Ian Rountree (3:33)

Thanks Shail.

Shael Khan (3:35)

I'm excited to finally have you on after many times of having podcast worthy conversations with you not in front of a microphone. And I rarely do this, but I want to talk about a tweet, an X post, whatever that you posted a few months ago and have pinned since then. So presumably you like it as well. But it just like has stuck in my head ever since then and I just, I, I could not agree more strongly with it. I think it actually I want to unpack it because I think it contains some insights into like the types of companies that really seem to succeed startups. Anyway, within this world of deep tech, hard tech, whatever the hell we want to call it, you list out the two types of companies that you do look for to invest in and we're going to talk about those two types of companies in a minute. But after doing that, you list out three types of companies that you pass on that you don't invest in. I want to talk about that first. Actually the first one is companies selling technology to incumbents, which I want to harp on because in these deep and hard tech categories, in industrial categories, let's say, I feel like that's the majority of companies. Actually the majority of startups have a technology that they wish to deploy and the markets that they are entering are comprised of big incumbents who control a lot of the infrastructure and the distribution and so on. And so the obvious thing to do is try to sell them the technology. And so you do see a ton of that. Tell me if you disagree. Why is that like a blanket pass for you?

Ian Rountree (5:09)

Well, I've learned this like many things the hard way. You know, I started Kantos, it'll be 10 years this spring and it seems like the easy thing to do because it scopes down your startup to oh, we just, we're going to use this amazing technology and we're going to like, you know, productize it in the simplest way and that'll make it easy to sell to said big customer. And then it turns out that there's just so much institutional inertia, sometimes cultural, sometimes it's actual switching costs of having to rip out whatever they're using now to move to your product, such that it ends up taking a lot longer than you think. And this has implications for capital intensity too. But, you know, we can address that later. It's more that it slows you down when speed is so critical to a startup.

Shael Khan (6:05)

I think speed is actually the key point about this because, you know, there's another piece that's not described in here, which people talk about a lot, which is like, okay, your thing, whatever your thing is, especially if it's going to displace some current thing, has to be 10x better, whatever that means, faster, cheaper, et cetera. So, but let's say you do have a thing that is 10x better in whatever way you would think, great, it's 10x better than the current thing. I'm going to go sell it to whoever buys the current thing and uses the current thing, and I should win because it is that much better. And I think in the long arc of history, if you had infinite time and infinite cash to burn to get there, you could win that way by selling to incumbents. You can't if you are time limited on startup speed.

Ian Rountree (6:53)

Yeah, and I mean to like add color to that. The main reason that startups are time limited is because you raise serially in like, you know, whatever you raise 18, 24 months of Runway. And so let's say you raise 24 months of Runway, you need to start fundraising, let's say six months before you run out of money. So you have 18 months before running to do whatever you need to do to unlock the next series of fundraising. And if your customer's sales cycle is longer than 18 months, you are de facto dead. And so you just, you have to make progress faster. And, you know, we could get, you know, this is maybe a problem with venture capital as a whole, but the game on the field is you need to make discernible progress within 18 months or you don't raise your next round. And a lot of times sales cycles do take longer. And there, there are understandable reasons for this. You know, the stakes are very high. In some industries, lives could be on the line. The customer wants to do their diligence and they're using something good enough today, question mark. And, you know, maybe they go golfing with the sales rep. From that company. And you have to overcome all this to get your product in there and start to scale enough such that you can raise the next round and you get to live to fight another day. And one of my very first investments at Cantos is in 2016 was a startup that had incredible machine learning and interoperability software that it was selling into the automotive industry, into industrial robots. Absolutely best in class. And we would hear this time and time again from their reps at big automakers. And the company died despite having some flashy investors and incredible talent behind it because Ford and Toyota sales cycles were too long to raise the next round.

Shael Khan (8:47)

Yeah, I mean the auto OEMs are like notorious for having the longest sales cycles of anybody, even for stuff that is not right, that's software. You think it'd be faster sales cycles there. I mean the other dynamic too, without spending too much time on this piece is pilot purgatory. Right. Like big companies love to pilot something. And the timeline between pilot and full commercial rollout is never certain. It's not well defined in general. And so again, just from a time.

Ian Rountree (9:16)

Perspective you get, well, sometimes they're literally different teams. Like I always, I always encourage entrepreneurs to understand the counterparty's incentives and if they're like whenever someone's behavior in a business context doesn't make sense to me, I try to learn how they're paid and usually the answer comes to the fore that way. And so if you can just understand people's incentives, you can navigate around that and sometimes quicken the sales cycle or, or assess whether you are pursuing a sales cycle that is compatible with your startup in the first place.

