Bucky Moore @ Lightspeed Venture Partners: Why You Cannot Do VC If You Do Not Do Pre-Seed

The best companies always feel expensive. If you look at just how unique these companies are on a topline basis, we're talking about billions of dollars of run rate growing in excess of 100% year over year. I don't think we've ever seen that before, right?

We're talking about going from $30–50 billion outcomes to multitrillion-dollar outcomes in the form of SpaceX, OpenAI, or Anthropic, where the actual sizing of the market is, at least from my experience, so imprecise that it borders on being a fool's errand.

Bucky, I'm so excited to make this happen. We've known each other for many years. Thank you so much for joining me today.

Thanks for having me, Harry. As they often say, longtime listener, first-time caller. It's been really fun to watch your media work rise over the years. As you know, I've been watching since the beginning.

1. Big News: Joining Lightspeed Venture Partners

Dude, I so appreciate that. But you have some big news today, so I just want to start on that. What's the big news for us today, and then we can roll from there?

Thanks. The big news is that today I am officially announcing that I've joined Lightseed Venture Partners as a partner. After 7.5 years at KP and almost 11 years in the venture business, this new chapter of my career is really exciting in the sense that I feel like I get to step into a truly global platform and really play a role in driving what was once the core of the firm forward, which is this early-stage enterprise investing that really set the tone for Lightseed's success and what it was able to become today.

I feel really grateful to partner with that team. That's the next chapter of my career, and I think it could be the last.

2. Why Mega Platforms Will Win the Next 10 Years of VC

Dude, I'm thrilled to hear it. Congratulations. Amazing news. I want to start on Lightseed. You are one of the few firms that, in the nicest way, are walls of money. There's General Catalyst, and there are a couple of other big names that have pretty much more money than anyone else. Why do you think these mega-platform plays are likely to be the winners in the next generation of venture?

I think we're at this really unique point in time, both in terms of the technology and entrepreneurship industries and, consequently, the venture industry. If you look back 5 or 7 years ago, we would be talking about companies like Databricks, Snowflake, or even DoorDash on the consumer side as the hallmarks of venture success.

I think what we're seeing now is that there's this new shape of company that's emerging that, in some sense, puts those to shame. We're talking about going from $30–50 billion outcomes to multitrillion-dollar outcomes in the form of SpaceX, OpenAI, or Anthropic, where Lightspeed is very proudly an investor.

I think what that means is you also have to take a step back and say, “Okay, where is the alpha going to come from in the industry if that's the case?” What I'm seeing, and what I've been thinking about for a long time, is that these platforms that have the scale of some of those that you mentioned, Lightseed included, get to have really interesting conversations about, “Hey, what if we invest $1 billion in one of these companies that could be worth trillions of dollars? What if we were to succeed in terms of turning $1 billion into $10–20 billion?” I think that's just not a conversation that's ever been had in the venture industry, and frankly, in any other asset class that I'm familiar with.

I think for that reason, it's really clear to me that having the capital stack that these large platforms have is uniquely beneficial at this point in time. But what I will say is that none of that matters if you don't maintain a lot of dedication to early-stage investing.

If you're Sam Altman or Dario Amodei and you're asking yourself, “Do I want to hitch my wagon to one of these firms by raising billions of dollars from one of them?” you're thinking a lot about what their brand stands for. I think these companies, in spite of running toward these trillion-dollar outcomes, are still very much startups and entrepreneurial in the way they think about their DNA. Therefore, they want to partner with someone who shares that DNA.

I think the only way for a venture firm to sustain that is by staying true to early-stage venture, working with raw, formation-stage companies, and spending lots and lots of time trying to figure out who that next wave of entrepreneurs is. I think it's really important that Lightseed continues that focus, and I think that's something they and a few of their peers do a really good job of.

Dude, I love you, which is why I sometimes ask spicy questions. My 2 questions from that would be: You mentioned some brilliant model providers there. When you look at model providers on the whole, taking out OpenAI, respectfully, I think the one lesson that you have is that they're not really venture investments.

I have the data. People who did Anthropic at $4 billion have got about a 3.5–4x return when you combine the dilution and the employee stock payouts. It's not actually that great, considering it's now a 12x model-provider company. Are these mega-exit companies actually venture-funded assets?

I think the story there is still very much being written, is the first thing I would say. At this point in time, to your point, these companies have margin compression. They're high burn because they have very high CapEx in terms of their need to scale their products by purchasing and running lots of compute.

On the other hand, you're also seeing this very promising trend play out in the form of these consumer apps and, increasingly, even enterprise apps that they're starting to lean into. If we look ahead 3–5 years, the margin profile, growth rates, and obviously revenue scale are going to look a lot different for these companies.

At this point in time, I think it's fair to say that you've taken a bit more dilution than you would if you were investing in some kind of late-stage enterprise software company. On the other hand, I think the scale of the outcomes that are possible with these companies, and the types of consumer- and business-facing products they can build atop these models, are really just starting.

If you look at just how unique these companies are on a topline basis, we're talking about billions of dollars of run rate growing in excess of 100% year over year. I don't think we've ever seen that before, right? You talk about ServiceNow doing billions of dollars in ARR and growing 20–30% year over year, and you're like, “This is an amazing company.” These companies are growing over 100% year over year while doing that kind of run rate.

Again, I think the margin question is a valid one, and the long-term cash-burn question is a very valid one. But what I'm seeing is that these companies are just getting started in terms of optimizing the shape of their business by layering these products on top of this very capital-intensive asset that you're referring to in the form of these models.

3. Are Foundation Model Companies Good Venture Investments

It's so funny. I had Vince from Thrive on the show about 15 months ago when they led the $30 billion valuation round. The thing that's so shocking is that when you look at their revenues today, it's about half of that valuation. We questioned it, and I questioned it, and he pushed back, quite rightly, but it just shows the scale and trajectory of the revenue that they've had.

I completely agree and understand that. Can I ask you, though, the thing that I'm struggling with today as an investor, Bucky—and I just use this show to learn—is where sustainable value is generated, where we're not going to get crushed as an investor? You see now, with OpenAI potentially buying Windsurf, the desire to move into the application layer. You see more and more advances in the models moving into applications. Where is sustainable value created, and how do you think about that?

My mental model for thinking about this is actually quite similar to when we were asking ourselves, as Amazon, Microsoft Azure, and Google were rising, which companies would survive that? As they were starting to get into multiproduct, I think what we saw in that era was that there are just so many categories of software that require unique understanding of the customer pain points, unique resource allocation to build the best product, and really just a set of insights that can only come from focus.

I think what we're going to see is a very similar set of dynamics play out here. Sure, in a core market like codegen or maybe enterprise search, where you see companies like Glean being independent today, but OpenAI famously saying, “Hey, if you're an investor in Glean, you don't get to be an investor in OpenAI,” which would foreshadow their plan to play in that space, I think you're seeing that there are some categories where these model providers are going to be very, very active.

