Investing Billions - E279: Why Size Becomes the Enemy of Venture Returns w/Logan Allin

Episode Date: January 9, 2026

Why does venture capital break when liquidity disappears and what actually creates alpha when markets get hard? In this episode, I talk with Logan Allin, Founder and Managing Partner of Fin Capital, about why private markets are structurally changing, how secondaries are becoming a primary liquidity mechanism, and why discipline — not optimism — is what separates enduring managers from zombies. Logan explains how Fin Capital built a full-lifecycle platform across venture and late-stage secondaries, why fund size is the enemy of performance, and how contrarian positioning creates real structural alpha over time.

So Alan Zaffron, founder and managing partner of IEQ Capital, said that roughly half of managers are on their last fund without ever knowing about it. They're not aware of that. I want to get into that. But first, just as a level said, tell me about where Fin Capital is today from an AUM and size standpoint. So public information, we manage over $1.5 billion in assets. We have about 130 portfolio companies and 25 team members. about 17 of those are investment professionals. We continue to exclusively focus on enterprise software for the financial services industry,

full lifecycle from pre-C to pre-IPO. And you started as a solo GP. I did. Yeah. So I started a solo in June of 2018, raised my first two funds, our VC flagship product, and then a growth in late stage focus product. And I didn't plan to be solo. But it took really a couple of years to start hiring because I ran,

right into COVID. And that made it very difficult to have in-depth conversations and relationship building and so forth to make those initial hires. But we got those done at the end of 2020 and now we're 25 people. A lot of LPs, even GPs privately tell me they don't really know what's going on in the venture market today. What makes this market different than any other market? I think the lack of liquidity is a real problem. This asset class kind of breaks down when you don't have that virtuous circle. And that has made our lives a lot more challenging in raising capital and educating on the asset class. Ventures, we all know, has significant power law return dynamics. It's long duration. Typical venture funds are a minimum of 10 years. Some of them

are extending to 15 plus years. And now you have continuity vehicles and other structures that are making that problem even more challenging. And companies are staying private for longer. It's been an emerging trend for a number of years. I don't see that changing anytime soon, if ever, because the availability of capital in the private market, to sustain growth and in some cases finance burn or to support very profitable businesses pre-IPO in M&A or to bridge to that IPO and do cap table cleanup and so forth is inevitable now. And so the secondaries market, a huge amount of dry powder, circa 200 billion on the sidelines to support that trend line. And look, the returns in TMT have been coming from private markets. And that

actually started in 2004 with Google. So if you look at it, at every IPO since Google's. That was 2004, for those that you remember, the private market investors have made more than the public market investors on a multiple basis, maybe not on a cash on cash basis. So the returns have been flying from the public side to the private side. What are the second order effects of that? Let's just assume that I agree that companies are going to continue staying private longer. What are the second order effects? Well, you have more early stage VCs using secondaries as their exit, right? And that shouldn't be something that is problematic. That should be something that's thoughtful from a risk management perspective and harvesting gains and creating that risk

buffer that you want to see within portfolio management. So if you're a pre-seed seed investor, which we certainly are out of our venture fund, and you're investing in an average valuation of $20 million to $50 million, if a company reaches $2 to $5 billion, you should be taking money off the table, right? That's just thoughtful risk management. And obviously that creates that flywheel circle that we're looking to get in terms of returning capital to LPs. And so I think the second aspect to that is that we have a fund that exclusively focuses on late stage pre-IPO secondaries where we're seeing a significant amount of bid-ass spread, meaning we're seeing discounts there at meaningful levels, particularly right now because those assets were priced between

2018 to 2021, and you're seeing a willingness to take a discount in some cases as high as 50%. And those are typically precedency investors who are either using the secondary as the exit as described or they're in their extension periods. And the death now for a VC is you actually distribute private stock to your LPs. That is an absolute no-no. And so we need solution providers like ourselves that can provide liquidity to those GPs who have done their job, right? They sourced the right company that was generational. They rode that way for 10 plus years. Now it's time to take liquidity off the table either in whole or in part.

