Earnest Sweat 00:02
Hey, welcome to Swimming with Alligators, the VC podcast

Kelli Fontaine 00:06
from the LP

Earnest Sweat 00:06
perspective with your hosts Alexa Binz and

Speaker 1 00:10
Ernest. Are you ready? Let’s dive in. So, welcome. Thanks for being here, Kelly.

Kelli Fontaine 00:16
Thank you all for having me. I really appreciate it. The opportunity,

Alexa Binns 00:20
absolutely. Can you give us your own version of how you go from journalism to fun events?

Kelli Fontaine 00:29
Yeah, so I’m from Tennessee, but I went to school in Colorado, and I had an interest in stories, right, finding the truth. I will say there’s some type of sense of justice there, but some just intellectual curiosity, so that led me to think that I wanted to study journalism. So I went to the journalism school at University of Colorado, really thinking, you know, at that point in time Paul is on at CNN, Larry King Live, like these deep dives into people in 60 minutes, uncovering the truth of stories and what’s going on, and there I also worked at the Athletic Media Relations department for University of Colorado, and so it really became about stats, right, and so it was always pretty decent at math, I like math, and I really liked the business classes I was taking, and the business people better. The people in the business school were more of my people, and so realized that I could take that curiosity, and that data could tell stories too. But data could be misleading as well, and so really understanding, you know, if we had a terrible game, a football game at the University of Colorado. We could say we had the longest punt in history, like, so always trying to get under, like, what is data, you know, that never believing the headline of data, but really understanding the analysis and pulling the threads to try to get what the actual data means, and say that began my, like, curiosity and using data to uncover truths.

Earnest Sweat 02:31
I one thing that stuck with me in our pre-call, and then just your first answer here is this kind of desire to find the truth, and that resonates with me, because my first job out of college was being an equity research associate, and that’s essentially what you’re doing, you’re trying to find the truth of what’s the true value of a stock and a company, you then took like a path of some different stops, like Credit Suisse, RPX, Capital Group, so you went into the finance world. How were you able to continue to feed that need to find the truth or true value of something?

Kelli Fontaine 03:12
Yeah, so the data and the numbers took me into finance, and that was Capital Group, and then Credit Suisse, but I wasn’t passionate about it. It was about making money. There’s no more meaning there. The people that worked around me, you know, are about one thing, money going up. And I was sitting in San Francisco, where all my friends that were truly passionate about what they were doing were energized and excited and felt like they were doing something, worked in tech, and so for me, I was like, I want to be passionate about what I’m doing, right? I’m curious, and it’s, you know, going through the motions of doing work is fine, but I wanted to be passionate about what I was doing, and so for me, you know, there’s always been an interest in tech, to be honest, but it wasn’t my natural skill set, and so I, you know, did a startup myself, which was point of sales analytics, again data focused. And then when I joined RPX, we created it was a defensive patent aggregation play, and I joined when they were creating a new product, which was an actuarial model for the smaller tail, long tail of companies, and you know that was again using data, but in a startup sense, building something, creating something, and I just love being a part of startups and building it’s really cool.

Earnest Sweat 04:33
Is there anything from that, that last kind of that journey into RPX and dealing with those data models that you still apply today? Any lessons from that? You still apply as an allocator.

Kelli Fontaine 04:45
Yeah, I think you know, for an actuarial model, you’re not trying, like in venture, we’re trying to say, okay, what’s going to be the best fund? We’re like, where are we going to find alpha? You don’t know that for like a really long time, and so. Trying to back into the data that actually matters, and trying to find correlation to performance, so you know, I think everybody looks at benchmarks on TVPI, DPI, NetAR, that’s great, but in an early stage venture, it doesn’t matter for like five years, right? I mean, you can tell something that, like, is going to underperform early, but not where the outperformance is going to come from because the compounding really happens at the later part, right? When you catch the outliers, it’s a power law game, and that compounding and movement really happens in the last part of the fund’s life. And so, what along the way can we say gives you the best chance of that happening, and so is it the traction of underlying companies, is it certain people, other firms leading the follow-ons, is it type of founder quality or customer quality? So, trying to figure out the shape, so that we can benchmark earlier when investing in emerging managers, because that’s our focus, and looking at re-ups. So, I think taking the actuarial models is, you know, it’s great if you have like one or two data points, but like looking at the nuance below it, and how we can really learn to truly assess earlier on than having to wait 10 years.

