Jeffrey Wang: preference

Transcript context

…Have you thought about, I don't know, A-Z testing, I guess? Like one of the limitations has been, well, people can only write so much copywrite to test, but now with these generative models, you can actually generate a lot of copy. And like you go to on-demand test more and more and more copy. Have you seen any maybe fun customer stories? Like can you, anything there? Yeah, so actually there's a very good example of this. I don't know if I can share the actual customer, but actually from before the LLM days, where they literally generated the versions of the copy themselves, and they made their product basically adapt, you know, multi-arm bandit style of like, hey, here's all these different variations, like just go figure out the best one. At an internal hackathon, maybe two months ago, I built a prototype of what you're talking about, which is, okay, now replace the copy generation with an LLM. So just constantly generating new variations, and then multi-arm banditing to figure out which one's the best. I think that is probably the future of copywriting, where it's like, you don't actually need a whole lot of manual work anymore. It can, almost everything can happen automatically. And it's kind of the micro example in my head of this concept that we really like, which is self-improving products, where, you know, at some point, you know, someone has to say, hey, I'm gonna build a product that does this, you know, like a newsreader or something. But then, you know, after you have that, like the title of the newsreader, like the description of the sections, your navigation, all of that, in theory, you know, if you can give it some structure that the AI can play with, the LLM can manipulate all of that for you, and then use, you know, A-B testing, multi-arm bandits and all of that to kind of figure out what's best. And that generative AI kind of makes that last piece of like, what are my options possible? And that's super exciting for us. And we wanna be there, you know, to help you measure that, help you deploy that, and make that like the way people build products in the future. I think I've talked about this on the podcast, but this idea of like just-in-time UIs, you know, like each type of user wants to interact in a different way. And like, what you're building is a way of that, right? Like, Amplitude has been really like dashboard-driven, kind of like a diagram-driven, showing the user flow. Now each user can say, hey, I don't really want the table. I just want the charts. Or like, I don't want the charts. I just want the data. What do you think about the future of like dashboards and like BI in general? But like, the analysts used to come up with like what you should be seeing. Now each user can ask their own questions.…

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