So David, you're one of the top partners at Flagship, where you were for 18 years, one of the top biotech funds. While you were there, you founded Seven Unicorns. Today you have your own fund, Averin, $450 million AUM. Why is now a difficult time to invest in biotech? So I think there's two different topics. One is biotech and one is life sciences. And on one hand, I think this is an amazing time to invest in life sciences. But the world around biotech has completely changed. But first, what do we think about when we talk about biotech? biotech is really developing drugs. And whether that's small molecules or proteins or cell therapies or gene therapies, all of that tends to get bundled up together in what we think about as biotech. And there's a set of things that have happened. One, of course, the cost of developing drugs has continued to rise. I think obviously AI has offered some insights into how that might change, but it's not systematic yet. But what we're starting to see is very severe pricing pressures. We hear it in the headlines all the time. Of course, it goes back to the inflation reduction act. What the IRA did, is it put in place mandatory negotiations on pricing for the most revenue generating drugs? Look, that's great for patients because it helps to get better access to really, really interesting drugs at lower prices. But on the other end of it, there's the developers. Now, we've also been hearing under this administration, under the Trump administration, around MFN or most favored nation pricing. And the net of this is the total potential revenue of drugs is threatened. So you could look at the IRA and you would say, okay, you take that in place, that probably leads to about a 30% NPV hit for drugs. You could argue it's maybe a little less, maybe it's a little bit more. It's a lot more if you take into account small molecules, which get a shorter timeline to negotiation under the IRA. And by the way, since the IRA investment in small molecules has gone down something like 70%, they said it wouldn't stop new drug starts. We're already seeing some really interesting data about what's happening there. But here's the thing that's happened on the other end, which is, well, the potential upside has been decreasing, right? The average price of a non-small molecule company has gone up dramatically. and interestingly we went from in 24 i think it was about 60 billion dollars of m&a transactions to in 25 140 billion in transactions on the same number the average value of transaction has gone up and so what does all of this mean well it means that the price is up but the ceiling is coming down and from my perspective knowing that you're going to be in a drug discovery and development company for five ten years and we know what that's going to do relative to the long-term value it's really hard to say, hey, look, we see this acute change right now, which is the support basis, which is how people argue for it. But really, we have a higher floor and a lower ceiling, which means a lower multiple. And so from my perspective, as much as I think developing drugs for debilitating diseases is perhaps one of the most important callings out there, the return profile that it has is just continuing to decay. 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Learn more at alpha-sense.com slash how I invest. said another way, you obviously want to get drug prices down, make it more accessible. But pharmaceutical companies were vilified as these villains trying to maximize profits and look at how much padding there is there. They're going to continue to develop. In reality, small molecules have gone down 70%. Two thirds of the over two thirds of the drug development has actually gone down. So obviously that hurts in terms of developing new cures. One of the few things that Republicans and Democrats agree on is that drug pricing should come down. And that means whoever's president next is probably going to be continuing in the same direction. And what we need to figure out is a better model to foster the innovation that helps to save lives. Because it's a part of the capital markets, it also, it doesn't even matter if you have these really passionate scientists that want to cure diseases, they still need to raise funding. If they can't raise funding, they're not able to. And then this gets to the core question of it, which is, if I have a choice to invest in, I don't know, sending rockets to the moon or a market where I know the ceiling is getting progressively compressed, even though I believe in the mission, there's no friction to make the choice of sending rockets. Are large pharmaceutical companies, have their multiples also compressed or has this only affected smaller molecule? It's affected some pharmas more than others. Of course, if you look at what's happened over the last couple of years, Lily has been a darling stock on the back of Trisepetide, its GLP-1, this weight loss drug. But at the same time, if you look at Novo, its competitor, its earnings ratio is probably one of the lowest out there in pharma, despite the fact that it started as MPEC. Why is that? They basically started to lose the GLP-1 war. Lilly has been doing a really good job of winning that one. And I think Novo would concede that. And I think the other bit of it is that Novo hasn't done a great job of building a pipeline behind it. And I think that's a really important thing where the market is probably punishing them disproportionately, in my opinion, for not being able to say, hey, here's what's next and what comes after that. And how does China play into all this? China is a massive game changer. So I think the statistic I saw is that about 60% of new drug starts came from China last year. It's about 30% of new starts all in at this point. And when you look at what's happening is China is creating