The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 16 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
People falsely claim to be Decagon customers on investor expert network calls
“We have people who had said that they've used us, and we literally never heard of them.”
AI agents will eventually replace websites and apps as enterprise front ends
“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…”
Zhang: Large enterprises scale AI customer service agents within weeks
“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…”
Zhang: AI Agent Moats Come From Continuous Improvement on Client Data
“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…”
Customer service AI deploys faster due to pre-existing human escalation infrastructure
“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…”
Experienced founders warned Zhang that AI customer support was too obvious
“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…”
Zhang: Winning top talent requires whole-team swarming like a sales process
“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…”
Zhang: Decagon maintains a strict principle against negative gross margins
“The only thing that we have a principle for is not to have negative margins.”
Zhang: Startups must communicate intensity upfront for candidate self-selection
“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.”
Zhang: Defining good performance is hardest part of replacing enterprise human labor
“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 …”
Zhang: Founders should ask direct pricing and approval questions in discovery
“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…”
Zhang: Enterprise APIs are the primary prerequisite for great AI deployments
“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…”
Decagon's AI cut Oura's immediate human-agent request rate from 33% to 5%
“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…”
Zhang: LLMs abstract rigid conversational decision trees into neural weights
“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…”
Fortune 100 enterprise customer support volume is 90% to 95% phone calls
“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.”