterms are going to be, like, kind of scary because I think there's going to be deep fakes, which used to be a really scary word, and now nobody talks about. Nobody says deep fake anymore.

A (21:03)

So what is the, like, specific? So I agree with you. I think this is a huge problem, and I think it's right to point it out. And that example of your mom, like, actually not believing it's AI is really interesting to me because for me, I look at it and I'm like, I. I can tell, but I know that that's. I look at this all day, so that makes sense. What's, like, the specific doomer take? Like, what do you think the do more take is?

B (21:24)

That shit's gonna go bad during an election cycle. And that's going to be the inspiration. But the really, the really doomer take is that it's going to go well for the team that, you know, then has to make the rule to not, I see, you know, to label stuff.

A (21:37)

And what specifically do you think is going to happen? Is it going to be like they're. They come up with a video of a politician, like, getting caught, you know, doing something? Maybe it's like the P tape, but like, real?

B (21:52)

Yes, yes. I think that, I think that scary stuff is going to happen where fake videos are made. Like, you know, the nature of the word deep fake came from like, people doing like, really grotesque things that like, they didn't actually do, but AI made it look like they, they did that. And I think that like, we are just like. So there's just like a thin wall that's blocking the average person from making videos like that.

A (22:19)

Yeah.

B (22:19)

And if you really want to, you can, like, I've never tried, but you probably could easily go make like really messed up videos. And that is going to happen 100%. So I think, like, that's my doomer take is something's going to happen with elections that like, that's what will trigger, you know, some sort of label that's like made with AI. I also think another interesting thing that's happening is this deal that Disney just did with OpenAI to put Disney characters into Sora, which is really just going to sort of train all of us to expect. It's a little bit confusing because Disney characters, many of them aren't real anyway.

A (23:07)

Yeah, mostly. Mostly. They're mostly.

B (23:11)

But like, we're just gonna be like, really used to like, not real stuff soon.

A (23:14)

Yeah. Okay, let's keep going. So my next prediction is I have been observing this split in software engineering and it's. I think there's like now basically three types of software engineers. Maybe there's four types. One type is just traditional engineer, never uses AI, which I think is getting less and less. But like, they're definitely still a thing. It's definitely, they're definitely still there, super skeptical, all that kind of stuff. But the more interesting thing are the. Are the other three. I think mostly what people are talking about and think about are two groups. One is traditional engineers who use AI in their process. And they're kind of, they're using cursor, they're probably using cloud code. But like really, they, they still think like traditional engineers, but they're using AI as this sort of like accelerant to their their normal engineering process. So they're still reading code, maybe they're still writing it, but like, they're deeply involved in every aspect of the software. So that's one. Second one is vibe coders who are at the opposite end of the spectrum, which is, I don't even know how to code. I'm just like making something that I don't understand. And I think that's like the classic dichotomy between the two types of coding that's happening. But I think there's a third way that I think we're starting to see inside of every. And is really. I think anthropic is really leading the way on this. And OpenAI has not yet really caught up to it. I think OpenAI is really, right now, for a lot of their coding tools, serving the traditional engineer who's incorporating AI. The third way is what we would probably call compound engineers, or maybe more broadly is agentic engineers who are engineers that have reinvented software engineering as a skill for an agent world where they are not looking at the code, they are not ever writing any code. They are fully committed to delegating all of the actual programming work to an AI agent, and they're moving up a level in the stack to essentially manage a single or multiple agents all at once. And they've decided to make that trade off of. Because I think a lot of programmers, and I understand this, a lot of programmers love writing code, and they've decided to make that trade off of like, getting rid of this old skill which has, I think for them, a lot of them, they feel like it has started to atrophy in. In exchange for this other skill. And I think many traditional engineers who are using AI don't want to do that because they love writing code. And I think many companies are not aware that they have a choice here because they're trying to serve. If you're. If you're trying to sell enterprise software contracts right now, you're going to run into a lot of traditional engineers who want to want to incorporate AI into the process but not reinvent it. And so I think a lot of companies are miss this group that I think we're a part of and a couple other people are where it's small companies that are reinventing what software engineering is from the ground up, and that will be its own skill. It's not vive coding. So I would say vibe coding is very amateurish, but it's definitely not engineering with AI, it's a third thing. And I think that's going to be a big deal in 2026.