these new drug starts. They're doing it faster, cheaper. They're doing it in very large numbers and they're transacting them. So I think the statistic that I saw was in 24, the total deal value of all of the assets sold from China, the total contract value was more than the value of EVs, electric vehicles being sold by China. And I think that's just an unappreciated trend that China is becoming, if you will, the primary producer of drugs. What are the second order effects of that? How does that affect the U.S. economy? It puts a lot of pressure on early stage drug discovery and development, which means... Downwards pressure? Downwards pressure, which means we got... Now you have to compete on price versus China. Good news. I think that drives you to AI, companies like Valo Health and whatnot. I don't think the uptake there has been nearly as fast as it could be. And I think China forces AI to become a major path for competition. I think it also raises the possibility, and this is something we believe very strongly in, that the business model will actually need to change. And that we actually have to think about what is it to draw the entirety of that curve of drug discovery and development and where are the right places for innovators and incumbents to ultimately play And how can we actually accelerate innovation in the broadest context of that We actually recently started a new company specifically in that space, which we can talk about more. But just getting to your question, we've seen this trend over and over with China, which is where they spend years learning how to do what we do, and then they do it better. And that's what they're doing here. And when we look at Boston, for example, drug discovery and development is a pretty important part of the economy. So what does it mean when chemists are going to have fewer and fewer jobs over time? It's not going to be next year, but at some point, if we see the shift continuing to go, it'll happen at some point. So you recently closed on your Fund One, an impressive Fund One, given the market today and given the venture market, and you're focused on the transformation of healthcare through technology. Tell me about your thesis. Tech transformation of health is perhaps the single most important trend over the next decade or several decades even. And the way we think about it is health in the U.S. is about a $5 trillion market. There's many facets to it, right? There's not just drugs, there's also hospitals or services, there's administration of care, there's a bunch of different layers. And our view is that whole field is going to change. It's already changing. And it's changing much faster than people appreciate. There's forces on like AI decentralization, meaning the shift away from the hospital as your notice of care, consumer taking more interest in their own health, whether it's longevity or other things, automation, robotics, et cetera. And all of these are really important drivers that are leading to effectively step function changes about not only how health is administered, how care is administered, but what we as individuals can expect from that care. And the exciting part of it is that humans can start seeing benefits from these very, very quickly because some of these products are coming to market exceptionally quickly and allowing people to take control of their own health destiny. And the big distinction there, it's not biotech because you're not developing pharmaceuticals and molecules. You're focusing on healthcare as an industry. Some people like to call it tech bio. Some people like to call it digital health. Some people like to call it tech transformation of health. Okay, maybe some people in that last case is me. When it comes to AI, specifically in healthcare, what's in the near term and what's in the long term in terms of how AI is going to disrupt healthcare? Let me give you a couple quick examples. I think that you have to think about AI in a couple of different levels. One, we all know AI is moving exceptionally quickly. And things that we thought were moats even two years ago just are not moats. So when we think about AI in healthcare, we think about AI in the context of durable businesses and how you can otherwise fundamentally change those durable businesses. What AI does is it allows us to do things that even frankly today people tell you are impossible. Let me give you an example. So one of the companies we invested in is a company called Hologen. This is a company that has exclusive access to data, the second largest pharma-associated GPU cluster in Europe, and they develop what are called super covariance. So that's sort of a fancy term for saying ways where they can design clinical studies with certain features so they can know that if it's successful, it's truly successful. Or reduce type 1 error, as it's otherwise said. And what they've done is they've been able to bring in a first-line Parkinson's asset that's phase 3 ready. They've gone to the FDA using their AI approach. And the AI has agreed that they can theoretically get it approved on just one clinical study where often in this case it would have required two. And that's really interesting on a bunch of different levels, which is, one, that could cut two and a half years out of development. Perella Weinberg says it's about a million dollars a day of NPV value that you create for every day you save in clinical studies. So math's pretty easy right there. But two, if you could start doing that more generally, the cost of clinical development goes down. This is the way that you fight the NPV issue that we were talking about earlier. And these sorts of technologies become a real game changer. I think they're only the second company ever to have the FDA allow for a trial to have been displaced by a clinical study, the first being Valo. And that's