But I think what's so amazing about this point in time that we're in is that this long tail of applications is so long and so fat that it's hard for me to see how the model providers are able to play in each of them. Again, I think what's going to happen is that there will be startups and, in some cases, existing incumbent companies that really figure out where those areas are where deep customer insight and deep focus are required.

I just have a hard time seeing how the model providers are going to be able to prosecute each of those. I'd certainly be a little nervous about how the codegen stuff is going to play out today, because it seems like that is far and away the killer use case for LLMs, and therefore the one that these big model providers are going to lean into next from an application standpoint.

Of course, the consumer side of things is very tricky as well, given that’s sort of the hallmark of all these companies in terms of what they put in front of consumers. But I again really feel like that dynamic is going to repeat itself, and there are going to be so many opportunities that exist outside of that core that you’re going to see big companies get built. Those companies are either going to have to be acquired by the model providers, or they’re really going to struggle to compete with them because they monopolize all the customer insights that come from being first, going really deep, and solving customer problems.

You mentioned Glean there, and hey, if you invest in Glean, you can’t do OpenAI. I’m just intrigued: Is the age of competitive investing over? You mentioned being an investor in Anthropic. You’re also an investor in Mistral. Does it matter anymore, investing in competitors?

I think every firm takes a very different view on this. I can tell you that when we were at Kleiner Perkins, it was something that was kind of a red line that we wouldn’t cross. The reason for that is because we invested in so few companies and went so deep with each of those companies that, in our mind, it was just too hard to feel like we could really provide that level of service to each company in a way that would make conflicts a non-issue.

I think it’s a little harder for me to speak about how we do things at Lightspeed in that sense, but to your point, you’re seeing a lot of these later-stage investments get made into multiple players. I think part of that is there’s just so much demand for capital from these big firms that these model providers want. On the other end, it’s really hard to say how this is going to play out, to the point that I think there’s a need for diversification on the investor side as well.

One argument would be, “Hey, pick one. Pick one of these companies and go all in on them.” You can see that’s sort of what Thrive is doing with OpenAI. You could say the same about Founders Fund. Another would be, “Hey, who knows how it’s going to play out?” I think what you’re seeing with, say, Andreessen Horowitz is they’re trying to invest in every one of these companies. I think it’s a rational strategy so long as you have buy-in from the entrepreneurs, so as not to ruin that relationship.

One of the reasons you have competition is because there’s a finite number of people who can write such large checks. When we think about the universe of mega-platforms, will that universe increase significantly in the next 5 to 10 years as we see outcome sizes expand, or will that remain relatively similar as LPs concentrate dollars into known brands?

I’m not an LP, but like you, I do spend a lot of time with LPs. What I can tell you right now is that it’s harder and harder for me to see how too many of these mega-platforms can exist in the coming years. The reason for that is, one, the commitment from the existing large pools of capital in the LP community, right? If you’re an LP that wants to fund one of these efforts, you’re really making a multifund commitment.

As you know, sophisticated LPs invest with any manager for at least 3 to 4 funds, and they know that is the optimal way for them to capture that alpha because it’s really hard to be timing the market, as we all know. So, if you say, “Okay, in the backdrop, it feels like a lot of these big LPs have committed to these platforms,” it’s pretty hard to see how they can commit to too many more of them, just on the basis of the physics of how big they are and how much capital they’ve committed.

4. Why Every Firm Has to do Pre-Seed To Win in VC Today?

I think what’s really interesting about this space that we’re in in the market right now is, like you said, there are these companies that can get really big, consume large amounts of capital, and generate potentially outsized returns for investors writing those large checks. On the other hand, it doesn’t appear as though the supply of capital from platforms like the one that I’ve just joined, or some of the others that we’ve talked about, is going to go up in size.

So again, you could argue that these 5 to 6 firms have this captive opportunity to really play a role in helping these companies scale and be their partner. I think that’s a really exciting dynamic for these mega-platforms.

How much bigger do you think they could get? We do a show with Rory O’Driscoll every week. I think Rory is fucking brilliant, by the way. He’s the wise sage who just schools me every week. But he’s very smart when he says to me, “Hey, we’ve seen this fundamental transition of capital supply from your very, very large Franklin Templeton, you name it, to Thrive and Lightspeed, who are doing these rounds and doing $30 billion rounds into OpenAI, for example. Fundamentally, if we continue to see that transition, how much bigger will these mega-platforms get?”

Look, I think that’s a tough one because it really is somewhat indexed to this question of how these megatrends—like space, robotics, and AGI—play out, right? If we’re really talking about companies that are going to get to some level of AGI such that they’re going to be not just multitrillion-dollar companies, but potentially larger than that, then these companies may not have to go public for a really long time because there will be so much demand to continue supporting them from the private markets, which, as you said, are very robust right now.

5. What Applications Will Model Providers Buy/Build? What Will They Not?

If we’re talking about how Starlink and the kind of assets being built around that could scale to those heights, these companies may not have to go public for a really long time. So, the honest-to-God answer is I don’t know. I think we’re going to find out as an industry over the next few years, and it’s really going to come down to how some of these truly blue-chip assets that are scaling to those levels trend and how the market shapes around them.

Do you think we’re going to have an incredibly concentrated supply of these truly blue-chip assets? What worries me is that we’re going to have the haves and the have-nots, and everyone will go, “Well, we’ve always had that. It’s always been a game of 1%s,” but I mean truly the 1%s, the 0.01%. Do you think that’s the case, or do you think there will be a more even distribution of value in the next generation?

I think if you polled investors right now and asked them how many of these really, really valuable companies are going to exist in AI, defense, robotics, and space, most of them will tell you there are going to be maybe a few of these companies that get to that really, really massive, unprecedented level of scale.

On the other hand, I think we’re still really early in the supercycle of each of these areas, right? There’s a lot of talk about how it’s going to be Helsing, and there’s a lot of talk around how it’s going to be OpenAI and Anthropic, maybe xAI. I just don’t think we know. When I look at a trend like robotics that is still so early, at least in my mind, I’ve convinced myself that this time is truly different in terms of the industrial applicability of these products. It really looks like we could be surprised to the upside.

But again, this is our job as venture investors: to be very, very optimistic. So, I think the number-one constraint to this whole experiment playing out favorably will be whether there are more than 1 or 2 of these per megacategory.

6. How to Approach Price Sensitivity in a World of AI

Price is always very hard when you have one of these prized assets. It always seems painfully expensive in the short term and, bluntly, very prudent in the long term, often. How do you think about price sensitivity when paying up for the 0.01% assets?

My former partner Mamoon has taught me many things, and one quote that sticks with me on this one is, “The best companies always feel expensive.” I think that’s proven true in every example I can think of.

