The Ledger, every show

“Our most recent customer actually turned off of Sierra to come to Decagon”

“In enterprises right now, even though there's a lot of hype for open source, the sort of share of open source inference is actually Going down right now because people are spinning up all these new use cases.”

“The labs themselves will have more application capabilities, but those will be fairly general. Like they're, you can maybe build general agents that can do this thing or that thing. But for a lot of these like core verticals, like ours, our thesis is that, you…”

“There are definitely scenarios where people use their BPOs a lot less or Don't need the BPO anymore.”

“We have people who had said that they've used us, and we literally never heard of them.”

“That's why I think the open AI's of the world will continue to move towards applications because it's quite hard for them to make money longterm on like their API, for example, because There's like such high competition, all the labs are building, and it's lik…”

“The reasoning capabilities matter a little bit less. I would say the models as they stand today are generally good enough at solving most of the meaty inquiries in customer service. I think it's like, instead of reasoning, it's more about instruction following…”

“I don't think that long-term necessarily we'll always see a five X difference between open and anthropic. So I guess, yeah, maybe, maybe if the question is more like, what is spread trade? I think like that, that multiple will shrink. Over time.”

“I think our view is that for the vast majority of use cases right now, it is still, like there's not going to be real commercial adoption with the state of the current models because of a bunch of things.”

“And so because the models are inherently non-deterministic, It's very hard for buyers like really trust a gen AI solution there. And so, especially agentic solution. So like, I think that option there is going to be really, really, really slow, a lot slower th…”

“The first thing I want to say is I'm like, certain there will be careers after AGI. The reason for that is, like, most of our jobs, for sure are for jobs, are kind of, like, made up. Most jobs are made up... So when AGI is here, like it will change people's jo…”

“Our view, the reason why we've kind of built so horizontally is that we believe that in our space, the winners are going to be horizontal. There's just not that much that is like super verticalized that where like you could see a pure vertical solution survivi…”

“Essentially what everyone told us, including like, you know, very smart, older founders that we knew and so on was that yeah, this is like excuse case, like super obvious. There's probably just going to be incumbents that are just tacking onto the product. And…”

“I would say even for large enterprises, like within weeks, because the only, the, everyone wants to just go live to everything. Right. But the reason why you stage it out is so you can make sure nothing's going wrong. And you can tell if something's going wron…”

“I think probably like eight X higher or something like that.”

“In the natural end state, it is more unified for the exact reason you listed, which is people want a unified brand out there, and the brand's very important to them, and for some businesses it's more important than others, but eventually this is like, this bec…”

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

“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…”

“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…”

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

“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.”

“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…”

“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.”

“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…”

“But I would say that, like, a good bar when you're fully up and running is, like, 6070, 80, in that range. And it just depends on, like, what sort of things the AI has access to. Like, if it's able to take a lot of actions and resolve a lot of things, then, of…”

“I think there'll be more of a learning from examples that will happen. Cause if you just think about how humans learn, if you bring like a really good human support agent, they learn by shadowing and kind of seeing examples and so on. There's probably going to…”

“I think in the near term, they'll still communicate in natural language, just because, like, each agent also needs to be compatible with humans, right? So if they talk to a human agent, a human support agent, or if we talk to a human customer, of course it has…”

“Right now a lot of the conversations are more reactive support. It's like, hey, I have an issue. Can you fix it? But over time, it'll be more and more kind of broader, right, in terms of, like, being able to do purchasing decisions, being able to upsell folks,…”

“We have one of our customers yeah, or a ring, like the wearable ring we did a case study with them where before having any sort of jam AI system, like one in three customer that came in would just not bother saying anything and just keep jamming agent until th…”

“But the, if you just think about the large enterprises, like the fortune 100, they just been around for so long. And everyone's just calls them. So voice is just like disproportionately higher there. Like a lot of them are 90, 95% voice and five percent chat.”

“Never really needed that, but, you know, we're approaching 200 people.”

“It's not something we're seeing at scale now where you have agents writing in for you.”