Shael Khan (9:52)

I will say I've learned this lesson the hard way as well. In you know, big industrial categories like the chemical industry, the mining industry and so on. It's easier said than done to not do this. So we're going to get to the flip side of this, which is like if you, if you're not selling your technology to incumbents, then you have to be full stack. And that has its own challenges. But I think you and I are aligned that despite those challenges, it may be the only way to succeed at a venture pace and a venture scale.

Ian Rountree (10:20)

Yeah, well, I mean speed is I would argue the most important thing, but there's also like ultimate value capture. And there have been a bunch of cases, whether it's selling some amazing chemistry into the battery supply chain or selling really advanced software built for an industry or something subsystem that goes into a larger plant or something where you have objectively superior technology and let's, you know, say it's 10x better than whatever there is today. And they acknowledge that this is great and they want it and they give you an offer to pay something that is way lower than you think it's worth. And when you push back, they say, sorry, yeah, like if you're just not in the pole position, then you're, you're not often going to get remunerated for the value you're creating.

Shael Khan (11:16)

Yeah, I mean, speaking less to the value capture and more to the timeline thing, I think I'm thinking about a company like Sila Nano, which is run by a friend of mine, Gene Berdzewski. I'm not an investor there, but close to Gene, who's amazing and like a total rockstar CEO, you know, they're doing silicon anode battery materials and it is clearly better. Everybody I think, agrees it is clearly better. And they've had to go. They're selling to auto OEMs predominantly and it's been. And they're getting there now, but it's been, I don't know, 13 years or something like that. And like it's a very rare founder who can keep a company alive and funded that long for something like that.

Ian Rountree (11:57)

Yes, definitely.

Shael Khan (11:59)

Okay, let's move on. So selling technology to incumbents is hard for all the reasons we described. Second category that you said is a pass commercializing science. I guess I want to hear what you mean specifically by that.

Ian Rountree (12:14)

Yeah, I mean, without getting to the semantics of like, do we call it hard tech or deep tech, frontier tech or whatever. There is a category of company that I alluded to before, which is you have incredible technology and you think therefore it is incredibly valuable. But that's not actually how business works. The only point of a startup or a business in general is to create profit margins above and beyond its cost of capital. And technology can be a very interesting means to that end, but it is only a means to that end. And just because your technology is mind blowing and is cited in a bunch of papers or whatever, does not necessarily mean it is valuable in an economic sense. And so if you are commercializing your Ph.D. for instance, you can often look like you have a hammer and you're just looking for nails. Whereas in a business context you have to reverse it and you kind of have to be obsessed with a problem and completely agnostic as to the solution. And I find that there are a lot of deep tech founders, especially PhD entrepreneurs, and particularly when they are commercializing their own thesis, then they Kind of have it backwards and they're waiting for people to tell them how awesome their technology is, when really you have to do a little more work to go show them. And so that's part of it. The other part is the timelines where I would much rather have a novel application of a existing or relatively new technology rather than wait for something to become market ready in the first place. And you know, I've lost a lot of money just like waiting for a startup to advance through technology readiness levels.

Shael Khan (14:02)

So I feel like there's two pieces there to what you're describing. One piece is the, is this a hammer in search of a nail kind of a problem. It's like somebody who's attached, they're personally attached to a particular technology that it turns out actually might not be like product market fit is elusive. And then the other is more like a TRL scale, for lack of a better term. Problem of like, if you're investing in like breakthrough science that hasn't been sufficiently proven, then it just takes too long to get there. Let's spend a minute on each of those, on that second one. On the like, it takes too long to get there. How do you, how do you think about things like fusion, for example, nuclear fusion. Right. Which is like anybody who's investing early in nuclear fusion, even if they, they were doing that 10 years ago or today, like it's, it's sort of inherently breakthrough science that hasn't been.

Ian Rountree (14:54)

I don't. The short answer is I don't. Yeah, that's just not. I would do. I mean, I used to spend a lot of time thinking about fusion and I would like, you know, I'm not technical at all, but like interested enough that I would like debate people on, you know, is it, is it DT or is it PB11 or whatever? Like, you know, I loved like getting wonky like that. But it turns out in, in my business context, I don't have the time to wait for that to become commercializable. And there are some very interesting initiatives to bring fusion energy about. It, it is, it is expressly the type of science that we at Kantos do not invest in.