I think it’s really about determining, one, whether this is one of those truly special companies. Obviously, the earlier you have to make that decision, the much harder it is, and the error rate is going to be higher. I think therein lies probably some reason to be a little bit more constrained in your thinking around price.

On the other hand, this dovetails into a question of what it takes to win a competitive round these days. I think there’s always someone who is going to believe more than the field, right? So, if that is important to the founder, then you have a hard choice to make. Whereas, if you think that at Series A this is a very special asset and they’re pushing price beyond the way your mind can rationalize it, history would say that those companies always feel expensive. Those companies can run and compound for a very long time.

I think especially today, when we’re in a world where these agent products are quite literally going from going after existing software spend to starting to replace human labor, it kind of comes back to this optimism I have around the size of these outcomes. I really believe that these software companies that are not just augmenting but, in some cases, replacing the work that humans do—and the budget allocated toward paying them for that work—are going to get bigger.

Right? So, the way I think about things today is, when you find one of those companies that has demonstrated some path to market leadership relative to the field, because all of these categories are very competitive, which is another very challenging dynamic.

7. Why is it BS to do Market Sizing When Making Investments in AI

My view is you really have to build conviction and go all in in such transient times. Does market size matter at all, or is it worth doing market-sizing work like traditional investors used to, when we really don't know more than ever before?

Yeah. The honest answer is, it depends. A case where I would say it does matter is if you're building, let's say, a cybersecurity company where the play is that you have a better solution to something that already exists. You know exactly how much is being spent on that thing, and therefore your opportunity is to go and capture as much of that existing spend on that thing and then grow with that market.

I think market sizing really matters in terms of just being sober about the size of the opportunity, and honest with yourself about the right way to build that company and capitalize it. I think there's this other case, though, where you're doing something fundamentally new. If you're doing something fundamentally new, the act of sizing a market is, at least from my experience, so imprecise that it borders on being a fool's errand.

Number 1, I think you've heard many people say this, but I very much agree with it: the best founders are just so creative and have so much ingenuity in terms of their ability to essentially set their own rules. What I mean by setting their own rules is they get to decide what market they're playing in, and they get to convince customers that there's this market they didn't really think about before, and that they should be in it.

I think, in that sense, you have this way of kind of dictating that, and therefore trying to size it is just really, really hard. Some of that is building new products; some of that is reframing an existing view of how to solve a problem into something that comprises a new market.

Then there are these compound startups. Rippling is, of course, the company that everybody loves to talk about in this sense. With Rippling, sure, you were kind of starting it thinking about it as a payroll product, but they have just been so unbelievably effective at layering on new products that have synergies with the existing core that the market size just keeps getting bigger every quarter.

Personally, I don't spend a lot of time sizing markets, but I do think that for companies going after an existing market, it would be crazy not to at least think about the size of that market.

Many people have said to me on the show before, like Nabeel at Spark, who's a co-investor with you in Anthropic, that the age of spreadsheet investing used to work for the last decade of enterprise SaaS, but it no longer works in this next generation. Do you agree with that, or, bluntly, is there still hope for spreadsheet investors in the next decade?

I would say that I think the window that spreadsheet investors have to gain access to these companies is just a lot narrower. These really, really blue-chip companies that are wielding AI in some interesting way—for example, let's say they're building some kind of agent that's going after a large existing pool of labor and automating it—are just raising so much money early, before there is a spreadsheet.

One's ability as a spreadsheet investor to get exposure to those companies at the kind of entry price and stage that they're used to, I think, is changing a lot. My view is that these spreadsheet investors are just going to keep getting pushed later and later stage. Again, I think the book is still being written on whether that's a good thing for the industry.

What I would say is that there's just so much conviction among top investors at the early stages for companies like that, that they're just willing to take more risk.

Sometimes in my head I wonder how spicy I can be, and then I just think, go for it anyway. It's not [bleep] live. My question to you is: You mentioned they're raising money early and a lot of money early. I mean this with respect, but I think you mega-platforms are destroying seed. Time and time again, I see $10 million on $50 million, and it is not good for the company. You beat us. To be clear, you beat the seed funds because you just come in and buy it.

I get it. We do $3 million on $15 million. You guys come in and drop $10 million on $50 million. It's a market—fine—but I don't think that is good for the companies, and rarely do I see that play out well. How do you respond to that? Do you think I'm wrong? How do you feel?

I can tell you that I have been involved in multiple situations where companies look back on their fundraising approach and say, “Hey, we raised too much money at too high a price, and now the flexibility that's afforded to us—not just in downside scenarios, but in some cases in base-case scenarios—is more limited than we'd like it to be.”

I'm completely wide-eyed about the trade-off there. Any time a founder I work with is thinking about going down this path, I try to have that honest conversation with them and say, “Hey, if I were you, this is how I would think about it.”

Of course, there's a way that you can raise more money at less dilution, and if that's all you're thinking about, then that path may seem like the right path. But on the other hand, there are so many scenarios in which preserving optionality makes a huge difference. Therefore, keeping dollars in and the value of your 409A, or your post-money of your last round, as low as possible is very, very beneficial.

To me, there are certain companies and certain types of founders that I think are better off and very comfortable going the “How do I raise as much money at as efficient a dilution-to-price as possible?” route. Then there are other founders who I think you really have to help understand the downsides of that, because they've never done this before.

Ultimately, it's the founders' choice. In terms of how latest-stage investors may or may not enable that, I personally take a view on that as well. When I believe the company's up for it, when I believe the company has enough pull and enough potential to be a little bit more aggressive with fundraising, I'm okay leaning into it. But I don't feel that way about every company I work with, and I'm honest with the founders about that.

We have hundreds of thousands of founders listening, and they'll be going, “Great, great. This is getting good, but which camp am I in? Am I in the one that could raise more and should raise more, or am I in the one that should stay leaner and be more milestone-driven and capital-efficient?” How would you delineate between the founders that should and should not raise those slightly—what, jumbo seeds versus normal seeds?

I think this actually comes back to the market-sizing question you asked. There are certain companies that have a very deterministic sense of their market opportunity. Let's say they're going and replacing something that already exists. You see this a lot in cybersecurity, for example. These kinds of companies understand the headroom, and they understand that if they get this much market share in this period of time, this is how big their business can be and therefore how valuable it can be, with a modest degree of confidence.

Where I get really conservative in terms of the advice that I give founders I work with on fundraising is when companies are fleshing out a new market. We just don't know. It could be really large; it could be nonexistent.

The cases where I've been involved with companies where they've done that wrong are when they just didn't understand their market yet. I think if you have a poor understanding of your market and there's a nonzero chance that that market could be very constrained, optionality is without a doubt your friend. I'm very honest about that with the founders I work with.

