The Exchanges

Q So concrete example, Goodfire is like the most, the most interesting one. Mechanistic interpretability. I didn't even think that was a market that was worth investing in, but obviously Anthropic does. Uh, and, uh, they seem like they have good vibes. What, what's the, I guess the, the summary of your, of like your take on the company?

A The way I think about the company is right now, almost all frontier and some many non-frontier AI models are complete black boxes. You don't understand why they produce the outputs they produce. All of the eval and studies on them are empirical studies, not intrinsic to the model. So it's like, Hey, here's the outputs we saw. And therefore this is the benchmark score, or this is how we think it did. If we believe as a society that Five and 10 years later in the future, these models are going to be critically important for making pretty heavy decisions, whether it's, I call it anything from whether somebody should get a loan or insurance or a legal decision, then I don't think that the black box approach is long-term scalable. It's just not how society can function, where it's, you say, you throw your hands up and say, well, this is what the model said. And then I asked it, explain yourself. And it said this other stuff. Great. Like that's kind of what we have today. That's the best thing that we have. Mechanistic interpretability is really going into the weights of the model and trying to figure out why did the model do what it did? And one of the more concrete and relatable examples of this that, you know, you guys may be aware of is GPT-IVO had this phase of sycophancy that, um, a lot of users really liked, but It's kind of one of those things that's not as easily detectable …

AI assessment note: “The way I think about the company is right now, almost all frontier... models are complete black boxes”

Q so since then, I wanted to start with Glean, obviously, because of, you know, we, uh, we're going to cover a lot of startups in this episode. So Glean has, Glean was like a billion dollars, I think, as based on my research, and now it's at seven billion dollars. So your, your, your options are good. What's your take on, like, how Glean's going and the market in general?

A I would say that Now being on venture side, I have a bit of a different take than I would have had at Glean. But broadly, one of the things that I love about Glean is it's such a boring, unsexy company that became sexy later. So from 2019, I remember going to parties in the Bay Area, and I would say enterprise search, and it's a shutting down the conversation right there. You know, like nobody would ever ask a counter question if you said enterprise search. They're like, oh, that sounds boring as hell. Leave me alone. Like, um, and, and fast forward to 2022, Enterprise search gets more, um, got more conversations. It was like, interesting. Tell me how you're doing this, this search. I think what was nice about that observation is in those three years, we did a lot of work and not, didn't take shortcuts on a lot of things that ended up generating a lot of value for us now. And I can go into what, what all of those things are, but if you look at glean from a high level business, it is top down enterprise sales. It's very hard to rip and replace. We have, we expand contracts very easily because the TAM is so large. It's every knowledge worker could use a version of enterprise search and then the AI on top. I still call it search, but information retrieval in the enterprise. And we've, we've, we solved a lot of critical problems. I can go into that too, in order to get there. Then …

AI assessment note: “if you look at glean from a high level business, it is top down enterprise sales.”

Q Just a question on that. Was there any, because you know, oh, you have a new search tools, like go search. And it's like, what am I searching? You know, like what was that blank canvas onboarding for people?

A Um, several different things worked well for us. Uh, I can think of two at the moment, but I'm sure there were many, many more. Um, I'll say one of them was say for, for a handful of companies, like many companies, actually, we would say, we want to take over your new tab page. And then the critical part was tell us what we need to do to earn the right to do that. No one wants to give away their new tab page. So, so, so we, Went the last mile. There were companies were like, well, we have a new tab page. We're pretty happy with it. So we'd ask, do you have a search bar on it? And they'd be like, well, yes. I'm like, okay, what is, what is that using? And they'd be like, well, it's using our internal thing. I'm like, do you like it? Clearly not. That's why you're referring to us. So let's just rip and replace that. But doing that extra mile was pretty important. So that's one new tab. The second one that we liked was a Chrome extension and then doing the, I forget what we call this, but When you were on your native product and you were issuing a search query, we ran a lot of evals and we thought we were better at every product at their own search. So if you were searching on Google Drive, we will do a Glean replace of the search bar and the page pretty natively. And it would teach people, it would teach people to use Glean and be like, okay, that's pretty useful. I think these r…

AI assessment note: “one of them was say for, for a handful of companies... we want to take over your new tab page”

Q is like, for me, it's like a survey episode of like, here's everything. We're also catching up with the former guests. It's always nice. Maybe we can end it on this like coding interview thing, uh, which, which literally you tweeted about today. What is the situation that, you know, I guess engineers should be aware of? And I think this like maybe ties into LLM psychosis a little bit.

