The Ledger, every show

“Having the older way of doing things actually serves as baggage because you have so many customers already locked into that approach. And because you have a lot of customers, anything you build has to be compatible with all of them. And so it just always inher…”

“Human labor is generally like an order of magnitude larger than software spend, like 10 X or more.”

“And so if you look at a lot of our customers, for example, they're spending more on the AI agent Than the previous CRM software for support.”

“I think in three to five years, it'll probably creep towards like just consistently 80 to 90, right? Because you're able to just so easily allow the end users to capture more logic and teach you new things.”

“I would say from our experience so far, very few people will build it themselves.”

“Yeah, roughly there. The lines get blurred because oftentimes what will happen is like, hey, I'm sitting down to do this project. Let me just have the agent Take a stab at it first, and then you go in and like edit things and move things around. So there's a b…”

“It's just way more productive. My last company, we were remote, so because it was during COVID, and I think there's pros and cons of that, but I think overall, just personality-wise, it just comes down to the founder's personalities. Like, Ashwin and I are doi…”

“I will say we could have raised at a much higher valuation up to like 1.5 to two X.”

“I think our space probably will have multiple winners, hopefully not too many, and hopefully we're one of them. I think it's just hard to say, like, why there would be a huge single winner here. The reason is that there's not that many network effects from bet…”

“Technically we really value just like clock speed really, really highly. And clock speed, I just mean like how fast your brain works and how fast you can learn. And this is across all functions, right? Obviously it's important for engineering, but for Sales an…”

“And so, I think our mistake was we over-indexed on that a little bit. Because I don't think that concept necessarily makes sense in all use cases. And in our use case, the types of things that people care about across different customers is generally pretty co…”

“And we've done case studies now where, you know, folks have been able to cut that down by, you know, 60, 70%.”

“We're generally just selecting for very smart people. First of all, I think we care more about that than like, you know, direct experience and so on.”

“We're five days and then a lot of folks come in on the weekends, but it's not like a requirement.”

“I think pretty much all the AI companies that are doing well have, you know, pretty heavy in office cultures. It's just, you get way more done, especially, especially in the early stage.”

“Generally, when I talk to engineers that want to join startups, for example, and let's say they eventually want to start their own company, which is a very common profile, it's, in my opinion, it's like way more useful to join somewhere where they've already k…”

“I think it makes a lot of sense for them to push into application layer, and I think they will. In terms of what applications, I mean, generally they'll probably start with applications where it's more consumer prosumer-y because there's, it's just more self-c…”

“I think before they tackle our space, there will probably be other spaces they have to tackle first. Yeah. Coding's probably one of them.”

“Again, obviously, we respect like the sales forces of the world that build amazing businesses, but we just don't think that's the right approach for the AI era.”

“And we'll probably start seeing that more and more in the AI agent space where you generally price per like the output that that's doing. I think that that works. I think that's just very clearly the right pricing model for our space”

“And eventually, if it's good enough, most consumers will just interact with the agent instead of even logging into the mobile app or the website.”

“Now basically we're almost, almost a year in at this point, they've been able to really restructure their customer support team. And again, we published a case study on this where they were able to quantify like, okay, what are the savings? Right. And so, so f…”

“And for us, actually those things help, but they're actually not the biggest difference maker. So in our use case, the type of intelligence that matters the most We would probably describe it as instruction following.”

“The use cases that emerged, like you have to have those two qualities. Like it has to be able to be something that can be rolled out slowly and doesn't have the perfect off the bat, but it's already providing value, right? Like I think coding agents is like a …”

“I think they'll get there, but it'll probably take longer than people think because, you know, even with our team, fine tuning these models is non-trivial.”

“And actually over time, the number of tokens we're using per conversation has gone up because we're actually doing more model calls to make the quality better, to do more checks, to parallelize more things.”

“I think a common misconception that people have is, you know, fine tuning is, is a way to like customize it for that customer. In fact, most of the fine tuning we do is like customizing it for our use case, like the customer service use case.”

“Generally in these conversations, we're not really having to convince people to like, Invest in this space. It's, like, more of, hey, we're the right approach for you, so you can partner with us.”

“The other profile we had a lot of in the early days were just like Ivy league athletes, I guess. And those profiles were kind of a good foundation for the group.”

“One of the things that we really try to do is, you know, kind of take the project and piecemeal it. So we're not just deploying across every surface area, every use case at once.”

“Realistically in, in today's AI world, it's very difficult to have, like, a 12 month roadmap to a T. You maybe know how, like, some themes of what you want to build, but ideally, if you have those things, you should just build it, like, right now, because it's…”

“Language is a lot easier with AI. So in the past, maybe a blocker would be, oh, my language just doesn't work in, or my app just doesn't work in German or pick your language. But now it's a lot easier to adapt to your app. So I think for those reasons, interna…”

“I do think like one of the big struggles being a solo founder is you don't have anyone to bounce ideas off of. So you just arrive at conclusions a lot slower.”

“Well, one of my big theses is that there's a lot of untapped potential there and to actually like turning them into people that, you know, want to do business or companies and things like that. A lot of them have historically gone into, you know, trading or ac…”

“When you talk to potential customers, they actually don't mind answering questions such as, like, okay, if we built this for you, like, exactly how much would you pay for it? Like, would your boss need to approve it or your boss's boss? Like, who needs to appr…”

“If you're going to be replacing human labor, you need to, you know, know what good human labor is. What we found is like, okay, well, can someone just tell us, like, what are all the, what are the answers to all these questions? And most people don't actually …”

“For enterprise use cases like us, like there's still a ton of hurdles to cross because those models, even though they're good, the hallucination rate's really high. So you can't really use them necessarily as is in, in kind of the current systems. And so a lot…”

“That is the biggest proponent of voice to voice, and ultimately the prevailing view is that first, whatever the final experience is, if you really want to make it indistinguishable from a human, you have to do a voice to voice or you have to at least take into…”

“Pretty much all AI initiatives are very top-down at this point, because it is such a board-level mandate, so the C-Suite's very, very invested in like, okay, where do we deploy AI? It almost means that if you want to get something going at a larger organizatio…”

“There's definitely a level of intensity that's important. And yeah, you definitely want to tell people that upfront because you want them to self-select into this culture.”

“Like you, for anyone you want to hire, you need the whole team to swarm around them for, you know, to win. Highly sought after talent. And you have to go and, you know, do, do all the things, right? There are some parallels to sales, of course, like you, you'r…”

“Unfortunately in the application layer, it is not as crazy as, you know, the metas and the opening eyes who are just like, there's only so many top level researchers.”

“You know how your agent is structured, you know the places where you need models to run, and you can take, you know, smaller fine-tuned models, and that improves the entire system, both in terms of performance, but also latency, and so on.”

“I mentioned I'm close with the cognition guys, so cognition would be in there for sure. Cursor also I'm actually kind of interested in like where those might run into each other in the future.”

“There's the Waymo effect that often happens where It will be objectively just way better than human drivers, and human drivers make a lot of mistakes, but because we're investing in new technology, the bar is a lot higher, so it has to be near perfect. So ther…”

“The only thing that we have a principle for is not to have negative margins.”

“That last step where you're actually solving someone's problem, that's where you generally can capture the most margin.”

“If you can really unlock that level of, you know, reasoning capability and just like smartness and combine it with folks that can, you know, teach them how to sell or how to build a company, I think that's a pretty good combination. So that's something I think…”