very exciting from my standpoint because again, it opens up a new frontier. Valo is your previous company. Correct. I'll click a little bit more on Hologen, how it works and what exactly it's doing. What they do is they have exclusive access to longitudinal patient data. What that really means is they see what patients look like over a period of time. And they have a whole set of different things about these patients, which can be genomes or proteomes. It can be just going in and getting your blood pressure checked. It can be diagnoses. It can be the medications that they take. Well, that might sound uninteresting when you go in for a single doctor's visit. If you look at a patient over 20 years, you see a journey. And, you know, it's hard for even a physician. This is no disrespect to physicians. It's just humans aren't designed for massive long-term detail retention with many, many, many, many parallel threads. They're designed to do analytics that are more short-term, recency biased, et cetera. And so if you take millions of patients where you have decades of history, you start to see patterns that a human mind can't. And so, for example, what you can start understanding is a disease that we characterize, for example, in the 1900s, early 1900s, because these are the things that a physician happened to see actually has a whole range of subsets. You can start to understand what those subsets are. You can also understand by analyzing clinical trial data where a drug seems to be more effective, what kinds of patients. You can stitch those two together. And without having to limit to the buzzword that people talk about as a biomarker, you can actually figure out how to design your study to make sure you're getting the right drug to the right patient at the right time in the course of disease to be able to have the best effect. And at the end of the day, that's really what doctors and patients want. People assume that you do a study and the drug either works or not, let's say on Parkinson's, but on Parkinson's it might work for a certain type of patient, not for another. And if you test on the wrong type of patient, then you'll get this false negative. That's exactly it. And this is one of those things where it's been hard in the past to make sure you're getting the right drug in the right patient. And more importantly, frankly, at the right time. Because when you think about Parkinson's, we probably all know someone who's gone from the early stages into the later stages. In the early stages, you might see a hand tremor, a shaking of the hand, and people just say, oh, I'm getting older or something along those lines. And they don't realize that they have Parkinson's. I don't mean that as any fault to anyone. But the earlier you are in Parkinson's, just like in cancer, just like in other conditions, the easier it is to have a durable intervention. And this becomes that nuance of finding those patients who might be progressed enough to be able to diagnose pragmatically, practically, but where we can also see a really important and impactful clinical difference. Is there a derivative or call it mimetic aspect to this where if you prove Parkinson's works for a small subset of the population, now other drug developers are looking at that and look at the data, figure out other types of populations. You kind of give hope to the industry. Is there an aspect to that or is it purely everyone's kind of thinking from first principles on different diseases and what has the highest MPV? It's been a first principles type of industry. And what you find is that the best chief medical officers of the best pharmas have really good intuition of what the most important variables are for designing clinical studies. And they're really good at it. They just are really good at it. But drugs are nuanced. They're complicated. We like to oversimplify of saying this drug does this one thing. That's not the way drugs work. Drugs have their on target, which is that one sentence, but then they have many, many off targets. And we call those side effects, but sometimes the side effect becomes the drug. And sometimes it's positive. Exactly. Like GLP-1s, they were created to suppress appetite and then they had these other longevity benefits. That's exactly it. And whether they're derivative, whether they're related, whether they're unrelated, in a way it doesn't matter. because the notion that a GLP-1 can cause you to lose weight, it can also cause you to reverse your type 2 diabetes, it can also cause you to lose liver fat, it can also help you to reduce the likely incidence of Alzheimer according to some studies at least I mean you could argue all of those are connected but at some level all that pretty profound Something like 70 of diseases have obesity as a covariant Absolutely. If you just get rid of obesity, it's like basically knocks almost two-thirds of things. And that's part of what makes these drugs so powerful. Biohacking itself has become almost a strife term and people are doing, teenagers are doing in their basements, but you're really cutting edge in terms of biohacking longevity. What's the frontier look like for longevity in the next five to 10 years? Good news. I think people are getting this general recognition that you got to take care of the basics, right? Eat well, sleep well, exercise. Don't smoke, don't drink. I think some of us don't want to acknowledge that those are the real things that you need to do. But when you put those five things out there, you're solving a good chunk of the initial issues outright. But then it becomes this question of how do we learn and how do we improve, right? So on one hand, we could talk about things that we choose to put in our body, whether they be supplements or drugs or other things. And on the other hand, it's what I think people like to call measured