The VC case for 'full stack deeptech'

For “deep tech” or industrial tech investors, a captivating idea on paper doesn’t always translate into a sustainable or viable business. Even a remarkable technological breakthrough isn’t guaranteed to survive the long sales cycles of the industrial world. So which companies are worth the investment? Ian Rountree, founder and partner at the venture firm Cantos, wrote a bare-bones thesis on X that offers guidance on this question. In it, Rountree lays out a stark list of the companies he invests in—and the ones he passes on. In this episode, Shayle and Ian unpack his post and explore how it applies to the current landscape of hardware and industrial startups. They cover topics like: Why selling technology to large incumbents like automakers or utilities can be a death sentence for startups The pitfalls of "commercializing science" Why capital risk to sell an end-product can be better business than licensing technology Why "weird" companies—"N of 1" startups—can generate huge amounts of talent and capital Why selling commodities (like electrons or minerals) can actually be a safer bet than entering a new market Real-world examples of full-stack success in the mining industry, including Earth AI and KoBold Metals Latitude: Earth AI’s play in the hunt for critical minerals Catalyst: Calibrating hype with Akshat Rathi Catalyst: Climate tech startups need strong techno-economic analysis Open Circuit: Pain, resilience, and bargain hunting for climate tech investors Credits: Hosted by Shayle Kann. Produced and edited by Max Savage Levenson. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor. Catalyst is brought to you by Uplight. Uplight activates energy customers and their connected devices to generate, shift, and save energy—improving grid resilience and energy affordability while accelerating decarbonization. Learn how Uplight is helping utilities unlock flexible load at scale at uplight.com. Catalyst is brought to you by Antenna Group, the public relations and strategic marketing agency of choice for climate, energy, and infrastructure leaders. If you're a startup, investor, or global corporation that's looking to tell your climate story, demonstrate your impact, or accelerate your growth, Antenna Group's team of industry insiders is ready to help. Learn more at antennagroup.com.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:02Speaker 00

  Latitude Media, covering the new frontiers of the energy transition.

• 0:07Speaker 01

  I'm Shayle Khan, and this is Catalyst.

• 0:11Speaker 01

  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. I would rather need more money, but make time my friend than treat them as pure trade-offs. Coming up, an ode to the full-stack deep tech startup.

• 0:43Speaker 00

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• 1:27Speaker 00

  and become category-defining brands. From breakthrough startups to global industry leaders, their team brings the expertise, relationships, and track record to accelerate your momentum. Learn more at antennagroup.com.

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• 2:16Shayle Kann?

  I'm Shayle Khan. I lead the early-stage venture strategy at Energy Impact Partners. Welcome. All right, so this one is a little out of the ordinary for me for two reasons. First, despite the fact that I am a venture capital investor, I actually generally don't have other VCs as guests on this podcast, at least not very often. I prefer usually to talk to operators and researchers who have a much deeper knowledge than anybody in my shoes. Second, I'm not generally in the habit of having a whole conversation based on a tweet or an X post, or whatever you want to call it. But I'm in the business of exceptions, so here's one. My friend Ian Rountree is also an early-stage investor. He leads Kantos, which is a pre-seed and seed fund that's been doing deep tech since long before it was cool.

• 3:01Shayle Kann?

  I think he may have been part of coining the term "deep tech" and is now part of coining whatever the next term is going to be. Anyway, Ian posted something about his investment thesis just a few months ago that has been basically stuck in my brain ever since then. So he said, and I quote, "We invest in two archetypes at Kantos. One, full-stack deep tech, selling an end product or even commodity, not selling technology. Or two, weird N of one, never seen anything like it before. Selling technology to incumbents, pass. Commercializing science, pass. Nth company doing the current thing, pass." I've been hung up on it because it resonates so strongly with my experience over the past,

• 3:42Shayle Kann?

  now, 19 years working with startups in the energy and industrial world, first as an analyst and now for the past eight years or so as an investor. I think it's correct, but it also describes a world that honestly excludes the vast majority of startups in this space. So it's worth unpacking. Ian, welcome. Thanks, Shayle. 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.