Shael Khan (15:33)

Yeah.

Ian Rountree (15:34)

Although I really hope for humanity's sake we pull it off.

Shael Khan (15:38)

And then on that first one, the sort of hammer in search of a nail thing, I've seen that a lot. Somewhat recent example for me is we ended up incubating a company called Voya Energy, which is still kind of in stealth, but is known to the public. And they're using metals as fuel, basically. In a particular way. And we kept running across as we were incubating it, we were working with the founders on it. You know, we were taking, we're doing an electrochemical approach and we kept looking around and finding a few other companies. We're all using combustion. And I was trying to figure, and it seems clearly worse to me for a variety of reasons to do that. And so we were asking ourselves the question like, are we missing something? Why? Why is that the way that everybody is doing it? And, and a lot of it comes back to there's a particular professor who is a professor of combustion, who has been the one to create the diaspora that exists, such as it is today, around this particular area. So it's exactly that thing of like this is a combustion person. That is what they do. And so of course that is what they are going to spin out of their lab. And that's where the starters are going to come from and the researchers and so on. Do you see this a lot? That problem in like you do a lot of stuff in bio world is the technology and solution in search of a problem statement, a bio thing often.

Ian Rountree (17:01)

Oh man. I should start by saying we're doing a lot less of it now.

Shael Khan (17:05)

Having learned the hard way, times have changed.

Ian Rountree (17:10)

We do very much believe that in our lifetimes the intersection of computation and biology will probably be one of the more prolific areas of innovation. It has been tough to invest there for a while for a variety of reasons. But yes, there's a lot of this, like commercializing science now that is an area, interestingly where the capital markets have really figured out how to underwrite to let's say, technology readiness levels.

Shael Khan (17:40)

Yes. I find this to be frustrating not being in the pharma world. Right. Because I look at the pharma world, I'm like, oh, like drug. The process of taking a drug from very, very early stage through to the market is like really well understood. The financing seems really straightforward. Why can't we just like replicate that across a variety of different markets? It just doesn't seem to work the same way.

Ian Rountree (18:01)

It's just, it's not standard enough. I mean, I think I've thought a lot about this. It's just not standard enough. Like you need enough in that industry. You can kind of look at, okay, well we're in, we have this kind of readout in our phase one trial and we're in this indication. We know this indication has this many patients and usually you pay this much for it and we can work out like, you know, big pharma when they acquire something, they've like run the discounted cash flow analysis on it, not, not like based on technical milestones. And it's just, it's not. We don't have a process that is as scientifically and regulatory defined and widespread enough that an entire capital market can develop around it. Now that said, even though there are dedicated investors for biotechnologies, it has been a really tough area for public and private companies for a while. Like a third of publicly traded biotechs were trading below cash because they just couldn't. If you didn't have a team that understood this, then like a broader universe of investors couldn't access that asset. And so even when you have very developed capital markets and dedicated funds that have been performant over decades, it's sometimes still not enough to weather certain storms.

Shael Khan (19:16)

But I still think in principle at least, leaning in this direction on some other deep tech stuff would be interesting. You see this occasionally in other places. Not to bring up fusion too much, but one that comes to mind to me is Pacific Fusion, which raised a billion dollars out of the gate. But it's actually a staged series of capital infusions contingent on milestones. It's a billion dollars lined up if they can achieve X, Y and Z over time. And I like that concept. I want to see that. I mean, you're an investor in like Solugen, right? If you had looked early days to what Solugen was doing, so this is in the chemicals industry. Could you have lined up a series of technical milestones ahead of time? Like could you have done this a priori and then said, okay, we're going to sort of predefine the capital roadmap here, or was it just too much uncertainty? Were unit economics too much of an open question? Like what stops us from doing that?

Ian Rountree (20:07)

Yeah, I mean, well, in Soligion's case, it was special because we met at Y Combinator demo day and they had maxed out their credit cards to buy $15,000 worth of home Depot components and had a small bioreactor using their technology and were making hydrogen peroxide at that time and selling to float spas in the area. You know, they had thousands of dollars of revenue and it was small, but you could at least like they were already. There wasn't like a long roadmap to.

Shael Khan (20:43)

First dollars of revenue. Yeah.

Ian Rountree (20:45)

And so it's just, it's just been scale up like that. I would define, you know, they, they had this cool science out of their, their PhD work at, at MIT and then it was just like scale up from there. It was more engineering after the seed round and we could, we could do the tea and we knew that if they got to a certain scale it would be this profitable. And then there were some question marks around which chemicals can we expand to and like how much of this is going to be specialty versus commodity. But that was a little easier than like trust me, trust me, I just need $200 million and then we'll make money.