self or wearables. And that's a really interesting space, right? Because you have what I like to call the minimally invasive, minimally informative, like the aura ring. And what I mean by that is, you know, look, I wear an aura ring, so I'm not going to knock it. but if I have a bad night of sleep, I wake up, I look at my aura and it tells me, you slept poorly last night. Thank you for telling me that. But well, that part, you know, being obviously a little facetious about it, you start to learn trends and behaviors about yourself if you want to, and that allows you to intervene. But you only learn so much. And so as we start thinking about the next generation and the next generation, you know, for example, we have a company in our portfolio called BioLink where they have a new form factor of a sensor, almost a patch where they use microneedles that measure what's in your interstitial fluid. And that can allow you to measure things like glucose, same as a CGM, but it can also be used to measure things like lactate and cortisol and ketones and hormones and beyond. And now you start to get this really interesting insight to this is what my biology looks like. So I made these changes in my life. This happened and now I can actually act on it. And so now you start to get insights of, hey, this is my biology. This is what I'm actually doing inside my body. I think this is going to be a really interesting frontier we have. It's subtle, but there's something very powerful about actually getting data on yourself and seeing it almost on an app or on a dashboard. Because you might think, well, you know, I should be more healthier. But a lot of the advice is general advice. But when you see it displayed for yourself, it's much more powerful. That's it. And we all assume we're doing better than we are. It's just a human nature thing where you change one meal. Like the Wabaghan effect. Exactly. And you just assume all of a sudden all your meals are clean. Then you start calculating the number of times that I went to go and get a snack. You know, how many M&Ms did I maybe, you know, pick up? Or maybe it doesn't happen to be an M&M, maybe it's something else. And you start realizing we're not as good as we thought we were. I started double clicking on biohacking and or longevity. And one of the things that all the both experts and non-experts in the field say, sleep is like the number one thing. if you could figure out sleep. And then I started double clicking on what does it mean to have good sleep? And it's REM sleep. And I started taking supplements around that. Is REM sleep an important metric or is it just a noise? It feels to me we're still early days in sleep. I mean, you know, when I look at something and I measure a bunch of things in my sleep, you know, there's the, what do they call it? Like deep sleep, REM sleep, light sleep, and awake. And of course, I think the deep sleep and the REM sleep are really important. There's gotta be some other things too, right? because you compare two days where you might have had your hour and a half or so of deep sleep and call it your hour and a half, two hours of REM sleep, and you just feel totally different. And the question is, what is that? Now, do I expect a be all and end all answer for where we are today? No, I just think we have, we're going to, we're going to have to learn a lot more. This is also getting into the individual. The problem when you say the individual, everyone's like, oh no, I need less sleep. Problem is probably not. We're much more alike than we are different. Exactly. And so I think there's a huge frontier there. I think it's great when people make an effort. I've been making an effort. It's hard to make an effort. But I still think there's gonna be a ton more to learn about sleep. And one of my favorite things that I hear every now and then in the entrepreneurial ecosystem is people who say they have a pill that gives you the equivalent biological effect of an hour and a half of deep sleep. Because I think that's the magic we're all looking for. That would be a good one. So from sleep to sleepless, you raised a fund and an impressive amount of capital for a first fund in one of the most difficult venture markets, probably since 2001. Give me some strategies that you use in order to raise this fund in this difficult market. I just take a general view that we made the best view of how we can generate absolute multiples on invested capital. And that relates anything to fund size, to a specialist focus, to how you architect the team, to what you look to invest in, to designing your hold, period. Just to put some numbers to that, the Swenson model, which was created in the 80s, back then you were getting about 24% DPI from private funds. And Alex Ambrose from Allocator Training Institute, he gave me the official numbers. 2024 was 9%, 2025 was again, roughly 9%. They're finalizing it right now. So essentially two and a half times less liquidity. So obviously the model breaks. If the model is built on 24%, it doesn't mean that the Swenson model was wrong. It was just a different market. And you can't use the same model based on different markets. That's exactly right. One of the rants I typically have on the podcast is about these labels that certain asset classes get. So lower middle market is good, buyout is bad, and these subsectors. But really, the subsectors are supply and demand, driven by supply and demand. I think one of the most interesting things about how you've built your fund is it's not just where am I interested in, where the opportunities, but also where is the supply and demand of capital imbalanced? Talk to me about that and how does that drive your strategy? There's a bunch of different dynamics that are going on. But one of the things that we've seen, for example, is that capital in life sciences broadly, or