And then the second group that we end up supporting from a liquidity perspective is former employees, right? That could be former founders that are out of the business, that pass the baton, or former employees who might have options exercise issues where they're expiring and they need to get liquidity. So we think the late stage pre-IPO secondary market is the most inefficient market in private markets broadly and the most attractive from an alpha perspective. And that's because most of the institutional capital are actually buying portfolios, not individual companies. Yeah, so if you think about where secondaries came from as a terminology, it was really the GPL-LP-led, so meaning you're buying portfolios from GPs or LPs, mostly LPs, right, because they're sitting on multiple managers, multiple fund vintages. They need liquidity if it's not coming from the traditional ways, and they want to redeploy that into either private equity or other asset classes. And that's become even more significant right now. You saw Yale sell $5 billion of their portfolio.

City of New York here, sell $5 billion of their portfolio. The challenge with that space is it's become more and more efficient and more competitive. What do I mean by that? Well, effectively, a banker runs a process. The LP says, I want to sell X number of portfolios, X number of positions, and I want you to go run that process for me. The banker goes out and they say, hey, secondary buyers, you've got two weeks. We're opening up the data room.

we have 50 managers. There's thousands of positions. The closest to NAV wins, closest to the PIN wins, right? Good luck. And what do you think happens? They all get closest to the PIN, right? So New York publicly came out and said, we're going to sell $5 billion of assets. They ran a process. Guess how many, guess how much assets they sold? Five billion. And so that's the issue that we see. And so there's a lot of folks that have, I think, viewed that opportunity as more beta, more credit-like, and the net moikes there are going to be much less attractive. Maybe you get to teens, net IRAs, right? But those durations of those funds are still 10 plus years. Why? Because they're typically buying out a mix of duration. They're buying out early-stage venture all the way through to more mature portfolios. And that ends up being very challenging to manage on a liquidity basis. How do you go about diligenting these late-stage pre-IP opportunities? The market or the legacy market is people going these secondary platforms, retail primarily and buying, you know,

they're kind of like they're going shopping for Christmas. They're buying their favorite brands. Right. I'm guessing you don't do that. How do you actually get real information when you're making those secondary trade? Yeah, I think the biggest challenge you hit on is those can be very opaque markets.

And if you don't have a high degree of information, you're going to make mistakes on the pricing and the fair value assessment of those shares. across the capitalization structure. It is a lot of work, which means it's highly inefficient. It requires a significant amount of expertise, and you have to do your work on the valuation side, and that requires information from the company.

So there's a couple of ways you can manage that. One is existing positions, right? Because we're full life cycle, we're typically underwriting companies, we're already in, where we do have complete information. We might even be on the board of that business. And the company knows, before they go public, and we're always underwriting to an IPO,

certainly there's some dual track opportunity there, but the company needs to be within two years of going public for us to get excited and do our underwriting, needs to be profitable. Needs to be growing, though, still at 20 to 30 percent, which means that if you look at all-time IPO outcomes, the top decile of IPOs were 20 to 30 percent growers. So we're really looking for the crem de la creme and the pre-IPO markets,

and then we're taking out, again, those pre-seed seed investors or former founders and employees, and we're pricing the entire waterfall. Now, we might run a tender process that's available to the entire cap table, or we do something more surgical. We're only buying out select investors, which is typically the case. Because most people want to continue forward if they know there's an IPO coming, they want to maximize the outcome they're going to hold.

But for a lot of folks on that cap table, they actually don't have that choice. We'll typically get our own team to do that valuation work, but we'll also bring in third-party opinion to provide that to the board and the management team to say, hey, much like a 401A valuation, this is how we're looking at the capitalization structure. And if you're doing the math on that, you're effectively looking at, okay, what is the discount I'm receiving relative to where these shares sit in the overall waterfall relative to any debt that sits on top and any structure that sits in the waterfall? And you've got to do that math and have a really strong margin of safety to ensure that you're going to drive or turn that. Going back to Allen's statement, half of funds don't know that they're on their last fund. First of all, how is that possible? And second of all, why is that happening?