When you say optionality is your friend, I could take that in 2 ways. I could say the market is unknown, and the optionality is extended runway. Actually, raising a larger round will give you more at-bats, enabling you to have more goes at an unknown market. But I think you meant optionality in a different way: having a lower price.

No, I definitely did. Sure, in the case where you feel like you're drawing dead, the ability to find a good home for the company and do good by your investors and your employees is, let's just say, much easier to come by when you keep the valuation down. We all know how that works with corporate acquirers. I was once on a corp-dev team, so I know that world very well.

But I think there's another form of optionality. If you really think that the market opportunity, or the range of outcomes that you're scaling into, is so vast, keeping it lean also allows you to say, “Hey, if this doesn't work, do I really have to spend the next 4 or 5 years of my life working on this thing that I'm not sure of?”

That time is so precious for great founders. I've been in situations with founders before where it feels like they are drawing dead and the market's not resonating the way that they thought. Sometimes I think having that extra 2 or 3 years of runway can actually be really, really punitive, given the opportunity cost associated with amazing founders' time.

I really try, on a personal level, to be honest with them about, “Look, is this really what you want to be spending the next 2 or 3 years of your life doing?” If you go and raise too much money, sometimes you can kind of be stuck with that. There are countless companies in the industry right now where you have really talented founders working on something that's kind of working, but maybe not working to the degree that they hoped, and in some sense they're kind of stuck with it.

Right. I really empathize with that, and I'm protective of the founders that I work with because I care about them and I value their time. I think their time is valuable. How fast do you know when a company that you've invested in is not working and not what you thought it would be?

Look, this is a hard one. There are examples like Figma, where they toiled in obscurity for some time and became amazing.

Do you buy that today? Dylan always seemed to be brilliant across the board. When you speak to John Lilly, who led the Series A at Greylock, he was clearly brilliant. The company was not hitting, but he was brilliant. Do you know what I mean?

Yeah. I think you have a lot of very special founders whose companies don't work, and so you can say that about a number of founders and a number of companies. But I think you're starting to see more and more evidence of companies that just took longer than people thought. There are so many now. It's not just Figma, so I think you have to stay open-minded to that.

There's another dynamic at play here, which is that so much of the low-hanging fruit has been picked off the tree in terms of software businesses that you can build. You're starting to see the most interesting companies be those where there's something deeply technical—a problem they have to go and solve that's never been solved before. In doing so, that can take, in some cases, multiple years to get right.

A recent example of this is Clay. Clay is this company that's growing very fast on the sales tech side, and if I'm not mistaken, it was 5 or 6 years of very little to no growth before it took off. I think you have to be open-minded to those outcomes. I personally try to lean into those outcomes because sometimes, if something takes many years to get right, assuming it's something deeply technical and R&D-intensive, that can also be something that's very defensible and hard to replicate.

I think the game has changed a little bit on this front. These more deeply technical software products just take more time, and you do have to be more open-minded to these timelines being a little bit different from the canonical idea that it either works in the first 12 months or not.

I'm a little bit worried, if I'm honest, that the game has changed so much in terms of revenue trajectory and scaling. When you look at your Cursors, your Lovables, your Bolts, you name it, their revenue scaling is so unparalleled. Then you look at a generation of Series A or Series B companies that are doubling, maybe 2.5x-ing, and they're going from 7 to 14 or 14 to 28.

When I send that to you, Bucky, for a Series B or C, I think you're going to stack-rank it against the AI companies and go, "This just isn't that interesting." Am I right to be concerned about that? Are we in a fundamentally different world of revenue trajectory and scaling?

Look, I think core to any VC's job is the ability to prioritize and ruthlessly reprioritize. Part of that is just asking, "What are the best ideas that I have in front of me at any given point in time?" I'm going to spend time on those. Right now, to your point, the bar is going up for what the best idea looks like when it comes to growth rates and momentum.

We can talk about the quality of that revenue and how it's very mixed. This has been discussed many times on this show and outside of it, so I don't need to repeat that. But I really think you're right to say that what great looks like has really changed.

I think the book is still being written on some of those companies that you mentioned, and their peers, in terms of just how durable that revenue is. I'm not going to repeat myself and go down that rabbit hole, but I think what you're seeing is that the pent-up demand for intelligence in all of these different areas of work is so unbelievably high that the growth rates and the market pull around these companies are like nothing we've ever seen.

As an investor, when I'm out there looking for new ideas, I'm often looking for the signals that I saw in companies like Glean or companies like Windsurf that have just had this incredible market pull and reception. It's almost made me feel like I've become a more discerning investor, in the sense that there are signals that I saw for those companies that were foreshadowing what was to come, and I can now look for them in other companies.

What are those signals? That's fascinating. You have such a unique perspective from Glean and Windsurf in particular. What are those signals?

First, I have to give kudos to my former partners [names unclear in raw captions] for being the leads and being involved in those 2 companies. What I would say is that those 2 companies, in particular, found this zeitgeist at the seniormost decision-maker level.

If you go and talk to a CIO or a CTO of a large enterprise today, they're furiously seeking out ways to apply AI to their business. The reason for that is because their CEO and their board told them, "You're going to get fired because the entire fate of our company depends on leaning into AI if you don't help us do this."

There is this voracity and appetite to bring new solutions that comprise what it means to bring AI into business into these companies like I've never seen before. I think Glean found that very early on, and the rest is history. It's just been on an incredible trajectory and, I think, scaling into a true household name that embodies what the AI app business of tomorrow looks like.

Similarly with Windsurf, they did a really good job of going to these large enterprise technology leaders and helping them understand where the future was going and the role that they could play in shepherding them that way. I think you're going to see more and more of that. Once there's a magic moment that a CIO sees, there's a bit of this mimesis that picks up, where every CIO is going to hear about the fact that they adopted this technology successfully and then they're going to want to go and do it themselves.

I personally am looking for companies that really can be something that the CIO walks into the boardroom and says, "Hey, this is that thing that you asked me to do. I've adopted it. It's working. Employees are happy. We're getting all these productivity gains."

I think we're just scratching the surface of where that's going to show up. You're going to see it in finance. You're certainly going to see more of it in software engineering. You're going to see it in cybersecurity. Glean and Windsurf are just good cursory examples of that trend that's going to continue playing out and why I'm so bullish on these enterprise apps.

It's so funny you said that about the signals there. You said that revenue trajectories are faster and clearer than they've ever been, which was a leading question for me because I always think about sourcing, selecting, securing, and servicing—the 4 pillars of venture.

You said before that you believe picking is more important than winning as a lead investor, which goes against what we just said. If the signals are clearer than ever, it takes less to pick the winner, and there's more emphasis on winning. I'm fascinated: Why do you think picking is more important than winning as a lead investor at a multistage firm?

