Invest Like the Best with Patrick O'Shaughnessy
00:11:04 · Eric Vishria, Patrick O'Shaughnessy
Having said all that, I do think one of the more interesting things, if you go from Silicon Valley out into the world and talk to these companies, these enterprise companies And you realize what the pace of adoption is and what the barriers to adoption are and everything else, there's a ton of opportunity to help the enterprises get there to be one of the things that I tell the companies I work on is, "Hey, let's be their AI sherpa. If we're in that position. To be their AI sherpa where we're crossing both worlds, that's very valuable, and I think that'll continue to work. [00:11:36] S0: What is Sierra teaching you about the adoption of this stuff? It's really interesting contrast to Fireworks where Fireworks is the sort of infrastructure provider, Sierra is feeling its way through what are really cool things that we can do for end consumers, enable companies to do for end consumers, starting with customer service, but I know with Horizon now going beyond that. Again, same question as for Fireworks, what do you know that the world doesn't fully appreciate because of how- You've seen that.
00:12:00 · Eric Vishria
[00:12:00] S2: My partner Peter and Brett, I think this is their third company working together, so it's like a twenty year relationship, which is just like an amazing and great place to start. And one of the things that I think makes Brett so special and the team is they're technologists, but they actually have like lived in enterprise world for a long time and really understand it and everything else. And I think actually he's personified this whole idea of, "Hey, let's be their AI Sherpa. Let's start with customer service, very automatable, and like be their AI Sher Now we have these long running agents with horizons that can do more and more stuff. And one of the things that I think is most interesting about this to me is, yes, it's an application company on the surface, but they're doing real AI work, and they're experimenting with models, and they're building agents, and they're very close to the metal of the models and the capability and the harnesses, and they're understanding the jagged edge of AI capabilities, which is very different than the human smooth arc that we understand. And intuitively, they understand that jagged edge of capability and they build around it. You saw the evolution of Cursor from the ide to like tab auto-complete to agentic work over and over and over again. They were Obsoleting their work from six months ago, and it's what Brett Taylor calls like sandcastles. We used to be building castles, now we're building sandcastles and they get washed away. And that's, if you don't think about it that way, yeah, you have to embrace it. Because if you were an artisan and you were like, "Hey, I built these perfect foundation of castle and it was bricks and it was like perfect, and I really care about this and it's gonna be here for a hundred years. You're just not gonna make it. So as you get emergent new properties in the models, which is, you know, every four weeks, you get new capabilities, they understand that jagged edge, they understand that application of that jagged edge or that valley to Their customer base, they're filling in those gaps and translating it. You can't just be superficially applying things. I think it's actually a complete inversion of how product development used to work to how product development happens now. In product development, you'd also say like, "Hey, product manager, you're trained up.
00:14:02 · Eric Vishria, Patrick O'Shaughnessy
The product manager should understand the technology, but like, really shouldn't be thinking about implementation, and shouldn't be specifying implementation, and shouldn't be doing this and doing that. And the product manager's job is to really understand the customer and translate that problem to the engineer so that the engineer builds a solution. Like, that was traditional product management. Good luck doing that now. That's a horrible way to do it. You can't do it that way. You actually really need to understand the nuances of model capabilities, what they're great at and where they fail, and you need to understand the customer problem and put those together and bridge those gaps to build valuable solutions. I think that's one of the things that Michael and team at Cursor did so well from the very beginnings. They really understood the JAGGED capability and built a product that allowed that translation from developer to that JAGGED capability and kept on iterating [00:14:53] S0: on that as the edge changed. It's kind of ironic that- Well, that sounds like the returns to being technical are going up, even as models supposedly are taking away technical edge.
00:14:53 · Patrick O'Shaughnessy, Eric Vishria
[00:14:53] S0: on that as the edge changed. It's kind of ironic that- Well, that sounds like the returns to being technical are going up, even as models supposedly are taking away technical edge. [00:15:03] S2: Well, I, I, I think there's two things, kind of- Yeah, yeah, a hundred percent. And actually, I think there's this weird thing where there was this whole discussion about the traditional roles of product manager and designer and engineer, whatever it is, and I think what there really are are people who understand customer problems, people who have taste. And people who understand the jagged edge of AI capabilities and are curious about it. Those are the three things. Those three are gonna be the ones. If you're gonna be, if you don't have those three things, you're gonna do great. And it doesn't really matter if you are an engineer or a product manager or a designer, but if you have taste and understanding of customer problems and understanding the jagged edge, you're gonna do well.
00:15:45 · Patrick O'Shaughnessy
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00:17:48 · Eric Vishria
[00:17:48] S2: dismissive of this idea that people are gonna vibe code their own shit and whatever. That isn't the issue at all with SaaS companies. The issue with SaaS companies is the competitive frontier completely shifted and everything they thought they were building against and it would make them win. Are not what's gonna make 'em win. Let's take databases. Databases have been a phenomenal area for software for a long, long time. Great margins, why? You had app developers that would build against these specific database interfaces that existed for that database. You would have more and more data over time. Migrating an app from one database to another database was a giant project that was like very, very difficult to do. So these were unbelievably sticky businesses that you could generate a ton of margin, right? Of course, you got Oracle and SQL Server and like, and a whole slew of smaller players like that did really, really well in databases. Well, let's think about that in the context of AI. Now, you don't have a developer building against the database interface, you have Claude or Codex building against the database interface. One, two. The beauty of database interfaces is they're very, very well specified. Well, it turns out, and it's very good, very good at things that are very, very well specified. Three, agents don't get tired of monotonous work of translating one specification to another, so it turns out that now all of a sudden, database migration, which used to be the like number one thing you- Wouldn't do in software is like, "Honey, it's just money. " Yeah. Yeah, it's just like, "Meh, put some money against it, move it. " So what changed? Well, what changes is the criteria to be an amazing database company changed. It isn't that we don't need databases or that everyone's gonna build their own database or whatever, that isn't what's gonna happen. What's gonna happen is the criteria changed. So now you're gonna have a ton more applications that start, obviously as we're seeing everywhere, people are gonna experiment a lot It's much cheaper to experiment, it's much cheaper to start a new application. So now you need databases that scale from basically zero usage to if it works all the way through, like that matters a lot more. Your cost matters a lot more.