How should I be positioned? with Marc Lipschultz (Blue Owl) & Jason Draho (UBS CIO)

Hi everyone, Dan Cassidy here. We are back now with the next episode of How Should I Be Positioned for 2026, coming to you today from our new podcast studio in 1285 Avenue of the Americas in New York. As you, our listeners, know on this podcast, we enjoy catching up with our industry colleagues to exchange views on markets and the macro environment, along with views when it comes to asset allocation.

With that, joining me here at the table today from the UBS Chief Investment Office, glad to welcome back Head of Asset Allocation for the Americas, Jason Draho. We're very fortunate to have with us here at the table in person today from our partners at Blue Owl Capital, co-CEO Mark Lipschultz. And Mark is our first in-person guest here on How Should I Be Positioned.

So Mark, absolute pleasure having you with us. Jason, great to have you back with us as well. Thank you for joining our listeners and clients.

Thrilled to be here and be the first guest. Absolutely. Well, it's our first time, Mark.

I'm so very pleased to have you on. We do have a five-timers club, so hopefully this is the first step in that five-timers club of appearances. I think we're going to try to work on like velvet coats or jackets.

Oh my God. It's like Saturday Night Live. Saturday Night Live.

Well, for the record, when I was in high school and they have those aptitude tests, the strong Campbell aptitude tests, I was actually told I should be a radio host. So maybe this has returned to my roots. Now, I don't know that alternative investing was an option back in the 80s when I took that test.

With that, Jason, I know you have a lot today you want to cover with our guest, Mark. So I'll hand it right off to you to begin that conversation. All right.

Thank you, Dan. So we're recording this on January 15th, so barely two weeks into the year. It feels like we've already had six months of sort of news flow in that time period.

So maybe just to set the context, we'll get into some of the bigger kind of the weeds later on. But just thinking about the macro environment, definitely kind of a constructive view overall, a lot of news flow that sort of could impact how people are thinking about it. Maybe just at a high level, how are you thinking about the overall macro investing environment for this year in the U.S. and globally?

So I tend to look at this from a bottoms-up point of view, the broader macro forecasting. There's people who are professionals at that, and we don't take a top-down view in that regard. We look at the bottoms-up, look at each company.

We have hundreds and hundreds of companies in our portfolio. Most of those are U.S.-centric companies, so our perspective is, I guess, particularly deep if we look domestically. And from that point of view, things are good.

And I will say that our perspective, this remains consistent in this regard, that's what we have seen throughout the prior year, and with all the tumult and noise about, is there a recession, isn't there a recession, what's the glide path? We have actually had a view, data-based, and seen it in the portfolio, that the economy in the U.S. in particular remains very strong. And that doesn't mean as strong, perhaps, as it had been the year before, but very strong.

And we saw inflation starting to really temper, not go away, but temper. And so all that informs a perspective that says, as we here head into 2026, this is a very constructive environment, most importantly for the investments, the portfolios, we and others already managed, of course, dollars already invested is our first responsibility. But for new investments, the idea of a moderated inflation and therefore moderated rate environment with a strong underlying economy, that's a good set of conditions.

So one of the consensus views of this year, and a view that we would share, is that growth is likely to accelerate this year versus last year. And there's easy things we can point to, you know, the one big bill, there's going to be some fiscal stimulus, you know, a little bit less policy uncertainty, you know, the Fed has cut rates, financial conditions at ease. And so the thought is that we'll see this sort of pick up in growth in the first half of this year, certainly relative to last year, although the data last year was not weak, as you say.

So going back to your comment about what you hear from your companies across the board, that conditions have been strong, you're curious, then, is there any signs of like, the view they have is like, okay, this is things have been holding up, but we actually feel like even better going forward? Or is it more of the same? Like, is there any inflection?

I guess that's kind of where I'm... I would say at this point, the tempo is probably things have been good. Everyone's always on guard, of course, as they should be.