Let's unpack this by first talking about what it takes to win in one of these really competitive opportunities. I feel like there's this meme going around that it's all about a famous VC picking you up in his helicopter and flying you to his house on an island, or the courtside seats at a Warriors or Knicks game, or the Michelin-star meal with a famous person joining.

Look, these parlor tricks exist. Every firm engages in them. Depending on the founders, they either respond positively to them or not. But ultimately, what I found in practice is that none of that stuff really matters. What matters is whether you put the work in to develop a deep connection and a deep set of insights with that founder, their vision, and the company that they're trying to build.

That just takes time. I think it takes time in the sense that every process I've been in that has been highly competitive, the winner, if it wasn't me, was the person that had been doing that work for the better part of a year. I'll give you a quote a founder told me once when an opportunity didn't go my way. He said, "The person that I went with just had insights about the business that not even my existing investors had."

The only way to develop those insights is from spending time thinking about the business at the level the founders do, more than just about anyone but the founders. How this comes back to picking is that you have to pick which companies and which people to do that with.

8. Is the Future of VC Domain Specialization

If you don't and you rock up to one of these processes that is very competitive, there's always going to be someone who is at a great firm with a great brand who has done that work, and that person will win. I see it every day.

So, is the future of venture domain specialization?

I think this is a very good segue into, theoretically, why domain expertise and specializing in domains matters. If the game really becomes, "How do I pick which founders to spend time with?" and, when I meet a new company, "How can I readjust my prioritization of spending time developing insights and rapport with that founder and that company?" domain specialization really helps there.

So again, there will always be brilliant generalist investors who can do a good job of this, and they just have uncanny instincts for startup quality and founder quality. But in my opinion, being domain-focused really, really helps with the picking aspect: picking who to spend time with and who to position yourself with for when they do decide to raise.

Ultimately, when they do decide to raise, it allows you to reinforce that: “Hey, did I pick the right person to spend time with, or am I just running away with this because I’ve spent so much time on it?” That’s a whole other bias you have to manage.

It’s so funny. I have so many LPs who ask me this question, and I actually disagree with you on the picking element there. I don’t think domain specialization particularly helps you pick. I think generationally defining founders are quite obvious, respectfully.

That said, I think, to your point, they choose you because you’re the smartest. So they go, “Bucky, to your point, made me think about it in a different way. Harry was super nice, but he didn’t make me smarter and he didn’t know the market like Bucky did.” So, totally to your point, it helps you win.

Can I ask you one? Do you even need to pick, my friend? You’re now at Lightseed. You can just wait. I mean, part of me, as a friend, would say to you, just wait until the Series C, pay up like Vince did at Thrive for the, you know, $30 billion round, and ride it, baby.

Look, that strategy can definitely work, but I would argue—and this is maybe the world’s smallest violin—that picking is actually much, much harder in these larger firms that have notoriety in the market. The reason for that is because the opportunity set they have access to and the number of founders who are willing to lean in and work with them is just higher, right? So you just have more inventory to choose from.

I think because you have a little bit of magnetism to you as a platform that a lesser-known firm doesn’t, you just end up having a lot more at the top of the funnel to sift through. If you’re not very diligent about how you prioritize and manage that, picking can actually be the failure mode of a lot of GPs at these funds.

Can you unpack that? What do you mean? They pick duds and that becomes apparent quickly?

I think ultimately it’s really hard when there are so many founders coming in your door, which many firms, like Lightseed or Kleiner Perkins, have the luxury of experiencing. It’s very, very hard to figure out what the 9-out-of-10 one is and what the 10-out-of-10 one is.

You can talk about that in the context of who the great founders are. You can talk about that in the context of momentum. But my point is, it’s a very humbling job for that reason. To say that no one has to pick at an existing firm because the great companies are the great companies—that just hasn’t been my experience.

On the picking side, when you’ve picked and you’ve picked wrong, what did you not see that you wish you had seen?

I would say the single biggest thing that I’ve changed my mind on as an investor in the 11 or so years that I’ve been doing this comes down to what I did before investing. As I said, I was a member of Cisco’s corporate development team.

At a place like Cisco, when you’re a member of a corporate development team, your job is to go and look at markets and technology and figure out: What are the lucrative markets? What are the dynamic markets? And then what is the right technology that the company should have to go and prosecute that market? Notice I did not mention founder quality or quality of execution in that entire statement.

So I think when you come from a role like that and move into venture, it’s very tempting to apply that same lens to looking for great companies. Again, I can’t say anything about this that hasn’t already been said, but it’s very, very obvious to anyone who’s been doing this for a long time: You just get this visceral feel that it’s all about the founders.

I would say the thing that I’ve really changed my mind on is that I used to go around developing theses and trying to figure out where the world was going at the level of markets and technology. Now what I’ve realized is not to say that work doesn’t matter—it’s actually very important and very useful—but really, all it does is give you a flashlight to say, “Okay, these are the areas where I want to go figure out if there are amazing founders or not.”

The hardest thing to do when you’re a thesis-driven investor is to do that work and have the humility and the restraint to conclude that there aren’t great founders in that space. That’s okay, because I’m going to move on to the next one. What matters is that I find those people. So I would say that’s the thing that I’ve changed my mind on.

To answer your question, the bad investments that I’ve made have been because I’ve downweighted the execution capacity of the team and the quality of the team that the founders can build around them, at the expense of my intrigue for the product and the technology.

Do you believe we have too much money chasing too few amazing entrepreneurs?

Honestly, Harry, I think I’m just too much of an optimist at heart to say that there’s too much capital flowing in. I think it’s easy to say that on the bad days, but ultimately there is just so much amazing work to go and do.

Really, I think we’re bound by whether we can help enough of these founders who come from unlikely backgrounds go and pursue their visions. I personally have a view that the industry is in a healthy place, and it’s just hard for me to say there’s too much capital chasing too few opportunities.

I feel like I’m seeing the future every day, candidly, and I just can’t spend time on every single one of these.

Do you agree with the challenge that I’m facing, Bucky? I’m going all over the shop today, but it’s very hot in London, I told you, and I’m so enjoying this.

Before, there were 2 or 3 companies that were competitors when you were looking at a market, and you’d be going, “I need to analyze them. I need to understand them. I need to meet them.” Now there are 15, often more. It feels like the competitive set for every company has exploded exponentially. Do you agree? And how do you think about that when investing in one and determining ultimate value creation?

9. How to Know What Company Wins in Super Competitive Markets

I would certainly agree with this. I think it’s the single biggest challenge of making seed and Series A investments right now. Let’s take these AI app categories that we’re meeting every day, for example. It used to be the case, as you said, that there might be 1 or 2 players that you’d have to pick between, and now there are probably more like 4 to 6.