Alexa Binns 06:17
What is that actual process look like

Kelli Fontaine 06:20
for us, and analyzing the data, so we built it over time, right? When I joined, we were keeping valuations, round sizes, it’s on a spreadsheet, obviously that doesn’t scale. We created a, I created a data structure, I use Salesforce, I’m not technical, I know SQL, but we built out, you know, different data systems over time, and we have a Cy sense as the BI tool we use, but obviously using much more of Claude and OpenAI at this point for analysis, but I think it really took, like, okay, let’s add in KPIs, let’s add in customers, let’s add in founder backgrounds, let’s add in, you know, what can we add in, and are is there any correlation, and is that correlation only because that was a point in time in the market, or is that still relevant today? And so it’s a, it’s an iterative process of like, how much you know our data team could add, how much I could add, and then once we added a data team, how much data we can actually track and add, you know, garbage in, garbage out, but it’s also what you do with the data, so, like, it’s you know, we can reuse it, and it might not be relevant today, but we’re still going to track it, and maybe it’ll be relevant in three years, and that’s how I always kind of felt about it, is since we anchor funds, and we’re typically the first institutional believer, like, we want to have this close relationship, so hopefully we can get more data about the underlying portfolio that can give us insights, and then we’ll figure out over time how to analyze them. So it’s been very iterative, always coming up with new analyzes to do, and you know, checking. We have 78 dashboards with dozens of widgets. We can always check the prior analyzes of what we do and where they stand, but always come up with new ways to look at the data and see if there’s any correlation we can find.

Earnest Sweat 08:07
I’m curious, Kelly, as someone who is very data centric, how do you cope with a job that is both using data and feel, and how do you kind of quantify for that?

Kelli Fontaine 08:23
Yeah, you’re correct. I’m very data driven, and I work at Early Stage Venture, which is, you know, about the person. I think you know the data is useful for re-ups or understanding an angel track record. I think the hard part is, is once it’s there’s something evident in data, the GP, and where that investor was in life is no longer where they are today, and so it’s very backwards looking, and so I use the data, we use the data more for like portfolio construction of our own portfolio of the portfolios we want to look at, you know, in this market, because the graduation rate is lower in series A’s. If they make the series A bar, which is less likely now, it’s much more expensive, so less reserves, more companies, right. And so, like, I think we look at what’s going on in the market and apply what worked previously and what the market is today, so it’s the marriage of those two, and then the data, you know, we launched two new business blind products with it, which is a co-investment fund and a secondaries fund that utilizes the data, but as far as assessing early stage managers, it really is about the GP, and so the data I would say, like, we can benchmark and do whatever we want, but it really is about the GP.

Alexa Binns 09:44
We glossed over a bit that today you’re with Cendana, and it’s used by our guests almost like, like Xerox, like this there’s the endowment model, and many of them are now following the Sendano model. Yeah, we. What, what are people saying when they say they’re sort of following your model, and is there sort of a nuance that you think is sometimes missed about what you all actually do that people think they’re building an internal fund of funds like you?

Kelli Fontaine 10:16
Yeah, I think an important part of Cindana is the relationships, right, and so I think that’s so big when you are diligent and seeing fun ones and GPS, you’re really getting a sense of the co-investors on the cap table, the downstream investors, the operators, the founders, and really understanding who has the biggest magnetism right now in the market. You know, I’ve had my entire career here in San Francisco, we have teammates in New York, and so ingrained in these ecosystems of where we feel like we can get that true, honest feedback, because that is the bulk of what we’re doing when identifying. I think you know, as you said, there’s a lot of people doing this now, and you know, emerging managers or fund construction, but our look at fund construction changes with the market, right. So, what we were looking for in Fund Three, when I joined a 50% reserves lead checks, like all of that is not how we’re investing today. And so I think you know you have to have a first principles approach as you’re building out your venture book or focused on emerging managers of like what do you believe to be true, who has a right to win, and where the alpha will come in early stage venture? Today, we still think there’s alpha in early stage venture, that’s where historically the top returns have come from, and we don’t think that history is going to all of a sudden change, and that the market’s totally gone away from that, but we just think there’s a little bit different way to approach it than what we are doing in fund three now that you know we’re investing on fun out of fund six.