We're all protect the downside, right, whether that's a company or us in an investment strategy. But I think actually, what we've seen is more of the steady pace at the company by company level. A lot of this maybe volatility, if you will, I think, in perspective, perception, consensus, you know, has really been kind of market centric a lot in whether you want to call it the chattering classes or the pundits.

Actually, the company level, we saw people continue to march along and say, listen, my business is good. When I look across, as I said, the many hundreds of companies that we do business with, we were seeing companies still with revenue and earnings growth at the high single digits on average. Now, I'm not suggesting that was the economy on average.

Of course, our job is to go around and select better than average companies. But at that pacing, and hopefully things will indeed accelerate. We don't count on that, and I don't think the companies yet, we have seen a shift into a more front footed posture in terms of, well, the organic development of their business.

Now, we are all observing increased activity in M&A. To date, it seems to be more skewed towards some of the larger big strategic transactions. But that is presumably a precursor to what will be continued consolidation elsewhere in the economy and elsewhere across, for example, the private equity landscape.

So a key part of the macro outlook has been the Fed, whether they're going to cut rates. As we kind of entered this year, the thought was, the Fed may be in a pause a little bit. Obviously, bigger questions now going on with the Fed, and we don't necessarily get into that.

But just thinking about the markets overall, there's often discussion of what's the right level of rates. And for equities, rates can go higher, but not too high. From your perspective, is there sort of a sweet spot beyond where we are right now that if the Fed cuts once, twice, three times, that's even better.

If they don't cut, that's actually okay, because it signs a growth of good. How do you think about from that macro perspective that actually filters down to your businesses and the investment opportunities that you see? So from a blue-owl perspective, a little bit like I was describing on the macro, we really try to be very data-driven and very much centered on on-the-ground facts and then work upward to a perspective.

And so, as I said, on the economy writ large, it's been strong, continues to look strong. With regard to rates, rates are really, of course, a function of inflation and economic vitality. So we just talked about the latter.

In terms of the former, inflation remains existent. Obviously, we're not in a non-inflationary environment, but it has tempered. We saw that at the companies.

We saw that happening through the end of the year. We consistently were talking about this perspective that inflation has not gone away, but it's nowhere near as dire as it was. So all that informs more of you of where are we with the rate path.

Well, we've seen a moderation of rates and without, as you said, trying to guess specific policy actions and even the politics that surround it. The current rate path, we can now say, if you will, empirically, has been working. That is to say that despite all of the fears that the higher rates are going to tip the whole system over, actually, companies were enormously durable through that time.

We didn't see any increase in default rates. That's pretty meaningful. You remember all the dire warnings when rates were back and SOFR was around 5%.

All the dire warnings of companies couldn't afford it. We saw and thought they could, and they did. Look at rates today.

This is a pretty comfortable place. We try to build strategies by design that are at least insulated to a wide range of rates and in some cases, since a big part of what we do in our world is lending and floating rate lending, we're actually, if you will, indifferent to base rates. The idea is to create strategies where you don't have to guess what rates are going to be.

It's a hard guess to make, but overall, this current rate environment marries with a pretty strong economic environment and strong company performance. We're seeing companies comfortably able to pay the bills, so to speak. Whether rates are going to be a bit lower, a bit higher, I think it's safe to say the economy is operating well in this overall range.

I would be surprised, now to try to take the estate perspective, I'd certainly be surprised to see rates materially higher or materially lower. I think we're probably operating in the zone. I think the 10-year treasury yields after the first week, kind of full week of the markets with all the different news flow that's coming at it was unchanged for the year to date.

I think that kind of summarizes a little bit of like the bond market is kind of looking like, eh, a little bit like that. Which sounds about right, again, when I try to marry that with bottom-up realities. Businesses are doing nicely, and so we're in a balanced place.

That's a pretty good spot to be. You think about where we were in coming in from the last couple of few years. Think about the inflation that we had two and three years ago.