B (26:38)

And what's going to happen to all of those engineers that refuse to get on board?

A (26:47)

I think it's a good question. My sense is that this kind of thing takes a while to move through an entire economy. And so I think for the most part if you are an engineer who wants to incorporate AI into your process but doesn't want to reinvent the skill of software engineering, there's going to be a home and a job for you for a very long time actually for sure. And I think if you, if you then zoom out though that kind that style of engineering is going to be on a pretty slow and steady decline. Yeah. In the same way that I don't know like the newspaper industry was affected by the Internet. It wasn't like all at once but like over time it's become like less, less and less.

B (27:30)

Right.

A (27:30)

Less and less profitable as a, as a, as a business for specifically for like the old cost structures of newspapers. And if you look at the growth, the growth will be in this new kind of engineering, in this new kind of engineering work. And so if you're for example a new grad and you're choosing between what, what kind of stuff you're going to do, I think you're probably going to be more likely to choose this third path.

B (27:52)

But it will be interesting. Like I wonder how many schools are still like I studied architecture and they still had us draw by hand.

A (27:59)

Yeah.

B (27:59)

Which was like a good skill to have but so useless in the real world. So like we all had to teach ourselves Revit in AutoCAD.

A (28:06)

Yeah.

B (28:07)

So I do wonder like how these schools are going to adjust. It's going to be hard to that

A (28:13)

and hopefully you know, that's why we do all this. All these courses and training at every. And we have a lot of like student discounts and stuff like that and it's not a replacement for any of that. But I think there are a lot of people will pop up to like serve that need for kids that are not being served by universities.

B (28:27)

And also the best engineers that at least we've seen are also very, very good traditional engineers. They've just adopted this new way of building.

A (28:34)

Totally. Yeah. Like Naveen who runs Monologue is a good example of that.

B (28:38)

Yeah, all of them, all of them are.

A (28:40)

Yeah, you know, they really are.

B (28:41)

So what about what do we think is going to happen with all of our non technical friends out there that use ChatGPT and like use it to like pull up recipes but don't really use it at work. Maybe they like drop in a CSV and like do some analysis, but like they don't actually. Will 2026 be the year that like AI is just something that we as non technical people natively use inside of products or are we still going to be sort of like in this world where I mostly just use it to like make, turn pictures into like, like drawings for my kid to use? Because the, and, and I have, I mean I've got a bunch of friends. I just had dinner with a friend yesterday who was like, yeah, like this AI thing, like it's just not working for me. And I was like, well, you're not an engineer. Like that we know for sure that is a thing.

A (29:32)

Who was this person? Like, where do they work or what do they do?

B (29:34)

They run the deal desk at Twilio. So they work at a really big publisher. They do a lot of math or they have Excel that does a lot of math.

A (29:44)

What's a deal desk?

B (29:45)

Deal desk is like if a salesperson comes to you and is like, I have a big deal. But they want to discount the deal desk at a big company is like, tell them no.

A (29:54)

Yeah, yes.

B (29:55)

They can do 10%. Yeah. So you know, it's a lot of Excel work and I, it's probably more sophisticated than that. If you're listening to this podcast, Graham. So I apologize. I, I, I just wonder if next year, because it feels inevitable, like will we leapfrog to like the point where the Graham no longer has a job or will we steadily get there because he starts using AI a ton himself?

A (30:29)

That's a good question. Okay, you're opening up some interesting threads for 2026. One is, I think we will definitely see layoffs that companies blame on AI in 2026. And I think mostly they will not be actually AI related, they will be about the underlying business, but they'll use AI as a good excuse. I think generally people like Graham and I don't know really that much about his job, but I would guess that they will find it valuable this year specifically because coding agents are good enough that once they make their way into Excel in a widely distributed way, he'll be like, holy shit, I can't believe

B (31:09)

it needs to be in his place of work.

A (31:10)

Exactly.

B (31:11)

It's not really in his place of work yet.