I can tell you a recent example in an anonymized way. One of the most recent investments I made was in an AI app company, and we had been spending time with this team since they had raised a very small seed round. We had been really excited about the category and building a lot of altitude on it, but everyone’s product was under development. So it was really hard for us to determine who had the best product.

Okay, that’s fine. Then figure out who the best founder is, right? There was a set of founders that had deep domain expertise in this area but were very light on the AI side of things. Then there was a set of founders that had very deep AI expertise and were very light on the domain expertise.

I can tell you that we waited to pick the company we pursued, and we succeeded in pursuing an investment in the one that we wanted. But I can tell you the price was a lot higher than it would have been had we leaned in earlier, right?

I think what that came down to is that we wanted to see whose products were good and whose weren’t. With hindsight, there’s an instinct that I’ve honed in on, especially with these AI app investments: You think it’s the domain expertise that matters. Without a doubt, it is the AI expertise that is more scarce and therefore matters more.

I can tell you right now that there are companies out there that have deep domain experts building application-layer AI companies, but they’re really struggling to recruit the AI engineering talent that you need. Given how fast this technology is moving, you have to have people in the company who have innate instincts for how to wield it and how to understand where it’s going, and therefore build for that future versus build for today.

If you don’t have people on your team who are truly AI-native and truly AI engineers, you’re just not going to nail it the way the team that does will. A good public example of this would be Harvey, right? Harvey has the perfect union of a former lawyer and someone who has deep, deep AI engineering expertise in the form of their CTO.

They’ve been able to recruit an incredible engineering team of AI practitioners because that leader is someone who has that expertise. The other form factor of this that I don’t think works as well is when you have CTOs who are domain experts—they’ve built something in the category they’re working in—but they don’t have that AI engineering expertise. They’re just not able to get the talent in the building that I think you need to be a market leader in one of these big categories.

It’s interesting that you said we had to pay up a lot more than we would have if we’d come in early. Bucky, I don’t think you can do venture unless you start from the beginning.

And what I mean by that is the idea that you could do B and beyond and do great is so much harder—almost impossible—today. I think you see that with all of the mega-platforms also doing pre-seed. And who won from Windsurf? Neil Mehta at Greenoaks led the seed. Neil is a prolific seed investor and brilliant at it, by the way.

DST are prolific seed investors, the huge growth firm of old. I don't think you can win venture unless you're doing pre-seed. Discuss. Do you agree?

Yeah. This kind of comes back to my view that I shared with you about how, if you're going to build one of these mega-platforms and sustain a compelling position in the market with one, you really do have to stay dedicated to the craft of helping people build things from scratch. To do that, you have to be in the pre-seed and seed business. I think the moment you stop doing that is the moment you lose the instincts for just how fast these companies can change and how quickly the story can improve, such that you sit back and are looking for perfection instead of really seeing what these companies can be.

I actually think these AI app companies we keep talking about are a great example. If you looked at Harvey at the Series A and saw its product, you probably weren't that impressed, right? It was just a very early product. The scaffolding of it was clear; what was possible with better models was clear, but it was still a very early and raw product.

I think one of the mistakes that a lot of investors have made in this wave of AI investing, as it relates to these app companies, is that they've failed to imagine what they can be as the models get better, as their understanding of the pain point gets better, and as they spend more time with customers. So I think where this comes back to this question is, if you're not spending time with early-stage companies and you don't have that sense of just how fast things can change when companies are moving fast, you start to lose sight of that. You make mistakes where you start to take a fixed view of these companies rather than a more fluid and dynamic one.

So I agree strongly with your statement, and I think it's especially important for these really, really large funds to be playing there actively for the reasons that I described. But I would add or amend yours and say, for the reason of access.

That sounded very nice—empathy and wonderful. I completely agree. We're also empathetic.

[Speaker?]

Yes, completely. But actually, it's a game of access. I speak to so many of my friends who are at just Series B and beyond firms, and they're like, “Harry, can you send this 50-customer call log to one of your companies that I've done? I want the first meeting.” And you're like, “You did 50 customer calls for a meeting? You did this 28-page market analysis for a first meeting?” The cost of first-meeting entry has gone through the roof, and so you cannot get that first meeting unless you've been at the pre-seed or the seed.

I would say it's possible if you make a very small investment in a company at the very early stages to use that as a wedge to build a compelling relationship with an entrepreneur. But it is by no means a given. I can tell you countless examples of where later-stage firms, or even just firms that weren't necessarily the lead investor in the early days, did something with low conviction, thinking they were going to get access, where it just didn't serve them.

I think it really comes down to this point about picking once again. If you're going to start doing that as a later-stage firm, you've got to be committed to putting the legwork in to actually use that as a wedge to develop the relationship that does give you the access, because I think the check itself does not. And so, where this comes back to picking once again is, let's say you do that 100 times—which of those 100 are you going to put that work in with, right?

You have to have taste, judgment, and an instinct for, as these companies are developing, which of those you need to really spend time with. I think that goes for any investor at any stage, which is again why I believe picking is more important than you do.

10. The Risks of Multi-Stage Investing: Is Signalling Risk Real?

Can I ask you another spicy one? If you go really early, you bring in a question of multi-stage investing in terms of signaling and the risk that comes with signaling. People go back and forth on it. I do see it impacting companies when you have your Accels and your Indexes. Maybe this is more of a European thing, where the markets are more consolidated, but your Accels and your Indexes lead a pre-seed or seed and don't do a Series A. It kills companies. Do you agree or not?

What I'd say is that when a larger, multi-stage firm does lead a seed round and decides not to lead the next round, that is certainly something that the next round of investors are going to want to understand better and think about, and will take as a signal. There's no doubt about it. I'm not going to deny that.

I will also say that any seed investor competing with a multi-stage firm will go very, very out of their way to instill this wild fear in the founder's mind about the risk of that. I can tell you that what I've seen in practice is that I don't think it's as much of a risk. Perhaps I'm biased. I have worked at a smaller firm before and been on that side of the fence.

What I would say is that when a firm doesn't want to go and do that Series A, it's really just the fact that the company hasn't necessarily achieved the milestones that they agreed upon with the entrepreneur in the early days for the company to be Series A-ready. Sometimes that's a downside scenario where things didn't go as well as you'd hoped. Maybe they took longer, and you just have to go and raise because you have a runway issue.

Usually, what I find is that it's just the quality of the company at that stage and how they've executed against the milestones that they set forth that determines the Series A's success, rather than the whimsical taste of the multi-stage firm that led the seed. What I find is that there are absolutely cases where a multi-stage firm will say, “We feel good about our ownership. We feel good about the amount of money we have in the company. We want to help you raise a Series A from someone else, and we'll do pro rata.” If that company is a good company and has hit its milestones, that round will get done, and it does all the time. Often, it's another multi-stage firm that comes in and does that.