So Alan was interviewed and quoted in the FT. He runs EQT partners, which is obviously a massive platform. I think his perspective is similar to what I'm seeing in the market, which is there's going to be a lot of consolidation. There are a lot of managers that haven't been able to produce Alpha. Frankly, they've probably pivoted more to asset gathering versus Alpha generation, which we think is highly problematic. And I think the view is that because the competition is increasing for the best deals and for capital, it is a winner-take-most business. And that's challenging if you're out fundraising as an emerging manager because LPs are then

basically defaulting to a flight to familiar. There was the old adage that you never get fired for hiring IBM or McKinsey or insert name brand name here. I think that's happening now in private markets with LP behaviors. And unfortunately, those LPs are actively seeking alpha because they have unfunded liabilities and they obviously are doing their asset allocation and their investment policy statements and aligning to private equity. But what they're actually getting is probably just market beta, unfortunately, in some cases. Now obviously there's managers in the top tier that are going to continue to produce alpha. But the larger their fund sizes get, the harder that is. You've seen some

debate now on X recently about can you get a 5x fund on a $5 billion vehicle? Maybe, but it's sure a hack a lot harder than if you size-constrained your funds. Kaufman Foundation came out with a report probably five, six years ago when I first started Finn that said every dollar in venture specifically, this doesn't apply to growth equity or late stage specific funds, but it certainly applies to funds that are multi-staged to a large degree. Every dollar you raise over 400 million has diminishing returns. And that that means that you have to size your constraint your funds to 400 million. That number could be 500 million like Benchmark has argued and not going to argue with Benchmark. They've done phenomenally well.

But it's definitely not a billion, right? And so if one of the best venture investors of all time in Benchmark and one of the longest dated LPs in the world in the Kauffman Foundation are telling us that you need to size constraint and size is the enemy of performance in this specific asset class, you should listen. There's this. meme in the marketplace that ventures almost two asset classes. You iterated this beta, essentially the large multi-stage funds, this alpha pre-seed and seed. I think one of the things that's really driving this perception is persistence. I had Professor Steve Kaplan from University to Chicago. He did a study where he found that 52% of top quartal funds persist. The problem

with that study, and it's not a problem with the actual study, it's that this was historical. Right. So taken to the extreme, if the fund size gets 10 times bigger, it's not prudent to assume that you're the same assumption. I think people are taking this persistence and just applying it to new fund size. I think that's logically not the right way to think about it. Agreed. And Kaplan's done a lot of the research that I referred to on fund size constraint as well. And certainly there's a lot of academics that have looked at this correlation math. And I think from our perspective, there's this really significant. tension happening with asset gathering and management fee generation versus return of DPI and alpha generation. And unfortunately, you can't have both. And so one of the ways to address that that I think you're starting to see is to have size-constrained venture funds that are thoughtful to that dynamic. And then adding a second fund as we did, which is focused either on growth equity or growth equity in late stage. In our case, exclusively late stage, we think the market is very

barbelled right now in terms of attractive and inefficient opportunities. And growth equity is the messy middle. And growth equity and funding burn, very high growers, but typically getting a ton of forward credit vis-a-vis their valuation on a present value basis. And sometimes they don't grow into that valuation as we saw. And so that's a falling knife potential dynamic that we're seeing, particularly in areas like AI and cyber right now that are getting massively inflated. And that gives us a lot of concern. And so to get out ahead of that, you've got to be pre-seed seed, maybe Series A investors and venture. And then you've got to look towards late stage pre-IPO secondaries where you can actually get to fair value because you're the one setting the price versus this massive competitive dynamic.