A (31:15)

And I also think there are always these tailwinds and headwinds. So there's always, Sometimes it's like, wow, AI is blowing up and everything. We're improving so fast and we're starting to see right now this, like, oh, is it improving as fast as we thought it would? And I think. We've started to see over the last year or so the, the big AI CEOs like Dario and Sam Altman in 2024 said that 2025 would be the year of Agents. And it really was like, we got, we got there, we did it. But they've also been saying, like, AGI is like, very. It's, it's. I think Sam said, like, it's less than a thousand days away, maybe like a year ago. So that's in two years. And now their timelines have shifted.

B (32:04)

Yeah.

A (32:04)

And so I think there's this really interesting thing happening where two things are true and that tends to get lost, which is one, I think AI progress is still really fast and it's kind of mind blowing where we are now versus where we were a year ago. And I think that will be the case at the end 2026. I think we'll be sitting here being like, wow, it's actually a lot better. And the world and AGI, however you define that, is a lot more complicated and hard than we thought. And, and so. And we will not have AGI in 2027 also.

B (32:40)

What even is it? Like, what even is AGI? I mean, I just remember a couple of years ago, I was like, yeah, AGI is a thing. It's been like the robots, like, they know everything and they can talk to you. And now I'm like, what was I thinking? Like, I would say we have AGI right now. It's just that, like, it needs to be able to continue to live on and run and, like, propagate inside of my computer and do things that, like, I don't have to request that it does. The models can do that right now. Cloud code can run for hours to do shit and fix problems that it makes. I feel like it doesn't have the tools to live on indefinitely and never really turn off. To me, AGI is a model that never actually really turns off the conversation. Might just be the fact that I have to go to a window in a browser to, like, engage with it. The conversation never really ends.

A (33:30)

Yeah, that.

B (33:31)

To. That's, you know, Brandon's version of AGI.

A (33:33)

Yeah, yeah, that's. That's. That's been my definition of it too. Is like, it. You. If you think about it from the perspective of human or childhood development, as childs, as children get older, they get more and more autonomous on a fairly linear curve. I don't Know if it's linear, but it's, it's a predictable curve. And you can like, leave them alone for like, if they're young, they're. You can leave them alone for like five minutes with a monitor. But as they get older, they have more and more time where they're, they can go play in the room for 10 minutes and nothing's gonna, like, they're not gonna die. And I think AI has been very similar. Like three years ago, ChatGPT is like one turn now. Claude Code and, and you know, ChatGPT Pro, like can run for 20 minutes to like an hour at a time, but that's actually quite far away from. They just run indefinitely. And it's worth it. It's economically profitable and worthwhile for you to pay for it to be constantly doing stuff without you like always telling it. Here's what, here's what to do. And I think we're. I think that's actually a very complicated problem because it requires continuous learning. It requires the agent to have like a good sense of what its goals are and also to be able to modify its goals in ways that make sense. And these agents have these little quirks in the way that they learn and their common sense that start to add up over time. And so what they would do diverges a lot from what. What. Yeah, I would do basically, or any

B (35:01)

human would do it kind of like it starts with a seedling and like an hour later they're like, exactly. The world.

A (35:07)

Exactly. And so I think we're getting better and better at that. But there's all this stuff that, you know, we, we, for example, we do a lot of alignment training, which is like essentially making the model be predictable and to do exactly what you say. And flip side of that is like sycophancy, where it's just like telling you what you want to hear. And I think we're going to have to get into a mode where they need to have their own sense of agency and almost like individual personhood in order to have more, in order to be skilled at being autonomous. Because you have to go let them play around and mess up up in ways that I think we've been hesitant to let them do for like, safety reasons. So I think that's going to actually happen a lot more in 2026 is. Is we're gonna use training approaches and architectures that allow them to like, go off and do stuff. That's very vague prediction, but that's, that's what I got. So we're close to time Rachel. I just want to just check in with you, see how we're doing, see if, like, there's anywhere else you want us to go before we close. Awesome. We are good to go. Sweet. Well, happy New Year. We'll see you next year.

B (36:16)

See, everyone.

C (36:24)

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