Public evidence record
Published podcast speaker
Claim ledger
16 transcript-backed records
01 / evaluation
“I think we just return to, how do you generate interactions that fit a coherent role based on what the creator's brand is?”
02 / recommendation
“Yeah. So I guess I would say back to replicating tone. You have the option to handcraft your prompts.”
03 / observation
“I think along the lines of how we model it, which may not be the best way of modeling it, yes, you get a lot of daily interaction from the category of users that we think are simply looking for someone to talk to or trying to alleviate loneliness in some way.”
04 / belief
“I'm definitely interested in doing something in the future, perhaps with providing a product where the end user are women. Because I think one of the things that kicked this off was that character AI has so many daily repeat users and customers will come back multiple times a day.”
05 / belief
“We're puncturing the fantasy that the creator is inaccessible. And so we realized that we need to be able to provide a coherent experience to the fan based off what the brand of the creator is and what sort of interaction type they're expecting.”
06 / belief
“I would say that most of the time when we give the product to somebody else to try, like we'll say, hey, creator or agency, we have this AI chatting system.”
07 / evaluation
“One context is that sometimes the product is sexting with a fan with content that's sold as if it's being recorded in the moment. And so latency, you have to be fast enough to be able to provide a response or outreach to people as they come online or as they send you a message because lots of fans are coming online per minute and the average session time seems like it's seven, eight minutes or so for reasons.”
08 / recommendation
“At the start, we had a very simple product that had a limited amount of language bottle generation. And based on this, we started using sort of low code prototyping tools to get a workflow that worked for a limited number of creators or a limited number of cases.”
09 / evaluation
“Well, I think you can get reasonable outcomes on sort of the closed source models. They're not very cost effective because you may have very, very long conversations.”
10 / commitment
“I think we have a lot of information about fan and so when a fan that's currently subscribed to one of the creators we work with, their profile subscribes to another one of the creators we work with profiles, we need to be able to manage sort of fan collisions between multiple profiles that a creator may have.”
11 / evaluation
“And so as a result, don't generally do a good job of chatting. And there's also elements of the fan experience that if you're training from data from a chat team, they will do a lot of management of people that don't spend, that we don't need to do, because we don't have the same sort of cost per generation as a human team does.”
12 / evaluation
“And we also work with creators where tone is not important at all. And we find that a product like this is really good for this industry because LLMs are good at replicating tone, either handcrafting a prompt or doing some sort of K-shotting or doing some sort of fine tuning or doing some other sort of optimization.”
13 / evaluation
“And then I say there's the technical challenge of replicating the personality, and then sort of the product or business challenge of providing the critical elements of a fan experience for a huge variety of different creators and different fans. And I think the variety of different creators that we work with is the key part that's made this really hard.”
14 / evaluation
“Because people are paying a lot of money for the experience, they may be paying 1000s of dollars to have this experience in the span of a couple hours.”
15 / evaluation
“As long as we can keep their disbelief suspended, then we can sort of make the fan happy, provide them a better experience than they would have had with a chat team, or provide them interaction that they wouldn't have had at all if the creator was just managing their profile and sort of accomplish the ultimate goal of making money for creators, especially because, you know, creators, oftentimes this is their only stream of income.”
16 / evaluation
“They work with traffic. And so overall, this landscape became apparent to me where you have these essentially small and medium businesses, these creators, and they're running either anywhere between a few thousand a month to 200k a month in earnings to themselves with no state of the art tools and no good software tools just because it sucks.”