Think about the challenge of bringing an economy from there to here. I mean, it's really quite incredible to think that today we, and not just consensus, we know that the data is pretty darn clear in the foreseeable future, that we're in a pretty balanced place. That is not an easy landing to stick.

We've talked about the macro. I want to transition to sort of more micro topics. Although the first one is on AI, which you could argue is also kind of a macro story, given how much investment is taking place, how much of the economy, the impact for the labor market, not so much now, but going forward, inflation, et cetera, et cetera.

And so, you know, a big part of this requires investing. The numbers that are being tossed around like, you know, $2, $3, $4 trillion over the rest of this decade to finance data centers, you know, and increasingly we saw towards the second half of last year that even the big hyperscalers having to go, they don't even have enough cash. They have to go and issue debt.

So how do you see, given what is in the pipeline for spending, like how is this going to be financed? What role do you think private credit plays? How do you think about like that opportunity set as an investor, given what's going on?

So AI is obviously one of the most transformative forces, not just of this moment, but probably in a generational sense. And then I think when I think about AI, I would suggest that we first break down, because you immediately, I think, drive into this question of, is it a bubble, right? And that's sort of the first thing on people's minds.

It's the daily debate in the press and it's the daily debate amongst investors. So I think in thinking about bubbles, there's two things we have to get at. There is the substantive question of, is this change, is this AI shift going to dramatically remake the economy?

Let's call that kind of topic one. I'll call that the secular direction of AI. The second is what we'll call evaluation and sort of, you know, what's it all worth?

Who has to spend how much? Who makes how much? And those two, I think you really have to separate to then make intelligent investments or at least understand the risks you're taking.

There's no singular answer, but I think it's important to say the following. The secular notion that AI is transforming and will transform the economy over the next five and 10 years, I can say with extreme confidence that is true. And I don't think there'd be a lot of people that will take the other side of that argument.

Probably many people would say it's scarily transformative. And then there's those who would say it's positively, optimistically transformative. But either way, I think if we agree that we are going to see the economy transformed through the power of AI, then to your question about capital investment, two things become true.

One, we're going to need a lot of it. That's crystal clear. And two, done by the right people.

That's going to be a really enormous investment opportunity and a very attractive one. So I'll come back to ways that we approach that from a Blue Owl point of view. The second part about whether AI is a bubble, you could believe the first and you could still believe the second.

Now, there's a wide range of perspectives. And I think, again, from the way we try to invest, we've developed strategies around AI where we can invest against the secular trend without having to take a perspective on the valuation question. So how do we do that?

We have become one of the largest providers of capital and one of the largest developers and delivering operating assets of these hyperscale data centers under long-term agreements with hyperscalers. So what we're saying is Microsoft has a highly intelligent view, Meta, Google, Amazon, Oracle. They have incredibly informed views.

I would tend to give a lot of weight to their views. But in any case, from a Blue Owl point of view, if I believe, which I do, that the secular transformation is going to occur, and therefore these firms are going to put the capital with their extremely strong balance sheets, I might add, behind that secular change, we can sign 15 and 20-year arrangements with them where what we're counting on is simply they're paying the bills as they invest in capturing the upside. We're trying to get paid for the picks and shovels.

We're trying to get paid to do that baseline infrastructure. And that presents an enormous opportunity, both in scale and attraction. Whether in turn that will be highly profitable for participants in the market, that's a different set of investment strategies.

We don't happen to pursue those, not because I don't think there are winning strategies. There obviously are. But I think you can believe two things at once quite comfortably.

If you are skeptical of the valuations happening, I do have caution on the valuations in some of the private markets around AI. In every sort of novel startup, there are now Series A rounds in Silicon Valley happening at $1 billion valuations, and it's not a singular case. I have a lot of very good friends that are in the venture business, enormously successful, by the way.