I can tell you that there is this meme where a company doesn't perform to expectations, and then the fact that the Series A comes together seems to be blamed on the fact that the multi-stage firm didn't want to follow on. I just don't believe that.

I mean, there is a hard answer, which is: if you back yourself and you believe that you're going to crush it, if you crush it and you hit your numbers, a great firm will follow on. If they don't, you'll get someone else. The hard part is the middle ground, which is when you do okay and you don't get the support, or when you're orphaned. I've seen that happen a lot, especially with the changes in venture that we've seen in the last 1–2 years. A lot of companies have been orphaned, and it does make it harder when you don't have an internal champion.

I think that's fair.

I do think a lot about that. Can I ask you, when we think about the next generation of venture or the next decade of venture, do we play collaboratively together in it? I mean this nicely, not conflictingly, but I'm more of a seed-only manager. I've got smaller funds, obviously. Do boutique seed specialists and these mega-platforms play collaboratively, or do the mega-platforms, bluntly, just have a different cost of capital and eat seed?

I think the answer is somewhere in the middle. Of course, multi-stage firms, by virtue of being multi-stage, want to be first, right? That's where the generational returns get made. We've seen that time and time again. If you look at some of the best venture investments in history, they've been these seed investments in companies that have gone on to grow really, really large, and they've come from an investor who's continued to concentrate more and more capital in that company over time, so that they have a large amount of ownership at the end of the day.

That is where I think the competition lies, and that's obvious, right? But I also think that the great seed firms, for one, are heavily reliant on collaboration with the multi-stage firms as sources of capital for downstream rounds. Conversely, I think that every good multi-stage firm is humble about the fact that there will be companies that were either non-obvious to them or not visible to them that these seed firms will find and will be good partners to.

For a multi-stage firm to alienate those seed funds and say, “We just don't want to work together at all,” would be crazy. I can tell you that none of the multi-stage firms that I know well do anything but seek to be very collaborative and follow what the seed firms are doing very closely for that reason.

What have you changed your mind on most in the last 12 months? For me, 12 months ago, I was quite dubious, honestly, of OpenAI's long-term sustainability and enterprise value. Now, I think it's unwavering that they'll be a $2 trillion company. It's unwavering.

So I think, for me, the thing I've changed my mind on the most in the last 12 months, specific to AI, is how to think about the net revenue mix of companies like OpenAI and Anthropic.

I remember when investors were considering participating in a $30 billion valuation round for OpenAI. The question in the room was, “Should we even value this ChatGPT thing as anything?” Is it worth anything, or is it just a proof of concept to show what the model’s capable of?

Conversely, I think people were looking at these API businesses, where they make the model available to developers, and saying, “Hey, this is going to be like Stripe or Twilio, or the next great API-driven business.” What happened in practice, which I didn’t anticipate, is that it turns out these API-driven businesses are really, really tricky.

First, you have this 100x year-over-year decrease in prices per token. You have downward pricing pressure that is inevitable, driven by the competition. Second, you have this almost-zero switching cost. Let’s say Claude releases a new version of its model, and I think it’s better and performs better against my evals, and I’m currently using OpenAI. It’s not terribly hard in most application areas to switch to that model.

So, you have downward pricing pressure, zero switching costs, and a lot of competition. Then you have this ever-increasing need for CapEx to drive that innovation forward. That just has a death-by-a-thousand-cuts impact on the quality of those API revenue businesses.

What you’re going to see is that those businesses where a company has the flagship model that everybody wants for a given use case—for example, you could say Anthropic’s been very dominant in code generation—will look very healthy. But the moment another player releases a better model in that use case, the revenue is going to yo-yo.

What I’ve really come around to is that it’s these products that are going to be built on top of these models, even inside the model labs and not just by third parties, that are going to be much, much more compelling businesses long term than the model APIs themselves.

Does Anthropic not have to acquire, then, and move into the application layer?

It seems very likely to me that, in some form or another, every single one of these frontier model labs will begin building both business- and consumer-facing products. I think what you’re seeing with OpenAI is certainly foreshadowing of that. You could argue xAI is trying to build its own super app around its models, and it’s hard for me to see how each one of these players doesn’t end up in that place.

Now, there is a unique play here, which is SSI, likely Ilya Sutskever and Daniel Gross’s company, which said, “We’re not going to do that.” You could say, “Hey, that’s a really contrarian move,” but what it allows them to do is keep a very lean team and take a straight shot toward AGI, as they famously talked about.

How do you analyze that? What does it allow you that the other strategy does not? Does that increase your velocity to AGI?

I can’t speak for the founders of that company, but the argument that I would make would be that today there are a lot of decisions that trickle into the R&D and research organizations of, say, OpenAI that are in service of helping them build better products in the short term. The model needs to behave a certain way so ChatGPT can be better, Deep Research can be better, or whatever it may be.

There are definitely short-term optimizations being made there. I’ve seen it with my own eyes when I talk to people who work at those companies. The argument for not getting caught up in that is that you can just be entirely long-term. You can make bolder research bets, allocate resources differently, and maintain a smaller team that’s more focused, as you said.

I think that’s really the argument: having to generate revenue and build a business that you can take public someday is going to come with short-term thinking. If you say, “Hey, let’s assume we have access to the capital that we need, and let’s say we can just sweep all that aside,” what does that buy you? I think it buys you less distraction and more ambition.

Fascinating. Did you do SSI?

I can’t comment on that at this point, but I suspect SSI will announce its fundraising and its investors and talk more widely about that.

My question was more like: do you just have to be in every landmark company? When you have as much money as you do, it’s like, fuck it, it reaches a certain size, we have to be in it.

My sense is that, without going overboard on conflicts of interest, being in as many of these companies as possible, given what I know today, is very rational. But I also think it’s rational to say, “Hey, we believe in 1 of them. We’re just going to concentrate all of our resources in that.”

I think there’s no middle ground. You either have to be in all of them or you have to pick 1 of them. That’s my view.

Can I ask what most people believe about AI that you think is wrong?

It seems like most people believe that this path to AGI is just an ever-increasing upward slope. Again, I don’t have strong intuitions on whether that’s true or not, but my instinct is that we should be much, much more open-minded to the possibility that we could arrive at some form of plateau and still have an incredible outcome for society and an incredible outcome for entrepreneurs and venture investors.

In a sense, you could say, “Hey, AGI is already here in certain pockets.” There are clearly things that these products can do that an army of the smartest humans in the world would never, ever be able to try.

Now that we have test-time compute—the same thing that brought us AlphaGo—that is sort of bringing an equivalent of that in all these different domains. Unlike the human brain, these AIs can just try hundreds, thousands of different paths to get to the best possible answer, whereas we have to think about the best one.

In a sense, humans are still predicting the next token, whereas I think these models with test-time compute infrastructure are able to figure out, “How can I try this 1,000 times and then decide what the best next token is?” As a result, to me, AGI feels like it’s here in a lot of ways.