A You know, like, so I tweeted, I'll just cover the tweet first. I tweeted about this, um, Guy who wrote a blog post about, he was in an interview from a, I didn't think it was a legit account. He thought it was a legit LinkedIn message where he was interviewing for the company. They sent him a coding interview. They said, clone this repo, run this code, make this edit. Kind of not untraditional. So it's pretty, pretty run of the mill type interview. It happens. And in that interview, he claims that he went to cursor and asked whether the code had anything Any vulnerabilities or anything you should be aware of. And it revealed that it had some link. They had a byte array that compiled into a link that would go and take a bunch of private information from you. So that was the TLDR. And, and I tweeted about that saying, you know, like, The, the world, interestingly enough, it was solved by vibe coding, but it could very easily, the world of vibe coders who don't really look at code, I imagine are more susceptible to being in attacks like this and in the future. And, uh, and it got me thinking about a lot of things like, what is, what do attack vectors even look like if people aren't looking at code? There's so much that can go wrong. And what are the implications on model safety and how models behave in those environments? So that's one. But I think the broader thing, and I'm curio…

AI assessment note: “I tweeted about this, um, Guy who wrote a blog post about”

Q about like, you know, .12 differences in, in like SweetBench, but, I wonder, you know, if you're talking about like, okay, I am investing thirteen billion dollars in Anthropik for Series F to underwrite cloud five, right? What, what does it have to do? Like, what kind of, what kind of conversation does that look like? I have no idea. I'm not saying that, you know, but I'm just like.

A I would say that despite what you said about the premium, I think it's everything you said is true. Um, I still do worry. I think cost is Is a concern for a lot of people. And so the period of the period of frontier does still matter. I'm glad Anthropics where it's, where it's at right now, but who knows where that changes when it comes to like cloud five and thinking about the future. One thing I think about actually, that's really nice is I think we can take for granted right now that furthering the intelligence of models and chat GPT, a consumer product does not lead to more users or more retention. It only is really applicable to us The thin slice of users who care about very smart type queries, right? And I would say maybe like under ten million, right? Maybe that's just a random estimate. But most of the eight hundred million users on ChatGPT are asking, like, how do I fix my dishwasher? How do I, like, rephrase this email that I've sent to somebody? And that's done. Like, we know how to kind of do that. So what's interesting there is, now that means we're at a point in consumer where, maybe this is too early to say, but OpenAI has kind of won, right? Like, How do you catch up to something where model quality is not going to be differentiated? You already have the users, you already have the retention, you already have great product and people are paying. But the, the int…

AI assessment note: “So it's more possible to underwrite the quality of the future models”

Q I'll point out, which is more fun, which is, uh, there was a new CTO joining Anthropic from Pesit. And, uh, you know, you're like the king of Indian posting. What's the significance of this for you? You know, last time you were on the podcast, you talked a lot about like the Indian, um, the university system and all that, and I, to see this guy rise up and

A In India, largely academics holds the, the same sort of prominence as sport would hold in America. Everyone talks about it. It's Asian culture, right? Everyone talks about it. It is top of everybody's mind. It is something a lot of people want to be good at, and it's extremely competitive society with a very large population. The way, and, and, and everyone on average people are quite poor. So education is seen as the means to social mobility by, A large amount of people in India. The way it works is similar to countries like China or some other countries where you take a big exam, you get ranked. A million people take the core engineering exam and the top 10,000 get in and the top 200 get into computer science. That's how hard it is. That's pretty hard. And those top 10,000 get into IIT. Everyone's heard of that. That's like where a lot of the great, you know, Silicon Valley people from Sundar to many other people come from, from IIT. And in India, Often what I've seen, and this is something that I'm generally very curious about is like, what is the motivation of humans and what is the dictator of outcomes in their life and their career? And one thing I've noticed a lot is, A, there are some societies that are inherently, I think, less meritocratic, where you get so judged for what you have in the past that you're not allowed to prosper later. And I think largely many work env…

AI assessment note: “top 10,000 get into IIT. Everyone's heard of that. That's like where”