And so the question you have to ask yourself is not, hey, i'm doing this test, how do i know if it's good or bad? It's actually, how likely am i to be right about this? And spend some time thinking about it. So if you run a test, let's sat you run a test. We ran a test when we first started mavin where we ran a course. So we justu i taught a course myself, and i created it from scratch and taught it. And i wanted to see, like, ok, what it's a coer base course like? And now there are a thousand arguments you can make against this test. You can say, well, you're a well known anonprener who has following on line, like, you're not the same as average o instructor, average gill instructor. You could say that whele you're teaching these courses, you're not building technology at all. You know, there's all sorts of counter arguments. But what you can do on the flip sine, so you could alw al omost and say, like, hay, there's no point in doing the test, or iming to do this test, but i'm not going to be sure if it's right. That's how i look at it. How look at it is this test was focused on learning very specific goals? Do i feel like learn these goals? And how much do i feel like i learn these goals? And how much can i rip apart what i've already done? And in that nuance, in the nuance of how much, not whether, but how much, i can then start to assess whether or not i'm happy with the sa, with the learnings that i got from this test, or not. And absolutely, to your second part of your question, the question was, are there times where you've done a tess and then you ended wrong? More often it's that i didn't do the test in the first place. It's the things that i forgot. But there are times where i've done tests and they've been incorrect. I mean, an example was my, my second company was a food delivery company where we built a sort of non demand restaurant. We were testing our product at a certain price point. We didn't realize that we just simply could not sell it at 15 dollars, and we needed to make it 18 to 20 dollars. So a lot of our test on costs ended at being wrong. We thought we could hit a certain price pont t was really difficult, more difficult than we expected. So we learn the hard way that even if you do the tests, you can still be wrong. And honestly, you just kind of have to live with the reality that no matter what, you're going to get to a point where you like, i can't test this any further. And honestly, if you get to the point where you can't test it any further, you poly test it weigh too much. In reality, you probably want to test it just enough to feel confident, to know the assumptions, and then you need to go do it. And as you're doing it, you have to remember your risky assumptions and watch the market respond to your product and say, oh, actually, that risky assumption wasn't that big of a deal. You know, it may ve een one big thing, as an example, that wasn't a big deal. A lot of people thoght it as going to be hard for creators to become good instructors. Turns out we don't worry about that at all. To day, most our creators have super good reviews from their students on their courses. The coor base course form out is good enough, and our teaching of how to teach a good coer base course is good enough that most courses are getting high reviews but the problem that we did identify that is hard is creators were going to have trouble understanding the ry. Of course, creation, the ri has been, in our minds, very clear. So we've been right about the r i, but it's been much harder than we expected to convince r s to sort of stick with it through two to four cohorts to get to the point where the system works and it runs itself and it becomes a big revenue generator for them. That's been something that's been more difficult. So we've done tests on those things. We pitched instructors, we got them on. We did first courses. But you just learn over time a lot more than you can learn always in your tasks. We want to do tests enough to understand, hey, is this worth the next years of my life to go and figure it out? Then you spend the next two years, and you ask yourself, are we at a point where i can spend the next two years of my life and figure it out? And you're just sort of gradually getting closer to the point where at some point you're like, oh, this actually worked. Great. Brilliant.