As we all know, pricing in private markets is driven by competition, not fundamentals. and that's going to perpetually create inefficiencies and mispricings in the market. I think it's one of those extremely obvious things that people don't think about in private markets is essentially a high level macro view. For example, retail, $150 trillion is expected to go into private markets. No one contests this figure or roughly that size, but people don't really think about the first and second order effects of that. They think that they're operating in this niche market and that's kind of impervious to supply and demand dynamics.

Why do you think that is? Well, I think retail is the new horizon for capital raising. And I think that's particularly problematic if venture is the positioned asset class. I don't think venture capital is the right asset class for retail. And that is because of the J-curve dynamics, the duration, and probably the misalignment that occurs. Because those GPs who are raising capital from retail are again gravitating towards that asset gatherer mindset. and they're trying to accumulate assets from where they can. And obviously retail now is maybe one of the last places,

last bastions that they can go for capital. And I think that herd mentality is ultimately going to hurt the retail investors. So I'm pretty concerned about bringing venture, particularly at the fund level and blindpool funds at that, to retail. If they want to play in private markets to your earlier comments, they have secondary players where we've seen a lot of consolidation recently. So why was Forge Global acquired by Schwab? and why are we seeing other secondary platforms on a directed basis getting acquired?

They want to give direct access to retail investors who, to your earlier comment, view it as brand exposure and they want to shop and buy positions in secondary. Let them take on that risk, right, with the right level of education and so forth around the asset. And there's obviously, I would have some concerns, as I did with Robin Hood early days, that there's not enough education embedded into the experience to say, hey, you should understand derivatives. You should understand what being long, only a short means. You should understand what a short squeeze is. And in our world, you should understand J-curves. You should understand

duration. So I do get a little concern about retail, both on the direct side and on the fun side. And to us, retail should be getting exposed to private markets, but it's probably through that late-stage orientation, either again on a direct basis or through fund exposure, because that is shorter duration. diversified, non-correlated to their public market risk and probably presents a better return opportunity. Yeah, there's a question of where should retail be investing and what's going to get them to invest in private markets? And sometimes what gets you there won't get you the next step. Agreed. And we saw this in crypto, right? Retail got heavily involved in crypto. A lot of things blew up in the wrong way. And that's unfortunate. And I think, you know, putting retail investors in front of things like NFTs, and cryptocurrencies that really don't have macro factors or drivers behind them,

very difficult to underwrite. It's highly speculative, highly momentum-oriented versus fundamentals. You're seeing now that corollary play out in private markets with the retail wave. Right before we were going to go on, you said, I believe Open AI is going to go to zero. Why do you believe so strongly in that? Yeah, it's a hot take, admittedly, but I'm very concerned about Open AI. I think that as a San Francisco, this is going to be challenging for our city. But there's a lot of problems with the way the business has been set up.

Obviously, initially as a nonprofit, now as a benefit corporation with a nonprofit on top, not a lot of presence for that type of business going public. And as Sam said publicly that he wants to take the company public. The unfunded liabilities on compute. And then the revenue mix coming almost entirely from consumers, right, a very small amount of the revenue, and this is public information. Open AI has talked about it very openly, having around 800 million customers, only of which about 5% are actually paying. And that means they're running a negative gross margin business. And they are also making commitments to compute

providers over time, as well as data center building projects. And Sam said publicly on a podcast recently with Brad Gersner that he's going to fund that through revenue. And even he had that his revenue was circa 13 billion or thereabouts, maybe give or take plus or minus 10%, like that is not enough revenue to finance trillions of dollars in future spend. And so our view is that if you are spending money on compute, you are then spending money on model training, e.g. content. And then you're also spending money on lawsuits from content providers who are suing you for taking their content to train your historical models. That's a real problem. And then the last thing I'll

mention is the minute they come out with a new model, the spend that they just put it to put to work in that past model and the models before it is all deprecated, meaning it's all useless. That was just a sunk cost. That's a big sunk cost. And so those add up and I get very concerned that the business ultimately ends up in the hands of Microsoft. And so, you know, I made this call in 22 and again in 23 in public forums. And I'm very concerned that they have built a bridge to nowhere, unfortunately. And you're his next door neighbor? He lives in my neighborhood, yes.

