Anthony Pompliano: I'm sure you guys want a date night with your wife. We don't care. We just want to be good at personal finance. So we have focused all of our energy on be the best in personal finance. The second thing that we have done for a tax question is we have actually gone and we have indexed the federal tax code and most of the state's tax code or the major state tax codes. We then put that into our own database called data pipeline. And then we basically have the agents run through it. And so think of it as like you ever seen the game where somebody like. Looks at a piece of paper and they put it down and people start asking them questions. They got to recall, you know, A1 was this, Z2 was this, whatever. Basically, Sylvia is really good at understanding where is all the tax code in that database. So when you ask a query to a model, let's say Anthropic, usually what they're doing is they're looking at how the model was trained, what's the information, plus web search. What we're doing is we're taking that query and we're saying, OK, we understand it's a tax question. Go get the tax code. Go to the source material. Don't go look for a blog post talking about a tax code from two years ago. Just go get the tax code. We then pull that in and then we use the power of AI. We use web search. We use all these other things. But the accuracy of getting the source information is really important. So the reason I say that is if that's the level of granularity you can get to, you mentioned pension. It is literally just a prioritization for us. We could have the best answers to pension questions. We just got to go build the data pipeline. We got to use Sylvia's AI model and we've got to build it into the harness to be able to answer the question. And so that's part of what I say is like the complaining. You know how many people have told us about pensions? Three or four. Put it on the list. Okay, now we've got another person, right? And as we build up and we realize, hey, this is something that people really want, then we just say, okay, our resource allocation goes to let's go be best in the world of pension. So we did tax, then we did mortgage, then we did credit cards.
We got to use Sylvia's AI model and we've got to build it into the harness to be able to answer the question.