• 4:23Shayle Kann?

  But it just, like, has stuck in my head ever since then, and I just, 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.

• 4:57Shayle Kann?

  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?

• 5:37Speaker 01

  Well, I've learned this like many things the hard way. You know, I started Cantus, it'll be 10 years this spring. And the, it seems like the easy thing to do because it, 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.

• 6:22Speaker 01

  And this has implications for capital intensity too, but you know, we can, we can address that later. It's more that it slows you down when speed is so critical to a startup.

• 6:33Shayle Kann?

  I think speed is actually the key. Point about this because you know the 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.

• 6:50Speaker 01

  Yeah.

• 6:50Shayle Kann?

  Faster, cheaper, et cetera. So well, 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.

• 7:21Speaker 01

  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 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 debt. And so you just, you have to make progress faster. And you know, we could get, you know,

• 8:04Speaker 01

  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 and 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.

• 8:45Speaker 01

  And one of my very first investments at Kansas 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's sales cycles were too long to raise the next round.

• 9:15Shayle Kann?

  Yeah, I mean, the auto OEMs are like notorious for having the longest sales cycles of of anybody, even for stuff that is not right. That's software you think could be faster sales cycles there. I mean, the other dynamic too, before we sit without spending too much time on this piece is is 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 perspective, you get.

• 9:45Speaker 01

  Well, sometimes they're literally different teams. Like, I always, I always encourage entrepreneurs to understand the counterparties 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, it 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 assess whether you are pursuing a sales cycle that is compatible with your startup in the first place.

• 10:20Shayle Kann?

  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'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 like, despite those challenges, it may be the only way to succeed at a venture pace and a venture scale.

• 10:48Speaker 01

  Yeah, well, I mean, speed is, I would argue, the most important thing, but there's also like ultimate value capture. And there've been a bunch of cases, whether it's selling some, you know, amazing chemistry into the battery supply chain, or selling really advanced software built for an industry, or a 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.

• 11:34Shayle Kann?

  Yeah.

• 11:34Speaker 01

  Like, if you're just not in the pole position, then you're not often going to get remunerated for the value you're creating.

• 11:44Shayle Kann?

  Yeah. I mean, speaking less to the value capture and more to the timeline thing, I think I'm thinking about a company like Seela Nano, which is run by a friend of mine, Gene Burdyshevsky. I'm not an investor there, but close to Gene, who's amazing and like a total rock star 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 automakers 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.

• 12:25Speaker 01

  Yes, definitely.

• 12:27Shayle Kann?

  Okay, let's, let's move on. So selling, 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.

• 12:42Speaker 01

  Yeah, I mean, without getting into 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. Like, 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, you know, is cited in a bunch of papers or whatever, does not necessarily mean it is valuable in an economic sense. And so,

• 13:25Speaker 01

  if you were like, you know, commercializing your PhD, 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.

• 14:07Speaker 01

  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.

• 14:29Shayle Kann?

  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 just 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

• 15:14Shayle Kann?

  nuclear fusion, even if they were doing that 10 years ago or today, like, it's, it's sort of inherently breakthrough science that hasn't been commercialized, etc.

• 15:22Speaker 01

  Yeah, I don't. The short answer is I don't. That's just not what I would do. I used to spend a lot of time thinking about fusion. 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 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 is, it is expressly the type of science that we at Cantos do not invest in.

• 16:01Shayle Kann?

  Yeah.

• 16:02Speaker 01

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

• 16:05Shayle Kann?

  And then on that first one, the sort of hammer in search of a nail thing, I also have seen, I've seen that a lot. Like, one, I sort of somewhat recent example for me is we, we ended up incubating a company called Voya Energy, which is still kind of in stealth, but, but is known to the public. And they're, they're doing, they're using metals as fuel, basically, in a particular way. And we kept running across, we were, 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 were 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,

• 16:48Shayle Kann?

  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?

• 17:29Speaker 01

  Oh, man. I should start by saying, we're doing a lot less of it now, having worked the hard way.

• 17:34Shayle Kann?

