Decagon

“Moats are most often discovered, not designed.”

“And then chat GPT happened and then everyone realized actually customer service is going to be the biggest market for AI. And they've been on the journey since then. You know, I think in customer experience in customer service, Sierra, Decagon, everything happ…”

“And the reality of a lot of, in full reality, a lot of the so-called ARR that you see with some of these companies that you mentioned is actually contracted ARR. So none of this is ever actually deployed in production at scale. Find me one real customer from a…”

“I mean, I think like Decagon has done an amazing job at this. Like, I think they go in, they basically evangelize that they're doing customer support better than anyone else. And then they're very good about saying, here are the benchmarks that we are signing …”

“But I do think we passed a threshold in like, I want to say about a year ago where a bunch of smaller companies or like new application companies, as they were trying to figure out, how do I really build an AI? Without just being a wrapper on top of open AI, t…”

“Decagon is a great example. I mean, Decagon is like a five billion dollar business today doing AI for customer experience.”

“So today, 90% of our workflow is on open source.”

“So we think for jobs like that, Frontier models that are very smart, that can try out a lot of things, make a lot of sense.”

“We don't just build our set of open source models and then, you know, it's done, we can move on to our next thing, and maybe we'll revisit this in two years. You often need to train new models all the time because As the frontier changes, as the capability of …”

“When we have open source open source models that we want to fine tune, we find that if we can clearly tailor our evals to customer outcomes, it's way better than just looking at, like, loss curves over time, right?”

“Performance latency and accuracy is definitely the driving factor for most of this, right? Cost is a nice benefit in that, you know surprisingly, this is one of the few like tasks where you kind of get all the things for free, right? Like we don't actually hav…”

“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.”

“If we ran our entire business exclusively on frontier models, I would care a lot about costs, and I would think a lot about that, but once you're already, once you've already made the jump to saying, okay, now, now we know how to think about open source models…”

“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.”

“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…”

“First of all, very few companies, if any, can do what Palantir does, which is like close massive deals off the bat. And like, it's kind of worth it to spend all that effort.”

“The capability of models today is far greater than they are being used for within the enterprise, right?”

“And so I think for the next few years, that's probably going to be you know, the primary thing that these models need to be able to work.”

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

“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.”

“The thing that we built and we kind of built this intentionally from the start was not an agent that does customer support well, but rather an agent that follows business process well. And executing on operational workflows, doing sales lead qualifications, an…”

“There are still things, I don't quite yet think we're at the point where we can have the AI agents make decisions on what to build, and kind of have that the taste of, is this done yet? Right? So we can outsource a lot of specific execution steps, but I don't …”

“All the AI coding startups are hiring like crazy. You know, they're like the most sophisticated users, presumably, of these models, and they are hiring like crazy.”

“Everybody has access to these tools, and so if our competitors are going to use them and build more things, we need to build more things, right? If somebody else said, oh, here's our roadmap, and now we can get through it in, you know, a third of the time, and…”

“Being able to have teams that are so kind of disparate from like a function perspective all working together kind of one kind of needs people in the office because everybody's kind of jamming on ideas together”

“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…”

“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…”

“Now, to the point of, Does that mean CRMs go away? I mean, my answer is no, because if you had you know, if you have a company today where your concierge is a human being, they still write your info on a CRM so that they can track it for later. So, and I think…”

“However, the bottleneck, I realize, at least for a lot of the work that I do, is business context, right? There's a lot of context for every idea around, okay, the constraints that we have, the goals that we're going for, and things like that that is difficult…”

“Automating things doesn't necessarily result in just kind of people laying off their entire teams.”

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

“As Jesse from Decagon wrote very eloquently a big portion of their volume goes through open source, about 90% now.”

“So like Decagon, the customer support AI company, they said that 90% of their usage now is being sent to Open models, but those are open models that they've had the opportunity to post train on and do a huge amount of customization based on all of their learni…”

“There will always be capability overhangs. They may not stay still, and so you gotta be nimble. But the Sierras of the world, the Cognitions of the world, the Cursors of the world, the Decagons and Harvey's, these are all agent labs for their field. They can b…”

“These Sierra Decagons, and also legal Harvey, these were niche markets before agents. These were niche markets that are like 10 to a hundred times larger because the agents add so much value.”

“Customer support has companies like Sierra, Decagan, Which are already almost ten billion dollar companies.”

“They're solving the problem of, you know, solving support cases and tickets. That is a very low margin business, right? So, like, you can't have a million conversations and have it cost a lot because there's not a big upside to that.”

“But I also think, like, you look at, like, all of our competitors, like, you mentioned Sierra, DecGone, and all of the other ones, we power all of them.”

“From a market perspective, there isn't, so it's the same ICP. We're not in the U.S. At the moment, though soon will be, expectedly.”

“Ultimately, I think Decagon and Sierra are examples of companies where you're moving from proceed software to basically utilization based customer support related agents, right? That is a real shift. That may impact some of the prior wave of sort of perceived …”

“We looked at a number of companies that were behind Sierra and Decagon and came to the conclusion that a direct head-to-head Against those companies, when you're a smart, it's just a little bit too hard.”

“If I were to rank order the level of disruption that is coming for these companies, business model shift is number one. And so, you know, we can talk about examples where that's most in practice today. You know, Sarah and Kimberly from our side led investment,…”

“Their valuations of those three companies, one is Cognition now at 15,000,000,001 is Decagon now at four billion. And you know, and the other one is Distill that just raised at two billion.”

“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…”

“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…”

“The other property, which I think is a little underrated, is that it's very easy to go live. And I think a lot of Gen AI use cases are struggling with that right now, especially at the enterprise level, because there's risk involved, right? Like people don't w…”

“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 …”

“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…”

“In the old days, to map out a conversation, you just build, like, a gigantic tree, right, of decisions, and that's very hard, because no one likes that experience, and, like, you ask something that's not quite one of the branches, and it just forces you down t…”

“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.”

“When you think about like moats in the agentic world, a lot of it is around, well, if you've kind of been working with a client for a year, Has your agent just continuously gotten better by learning from the data? And that's, it's like, that's a different con…”

“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…”

“The number one thing is just APIs for the AI to use, right? So APIs to take action, APIs to look up data, APIs to you know, reformat things. That is often like, hey, if you have those, you already know that within the first month, it's already gonna be a great…”

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

“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…”

“I'm very bullish on Google, actually.”