So again, I'm not even trying to take the under on their decision-making. But a billion dollars for the first day of, here's my idea, you're raising the bar high. And then the number, we all see this if you follow the daily flow of venture activity, $10 billion valuations, that just all suggests you're going to have to take a lot of value, create a lot of value.

And there I think there's a lot of room for caution, a lot of winners and losers. And in fact, the whole business will be about winners and losers. The issue is when you start at a billion or 10 billion, it's not quite as easy to take the losers and make them up with the winners.

So all that's a way of saying it's hard to be more excited about this opportunity set. For us, I think the way to participate for many people is in the base infrastructure and really participate in this more downside-protected picks and shovels approach. But there's room for both.

So I'd like to maybe drill into this, but I might ask you questions that you don't want to answer. It's giving away some secrets. But the obvious parallel to what's going on right now with the AI story is the dot-com era, the 1990s, which was a bubble, but it was both sort of an equity bubble.

We know how much the markets rallied and sold off. I think oftentimes the general public is not aware how much debt was used to finance the building out of that, how credit spreads actually started to widen by 97, that you already had rolling default rates picking up. It was almost that was sort of a bigger problem.

We don't see those kind of debt levels right now, but this is where these concerns about as debt finance increases, they are a concern. So there definitely feels like the valuations on equity are stretched. The fundamentals still look kind of solid.

So do you feel like that if you're lending to these companies that, you know, look, you're just getting a good return of capital. You're not looking for this moonshot super upside. So you can feel kind of more comfortable managing those risks.

But as those companies start to issue more, or if it's not Microsoft or Amazon or Facebook, like Pristine, like, you know, really rocks all balance sheets, would you feel, you know, I'm happy to lend to them, but I'm not going to want to lend to OpenAI. I'm not going to, you know, pick any company specifically, you know, something that isn't a AAA rated kind of company. So let's headline with the fact that the core of our business, and so this informs my perspective, is in fact doing business with the Pristine hyperscalers you described.

And that is where we are lucky to be one of their go-to partners. And so those companies, to the point, and I do like to sort of say this out loud, you know, when we do business with Microsoft, which we do under very long-term agreements, Microsoft's credit rating is superior to the credit rating of the U.S. government. Now we can probably think that's a difference without a distinction, AAA, AAA with a negative watch by one agency, you know, but at the end of the day, you know, that's the kind of credit in that case taken to the far extreme, but all of these companies are amongst the very largest market caps in the world, best operated companies in the world, and best informed about the path to this technology.

So it's also not just sort of like a toss-up as to, gee, I wonder if they're right or if, you know, people that think otherwise are right. I mean, either could prove true, but I put a lot of stock in what Sergey Brin thinks and what Larry Ellison thinks, and the list goes on. Mark Zuckerberg, these are geniuses in this arena.

Let's go back to the analog to the dot-com bubble. I was working in the alternative investment business through that time. I spent a lot of time personally around Silicon Valley at that time in the so-called, you know, dot-com, bricks-and-mortar dot-com world, as were the words then.

So there are some natural gravitational pulls, some natural similarities, right, because there's a transformative technology, lots of money shifted in, extremely high valuations for the latest hot idea. So there are some rhymes, and I think there's a little bit like, you know, does history repeat or does it rhyme? And here I think the rhymes are useful, but it's not about repetition either.

You noted that there are both the equity and the debt, and that's, you know, we talked about this a moment ago. There are very different strategies. But with regard to the transformative effects, let's start with this similarity.

Turned out to be absolutely true that the internet, which is what that was, right, dot-com as we called it, that transformative effects on the economy couldn't be much more significant, right? Maybe the debate is, is the internet transformation or the AI transformation more significant? We'll all come back and talk about that 10 years from now.

I'll be well past my five visits, I hope, at that time. And so, you know, so that was true, actually. So we can start again with, was the secular observation correct?

Absolutely. Were there tremendous winners? Absolutely.

Those hyperscalers we just talked about, you know, have their origin stories back then. So back to the point, I'll flip it to the equity side. Well, there were some tremendous winners, but an awful lot of losers, and that's again why I say picking amongst the winners and losers.