as we where we like to focus, tech transformation of health has generally bifurcated. There's a lot of capital in the very early stages. And there's a lot of capital in the very late stages. I mean, we've seen these mega funds on both sides. And what's happened, and frankly, it's exacerbated by all of these mega IPOs, which sort of generally take capital out of the system as a whole for everyone else. whether it's the chat GPTs or the open AI or Anthropic or SpaceX or whatever, whatever they happen to be at the time. And what it tends to mean is that the middle phase of these companies, sort of the classic series C, D, E is undercapitalized. And what's interesting about that is you get great companies who just get stuck having a very, very hard time raising money. and it's interesting because what you'll find is, look, great entrepreneurs will figure out what to do. We have a company in our portfolio called Freeno and they recently signed up to do a SPAC pipe and go public with Perceptive. And it's great because in a difficult market, you take a company that's moving forward to the late stage and they find that capital. But the thing that's happened is this has become an area that's underweight in capital. If you just think about simple supply demand, if there's not a lot of investors in the space, prices are going to be lower. It just happens to be the dynamic. And so the way I think about these sorts of things is the investor has, you could view it as an opportunity where you can play where other people are or not. And that allows you to get access to better deals. It allows you to become closer with CEOs. But also if you're getting great companies later on in their life cycle, you have a nearer path to liquid it. The problem is that these narratives are mimetic. Like if everybody else is going around saying the opportunities are in the lower and upper market, yes, and when you raise the capital, you could deploy and there's alpha there, but the fundraising becomes the bottleneck. That's absolutely the case. And I think often what happens, and we heard this, for example, on the road, which is, oh why don you prove this model out for five years and then we invest And the problem is in five years since nature abhors the vacuum it not going to be there And so one of the things that I always thought about is look either investors want to be your partner or they don And I don want to be sort of overly simplistic about it. But if you have a strategy and you stick with your strategy and you're firm with your strategy, people will either support it or they won't. And if they don't want to support it, I mean, you shouldn't form that partnership. But if they do, then the question is, how do you get people comfortable with what you're doing? And I think that's one of the things that we try to think a lot about, which is we pick our strategy, we're dead focused on it, and we're going to execute the best we can. The former CIO of CalPERS, Dr. Russell Reed, I think you've met him before. And one of the things I asked him straight up, what percentage of the market is beta investors versus alpha investors? He said basically more than 95% of the institutional market is beta investors. So a lot of people intuitively think, well, I'm coming out with this alpha story of here's where the risk adjusted return, you really only could message that to 5% of the market. Exactly right. Which is people don't want to take the, they don't want to take risk on a different strategy inherently, right? And it's a challenge, right? Because paraphrasing Steve Schwartzman, right? You get alpha by doing what other people don't do. And the issue on that is if other people aren't doing it, it's not proven. So how do you get someone to feel comfortable taking that risk? and part of it, what we try to do is make sure people understand what we're doing, why we think we have a different angle on the market and why we think we're going to get disproportionate returns as a result of it. David, you've had a lot of impressive accolades, including if not the fastest, one of the fastest dual PhDs from MIT and Harvard, I think you did in five years or so. You then went on to have this prolific career at Flagship and you started Valo Health, incredible company, and now you started this fund. given all that, you still probably made some mistakes in Fund One in this market. What are some of the mistakes and or learnings from fundraising this kind of market? Mistakes are probably one of my favorite things to think about. So, you know, I reflect a little bit on sort of what we chose to do, which is there was probably an easier path that we could have chosen to go. But I remain to this day convinced that we made the right choice by not going on that easier path and picking the strategy that we did that was not going back to this alpha versus beta harder on the way in but actually better strategy I'm going to answer a slightly different version of the question which is if I go back to my time doing my MD PhD at Harvard and MIT I'd say one of the things I did not appreciate then as much as I appreciate now and it's partly because in academia academia is sort of about individual performance it's not about team performance at some level The importance of teams is you just can't say enough about it. And I think one of the things we tried to do really, really well was hire an amazing team. You know, bringing on people like Jeffrey Lowe, formerly of Indreason and Novo, and Tristan Hunt, formerly of BCG and Roy Vance, and Tomer Zatelny from Citi, Alex Lau from OpenView, Ben Tomaszewski. I mean, it's a great team that we have. And I think the ability to form and function as a team is incredibly important. What are some learnings from that? One of the things that you start thinking about early in your career, for example, is speed is more