Even if we were to say, “Hey, the capabilities that we have today are it, and it’s not going to get any better,” we are so early in bringing these capabilities to bear in society and in industry that I personally think it’s an incredible wave of technology, even if progress halts.

Okay. I think there are a lot of people holding out for this moment of singularity. I’m not sure it’s as black-and-white as that, and I’m not sure it’s as critical as that for the industry to play out favorably for all these different stakeholders.

My question to you is: what do you think the likelihood is of plateauing, like we saw in self-driving for many years, versus a continuing progression in efficiency, which we’ve been seeing over the last year?

I think when it looked as though pre-training was no longer as lucrative a scaling dimension as it was originally positioned to be, there were a lot of people who were rationally saying, “Hey, progress is going to slow down, and things might be the way they are now.”

Then this test-time compute paradigm came along, and now we have things like post-training and reinforcement learning that are presenting additional scaling dimensions. It’s just really hard to say, because there are these amazingly talented people inside all of these research labs who are trying new things every day and trying to figure out what that next scaling dimension might be.

I think the right way to frame the answer is: when do we run out of new scaling dimensions? Right now, that appears to be very unlikely, at least in the near term, but at some point it could happen.

I’ve also just learned to never bet against human ingenuity. Given that the best and the brightest are now so heavily concentrated inside these big labs, trying new things every day, I personally believe there will always be new scaling dimensions. Whether the next one is as steep in terms of progress as the last is hard to say, but it’s really hard for me to imagine a world in which we just run out of ideas.

One thing I’m fascinated by is that everyone always says, “Enterprise adoption always goes basically much slower than you think.” But when you look at actual adoption cycles today, it would seem that’s not the case. It would seem enterprises are adopting AI faster than they’ve adopted any other prior technology cycle.

To what extent does the conventional wisdom hold—that enterprises adopt slowly—versus this being fundamentally different?

I think this is fundamentally different. If you compare it to cloud, for example, adoption was fairly slow in the beginning, right? It was kind of gradual, then sudden. Here, I think the difference is that there’s this broad-based consensus that failure to embrace AI to the fullest extent as a company is just existential to its existence.

If you start to ask yourself what it means for the entire industry to conclude that, “If I don’t adopt this technology, I’m going to be left behind,” what you start to see is this voracious appetite to go and adopt it at all costs in every nook and cranny of the business. I think this honestly explains why you’re seeing these companies grow faster than we’ve ever imagined.

I think it explains why investors are so bullish on these app-layer companies because they're going and talking to these CIOs and hearing things they've never heard before, like, “I have to adopt this everywhere or I'm going to get fired” type of urgency. So you're just seeing unprecedented appetite and urgency because of this view that if I don't adopt this technology, my company will perish. And again, I think that's just yet another reason why we're in this really, really unique point in time for entrepreneurs and investors.

11. Quick-Fire Round: Lessons from Mamoon, Fave CEO, Next 10 Years

Dude, listen. I've so enjoyed this. I want to do a quick fire. I say a short statement, you give me your immediate thoughts. Does that sound okay? Let's try it. Dude, you spent years with Mamoon. We both love him. What was your biggest takeaway from investing?

I think Mamoon is known as someone who is very metrics-driven, and I think that could not be more false. He has this incredible taste in people.

Stack-rank

market, traction, team.

Team, traction, market.

I've already told you why I think people are more important than everything, for one. And I think that some of the biggest mistakes I've made as an investor are when I've ignored traction because I've had reservations about the market. Traction is so hard to manufacture, and I think that traction signifies a quality of founder that is good enough to figure out how to overcome any market-size limitations that exist. And so I've learned to overweight it.

To what extent is liquidity a short-term, temporary constraint problem versus a permanent structural challenge?

I do not think it's a permanent structural challenge because I believe that, in the same way that great entrepreneurs flock toward whitespace, there will be solutions and new products that get devised by investment managers to solve for these liquidity challenges that we're faced with today.

Lightseed. There we go. Totally agree. Yes, absolutely. You have a continuation fund, I think, which solves exactly that problem.

What do you believe about the future of venture that you think most people would find shocking?

I see a world in which both ends of the barbell really, really continue to rise, meaning small, dedicated specialist firms on one end and large platforms on the other end. And I think that uncanny valley in between is going to be an increasingly challenging place to be over time if this notion of trillion-dollar companies continues to play out the way it seems to be today.

And that uncanny valley is your $500 million to $2 billion funds. I think that's fair to say.

Yeah, I agree with you there.

Okay, fantastic. Who is an unsung hero in venture? Do you think you've seen many great operators in venture? You've worked with them. Who do you think is an unsung hero?

Look, I think someone who's been very generous to me over the years is the person who actually hired me into venture. It's this guy named Mike Dauber, who's a partner at Amplify Partners, which is a wonderful new firm that's really, really gotten off to an incredible start, again with a focus on both early-stage and these more deeply technical software businesses. They've since branched out quite a bit.

What I can tell you about Mike is that he is just an incredible mentor, and he has imparted so much belief and wisdom on so many young people in this industry. I think he has helped a lot of people gain the confidence and clarity of purpose around what it means to do this job well and why they're capable of doing it. And I'll be forever grateful to Mike for always believing in me.

Every time I've made a change in my career, every time I've had a tough decision to make, I've called Mike, and he's really, really been someone whose feedback I value immensely.

Phenomenal guy. I totally agree. Brilliant investor. Totally share the love there.

Penultimate one: How would you most love to hear your entrepreneurs discuss you and working with you?

I think the first thing I'd say is that we both love having each other in our lives, right? I think that's the core thing that's just so important for that founder-investor relationship to have. And obviously, there are some derivatives of that that create that dynamic, right?

One of those is: Does this investor have a deep curiosity in me? Do they have deep and unwavering conviction in my vision? And do they have the instincts as to when to be helpful and how to be helpful and, most importantly, when not to be helpful and when to get out of the way?

Totally agree with you there. I love that. Also, loving being in each other's lives. I say this to a lot of founders I work with. This is hard. If we don't enjoy hanging out and you don't like me and I don't like you, it's just not fun. It's funny how few people say that.

Final one for you: When you look forward 10 years, where do you want you and Lightspeed to be?

I think I'd love to see Lightseed continue to assert itself as a truly global, multistage, generalist platform, and I would love to be a part of shaping that legacy in the sense that I have driven and helped drive excellence in the early-stage enterprise investing that the firm does.

Dude, I don't know how long I've known you for. It's quite a few years at this point. I feel like this was very much in the works. I so appreciate you putting up with my wayward questions and my pushbacks. You've been fantastic.

Thanks, Harry. This is a lot of fun, and I hope to do it again soon.