For us, for Blue Owl, I find that to be very challenging. And I think similarly, and anyone would tell you this, that's the nature of these big transformations around tech. There are big winners and a lot of losers.

So I'll leave that for other experts to try to pick through. But the last part is this whole part about debt and kind of base infrastructure. This is where actually the similarity entirely breaks down.

Borrowing back in the time of the internet transformation, the dot-com, was by companies that had no cash flows and no credit to offer. So you were debt financing essentially what amounted to no revenues. Today, the people that are borrowing the money are the most credit worthy companies in the world.

That is a, it couldn't be more opposite if we tried. That only matters if it's in the hands of someone who can't pay it. Our whole job at Blue Owl is to find companies in the context of whether it's a partnership around AI or a loan, which as you know is a big part of our business.

We will end to companies that have obviously far lesser credit than Microsoft. It's safe to say nearly every company does. But we work in a different world where our job is to find companies that have much less developed and large cap perspectives, capabilities.

So if we take that perspective, but now we're applying it to some of the very biggest and best companies, they're going to pay their bills. I think where things are getting totally lost in this conversation is this idea that these companies amongst the biggest somehow aren't going to pay for what amounts to its moderate debt even if they took on a bunch more debt. I don't think any of us should really question whether Amazon can pay its bills.

It's a bit of a silly exercise. I think this is where people are going to miss an opportunity because if you don't distinguish what you might view as this sort of winner-loser arena from what are decidedly and only a matter of degree thriving, surviving companies because you're conflating the venture side, the sort of cutting edge side with the picks and shovels being delivered to the very best companies and credits in the world. So I'm not going to say pushback, but just thinking about what are risks in a further down line.

A lot of the 90s comparison, you can look at different metrics for the economy overall, increases in debt, investment, and this is the concerns like are we about in a bubble? All these metrics look like 1996, 97, not 99 or early 2000. Well, they could.

They do and they don't. Right? Again, the top line story looks similar and maybe even things like, oh, well, people are borrowing a lot of money, but that's pretty different because the question is, well, who's borrowing the money and what are they doing with it?

It's one thing to borrow the money, build a bunch of dark fiber, hoping if I build it, they will come and that's completely different from I built an asset that is long-term leased by someone who is assuredly paying their bills. Also starting point broader as an economy, we're nowhere near as leveraged, right? That is to say, if you look today, actually, corporate balance sheets are in very good shape and some of the conversation we're talking about are companies that just never borrowed at all starting to borrow and in meaningful quantums and absolute dollars as a share of their market cap.

Is it meaningful when one of these hyperscalers borrows $30 billion as a share of their market cap? Not at all. So, I think, again, we have to be a little bit careful of applying numerator-denominator, so to speak.

Right. So, but it kind of leads to my question that things look, I think, good now, but when things look good, I guess my question for you would be, how likely do you think it might be that things are good now, but as more money comes in or looks to lend, that we do get situations where it's not the highest quality companies issuing that, you know, that in three years like people are just sort of chasing income or yield or, so it's okay today, but the risk of something going down that path, so if we sit here three years from now, then it's like, oh, this is really getting kind of dodgy. We're definitely not, I think, there yet, but is that likely or just the nature of the industry itself would maybe dictate that?

It's a great question and implicit in a great observation. I keep reverted to talking about these large hyperscalers and, you know, it's not a hammer and a nail, but like that's who we do our business with in vast preponderance. You are absolutely, of course, correct.

There are other people investing a lot of capital with short-term leases. There are companies like NeoClouds that have exciting business models, very exciting business models, but have much more in the way of speculative capacity. So this is not a uniform answer on the infrastructure side either.

So like any changing environment, probably changing or not, investment selection matters. That's why, why does UBS matter so much? Because UBS works with its clients, right, to come up to a good informed answer.

