Yeah, it's absolutely been a discussion. I think a few things going on. Right. So I think the, you know, first of all there'll be a lot of interesting dynamics at play over the course of the next several years. We already see this with companies that are reporting, you know, they have those charts that show the number of years or number of months to 10 billion in ARR or 100 million ARR. And you see some of these new, some of these new companies shattering these records. I mean OpenAI among them. But there's plenty of these other coding tools that are AI backed or AI native maybe is a better term that are showing sort of these, this track record. And I think the big question is going Back to our customer lifetime is it easy come, easy go. You get a bunch of people who are really excited to pay. There's a bunch of tools that you know, they could pick, hey, I'm going to play around with this. But then there's not really any stickiness, any loyalty to it. Right. I think we see this even at the foundational model providers where, you know, it's depending upon who is the latest model release, whether it's Anthropic, Google, with gemini or with OpenAI. Oh cool. I'm going to jump over to Gemini now. Oh, Anthropic released a new version of Sonnet. I'm going to jump over there. And so I think we're going to see that a lot. And so what is that? Revenue sticky. Now I think the number one assumption in your question is do we base pricing on user sort of adoption or like looking backwards in time. So I think this is a fundamental myth is that we need to have a product in market in order to understand what the price should be. This is I think a fundamental misunderstanding and it highly delays when folks think about their pricing, when actually pricing should be at the very beginning of a development process. Hey, we're building this thing. We understand what the value proposition is and the CPG companies have known this for years before they invest in R and D or manufacturing or distribution. We have a concept we can go out and talk to customers about. Is this interesting? Is this something you would buy? What is the value of it to you? How, what would you be willing to pay for it? And there are many better and worse ways to ask those set of questions, but just at a high level. And then I think one thing as it pertains to the AI problem that you're the AI area specifically is what we're really seeing out there is, you know, your, your, your price is determined always by a set number of factors. So what's the customer value? What's the customer perception of that value? What's a customer willingness to pay? What are your competitors, your cost and what are your competitors doing? And so the thing that's happening right now with this, these AI pieces is that the costs are fairly concrete. And when I talk about costs in a pricing context, it's not usually the fixed cost of development because those are usually not what is material to a pricing decision, but rather the variable cost to serve. And so if I'm One of these SaaS companies that is using paying OpenAI or Anthropic, a foundation model provider for this back end, this is A significant amount of cost compared to what I'm used to providing because storage network compute almost marginally effectively zero. Software companies have been very, have benefited from those type of economics for a long time. So that cost component becomes very fixed. What's the other component, though I mentioned of those, the pricing consideration is the customer value. And I think this is another assumption that's buried in your question is that I'm building these fantastic capabilities so therefore the customers must value them. And I think what we're seeing right now is a lot of rush to companies to cover their costs when the value part of that equation is very uncertain. Customers are first of all being inundated with AI messaging. If you had an AI enabled product in 2015, maybe that was unique. I think customers in 2025, when they see AI, they're like, again, like, yes, because it's, because it's everywhere and so they don't really know what to do with it, what to make of it or if it can actually solve their problem. So I think we're at an interesting transition point right now where the value still needs to be proven. And I was, I was attending a talk a couple weeks ago is another pricing expert who I really respect, a guy named Ethan. He's a pricing expert for Insight Partners. And he had this really great phrase which I think is apropos for this, which is you have to earn the right to monetize. Because I think we saw this first wave of companies post ChatGPT that went out and said, hey, we're tacking on this AI capability. We know it's going to cost us money, so we're going to charge you for it. I think the perfect case study of this was Microsoft, what they did with Office365. Office365. I don't know what the exact pricing is today, but say, you know, that includes Word and PowerPoint and Excel 10 per seat. They said, well, we're adding this AI copilot for Office 365. So instead of you going in and writing your Word document, you could use the copilot to write your documents. So that's so valuable. That's such an upgrade from base Word. That's not worth just another $2 per seat. We're going to charge that an extra 25 a seat. So the base, you know, office was 10 and then plus 25. The problem is everyone used co pilot for office 365 is like, this thing sucks. It doesn't do anything I want it to do. And so they got Ahead of themselves. I think it was a, yeah, I think it was a smart strategic move and I have all the respect in the world for Satya. I think he's done an amazing thing with that company from, you know, his, the previous regime and the turnaround story there. I think it is an example though that everyone can relate to where they see, hey, just because you have this newfangled capability and you think at some point it's going to live up to this promise, it doesn't today. And so you have to earn, you have to prove that in the market that it is proving value and that then you could price appropriately to that. So I think we're in this crawl, walk, run space and it's, I think a little unique for folks because we haven't been in one of these phase transitions for a while. Maybe the mainframe to PC era, maybe the Internet era. A lot of these things rhyme. They're not, you know, the analogies don't always hold. But I think that's where we're at with this needing to price. But you can go out and talk to your customers before you launch to understand pricing and happy to talk about what those type of conversations look like.
