The Information's TITV
00:54:02 · Akash Pasricha, Dan Shipper
[00:54:02] S0: Right. [00:54:02] S2: And it it it reminds me using Gemini how strange it is that almost all the other models sound a lot alike. Like, their data mixes are very similar. And Gemini is the first one that I've used, like a a frontier model, the first frontier model I've used in a while that just feels like it's trained on something else. And that's really cool. [00:54:21] S0: So so this is kind of interesting. I mean, so so Google, if I hear you correctly, you're saying that if you want to basically, what, be a creative writer, you know, Google is the model suite you can use. Where I'm going with this is actually, I I wanna get your take on, if we go through each of the labs, I wanna know from you what type of work you think they're prioritizing. Sounds like Google and the Gemini family, it's creative work that you think they're prioritizing [00:54:51] S2: I wouldn't say creative writing. I'm thinking more about, like, non fiction writing, like the writing you might do do at work. Or, you know, for us at Every, like, we we write, like, long form pieces. I wrote this, like, 8,000 word piece on the history of Codex, like, [00:55:06] S0: Codex It's is having that still personal personal.
00:55:06 · Akash Pasricha, Dan Shipper
[00:55:06] S0: Codex It's is having that still personal personal. [00:55:08] S2: It is... Yeah. Like, that is a personal first person narrative. Okay. But it's not creative writing in the sense that I don't necessarily look at it as something that I would wanna write a short story with. And I also don't necessarily think it is the best at nailing a particular person's style. I think Claude is actually much better at at just doing the style or voice. But in terms of how it structures and lays out a series of thoughts, it is the best. [00:55:32] S0: Okay. So... And so let's go rapid fire through the the rest of the labs here. Just give me, you know, two words here to describe the type of work that you think each lab is prioritizing for. So let's let's go with meta, actually. Consumer [00:55:50] S2: consumer shopping. Consumer shopping. Okay. Or, like, consumer interactions, you know, what... Whether that's, like, keeping up with your sports team or or finding stuff to buy or whatever, like, all the kinda, like, stuff that happens in your day to day life as a as a regular consumer. [00:56:06] S0: What about Anthropic? [00:56:08] S2: Power creative tools. Power creative tools? [00:56:12] S0: Yeah. Not power enterprise tools. [00:56:14] S2: I mean, I think that they care about that, but the the, like, the feeling that I get from Anthropic is, like, it's for it's for pros. It's for creative pros. [00:56:21] S0: Okay. Yeah. What about OpenAI? [00:56:23] S2: Knowledge work. Like like, more more specifically for the general knowledge worker that just needs to get shit done.
00:56:23 · Dan Shipper, Akash Pasricha
[00:56:23] S2: Knowledge work. Like like, more more specifically for the general knowledge worker that just needs to get shit done. [00:56:31] S0: Non coding knowledge work? [00:56:32] S2: Both. But I think a lot a lot of it is... I think the the CHECHVT harness is extremely good for noncoders. [00:56:40] S0: Grudbeck Rock. [00:56:43] S2: People who want to get conspiracy theories from their AI. Or or or... You know, actually, think there is there is something, like, really interesting, which is there are some things that none of these models will tell you except for Grok, and that is kind of important. You know? Like, for example, it's very common right now in tech. I'm not naming names, but it's very common right now to take peptides. Claude's not gonna tell you how to dose your peptides. Grok will. So do with that what you will, but I think that's actually an important thing to be able to to do if if if that's if that's your back. [00:57:19] S0: Okay. I wanna ask you a question about Grok. I don't... I didn't miss any of the main labs. Did I? [00:57:23] S2: I think you got it.
00:57:23 · Dan Shipper, Akash Pasricha
[00:57:23] S2: I think you got it. [00:57:24] S0: I I hit got most of So so let's stick with Grok here for a second, though, because Elon had an interesting tweet. He was talking about the economics of GrokBot and how they're basically losing way too much money on Grokbat as of now. And the sense I was getting is that's not gonna get a whole lot better in the near term here. I mean, it kinda leads to a question around to what extent the labs are subsidizing these models and whether or not prices will come up, whether or not you think these personal agents will be good enough for people to pay any, if not a lot of money for. What's your what's your read on this?
00:58:03 · Dan Shipper, Akash Pasricha
[00:58:03] S2: I mean, the the history of the way that model pricing has worked is that it has just come down dramatically over time. And even if the model tiers... Like, they they with the recent OPUS five five release and and the recent recent Ash releases, they did reduce prices by, I think, like, 50%. Before that, they were holding the tiers steady, but the but the amount of tokens that that were used in each tier went up and up and up and up. So what... So model so model prices have have continued to go down and usage has has continued to go up. Obviously, the labs are highly subsidizing their their their model costs. And, like, training and... And the way that we build models today is extremely inefficient, and they're constantly finding ways to make that more and more and more efficient. And I I I think that there's going to be a category of personal agent that you're not gonna wanna pay for, just like, you know, in a in a similar category to you don't wanna pay for Instagram generally. And there's a whole host of pro agents for professionals or prosumers that people are absolutely gonna pay for and already are. [00:59:14] S0: You launched your own agent, the Every agent. What does it do and what are the economics of it? Are you making money on it?
00:59:14 · Akash Pasricha, Dan Shipper
[00:59:14] S0: You launched your own agent, the Every agent. What does it do and what are the economics of it? Are you making money on it? [00:59:23] S2: Yes. So every... The Every agent is an agentic coworker that lives in Slack. It can do any task you give it. So you can delegate writing tasks, you can delegate coding tasks. It it works in the way that we work. So, you know, at Every, we have a a whole bunch of people who are constantly testing new models, trying to figure out workflows that work at the edge to push the models to their limits. The Every agent gives you all of those things in in one package that you can just add it in Slack and it helps you do work. And it also helps you spread that work to the rest of your team. One of the things that we find at Every is we have so many people in our audience who are AI pros and love using it and think they do great work with it. And it's extremely hard to get other people in their company to to work in that way. And what we found is the best way to do that is just do the work in Slack. And so if you just at the every agent and and do your work with it, you you kind of bring your coworkers along automatically without having to explain it them because you're showing it to them. [01:00:17] S0: And is it profitable?