It's not just like a singular answer. It's not any data center is a good idea. In point of fact, many data centers are a bad idea.

So this does get down to picking the asset, picking the investment, picking the manager to pursue the right strategy. Absolutely, there are going to be disappointments. So now let me be very clear.

I'm not Pollyanna on what is happening on the infrastructure side or the application layer side. I am very optimistic about the transformative implications, and I'm extremely confident about the ability of certain big companies to thrive, but that's very different from this uniform view that everything's going to work. You build a lot of capacity, now the analog starts to build.

Someone who has very limited credit capacity and very limited cash flow builds a lot of capacity that is a long-term asset on a short-term lease, so to speak. That has historically led to moments of great disappointment. So that's not a prediction, because we'll have to see how the capacity develops and the use develops, but the risk of, hey, I built an asset that I really need 15 years to pay for, but I really only have a user for the next three to five years, that's not a business that we focus on.

But a lot of data centers, that is what they do. So there, you can't just say, I want to be in data centers and one size fits all. Then you could walk yourself into a trap, because a three-year lease data center to someone who has very limited cash flow, limited credit capacity, pretty different from a 17-year, 20-year lease data center to one of the best credits in the world.

Thank you for implicitly endorsing the high, high importance of asset allocation in my talk. Well, it's true. I mean, it's just that.

If it was this easy, you know, I'd just throw darts and you'd get an answer, and you don't. These distinctions are really important. And that's why people who are willing to take the time or a partner with a great advisor can parse their way through and say, wow, like in this, you know, if one moment everyone wants to be an AI, you got to have due moments like, okay, where do I want to be?

We're almost in a funny world where everyday story now is about the bubble and people like, oh, I'm nervous. I'm anxious. I don't know if I should be investing.

We're missing the opportunity because in the core of that, both in the high and the low, whether you were being over-hyped or you were being, you know, concerned, lies some great opportunities and lies some mistakes. You got to pick right. So I want to cover a few more topics before we run out of time.

One last question on AI. Not the opportunity, but you talk about the transformative nature. So it certainly was.

I think every company is trying to figure out how to incorporate AI into their business. For me, our investment process, I'm curious, like how have you, you know, started to incorporate AI tools into your business, particularly your investment process, like how you might evaluate opportunities. Like what do you actually sort of, you know, sort of deploy at this time or at least thinking about trying to sort of, you know, leverage?

Yes, certainly practicing what we collectively preach on trying to adopt the right tools and use them. Well, understanding they're still developing and evolving and we have a zero risk tolerance environment, right? So we have to adopt these tools thoughtfully, proactively, but pretty darn methodically, as do you, because we're dealing with people's money, people's investments.

So there's no room for mistakes. So what does that mean for us? It does mean trying to be very front footed.

It means trying to make sure we understand the cutting edge. It's not about taking cutting edge tools and putting them into an environment where we shouldn't tolerate the unknowns of those tools applied to what we do. So what does that really look like?

I'll kind of break it down into three pieces. The most important piece from the moment any of us in common parlance were uttering the words AI or large language models or open AI is understanding where the risks lie, right? The first place we start at Blue Owl, and again, this is different depending on your business, but since we do things that are very much about downside protection, stability, predictability, first thing we're always going to ask is, well, what could go wrong?

What's the risk? So the first thing we did from moment one and do every day is, what could AI do to adversely impact a business we already are a investor in, or of course, any business we're looking to invest in? And we went and we went very thoroughly and continuously go thoroughly through the portfolio and every investment conversation and talk about, in that case, what could the cutting edge do?

Because that's where cutting edge applications, we have to have a very clear eye on. We have an office sitting right in the middle of Silicon Valley. We've been deeply involved in the tech arena from very early in our business.

So I think we actually have a pretty refined understanding, including being one of the largest participants, as I said, in the infrastructure layer, the data centers, we have a pretty good understanding of what AI is today. Nobody would be foolish to say we all understand what it will look like in five years. But what we have to do is stay vigilant.