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slash invest free and start building something amazing. Get more with Northwest Registered Agent at www.northwestregisteredagent.com slash invest break. So if you don't read Howard Mark's letters, highly encourage you to do that, dating back to inception. Howard's more of a credit investor, as I think we all know. But what he writes about very much applies to equity markets and the broader macro. And he talks about in these very significant periods of exuberance around specific sectors,

that there are mispricings and mistakes. And if you can find those and take a contrarian view, but be right, that is where you generate alpha. And so we as a firm look for pockets of the market that are highly inefficient from a pricing and access perspective and require a lot of work because others aren't willing to do that work, frankly, to access those opportunities. and that's where we found the opportunity to generate outsize returns with risk buffer. And I think that is how Howard writes and thinks. I haven't had the pleasure of meeting him. He won't know me from Adam, but I'm a big follower of his work.

And I think those comments and certainly his advice to market participants are now more weighty than ever. That's a big part of it, which is how do you operationalize that? How do you know that you have structural alpha? And the answer is you have to do something other people don't want to do. There's also another study that the further way the portfolio companies are or in second-tier cities, those investments tend to do well because not everybody's bidding them up. Everybody wants a San Francisco one in their neighborhood that they just have to jump on a bike and ride over. That's right. Yeah. Howard calls it second-order thinking, which is how do you look at what's happening in the market,

avoid herd mentality, and go the opposite direction. So, for example, in 20, 2021, we raised capital, and I went to our LPs and I said, we don't really want to deploy the capital that we just raised from you. And that was from the perspective that we were seeing the ZERP area behavior that was nonsensical to us. And we felt like putting capital to work in that environment was going to be antithetical to long-term returns. And so we actually went in the opposite direction. We raised a pre-seed seed fund. We ended up raising two of those funds and putting those to work over the course of 21 and into 22 at very low average valuations. And that turned out to be prescient because we saw what happened as the ZERP trend started to unwind and rates

started to come back up. And now we have this funnel of companies that are maturing through that we can invest in in subsequent rounds and really use that funnel to go from pre-seed through to early stage through to late stage opportunities. And so I think that is critical. important and encourage all GPs just to see the forest for the trees when everybody is chasing a trend. And we've been very clear on AI, which were significant investors in and have been since 2018, that we were not hardware investors. We never will be. So that wasn't in scope for us. LLMs, we avoided. And some of those might end up in our anti-portfolio. But we were very clear that we thought that open source would catch up and start to commoditize those

capabilities and that Google in particular was going to be a massive force. They might get there late, right, which it turns out they did, but they were probably going to be right and they would probably win. And so we avoided the LLMs and we went after orchestration layer and application layer opportunities, true enterprise software companies that were using orchestration technology to provide enterprises the ability to adopt AI in the right ways, and then application layer on top of the Gen AI LLMs, either proprietary or open source, but very much customized to the use cases. And we felt those were going to be the outsized opportunities. And you find corollaries here in the cloud wave, right? In the cloud wave, who made most of the money? It was the public equity

providers, right? It was Google, Microsoft, Amazon, and Oracle, right? The four cloud infar providers still obviously doing incredibly well on this AI wave as well. It wasn't the private market companies that were going to go build cloud infrastructure. They were going to build orchestration application layer, a la Snowflake, the best returning company from that wave. And we think the same thing is playing out in AI. It's easier send than done to go against the herd. How did you deal with LP communication pressure and all the things that come with having outside capital? So I think LPs have to believe in your thesis. They have to believe that you're going to generate alpha consistently and repeatedly.