Shael Khan (21:21)

Which we see a lot of and occasionally works. Right?

Ian Rountree (21:25)

It has, I mean to be clear, like I, my opinions come from my own experience and are in the context of like my firm and my background and my capital base. It doesn't mean it's the only way to make money.

Shael Khan (21:37)

Okay, so that, that's two sort of tough categories. Selling technology to incumbents, commercializing science. The third one I don't think we need to talk about a whole lot because it's kind of self evident. But you said like nth company doing the current thing. I share that view as well. It's just, it's much, much more difficult for a variety of reasons to get a venture grade outcome if you are in a really crowded market. Doesn't mean like some, somebody breaks out of those crowded markets sometimes but the bar is so, so much higher for you. It's harder to raise capital, it's harder to attract talent, it's harder to just separate yourself from the pack basically.

Ian Rountree (22:15)

Well this gets, this gets back into the commercializing science thing a little which is there's a type of startup that I have invested in in the past that's like well here's all the technical reasons why we're the best.

Shael Khan (22:31)

Because X, Y and Z, like we could create a chart and it's going to show all of our competitors and we have the full X and they have the partial.

Ian Rountree (22:38)

But sometimes you do legitimately have something that is better than the incumbents. Like you know, in. I'll pick on one of our, one of our own portfolio companies. We invested in a company that's doing amazing processing of radar technology like Mind Blowing can take off the shelf data from your run of the mill radar and resolve more or less a three dimensional image they call an RF camera. Like Mind Blowing. Cheaper than a camera can see through fog, in some cases see through walls. Put this thing on cars, on drones has so many implications. And there's you know, a much better funded company incubated by VC called Chaos Industries, which I personally think has worse technology but they're doing a lot better because they've productized this, they're very good at selling it, they're very good at marketing it. They, they have a lot more capital and they're landing contracts with the government left and right. And you know, my hope is because we've invested in a much better technology, we can catch up. But like I've seen this movie before and sometimes having the best technology doesn't win you the race.

Shael Khan (23:53)

It gets back to the old trope inventure of right, like a combination of team Tam tech and timing. But like you can have the best tech and you don't have the other things going for you. It isn't, it isn't sufficient. It may be necessary. It's not actually, I don't think it's always necessary either. It depends on the situation. It's certainly not sufficient.

Ian Rountree (24:10)

Yeah, when it gets into like the, the intersubjective nature of capital markets where like you can be objectively right, but if everybody else is wrong for long enough, you are de facto wrong and they are de facto right. And so you have to account for. It's tempting for self styled intellectuals to sit and think that like, oh, I've just outsmarted everybody, but like the market can afford to be wrong longer than you can afford to be right.

Shael Khan (24:40)

Yeah, that's the other point. Right? Like how, how, what does it take to prove your rightness, how long, how much money, et cetera. I think back on the heady days of all the solar technologies and the thin film technologies, predominantly in the late 2000s, early 2010s. And I think the common story that everybody tells about what happened there is that VCs invested billions of dollars into a bunch of different thin film technologies. And then meanwhile, China scaled up crystalline silicon, which is the dominant technology, cost got so cheap that there was no way to compete. And that's true. It is also true that in principle, some of those thin film technologies could be cheaper, right? Like they could still be cheaper than crystalline silicon is, even at a slower cost today. But to get to the point where they would be cheaper requires a lot of scale and a lot of capital. And as crystalline silicon prices were crashing, nobody was willing to fund that effort. And so, you know, you may have been right. At least some of those folks may have been right. But it means nothing essentially in the grand scheme of things because they were never able to prove it.

Ian Rountree (25:54)

Yeah, I used to kind of think that you could, like if you had an amazing enough technology, you could sustain years of no commercial progress, assuming you could fund it such that because you were taking no market risk, that is, it was, you know, patently obvious that your technology was better once you came to market, you could jump up the commercialization curve faster and rather than needing to start small, you could just start with a giant contract because your stuff is so awesome. But one of the things I didn't see there is that the learning curve matters. And once you start doing a thing, you tend to get better at it. And if you're commercializing something at small scale, kind of working out all the kinks that if you're, if you're, you know, sitting in your lab making your technology better, then you bring it to market, you only get to learn then and it's kind of like too late. And so I, I like, I actually like startups that start small and they just get that little compounding and learning every little like sales motion, getting to know your customer better and internal operations. And how does technology hand off with, with manufacturing and closing that design for manufacturing loop and all those little things. If you're just developing the technology, you have to punt them and then do them all later and it's maybe too late and you've got all this technical debt or something. This compounding is a wonderful thing.

