The MAD Podcast: How AI Gets Built — with Matt Turck
00:58:51 · Nathan Benaich, Matt Turck
[00:58:51] S0: Yeah. It's basically like you're you're kind of going through like a theme park or something and you just you discovered like level one and there's like this entire like other world that you just haven't even opened the door to. [00:59:00] S1: And there are a bunch of people that are [00:59:01] S0: already in [00:59:02] S1: that world. [00:59:02] S0: It's like 93... 97% of the world or something, which is... It was just insane. So that... That's where I was like thinking, okay, this should be like a genius bar for AI or like a Geek Squad for AI or something, you know. Like I find it shocking that, you know, we're we're in New York, like we have amazing Apple store, like all these concept stores for brands. Like why does OpenAI not have like an OpenAI store? [00:59:21] S1: And what would you do in the OpenAI store? You'd walk to a genius person and they would walk you through use cases?
00:59:21 · Matt Turck, Nathan Benaich
[00:59:21] S1: And what would you do in the OpenAI store? You'd walk to a genius person and they would walk you through use cases? [00:59:27] S0: Pretty much. I mean it would take time, but I think, you know, people end up showing other people, you know, with these kinds of viral products. But I could like, you know, very easily see, like, you'd run sessions on, you know, different levels of experience and like, I don't know, maybe one of them is for like small, medium business owners, maybe some of them for like, you know, busy families, like other ones are for like healthcare providers, like, you know, anything you can imagine, but where you're really walking through people, walking people through what you can do by just like flicking the screen and going on work or going on Codex. And I think that would make a big difference because it would make the technology much more empowering and less about like, wow, there's a lot of people out there that are doing things with this that I just don't understand. And I don't have like the time in the day or the volition or like patience to go learn it myself. And maybe it's it's a bit like, you know, everybody should do exercise, but like most people don't and you need to hire a PT to just go do it.
00:59:27 · Nathan Benaich, Matt Turck
[00:59:27] S0: Pretty much. I mean it would take time, but I think, you know, people end up showing other people, you know, with these kinds of viral products. But I could like, you know, very easily see, like, you'd run sessions on, you know, different levels of experience and like, I don't know, maybe one of them is for like small, medium business owners, maybe some of them for like, you know, busy families, like other ones are for like healthcare providers, like, you know, anything you can imagine, but where you're really walking through people, walking people through what you can do by just like flicking the screen and going on work or going on Codex. And I think that would make a big difference because it would make the technology much more empowering and less about like, wow, there's a lot of people out there that are doing things with this that I just don't understand. And I don't have like the time in the day or the volition or like patience to go learn it myself. And maybe it's it's a bit like, you know, everybody should do exercise, but like most people don't and you need to hire a PT to just go do it. [01:00:24] S1: And to finish the thought on the other part of of Codex, you have a slide where you said that non developers are growing usage of Codex faster than developers are. And from August 25 to June 26, individual non developer users increased 137 fold. So those are no longer already coding agents. They are agents that code, but for like a broader group, beyond coders.
01:00:52 · Nathan Benaich
[01:00:52] S0: Yeah. It's kind of unclear because they could write code to go execute your knowledge work, but the individual who's using the system doesn't really see it. So I'd say I'd say that that result is a mix of really simple things like Google Drive connector that actually works. Like it's kind of nuts that the default, you know, Google Drive connector, for example, can't do a lot of things that you would want it to do and you have to go to this third party like GWS CLI, which was written by Google engineer who got fired for doing it. But like, if you don't use the CLI version, like your agent has, like, really, really a high level to Google Drive... Have access to Google Drive, which precludes many, many workflows. So just basic good integrations. And then the second thing is this, like, recursive cycle of models, labs releasing a model, data companies or companies that have a certain workflow that they're trying to implement the model on showing that on their internal benchmark, said model doesn't do very well, but they have the environments and the data to make it do really well. And then the lab realizes hopefully that they want to hill climb on this capability. And so they buy the data, improve the model performance, and then this recursive cycle continues. And I think ever since like the launch of Codex and then... And before that actually like Claude Code with those connectors for legal, for marketing, etcetera, that was kind of this approach of like, let's build the integrations to the tools that the model needs to be good at that kind of human, like white collar work. Let's do hill climbing on certain workflows that are, like, important for finance, legal, marketing. And then, like, let's release those those products with a bit better marketing, a bit better case studies starting with our own staff. And then there's been this constant link debate of like, do we call it work? Do we call it code? Which slider should it be in? And I think, you know, still haven't really figured it all out. But but now I would say like, it's it's like so powerful.
01:02:49 · Matt Turck
[01:02:49] S1: And speaking of hill climbing, we talked about open source, we talked about the big labs, it's, we talked about sovereign AI as well. It seems like there is this, emerging theme around, enterprises and before them, probably the vertical AI startups taking control over their AI versus solely depending on Anthropic OpenAI. Is that an important theme for you and something that is investable?
01:03:19 · Nathan Benaich
[01:03:19] S0: Yeah. Well, it's... I think that that trend has been growing and it's a mix of costs optimization, like sort of data sovereignty, data residency issues. So not wanting to like put all this information into a third party system, which you may or may not trust the privacy policies of. And then three, having a certain like set of use cases that are the real ones you care about and that you just kinda like don't wanna wait for the model lab to start caring about them to get better. And then maybe last one would be, yeah, some of these like more nationalistic tendencies, I guess. I think in that area, what wondering is like who's best placed to deliver that service. Of course, like one of the biggest ones would be Palantir, which was done partnerships with like neo clouds and has all the data infrastructure already. And so it was like well positioned over the last few years to like start providing these services. That probably works in US commercial and not so much in Europe. There are like sort of like these neo Palantir style companies in Europe that are like, you know, started up to go do the exact same thing with a different like nationalistic flavor. And the third bit would be like, what about the inference companies that have been serving open source models and that maybe are well positioned to not just serve, but also provide tools to look at the traces of how their models, how these models are being used in an enterprise, use the the data of these conversations to then provide like a post training service to close the loop. Maybe they're like well positioned or maybe it's like the Neo Clouds themselves who have started to build inference businesses on top that would be well positioned too. Or maybe it's even like the data companies that have not just... Or who have started to move outside of providing our environments for labs, but saying, well, your company is in an environment. And so, you know, we've proved that we can do it well for labs. Maybe we can do it well for you.