important than durability. I heard something earlier today. It was actually very entertaining about someone who's about to join a Y Combin or Light program. But instead of you going in with your idea and your partners, they match you to partners. And then you guys have to come up with ideas. And I'm like, well, that sounds a little bit like a reality TV show. But my first instinct when I heard that is, well, what happens when you have your first fight? because teams are easy to think about when things are going well, but in every company, there's part of the journey where things are difficult. And I think the real quality of a team emerges when things didn't go as expected. And you can start locking arms and saying, how do we solve these problems together? And I think that's where this teaming becomes so important. It's so easy to talk about, but getting in the trenches and finding people that you can solve problems with and big problems with, it's hard. And you need to form that trust. You need to form deep bonds. It's very hard to interview for it, frankly. but building off relationships that you've had for 10 years, I think it's incredibly powerful. You almost need to have a fight in the interview. Exactly, exactly. That'd be a great way to stage it. Speaking of team dynamics, you started your fund with Eric Berry, your brother. He is incredible in his own rights. I think he raised something like 17 million, sold for just under one and a half billion, one of the most efficiently run business. Tripleift, one of the most efficient companies I've heard about. What was it like working with your brother? So if you went out and you form a fund with some person that you might've sat on a couple of boards with, you know you might have gone through a board level hard time but at some level board members aren't really the accountable party it's the ceo right you might be accountable on behalf of your fund but you're not accountable at the end of the day it's the ceo's again and so maybe you got to know them maybe you became friends but if you have a real disagreement how's it going to go the great thing about working with your brother i mean i've known him all his life right i mean we've had arguments we know how they resolve and the great news is we're not going to break up a partnership over a disagreement whereas two random people might just say ah it's too hard the familial bond especially now you guys have both had a couple exits is stronger than the fund and the combination of having that bond and the fact that we both had our careers i think actually makes it very very powerful for us the other thing that's really useful for it is we have very different views on a lot of different things i think bringing those completely polar opposite framings is powerful because it allows us to think about, for example, an investment, a company, a growth pattern in very different ways. I was going to actually double click on that. You guys are so different. Similarly to me and Curtis, my business partner is we're so different in terms of complementary, but our values are aligned. I think we went 13 months without any single like disagreement. It was like eerie. I'm like, this is not healthy. And then finally, we had like a half disagreement. Talk to me about that. Like what's that? Because the canonical advice is co-found something with somebody that has complementary skill sets, but it could become really difficult if they're literally complementary to you. Your values may be very misaligned. Yeah. Well, the good news is our values aren't disaligned and I agree with them. But there's a subtlety there. Exactly. And I think your values have to be aligned, but the complementary skills is really is really useful. Eric shorthanded this to someone once and he said, I, meaning Eric, am like your fixed income and David is like your triple lever DTF. And, you know, what's great about it is part of what he's getting at is Eric is such a deeply experienced operator. I mean, if you think about building a company from 16 odd million dollars in venture capital to 300 million in revenue, right? You're doing well over 100 in EBITDA. You are hyper-focused on executing almost as well as anyone out there. And that is a skill set that's very rare to find. And from where I come from, being in the venture capital world, it's sort of how do you think about asymmetric value creation? How do you think about those rare events that can create massive upside? Those are totally different activities. But frankly, in every single company, you want both of them. And one of the things that we require for us is we want to make sure every single member of the team is on board with our investments. It doesn't mean that things are unanimous. It just means that we want to make sure everyone's on board. If Eric's seeing something that looks good and I'm seeing something that looks good, it means that we're seeing from our various perspectives really interesting upside in the form of that perspective investment. And I say that because that complementary skill set means, for example, if I say, hey, Eric, what do you think about A, B, and C? I know he's going to do his deep work in that space. and if he says to me, hey, these guys need an injection of creativity, you know, I'll go off and do something and he might regret what I do, but that would be more in the sort of brotherly version. It's funny. It's gotten to a point for us where I get more excited when Curtis is excited than when I'm excited. When I'm excited, I'm like, okay, that's the fault. That just doesn't mean anything. When Curtis is excited, holy crap. Exactly. Like I wake up excited. It's just sort of one of those things. On that note, thank you, David, for coming by and congrats on all the success. Well, thank you. 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