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Shael Khan (28:45)

All right, so let's talk about what to do. We've mostly been talking about what not to do. So you have two archetypes here. I want to spend most of our time on the first one, which you described as Full Stack, deep tech selling an end product or even commodity, not technology. So say more. What is Full Stack?

Ian Rountree (29:03)

So, so when I say full Stack, I'm subtweeting a 2015 post from Chris Dixon at Andre and Horowitz, who's largely been a crypto investor. But back in 2015 he described a full stack startup and was largely alluding to companies like Uber and Lyft and Airbnb, who rather than trying to sell software to the taxi and limousine industry or to the hotel industry, were leveraging software to influence the real world while not necessarily building hardware themselves. I thought that was really interesting and largely apply that same thinking to more industries and the types of technologies that we invest in. Where you are building some software but.

Shael Khan (29:52)

Also some physical component, there's nuance to this, right? I mean it's sort of a similar. Full Stack is similar to vertical integration, right? Like, but it's not exactly the same.

Ian Rountree (30:03)

There's heavy overlap, but it connotes the combination of technology and non tech product or services specifically. Yeah.

Shael Khan (30:13)

I think the key thing for me actually more than like defining full stack is, is the selling an end product or even a commodity, not selling technology. Whatever the thing is that your thing unlocks. Like go. If I'm vertically integrating in a direction, it's downstream to start, at least sell to the end customer the thing, whatever your technology makes better, figure out who the end customer is for the thing that that made better and then sell that product. But that is expensive. Like let's be clear about the trade off there, right? Because I think it is, it's like definitionally more capital intensive to do that. Do you disagree with that?

Ian Rountree (30:53)

No. This is clearly the downside of going full stack is that you typically need a little more money to do it and the time is money adage is appropriate, but there's a multiplier on time as we talked about earlier for startups where there's such an importance around making progress quickly when layering in the intersubjective nature of capital markets that like if you fail, like if you make progress quickly, great makes it easier to raise your next round and therefore do all the other things you need to do. But if you don't, the lack of momentum will kill you because it'll become multiplicatively harder to raise capital the less progress you make. I would rather need more money but make time, my friend, than. Than treat them as pure trade offs.

Shael Khan (31:54)

Can you give me like a canonical example for you of like a company either you are or are not involved with that is full stack in a category where they could otherwise be selling tech to incumbents.

Ian Rountree (32:05)

Yeah. So, I mean, the. A great example is mining, and there's a few companies in this space. Full disclosure, one of our largest investments is Earth AI, but you also have Cobalt, which has raised a lot of money and for AI and there's a couple others in this space. So mining is an industry that is massive and there were just not that many startups in. And I thought that was interesting because it's such an important industry. This is definitionally a commodity industry, and it is increasingly important for semiconductors, for, for defense tech, for, for electrification of the grid. Yet we're not seeing much innovation there. There had been some startups along the way that said, hey, we're going to use satellite imagery AI to help people mine better and know if there's a deposit near your existing mine or something like that. And it turns out it was very hard to sell that technology into mining companies. And two, they weren't willing to pay much for it. And so the company we invested in, Earth AI, and I believe Cobalt, may have had a similar journey, although I won't speak out of turn, said, well, hold on. How much is it to acquire these mineral rights? How much is a drill? Let's just hire some geologists and go apply for the rights. Earth AI went out and bought rights and drilled their own hypotheses. And we now own deposits that we think are very valuable. There's a lot more work to be done to prove them out. You've seen Cobalt go out and acquire a deposit. They're using AI to maybe find and definitely mine a little more efficiently. And this is one where if you had taken the typical startup path of just selling software, maybe you make a software license. But if you are willing to go out and take a little more operational risk and need to raise a little more capital to be sure, then you can end up owning literal gold in the ground. And that's a lot more interesting to me as an investor than a mining SaaS company.

Shael Khan (34:18)

The other category that I think, as you describe this, that I think it's equally applicable to, is the AI for materials discovery category, where there's a bunch of companies doing that now, where, like my question to every one of them when I've talked to them is like, okay, let's say you can you build your magic model and you can use that model to discover novel materials. Are you going to license the model and the technology to a big company, Are you going to try to, you know, sell the IP around the material you discover or are you going to do what you probably should do, which is make the material, whatever you discovered, if it's better, you should just make and sell that thing and that ultimately that's your business. You're not an AI discovery company necessarily, you're an AI enabled materials company and some of them are doing that. But it's kind of the same story as I think you're describing in the mining industry.