And to date, what we have found is there are, again, areas of risk out there, but they aren't as simple as people think. One was something was good. Now it's bad.

It gets down to, let's take something like in the software arena, there are incredible software businesses before, now, and in the future. AI is not a magic wand. In fact, a really well run, deep moated software business is a beneficiary of AI in all likelihood.

They're adopting the tools. They have the customers, the workflow, the data. So once again, people are going to throw babies out with bathwater.

That's going to be a tremendous mistake. They're going to miss great opportunities. Same time, you don't want to whistle past the graveyard and ignore transformative impact.

So job, again, of a good asset allocator manager is to draw that distinction. So first, it's defense first, and we've done that and do that very thoroughly and carefully. The second is how do we use AI internally in terms of our own business practices?

So that's about adopting tools that might impact, let's say, the more operational size of our business. So on the investment side, we obviously have a very different standard for how we're going to allow an investment decision to be impacted by a yet to be proven technology. But in areas like accounting and in legal, there's already some well-developed and developing tools.

We have a partnership with Harvey. Harvey, as I think you know, is the leading developer of tools, AI applications for the legal industry. We have formed a partnership with them to help take those tools and actually develop them forward, customize them to actually work in the alternatives industry.

So there's a tremendous win-win. We will be one of the early beneficiaries of having the most advanced operational legal tools and workflow tools for our business, and Harvey is able to then develop those tools and bring them elsewhere in the marketplace. So there's kind of the operational internal applications.

Then the last is kind of decision-making and how we operate day-to-day, outward-facing. So there, I'll leave you with two ideas. One is we're already developing, for sure.

We have already taken and trained up models on all of our investment committee memos, all our portfolio committee memos. We've trained up our models on all our different LPs and all their investments, all their portfolios. So we can now do a much better job of risk management on the one hand.

So I remember the days of Silicon Valley Bank, which would have been in the earliest days of the world of AI. So those weren't tools that your others had. And we had to spend a weekend sorting through, you know, did we have any exposure across hundreds of companies to Silicon Valley Bank?

Today, you know, I have a tool in my pocket right now where I could take it out and query it at this moment and in a matter of seconds have an answer, like, where do we have exposure to Silicon Valley Bank in our portfolio? Is it perfected yet? No, this is the point of evolving technology.

But boy, we could get, you know, 80% of the answer in seven seconds. And we can use the rest of the time refining the remainder. So, you know, our LPs, my partner David sitting here, we can answer a question for one of our investors sitting at a table, anything about their portfolio and about where they've invested with us and performance.

So all those kinds of tools we've developed. The final layer, of course, now is to develop a sophisticated set of tools to incorporate all of this into the fundamental decision-making around investments to be ever more data-driven. We're working on that, but that is not a tool we would rely on yet.

It's not a tool we have yet, but we are absolutely spending our time now on that next question, which is how do we really make the decisions we make, they're informed by decades of experience and they work. But how do we make them better, more data-driven now that we've collected data and have a way of harvesting it in a way we couldn't have before? So I think this is a good way to kind of lead into my last two-part question because, you know, the idea of like how do you filter through and think about these investment ideas.

So the first kind of part of the question is, as you look at the landscape of economic environment, AI, other factors that you might consider into it, you know, where do you see like the more interesting opportunities, where are you leaning in? I mean, obviously AI data centers is one, but if there's like more specific things or like you think the next level is this, like, so what do you like, whether it's private credit or other parts of private markets or elsewhere, so that's the first part. The second part that is investing is risky, I mean, like that's we all take on risk.

Private credit is, you know, certainly no different. There's like, you know, concerns in the private credit space, a lot of money has come into it. Where would you say in terms of given the concerns that people might have, like what do you think risks that the public might have, like those are overstated, that's not true, but these are legitimate risks.

