The Exchanges

Q So, you mentioned this a little bit, but when you reflect back on that sort of first chapter of MemSQL, What are the, the things, the most tangible things that you learned there, and the types of things that sort of are still part of the way that you think about building and running companies?

A Yeah, I think, um, I'll tell you a few things that I learned, and also some things I took for granted. Um, so, some of the most important things I learned, one, I think you have to be extremely paranoid when you're building software about quality, and What I mean is, it's actually like super, super hard to build a product that actually works and people actually use. It's pretty easy, and now I would say even like easier to build a prototype, but the craft of actually taking something from 95% to 99% or a hundred percent is very challenging and not something they teach you in school. Um, and there was one guy at MemSQL named Adam, uh, and he was a pretty senior database engineer from Microsoft, and Anytime someone broke a test or anytime a customer ran into an issue, he wouldn't brush it off. He would pay attention and he'd find the relevant engineer and kind of force them to pay attention to it. And I think being extremely paranoid and that level of diligent about quality is not only important, it's just existential. Um, and so I, that was one of the probably biggest learnings for me. Um, I remember when we were selling a big deal at Goldman, The managing director pulled me aside. I was like, 23 at the time, and I, you know, I was, I had no idea what, really what I was doing, and he was like, hey, we're about to make a really big investment in your software, and if it crashes, …

AI assessment note: “one, I think you have to be extremely paranoid when you're building software about quality”

Q Did you do that just by filing off all the rough edges or were there in those first six months, really important phase shifts that happened in the product that you were building toward?

A Yeah. So the first six months we built Very little interesting technology, and I remember talking to, I won't name any names, but, um, VCs and stuff, and they're like, hey, you know, what are you building here that's durable, and what, you know, what, what are you building, what's your moat, and, ah, what's gonna stop, um, people who are now writing AI code from just rebuilding brain trust, or how come customers aren't gonna build this internally, and I just didn't care, cuz I was talking to customers, and They didn't care, and so why would, why would that matter? Um, what started to happen really interestingly last summer is that Notion, who was way far ahead of everyone in terms of real adoption of their AI products, and really pushing the boundaries of the latest models, they had, and they also had more people working on AI, um, they were, like, searching for stuff and trying to dig through the logs that they had in Braintrust, In a fairly unique way. So normally when you're working with observability products, you try to do very structured queries like, you know, user ID equals Brett or whatever. Um, and in AI, primarily because there's so much text floating around one, you have these enormous rows. So every span in brain trust land, which is like a row of something that you'd log in brain trust, the average size is 50 kilobytes. In traditional observability, it's 900 bytes…

AI assessment note: “the first six months we built Very little interesting technology”

Q To wrap up, and it may have been somebody you already sort of talked about. When you think about getting a company in a product market fit and early company building, Who, who's taught you the most, and was there like a particular tangible thing that they imparted on you?

A Honestly, I think there's two people I'd point to, um, and these were the first two people that invested in BrainTrust and really helped us. The first is Alana, and I think that she grew up, um, learning a lot about sales from her dad and then worked in product, and I think that she's super technical, so if you're a nerd, you can, like, communicate with her easily, um, And it doesn't feel like you're talking to a, uh, someone who's too salesy or something, but she deeply understands the importance of getting the right people like customers and, um, candidates around a company to make them successful. And she has very high taste for those things as well. And I, I, I just don't think that comes naturally to a lot of the people that have the skills or gifts that would enable them to create a great product. And I think the meta point here is if you can create a great product or you're very technical or whatever, you need to like almost surrender or make yourself vulnerable to people that are wired a little bit differently and they are wired around people or wired around markets and sort of benefit from making them a really important part of your company. Like the way that she works with companies is so oriented around the people that she gets around the company early on. That is just a very unnatural thing for people, for, for especially people like myself who are super nerdy. So I…

AI assessment note: “Honestly, I think there's two people I'd point to”

Q Share more about the, the couple mistakes you made. Why did you make them?

A As an engineer, you are very used to solving problems that are, um, in your control, and by that I mean what comes by your desk is potentially a very ambiguous, technically challenging, or maybe impossible problem to solve. But the difference between you having the problem and solving it is literally typing, like, keystrokes. Like a 10,000 line PR is a large change. That might be, well, nowadays, maybe it's, ah, not many keystrokes, but, um, even back then, that might be like a 100,000 keystrokes or something, which, if you knew exactly the keystrokes to type, you know, it's, it's not, not that much time, like a few hours of time to just type 10,000 keystrokes. So this is entirely within your control. And I think that in some ways that's great. As a founder, you, you don't feel that you're burdened by, um, you know, whether or not something could be solved. You feel like, you know, if you do want to solve something, you can solve it. But I think the key thing that it, you, you sort of fail to learn. And I think that sales or go-to-market founders often have this intuition earlier than engineering founders do is that markets and what people actually want are in many ways out of your control. And I just had no appreciation for that. So my bias going into Impira was if I come up with something that is technically challenging to solve and seems like a good idea, then people will wa…

AI assessment note: “I was just Completely ignorant or unaware of the fact that the idea of a market”

Q love the product that you've built. Is there anything else that has gone on that has allowed you to so closely associate with those companies? Or have you thought a lot about if we want to win the category and build the trusted brand, the number one way is to get all the people at the forefront to say that you're the best is sort of any thoughts on that?

A Yeah, I honestly, I haven't overthought it. Um, I feel very grateful that people talk about the company that way and they, they do that. But I, I think that at the end of the day, All those companies that say nice things about us, we've been through some hard stuff together over time. They've broken our product. We break all of their products, like we use all of those companies' alpha versions of their AI products. We have lunch and dinner together. Many of the relationships are longer than the lifetime of brain trust, and I think that there's sort of genuine mutual friendship and trust that we've built with each other over time. And it is in a very simple and literal way gratifying to share and see people that you care about succeed. I think, for example, if you hire a new investor at first round or we hire a new employee, they're doing a really good job. I think you feel, you know, as a human, you feel a sense of pride sharing that with the world. Um, and I mean, I think the culture that you built here is a really great example of that with, with sort of newer investors. And I think that if you are really focused on like a shared set of problems that you all care about and you work really hard together and you, you push through those challenges, then I think that on the other side of it, you sort of have the opportunity to, to create that mutual, um, interest and, and, and go…

AI assessment note: “genuine mutual friendship and trust that we've built with each other over time”

Q What has building brain trust thus far taught you about what makes a good market?

A You know, there's a few things. Early on, we, at both Impira and MemSQL, I think there were times when our go-to-market was way more sophisticated than our product, and by that I mean we had, like, great sales talent, we had a sales process, we had all these website metrics, and if anyone at all came to our front door, we'd, you know, be on top of that opportunity, and I, I wanted at Braintrust to, again, in the spirit of skepticism, Build a terrible go-to-market motion early on, but make the product, make Braintrust only successful if the product was so good that despite being grossly incompetent at selling and marketing our product, it would somehow take off. Um, and that meant that when the first few people started using the product, we, we didn't talk to them at all about pricing. And I, I didn't talk to anyone about pricing until they started putting us in production and they're like, Hey, I have this thing in production. Now there's liability, you know, like I need to do some kind of business with some kind of commercial entity to be able to, um, to be able to continue working with you. Can we please pay you? And that it's kind of interesting. Like we started in August and then November, this happened with the first three customers that we had, uh, and it's sort of continued from there. And I think now, you know, we, we are building a really world-class sales team and mar…

AI assessment note: “only successful if the product was so good that despite being grossly incompetent”