Ian Rountree (35:09)

Yeah, totally. I mean one of the initial thread that I started pulling on that led me to my preference for full stack hard tech startups was I invested in a construction software business that was doing AI for planning and there were a couple of these out there and we were sort of selling against some of those other companies and the general contractors are really slow to adopt. And I was like, couldn't we just like buy a failing general contractor? Like just do this better? And it turns out it's not just the technology that that improves. Every single time we've invested in a capable team or watched a capable team go after an industry with a lot of inertia, there are a thousand little things that can be improved upon that if you're not taking that on and you're just selling into the industry, you're not going to help innovate those areas.

Shael Khan (36:07)

You mentioned even commodity thing. Let's talk about commodities for a second. A lot of the world that I trade it, I'm like, you know, focus in energy and industrials and like when you boil that world energy in particular down to its core constituent parts, it's mostly commodities, right? Electrons or mmbtus or whatever. And notoriously, commodities are difficult markets. Commodity sectors are difficult markets to build startups in. That's like a, it's like a trope. I think there are a bunch of ways that you can do it. But you said in here, even commodities. So what is it that makes a company who is going to end up, if they go full stack, they integrate downstream, they're going to sell a commodity. What does it take for that to be attractive to you?

Ian Rountree (36:56)

Yeah, I love commodities. For a long time it was used as a pejorative in venture capital. I love when a company is selling a commodity, when the technology that is embedded in their full stack business actually gives them a cost advantage that's incredibly powerful. And taking a step back, what we do as investors is in a way price risk. And so if we're thinking about the types of risk that a startup takes there's technical risk, there's execution risk and there's market risk, and you always have execution risk. So let's focus on the other two. In hard tech and deep tech in the physical world, you're typically taking a bit more technical risk than some of our peers who focus on maybe software and AI applications and not foundation models. A lot of technical risk there, of course, but if we're taking more technical risk and we are on balance basically paying the same prices at seed, series A, series B, whatever, as companies that are not taking more technical risk, then unless you are offsetting that with a equivalent decrease in market risk, you're probably just going to make worse investments. These are the physics of finance. And so why I love commodities is because it offsets the technical risk we're taking with less market risk. Because I know if I'm selling a commodity, I. E. My product is molecularly identical to the competitors, but I have a cost advantage. I know you can sell that. I love when like in my memo, I can just look at the spot price of something on a liquid market. And I, and I know that's, that's the mark that we're shooting for. Whereas if you're developing something new or you're having to convince a customer that they need it, even if you know it's objectively better, then there is inherently market risk there. And that just makes it a riskier asset.

Shael Khan (39:07)

I've heard Vinod Khosla say something very similar, like he'll take technical risk, but he won't take market risk. The other thing that I would say here about commodities is like, I think.

Ian Rountree (39:14)

Yeah, but he invested in impossible foods, forgetting that there was market risk. There's.

Shael Khan (39:18)

Yeah, I mean many things have. I think nothing is as simple as that makes it sound. Right. Like there's market risk where you think there's not. But also commodities are not commodities in the way that you think that they are. Like I mentioned that electrons are commodities. They're kind of not. Right. An electron is a fungible thing and it's similar to every other electron except where and when it is delivered is very, very important. And so there are lots of non commodity businesses built on selling electrons because they're able to sell electrons in the right place at the right time or both. And I think that's true of most commodity markets. Right. Like very few of them are truly like indifferent to time and place. And that additional factor matters in terms of whether something, whether it's truly like a knife fight to the bottom on cost, which is why people don't like commodities from an investment perspective.

Ian Rountree (40:12)

I don't want to go on too much of a tangent, but there's an interesting corollary here to the type of real world full stack business that, that we both like and sort of decentralization of infrastructure. Like if there is advantage to defy economies of scale and co locate your product, your behind the meter energy generation, whatever, then you are operating your own sub facility but you're still taking some market risk by virtue of like customer concentration, you know, because you can presumably as a startup only afford to have so many of these co located things and you know, if they're with the same two or three customers and they change their mind or someone gets fired and the new gal doesn't like you or whatever, that's risky. So I've, I've invested in some of those but you just have to be clear about like there's, you know, whether the counterparty is, is going to slow your sales cycle down.