Earnest Sweat 12:20
one thing that I loved about our prep conversation is you spoke about when you first jumped in to Sadhana, you did an analysis, of course, on brand, and you found that pre-seed outperformed seed, but you said since then you’ve, you’ve, you’ve come more skeptical of that conclusion. Could you explain that, and how that’s kind of taught you not to be trapped by data insights?

Kelli Fontaine 12:48
Yeah, so again, I have never been an allocator before. The only reason I knew what a fund of funds was was because I’d known Michael Kem for 10 years before I joined Sedonna, so this wasn’t like I was a well-researched allocator. Again, I had worked in startups and in the venture ecosystem, and been my adult career around here, but I didn’t know exactly what to do. So, the first thing I did was get our data systems up and running, and then it was like, okay, well, we have kind of two distinct buckets now, because the rounds look very different, right? The seed was getting larger, and the pre-seed was getting larger, but you know it was very.. There’s enough delta in the pricing that they look different, and they were called different things, and the managers operated differently. There’s some revenue at seed, there’s no revenue or even product at pre-seed, and so it’s a different risk. And so, let’s look at the analysis, and so literally, pre-seed was the same on graduation rate, even though there’s more risk, it was the same on mortality, which is crazy, but I think that was probably because of acqui-hires, it outperformed, you know, on the year of entry MOC, so not just venture the fund vintage, but the MOC entry dates, and so looking at that, it’s like, wow, you know, for taking more risk, you get more alpha, like, why would you not, less money? I think that’s, you know, it’s one of the things that worked in a market at that point in time, and it’s really just about the best GP, and so, you know, there’s this opportunity in LA or New York or other places or even San Francisco, right. Well, San Francisco has so much capital focused on early stage now, and institutionalized angels and seeds became a thing that pre-seed kind of probably arbitrage away in the Bay Area specifically, and so like just looking at why things worked at a specific point in time and applying that data to today, and so I think that was a learning for me, of like, oh, this analysis, I can look, and this is working in the portfolio, and really, you know, that’s applying the lessons from that, and what worked, and why it worked, and then what does that mean for today, and what, where, where we think the market’s going.

Alexa Binns 14:56
I would love to hear where you think the market’s going.

Kelli Fontaine 15:00
Where are you coaching your LPs that you’re spending your time? I think we’re looking, I mean, it’s, we’re looking for the best investors, right. We do think there’s something really special about funds ones and twos. We think that, you know, either your more recent to your operating experience, founding experience, you have built a personal brand that’s big enough for you to spin out by fund three and beyond. You’re spending 70% of your time supporting companies versus sourcing. You have a full portfolio, so your time is different, and you’ve had to – you’re further away from that experience. The networks that you had from operating, right, those people probably founded companies, so you’ve had to rebuild networks. Networks have a shelf life, so you’ve had to rebuild those, and so we just think, you know, funds ones and twos are really special if you can find the right ones. And then there’s still some that will continue to outperform, but they’ll look different, and typically they scale at that point too. And so it’s really working with our GPS closely and understanding what they’re building, where they’re spending their time, what lessons they’ve learned from sourcing and supporting, and where they’re leaning into what lessons have they learned. Everybody’s building a business, they happen to be in venture firms investing, but how they are building that business is really important to us.

Earnest Sweat 16:19
Are there any trends that you’ve, you all have seen that you’re getting cold on, of you know, different structures, different focus areas that you think are just kind of like overplayed at this point, or just won’t be competitive in this new market?