How do you sort of think, what's really sort of what can maybe keep you up at night versus things that people talk about a lot, but like, no, those actually aren't big risks. So the favorable news, there's a lot of things to keep me up at night and I'm not such a great sleeper, but here's an important point. It's not about concerns in the base portfolios we manage.

I feel great about those, and by the way, that's not just about us, I mean, let me extend that point. Things that I'm actually not concerned about, where the world seems to have a misperception is, for example, as you note in private credit, private credit portfolios, not just ours. Across the well-managed large cap, that's where I'm more familiar, lenders, people are doing a very good job and portfolios are in very good shape.

And remember where we started this conversation, what's the environment we're operating in? We're operating in an environment with moderated rates, solid underlying economic fundamentals, that's not the environment where one should be gravely concerned about credit. When you put the word private in front of credit, it isn't magic, it's still credit.

I think part of, and whether this is legitimate concern, and now on the answer, I think people have legitimate questions that don't understand. Gosh, I haven't heard about this thing, private credit, or I've heard about it, but I don't understand it. Well, onus is on us to provide education about how we do, what we do, and what we have in our portfolios.

But it turns out to have a pretty simple answer. We lend money on a senior secured basis to very high quality, heavily diligence companies, and we have very, very strict agreements on what they can and can't do to protect our capital. Will there be problems?

Of course. Credit, as I said, investment by definition has risks. The key is to manage those down to being very moderate risks, or much less, or pay a lot more than the risk you're taking.

And that I feel very, very comfortable. That does not keep me up. So again, people say, well, it's a new thing, private credit.

It's not. It's just credit being done in a different format where we're not dealing with the daily trading behavior. Credit's been done for time eternal.

There's a lot of data to tell us how credit performs. So I think that's an important point to understand. Credit and private credit is just another version of how you apply it.

And I would proffer, maybe not surprisingly, a much superior way in many cases. Not every case. We need good, liquid, viable public markets.

We need a great, healthy banking system, and we need a really great, vibrant private credit system. Today, by the way, we have all three. That's also a really good feature for 2026.

So where do I see concerns, risks? Well, the things that actually keep me up at night are what we might call more exogenous. It's the geopolitical risks, mostly because we all occupy a world where those things are the ones that actually impact true human lives, like literally life and death, but also the transformative impacts across the globe, the economy.

Those are dramatic and they're very much harder to predict. Very much harder to predict. And in fact, history is a guide.

Markets are generally good at incorporating geopolitical risks, because what do you do? How do you assess what's going to happen? And so that's the kind of thing that concerns me writ large for investors, is more of these exogenous variables and not underestimating or either over-obsessing or under-obsessing on these kind of bigger tectonic plates.

For us, again, as a business, we then get back down to sort of tending the garden, which is at a very specific company level. We're managing what could those risks mean for our companies. And so I think rather than sit and worry about it at night, what I'd rather do is think about here are the things that could happen in the world.

We're always thinking about what could go wrong, because again, we're in the downside protection business. And then thinking, well, if that were to go wrong, what would the impacts be? Are we protected?

And in the hopefully rare instance where we see exposure, how do we eliminate that exposure or manage that exposure? To me, that's a more productive way to spend my hours up at night than just sort of worrying about all the things that could happen with no answer. I'd rather think about the things that generally could happen and what we're going to do to protect ourselves.

Got it. Thank you very much. I'm looking at my sheet of paper of questions that I prepared, and there's at least three or four that we didn't get to.

I think we've kind of exhausted our time for today, but this is the reason why to come back for the second time and work your way towards that. You'll have that jacket in no time, Mark. Yeah.

I was trying to slow walk a little so I could make sure I get a quick invitation back. Well, Mark, thank you very much. Jason, you as well, and David Sirianni in the room with us, thank you for your coordination efforts.

It takes a lot to get these podcasts together, and Mark, we look forward to having you back on the show at some point. Thank you very much for having me, and I hope you'll have me and not my AI replacement. Definitely.

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