Shael Khan (41:20)

Yeah. There are also interesting examples that are like companies in a commodity space with a differentiated input and, or companies in commodity space that like their execution and ability to learn in that market allows them to enter into a new market that's non commodity.

Ian Rountree (41:37)

So let's think like give an example.

Shael Khan (41:39)

Crusoe. Right. So Crusoe was flare gas to Bitcoin. That was, that was the start of the company. They, they went and locked up assets that were methane flaring. It's wasted energy. They turned that, they, you know, put little data centers there and mine Bitcoin. That's, that's a commodity, right? Bitcoin's clearly a commodity and they did that a whole bunch. And then that allowed them to sort of like build up more expertise. They built, they started going beyond Bitcoin and into cloud and they had their own little cloud managed services thing and they had all this experience building small data centers and then like the right place at the right time came around and to give them credit, like they fully went after it and took full advantage of it. And then now they're building, you know, Abilene Stargate campus for OpenAI and Oracle and a bunch of others and they just raised money at a $10 billion valuation. Now they're a totally different company.

Ian Rountree (42:31)

Yeah, I think Cor, we've started mining crypto too. I don't know if it was because they were flaring, but.

Shael Khan (42:36)

No, no, it was different. I mean core Weave was just, was just doing crypto mining. A lot of crypto mining companies are now, you know, AI data center companies, that, that pivot is not unique to Crusoe. But I think they.

Ian Rountree (42:46)

Everything is computer. Yeah.

Shael Khan (42:48)

But they've been able to particularly take advantage of it. What's interesting to me about it is like they were, they were certainly in a commodity business. They had to differentiate. The original version of the business had a differentiated input. Right. It was flare gas was their input to create Bitcoin. And that's cheap energy.

Ian Rountree (43:03)

Right.

Shael Khan (43:04)

If you could take advantage of it.

Ian Rountree (43:05)

That's what I mean. If you have, you have a, you have a structural advantage in producing a commodity, that's like the holy grail.

Shael Khan (43:12)

Right? Right.

Ian Rountree (43:13)

Like if I, if I can make dollar bills for 70 cents, I'm a trillionaire.

Shael Khan (43:18)

So I have a different frame that I often use to describe to categorize startups. And my version of it is wave makers and wave riders. So like there are companies that make a wave, they do a thing that. But for the existence of that company, that would not have happened, certainly would not have happened in that timeframe. Or they're wave riders.

Ian Rountree (43:39)

Right.

Shael Khan (43:39)

They correctly predict a trend a few years ahead of time and they time the development to their technology or their company correctly to that trend, and then they're able to ride that wave. You know, Tesla being the canonical wave maker, like the EV thing wouldn't have happened, at least on the timeframe that it has, but for Tesla. And then for every Tesla being the wave maker, there are hundreds of wave riders, EV charging companies, battery technology companies, et cetera, et cetera. Right. And it's useful frame in the first place, but it's also valuable for me because I think the onus on what matters the most is different across those two categories. There's a certain type of, particularly on team, there's a certain type of founder and founding team that is required in the wave maker category because it is so hard because you are swimming against the tide and you have to bend the arc of the universe to meet your needs. I think it'd be similar in the full stack deep tech concept. Right. It's harder to do, you need more money, you have to do more things.

Ian Rountree (44:42)

Definitely.

Shael Khan (44:43)

Right. And so how do you think about the archetype of the founder that can do the full stack deep tech thing?

Ian Rountree (44:48)

Our preference for this type of business has also increased the onus on the entrepreneurs. And you know, when we thought that you just needed incredible technology and, you know, sort of good enough business sense, I was not, not that we were lowering our bar for entrepreneurs, but I was sort of looking for different things. And now we flesh it out actually have internally like a way of, of scoring founders along six axes and how we tease out each of those. Um, and a lot of them are around the qualitative. It's sort of, you know, it's talent, gravity, it's, it's narrative ability. And if you're going to raise the capital required to vertically integrate a business and go full stack, then you just have to be that much better at fundraising. And I think you have to be really honest about the fact that, you know, a lot of people don't like the reason I'm on this side of the table not operating a company is I know I don't have those qualities. I have enough of them to run a small investment firm, but not to build a full stack business that's going to come at a giant advantaged incumbent. And to do so you probably need to raise nine figures of capital, probably ultimately billions of capital across equity and other forms of capital. So the, the type of person you need to make a wave is like you said, like, you know, bends the arc of time toward them. We'll say that a founder has to have such a powerful gravity well that like we feel ourselves being physically pulled toward them in a meeting. And if we don't get that sense, we sort of say, okay, well maybe this isn't a wave maker and we've just found ourselves looking for people that are both incredible technologists and also have this ability to communicate things in a hyper fluent way. They can kind of go up and down the stack of understanding, communicate it to an expert, communicate it to the general audience and get people so fired up that they bend the fabric of space time to their will.