Kelli Fontaine 16:35
I would say we get pitched a lot of 15 company portfolios, so concentrated, and you just have to be able to articulate why that’s the right structure. 2% of all companies become unicorns, 8% of our fund one companies became unicorns. So I think that was a time and place in the market. There’s less graduation rate today, fewer companies matter, and they happen to be bigger. So for me, you know, just analytic, being an analytical mind, I get a lot of these. Well, I have, you know, this hit rate in my prior angel track record, and it’s like, okay, but like, can we really articulate why that’s repeatable, right? And so I think for me, the 15 company portfolios we’ve seen are quite a bit of, and it’s just something I am not sure about. I think we see a lot of defense tech, national security, and deep tech right now. We have been investing in deep tech. I think our first investment was a specialized fund in 2015. Our generalists have always touched it, but I would say with that, and we actually have a lot of GPS that focus on students, because AI native founders tend to be younger, and so anything something becomes consensus as venture is a time to kind of understand, has all of the alpha been arbitraged away? If you’re focusing on defense tech, you know, Palantir and Shield AI and Andrew, you know, those were started way back when. Do we think that there still can be others built today? Yes, but once it becomes a trend, the top companies were started years and years ago, and this is historically true. You know, we’re talking about AI and 2425 26 Well, when was Open AI Anthropic formed? So I think, in general, like we are looking for people who can see around corners, and, and you know, AI is obviously a part of everybody’s story today, even if in your deep tech, how is AI affecting you? How are you using it? So I think there we’re really looking for not to negate podcasts, I listen to a podcast every day on my way into work and home, but I think there’s a lot of talking points that venture, you know, every GP kind of has the same thoughts, and so we’re looking at, you know, for a new thought that we haven’t heard before, our new angle, or some type of way of thinking. We know that this is best founder driven, and that the founder should, that some of 1000s of founders should be smarter than any one VC, but if they can articulate a contrarian or first principle thought that gives us conviction that they are thinking about the world in a way that will find the non-consensus ideas, that is really what drives the alpha in early stage investing,

Alexa Binns 19:18
what are you telling your prospective LPs that they’re missing if they’re only. if they’re only getting into Andrew, as you said,

Kelli Fontaine 19:43
I think if you look at, like, a let’s use Facebook as an example, because we’re talking about large IPOs that are happening, that at that point in time was the largest IPO ever, you know, if started 2004 around in 2005 you would have had an 8,000x by the time an IPO, if you would have invested in the late state. Rounds that happen pre-IPO, you would have a 14x today, 16 years later, so an 8,000x in eight years, a 14x in 12 years. So I just think you have to put that in perspective, right? Early stage venture, getting an idea stage is where the true alpha has always historically come the late stage, there’s more private capital, there’s more private companies of scale than ever before, there’s less public companies than ever before, and to treat it all as like one big thing, it’s not the way you treat public markets, there’s small cap, there’s mega cap, it’s treated differently in private equity, they’re small middle market, there’s mega buyouts, they’re treated differently, and I think you have to view the same in venture now, with how the quantum of capital that’s been raised, and how long companies stay private for, and how large these companies are, and so you know, I’m not saying there’s not an opportunity to make money at late stage, I’m just saying it’s silly to put all of the eggs in that basket, because there will be a wave two of AI. There was a wave 123, of the internet, of mobile, of any technical revolution. It’s built on the prior tech that became big and allowed the next companies to be formed. And so, if you’re only focused on the late, then you’re missing out on the next wave, and where the alpha is truly generated at the early stages.

Earnest Sweat 21:25
Not to ask you to do too much of looking into the crystal ball, but what do you anticipate will happen after a number of these mega IPOs come out? How’s that going to impact our market of focus on early stage ventures, do you think it’ll loosen up the capital markets and interest in the early stage, or you’re just curious about that?

Kelli Fontaine 21:52
Yeah, it’s interesting, because I’ve, you know, allocators typically set their plan, endowment model, and like this is what we’re gonna do, but there’s still this pull of, like, you know, we don’t have enough SpaceX Open AI anthropic exposure, we’re missing out, and so that’s where the energy and effort goes. I think there’s enough, you know, 11 labs cursor, there’s enough of these later stage AI where it’s like the next interest of like getting into one of those before they exit, so I think if anything, the current market shows 75% of the capital and venture has been raised by these mega funds that continues. I don’t see that changing, unfortunately. I think you know the good thing is, is that I think the markets become more efficient at early stage, like you know, right now it’s right now it can be, I think, 21 was not, it’s not going to be a great vintage, right, for anybody, and it’s not just valuations, it’s that there’s too many people got funds, too many companies were funded, and so a constraint of capital and best ideas only making it is not a bad thing at the early stage, and it actually will be good for early stage returns, which then will increase the cycle, will happen, right? An increased allocation to early stage venture, money’s going there, then like the competition increases, and the returns are arbitraged away, but I think if anything, it gives me conviction that the next vintages will be good if so much focus and money is going into later stage, that’s capital for the companies that are being formed and started today, right? Of where we’re playing, so they have to put capital into something without money that’s being raised, and you know it’s for the early companies that truly can hit scale.

Alexa Binns 23:37
We would be remiss not to ask you about some KPIs, given this is where you spend so much of your time. What do you, what are you actually paying attention to? Which are the ones you consider actually worth tracking?