And if they don't, they're probably not going to be re-up long-term LPs. And you have to unfortunately live with that. We did have a lot of explaining to do when we invested in Circle in 2022 right on the back of a lot of blow up in crypto. And we also invested in publicly in the pre-IP. financing with Black Rock, Marshall Waste, and Fidelity, when the company, at $9 billion, when the company, and again, publicly in 2021, generated 80 million of top line and Burns, circa 300 million. So LPs were very concerned when we underwrote to a $9 billion valuation at that point. And obviously our view is that rates were going to come up.

That was going to drive NIM, but there was going to be other ways that they could monetize on the platform, which they've demonstrated now through the Circle Payment Network. We also had a view that regulators were ultimately going to get their arms around USDC and the digital dollar. So we called it correctly. We were highly contrarian. We caught a lot of heat, but we explained our perspective through deep research and forecasting and perspective on the market. And obviously, we think that our thesis, albeit contrarian, in the time, has proven out to a degree and is still playing out in the right way. Is that the cost of doing business? The cost of being a contrarian is losing some of the those weaker hand LPs and consolidating around your true believers? I think it is. You have to show the

repeatability in that. And that may mean that it takes time. But we think that long term, particularly from an integrity of your investment thesis versus being herd following and style drift oriented and just focusing on your investment box and what you feel your best at from a differentiation perspective is the right long-term approach. For me, as a solo GP, and the founder, I definitely wanted to stick to where I felt like I had the best edge in selecting investments, but also adding value post investment and creating unfair advantages for our founders. And we think that that is an all-weather approach across cycles, which means that we can persist and hopefully won't be part of that consolidation wave and we'll be able to continue to grow and scale.

We don't care about AUM. It's just not a metric we measure the firm by. We very much focus on DPI and our metrics on the performance side and the relevant benchmarks in our asset class. We also care about legacy building for our LPs as well as for our founders and then for our team, right? And that's our mission is to be the go-to enterprise software investor for financial services. And we think that puts us in a very nice spot to continue to grow thin capital into the future. Did you have to do a lot of anti-selling as you were picking your LP base and did you have these difficult conversations up front? Or does it kind of, does LP behavior play out as time progresses?

We had a lot of upfront conversations, right? We are a specialist manager. We focus on enterprise software. Thankfully, so do Toma and Vista and IVP and many storied firms that have been around far longer than us. So they trailblaze a lot of that education on why enterprise software is the best place to be investing in private markets. And some may argue public markets as well. And that's because they are all weather. And as rates come up, you don't get the multiple compression that you do in a direct to consumer or direct to small business company.

And these are much more enduring long-term businesses. They're far less capital intensive. They're not typically regulated. If they are, it's light. There's no real legal risk or credit and balance sheet risk. you're really only taking on execution risk. And if you feel like your investment box, the way you index on founders, we publicly said, and we continue to be very focused on repeat founders as our CEOs, I think then you can start

to mitigate that execution risk, particularly if you're hands-on active investors as we are. Alongside FinTech, you're also deploying in other emerging spaces. What are your favorite spaces today? And what's your thesis on it? Beyond application, orchestration layer AI, cybers become a huge area of focus. As we saw with cloud, cloud infrastructure, cloud applications got out ahead of the cybersecurity capabilities. So you started to see a lot of vulnerability in enterprises. We believe that the MIT report and other reports that have shown that AI adoption, the enterprise is sub 10%. We think a big part of that is orchestration, right? Having the right tools, data governance, entitlement, and so forth. But the other big part of the of that is security. So how can I make sure if I'm deploying this AI agent or agents in the front, middle or back office, mostly front and middle office these days, how can I make sure that they're not taking PII and putting it out in the public realm? How can I make sure they're not hallucinating