Shael Khan (47:07)

All right, just to close out the other category of things that you do look forward to invest in, which I also share, you described as weird n of 1 never seen anything like it before. So here's my question for you. Apart from those things, I mean, I'm drawn to them too. But apart from just them being cool, how would you articulate why are the weird n of 1 never seen anything like it before? Ideas, good venture investments unbalanced.

Ian Rountree (47:33)

To continue the astrophysics parallel, if you're in an area with other astronomical bodies, you're sort of competing with their gravity to pull in talent and capital and pr, then that's harder than if you are the only body to reach some critical mass in an area with a lot of, you know, a lot of matter. And if you're like the, you know, you know, we, so we saw an early stage company recently that I thought was weird and interesting. We ultimately didn't invest where a woman had had left Wall street to build, as she calls it, De Beers for dinosaurs. And she's using, you know, some satellite imagery and AI and a field team to go out and find dinosaur fossils which have been selling for higher and higher prices. And I thought that was really interesting because I never heard, I mean I've been doing this for 10 years. I see like a thousand startups a year more. I never seen anything like this. And if it's an area that is sort of big and interesting enough and I don't know if fossils are, I didn't go that deep. But um, then she's going to build like the company and when people think of dinosaur fossils, they're going to think of her company. Whereas if you've got, you know, you and I both invested in long duration energy storage businesses, but if you've got like the 20th Eldes business, it's going to be a little harder to stand out. And the, and the venture capitalists you need to raise money from have probably made a bet already and a lot of them don't want to make a competing bet and it just complicates things.

Shael Khan (49:19)

Yeah, but I want to separate two things. I mean there's a part of this, it's just the flip side of nth company doing the current thing. Right. Like if you. It's just first to a market, I guess would be another way to put it. That's a piece of it. But the other piece of what you described is weird. Never seen anything like it before. Like it's something above and beyond just. You are the first in this category. It's, I think to me an enormous amount of startup success ultimately comes down to narrative. How well the founder is able to construct the narrative that raises capital and attracts talent. But also just if the narrative, if the story, if I can tell myself the story of what this company is trying to be and my eyes light up as I'm trying to do it because it's so interesting and so weird or so impactful, if it would have such a big impact on the world, I, I'm drawn to it. And that creed, that's a part of the magnetism that we were talking about before that, that, you know, can come from the founder but can also come from the vision like I think of a company like Colossal Biosciences who's, you know, the tag. I don't know anything about them apart from that they're Trying to bring back the woolly mammoth like that. That's interesting.

Ian Rountree (50:30)

That's weird.

Shael Khan (50:31)

Yeah, it's cool. So, yeah, I guess I just want to. I want to clarify that it's not just being first. It's not being the sole body in that part of the universe. It is also about that part of the universe being exciting, I guess.

Ian Rountree (50:43)

Right. It's not valuable just because it's weird for us. Weird as a filter for might be unique and unique in a valuable way. Look at this defense tech wave. And now it's like the hottest area outside of AI. And that was more or less created by Anduril. And I'll give a lot of credit to Palmer, one of the four founders of that company, for like, completely reversing this trend. And that is. I don't know if I would have called Andrew weird in the beginning. Maybe I would have. Like, now it's sort of hard to look back because it's so big and has spun off all these other defense tech unicorns that. Yeah, when I first heard about it, I thought it was weird. And weird sometimes means controversial. To be clear. Like, to lean into these areas, you necessarily are going to have to disagree with people. And if you're not comfortable doing that, then it's going to be difficult to build a weird, unique end of one company.

Shael Khan (51:46)

All right, Ian, this was, unsurprisingly, a lot of fun for me. Thank you again for joining.

Ian Rountree (51:52)

Of course. Yeah. Well, this is just one of our normal conversations. We hit record this time.

Shael Khan (51:56)

That's right. Ian Rountree is a partner and the founder of Cantos. This show is a production of Latitude Media. You can head over to latitudemedia.com for links to today's topics. Latitude is supported by Prelude Ventures. This episode was produced by Max Levinson. Mixing in theme song by Sean Marquan. Stephen Lacy is our executive editor. I'm Shayl Khan and this is Catalyst.