Kelli Fontaine 23:54
I think understanding revenue and customer quality is important to understanding, especially in AI right now, because you see a lot of this hockey stick growth, but actually understanding, so you can, you know, you might have four of the same flavor in our portfolio of AI companies attacking the same. How is their go-to market different, right? Like, what’s their revenue profile look like? We don’t have much legal AI compared to what’s in the market, but I would be very interested in tracking, like, what cost, like, which customers they have. What are the ACBs? Like, what’s different about the businesses and makeup, because I think that’s important today, like the quality of the companies versus just the king making marks, quantum of capital raised again. I think you see these companies that are hyper scaling, but like, can you be efficient with the capital that you’re raising as well?

Earnest Sweat 24:47
You know, I know a few of you are portfolio managers, and not only have you picked great funds and fund managers, but also you, you all get them all together. A way to be able to really share ideas and see where the market is going. I’m not going to ask you to give any secrets away from that, but I’m curious about the changing of the market with graduation rates being extremely different and more efficient, as you mentioned, than they were in the past. How does that change what you even look for in diligence in a fun one or fund two, right? Because it’s just tougher, like, they have to get so many things right with finding even one or two companies that can be a fun returner.

Kelli Fontaine 25:38
Yeah, and I mean, typically by the time you’re raising funds there’s not enough time in two and a half years for a company to bake or an outlier to occur. I mean, in AI it can’t happen, but let’s like, that’s not what we’re looking for. I think it’s that there’s enough progress, and that goes back to the KPIs that are important to me. It’s like, are these like, do they have a product in the market, were they able to ship quickly? They should be able to, right? Everybody should be able to ship quicker than ever, right now. Like, so what is the traction like? What has been the customer feedback? What is their sales plan and understanding? So we have core tiles of revenue, and so I would say that’s why that’s important. And again, it’s what I just said about portfolio construction, of you know, people are like, oh, I’m going to be more concentrated, like actually, like if graduation rates are lower, you know that would mean that you should probably have a few more shots on goal today, because things can look good at the early stages. You can get in May and they can still go to zero, right? I mean, I think people think things are de-resply in A or B, like B’s are still very, very risky, and so I think in general it’s that you know, and we do try to impart what we’re seeing, but take feedback, right? We do monthly calls with our managers, each of them individually, but I think, as you said, we try to get people together. So, what are we hearing on these calls, so we can share it with one manager to the other? Well, we heard this is happening in the market, we have a Slack for them to ask each other questions, but we do a lot of in-person, so that they can share ideas and insights. We think we hear this from founders on reference calls of, like, we really love spending time with the other founders in the community and be able to learn from each other, and so we try to do the same thing with RGPs of really facilitating being that human router for connection

Alexa Binns 27:24
you described at the top of this interview that you’ve developed a couple different newer products since the Emerging Manager Fund of Funds. Can you give us sort of the like where that demand is coming from and how you’ve structured those, what they look like?

Kelli Fontaine 27:40
Yeah, so we have a joint venture with Klein Hill, and Klein Hill is a secondaries focused fund based in Greenwich, Connecticut. Obviously, broad secondary, so they do some venture, but it wasn’t their specialty, and so obviously taking our data and relationships, and that kind of came in organically. Obviously, we have the data on relationships, so secondaries would love us as a pipeline, and we’ve known the team there for a really long time. Actually, the people on point worked at Cambridge Associates and underwrote to Donna Fun One, so it’s a long time relationship. And so we came up with that product, and it really, what we’re focusing on is, like, you know, where do the companies have traction, and the manager still has conviction, and there’s still growth, typically pretty late stage, 100 million of revenue plus, but it hasn’t raised in quite a while, so the multiple to valuation looks like a great entry price right now, and so we’re really looking at what’s working in the portfolio, and then you know it really came about also because our GPS, the makeup of fund ones and twos, are a lot of family offices, and they’re not, as you know, sturdy as an endowment, and so some of them would look for liquidity along the way, and they would come to us and say, “Hey, you know, we have a family office asking for liquidity, and so now we have a way to actually transact on it, and so that’s for the secondaries, and for the directs, you know, there’s 250 plus series B and beyond rounds in our portfolio per year, and our managers are not focusing on emerging early smaller managers, they’re not set up to do series B and beyond, they can do an SPV and opportunity fund eventually, but we created a way to share carry back to them, and so using the frameworks of the data where we saw alpha, so really cutting those 250 opportunities down to 50 of where we’re focused per year, and then we’ll do about eight of those per year.