and doing all the things that we need to manage? That requires a very significant cybersecurity layer. And you saw the WIS exit that was cloud security, right? We think there's going to be comparable companies in the AI security space that secure enterprises. against AI attack vectors, things like deep fakes, things like AI agents potentially going rogue or taking PII. We also have a problem where employees are bringing their own AI to work. They're opening up an AI application on their web browser. They're adding company data to that application. We think those are, you know, very significant risks. And that's why you're seeing this more conservative step function orientation to enterprises and actually embracing AI. There's

view that cybersecurity, you should go with very niche players that just focus on cybersecurity. Why are you guys going into that space? So we have had some success in cyber investing as well as in areas like fraud and risk tech. I think that for us, we are looking to add cyber expertise to the team. Certainly, we have a very deep rolodex of CSOs within our LP base that we can contact to do validation on companies through POC, thematic work. and then ultimately commercialization post investment. So that de-risks the proposition quite a bit. You're direct to the customer. Exactly. And so for that to work well, you know, we have to be, you know, at least knowledgeable about where the pain points are and where the gaps are. We get a lot of that data firsthand from customers and expert networks.

And then we're outsourcing those companies. We've got a great cyber pipeline. We're going to be announcing some cyber investments here, I think, in the near term in Q4. And I think you'll see us doing more of that. Beyond cyber, I would say quantum computing is an area we've seen recently from Google and others, that it's coming faster than we all think. I think if you started the year out and you asked a ton of quantum experts at different academics, institutions, they would have told you, ah, cyber computing at scale, democratized, 10 plus years out.

Now I think if you ask that same question, they maybe tell you it's probably five to seven years out. And what that means is that you've got to prepare from an encryption security perspective. and you've got to be building software with quantum in minds, right? So if you're not building software with a quantum future in mind, then much like building software 10 years ago where you didn't have AI in mind, it will catch up to you quickly. And so for us, quantum is another area where we think there will be some very attractive early opportunities.

We did our first AI investment in mid-2018. We were very early to that trend. Most GPs started investing in AI in 2021, 2022. and we developed a lot of expertise. We hired a head of AI in 2021. I don't know how to prove this, but I think we were one of the first PE firms to have a head of AI. And now I think hopefully everybody has a head of AI.

And we were building our own AI capabilities with Lighthouse, our platform, but also really scanning the market and understanding where the opportunities existed in AI. What would you like our audience to know about Finn and anything else you like to share? We've shared a lot of it. We're contrarian thinkers. We don't have a herd mentality. We're full life cycle. We provide for LP choice, whether you want venture or you want late stage exposure. We have mixed duration opportunities. We never require stapling, produce a lot of co-investment. We also have separate accounts where we can customize mandates. I think those are all important things for LPs, but so is understanding that the GP is doing real work on their behalf, but also on behalf of founders. So we're very focused on business development and corporate development as our two core operating value principles. Those are highly repeatable and they really move the needle for the company.

And so for us, we want to continue to do that work, continue to add to the team, continue to invest in AI to be able to sustain our competitive moats. And I think, you know, for most LPs now, they're really indexing on managers that can produce alpha across cycles that are all weather, that are not impacted by the ball you're seeing in the market, as well as managers who have exit optionality, right? If you can't sell, if you, if your only exit is through an IPO, you're in trouble, right? You have to be able to sell through the sponsors and build relationships directly with sponsors as we've had. You have to build relationships with strategics and corporate development departments. And then the third piece, you have to understand the secondary markets and a great deal of intimacy at this point. Otherwise, you're going to be sitting there with effectively, you know, going back to the EQT Allen quote, you're going to be sitting there with a lot of zombie funds in your portfolio.

To take it full circle, you have to. to do the hard work. That is the alpha. Well, thank you, Logan, for jumping on the podcast. Thank you to New York Stock Exchange, Wired, and the Q for hosting us and looking forward to doing this again soon. Thanks for having me. That's it for today's episode of How I Invest. If this conversation gave you new insights or ideas, do me a quick favor. Share with one person your network who'd find a valuable or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.