Earnest Sweat 29:59
I. Um, on the kind of subject of secondaries, in past cycles we’ve had, you know, secondaries, kind of founder secondaries happening at probably not the best times for the companies, or kind of thinking of kind of the long-term stability of a company, you mentioned to me that you know that the founder secondary sales should probably be more aligned with GP secondary sales. Could you walk us through kind of like your logic for that?

Kelli Fontaine 30:32
Yeah, well, I think you know people who took secondaries in 2021 look really smart, and so thankfully we had managers proactive in our portfolio, when they got these huge markups, they de-risked and took about 10 to 30% of their position off the table. We always had kind of advised never sell 100% unless there’s like complete a complete reason to, but de-risking the position along the way. Again, I think companies stay private longer, these marks, they have to grow into time, cost, value, risk that can happen. I think you know half of the 21 vintage uniforms have never been raised again, so you can say half of those are dead, probably. And so, looking at that, like it’s probably smart to de-risk positions along the way, but when it comes to founder secondaries, I think one thing to think about is like the capital that we raise, where we like to raise for mission-driven capital, and so a lot of the capital that goes into venture is hospitals, endowments, foundations, pensions, and so when you’re cashing out and taking money before you send money back to these hospitals, like you’re taking their money and pocketing it, and so I think if a founder is taking some off, like understanding that founders take less salaries, but it should be a line of conviction in their own company, and almost taking that as a signal is it’s time for you to de-risk some too, if they think taking that capital that came from your investors into their pockets is kind of the right path, and so I think, like, just the game of venture and early stage venture is so much focused on sourcing, picking, supporting, you know, winning, and supporting, but there’s a whole portfolio management side that I think has been missed along the way, and like, we’re really waking up to how important that is, and venture and understanding when to exit is almost as important as like the right companies to be in, and so I think it’s just an important way, and one of those signals to look at is, you know, if a founder is, how much of how much of their shares are they selling, and how much are they pocketing at that point, like, is it enough to buy a house and like give them some breathing room, or is it enough to make them extremely wealthy? Right?

Alexa Binns 32:44
Any other advice or opinions on that portfolio management, financial management side?

Kelli Fontaine 32:52
Yeah, I think it’s good to do portfolio reviews. I think, like, we, you know, this is a game of power laws, and so people don’t want to write off a company that might inflect those are very, very rare, to be honest. Like, it’s very rare that after year seven, a cockroach comes back alive, and they just didn’t give up. And you know, it goes back to, like, is there a way to support companies, you know, getting liquidity back? If it’s really going to be the five companies, and that’s your job as a capital I investor to identify, like, what you think, if you know, after several five years, you should kind of know which five companies really have the potential with the talent, the traction to break out, and so the others, like, is there a way to manage it and get one XDPI from like the other 30 companies in the portfolio back to your LPs, acquire hires, you know, when we look back at our historical returns, 10% have come from acquired hires and 10% from that modest exit. So, acquire hires actually do return capital back as much as a modest exit, and so I think again that everybody just kind of focuses on the power law, but you know, portfolio management and actually getting capital back to your LPs quicker. It comes from portfolio management, and it goes back to the secondaries too. Understanding if you were going to underwrite this company, you know, if it was a 21 unit port, how many years of the current growth rate does it have to have till it grows back to that valuation? How likely is it? So, like, really like thinking through what the math is and what the impact to your LPs and to your fund will be, so I think it’s just a lot more exercise on the actual portfolio.

Alexa Binns 34:30
Well, I had an interesting conversation this week with a GP. I’m a small LP and he has since retired, this is an older fund, asking what are the things you would, in retrospect, have done differently, and he described always letting the market actually judge the next round. You know that enthusiasm you have if you’re the insider, he said. You know, maybe jumping the gun, they really should have market tested every single one of their deals at every single round. Found, and you’re providing that in a way as a secondary, second, second voice. It’s like you’re still, as the GP, I love that you’re still supporting your founder, you’re finding them this secondary market, but it’s being marked by a totally new party, and I think that’s really healthy for everybody.

Kelli Fontaine 35:24
Yeah, and I think I understand where that mark is coming from, right? Like, is it a decent size check for you, but is it like a drop in the bucket for that fund? So, like, how much conviction do you think they actually have, and just understanding like all of these dynamics, and take making your decision based on kind of that market check,

Earnest Sweat 35:44
we’ve spoken a lot about the changes and how they’re impacting GPS, but allocators are being impacted as well, and one thing I loved talking to you about in the earlier conversation was around the dynamics of how the venture asset class has maturated, and how it’s kind of setting allocators up for not success or failure when you’re lumping in all the different types of players in the market, and you said the analogy you used was around it would be like if all public equity allocators had to put micro cap and large cap and mid cap all in one, so could you, could you talk about kind of like how it’s impacting our industry and what’s another approach that we should take when looking at the industry.

Kelli Fontaine 36:37
I think again, like private equity evolved to this, right, and I think there’s a lot of interest in the mid market and small cap in private equity. I think people are concerned about the mega large cap mega firms and private equity because it’s harder to exit there, and if I just take, like, okay, we’ve learned that lesson, and allocators kind of allocate between the two buckets and one exposure to both, but they’re looking for the spin outs, they’re going to do the smaller, earlier stuff. Then that same, you know, if we fast forward this, like, you know, ventures of mature enough asset class now to where there’s a quantum of capital that’s raised, that’s a very different structure, you know, a billion $10 billion valuation is very different than a 10 million to $20 million valuation, like those are so different profiles of companies of funds that invest in them, and so they should be treated differently, and you can have your like opinion on where to allocate within the venture, but like totally disregarding one part of it, and then going to the other that’s working today is probably not the right approach, but again, like I think again we work on early stage. I don’t think you should be all early stage, but I think if you’re saying like everything that is late stage, because duration is long and venture, and so I’m going to only do late stage because you know there’s a 10x multiple that can happen from 10 to 100 billion. There’s still risk there, it’s still a venture, there’s still risk, you know, getting from 100 to 10 billion is very hard. 100 million to get to 500 million, it’s a very.. you’re having to go to internationally new products, like it’s a very different skill set, and hard for some founders, and so I just think there’s still risk there, and it’s a different profile company, and a different profile of return when you’re raising billions of dollars of capital and managing those, and then it’s a very different thing to, you know, be at the forefront of innovation, and so you are not correlated with the market at all at the early stages, other than there being capital for these companies in 18 months, if they get everything right, and understanding that right, and so I think there’s a risk spectrum, but again I think it’s just allocators in general that have been around venture since the beginning are seeing this and investing across of it, but like new allocators that have not, don’t have as much history, or you know, more fresh portfolios. I think understanding where venture is today and making sure that they’re covering it in a way that aligns with their conviction on the spectrum.

Alexa Binns 40:21
Anything that’s just driving you nuts right now, Kelly, you crack me up. I want to hear what right now, like if there’s

Kelli Fontaine 40:29
something that you’re just like, holy cow, everybody has this so wrong, or like, what are they thinking? Huh, that’s a good question. I just think the FOMO and momentum, like I think everybody’s excited about AI. It’s been dizzying being in San Francisco, like you know, I will tell you, like it’s been hard for me to have conviction on something I’ve waffled, and I think you know years into this I finally felt I got that December was like the most dizzying time for me when Claude Code came out, but I think where I am today in building in our own AI tools, and where I am today, I like, because I’m actually building with these tools as well. I think I’m finally like, okay, humans are all going to have a job, and I think you know it drives me nuts that, and this is one thing I think there is a part of where you’re investing in an early stage venture, you are investing in the future of our country. The economy, like tech, has really, like, brought so many jobs, and the marketing that we do, and the loudest voices kind of drive me nuts, because it people don’t like us across the country, like, and they’re skeptical of the technology, and they think it’s coming for them because of the marketing and how it’s done. I think this over hypeiness of what it can accomplish too is going to set people up for failure. I mean, Open AI and Claude still make a lot of mistakes when I ask questions, right? Are you going to just let it run your business? No, like there’s still a human in the loop, there’s still a need for humans where the technology is today, and yes, if we automate things away, or you give me power, I can do better work or deeper work, but there’s still a need, and I think just the marketing angle, and that the loudest voices kind of dictate how everybody views venture and views the tech ecosystem. I don’t love that, because I don’t think that speaks for everybody, and they are the spokespeople for everybody publicly.