  Times have changed, yeah.

• 17:37Speaker 01

  We do very much believe that like, 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.

• 18:08Shayle Kann?

  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.

• 18:29Speaker 01

  It's just, it's not standard enough. I mean, I think, and 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 Run 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 regulatorily defined and widespread enough that an entire capital market can develop around it. Now, that said, even though there are dedicated

• 19:12Speaker 01

  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.

• 19:44Shayle Kann?

  But I still think, in principle, at least like 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 quote unquote billion dollars out of the gate, but it's actually like a staged series of capital infusions contingent on milestones. It's like 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 at 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

• 20:25Shayle Kann?

  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?

• 20:35Speaker 01

  No, I mean, well, in Solugen's case, it was special because, you know, we met at Y Combinator Demo Day and they had like 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 like float spas in the area. Like, you know, they had thousands of dollars of revenue and it was small, but you could at least, like, they were already

• 21:09Shayle Kann?

  Right. There wasn't like a long roadmap to first dollars of revenue.

• 21:12Speaker 01

  Yeah. 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.

• 21:50Shayle Kann?

  We see a lot of, and occasionally works, right?

• 21:53Speaker 01

  It has. I mean, to be clear, like, 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.

• 22:05Shayle Kann?

  Okay, so 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, somebody breaks out of those crowded markets sometimes, but the bar is so, so much higher for you. It's harder to raise capital.

• 22:38Speaker 01

  Yeah, exactly.

• 22:38Shayle Kann?

  It's harder to attract talent. It's harder to just separate yourself from the pack, basically.

• 22:43Speaker 01

  Well, this gets, this gets back into the commercializing science thing a little, which is,

• 22:50Speaker 01

  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 our tech-

• 22:58Shayle Kann?

  Right, right. We're the best 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 Y, right?

• 23:06Speaker 01

  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, has so many implications. And there's, you know, a much better-funded company incubated by a VC called Chaos Industries,

• 23:49Speaker 01

  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-

• 24:18Speaker 01

  Doesn't win you the race.

• 24:21Shayle Kann?

  It gets back to the old trope in venture of right, like a combination of team, 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 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.

• 24:38Speaker 01

  Yeah. Well, it gets into like 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.

• 25:08Shayle Kann?

  Yeah, that's the other point, right? Like how, what does it take to prove your rightness? How long? How much money? Et cetera. I think back on, um, you know, the, the heady days of all the solar technologies and the thin film technologies predominantly in the likely 2000s, early 2010s. And, um, you know, the, I think the common story that everybody tells about what happened there is that, you know, VCs invested billions of dollars into a bunch of different thin film technologies. And then meanwhile, China scaled up crystal and silicon, which is the dominant technology and costs got so cheap that there was no way to compete. And that, that's true. It is also true that in principle, some of those thin film technologies could be cheaper,

• 25:53Shayle Kann?

  right? Like they could still be cheaper than crystal and 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 crystal and silicon prices were crashing, nobody was willing to fund that effort. And so, you know, you, you may have been right, at least some of those folks may have been right. Um, but yeah, it means nothing essentially in the, in the grand scheme of things because they were never able to prove it.

• 26:22Speaker 01

  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, i.e. it was, you know, patentably obvious that your technology was better, and 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 it, 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,

• 27:05Speaker 01

  you're kind of working out all the kinks that 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 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, like if you, if you're just developing the technology, you have to like punt them, and then do them all later, and it's maybe too late, and you've

• 27:47Speaker 01

  got all this technical debt or something. This compounding is a wonderful thing.

• 27:57Speaker 00

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• 28:39Speaker 00

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• 30:07Shayle Kann?

  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?

• 30:25Speaker 01

  So when I say full-stack, I'm subtweeting a 2015 post from Chris Dixon at entries@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 leave limousine industry or to the hotel industry, we're leveraging software to influence the real world while not necessarily building hardware themselves. And I thought that was really interesting and largely apply that same thinking to more industries

• 31:09Speaker 01

  and the types of technologies that we invest in where you are building some software, but also some physical component.

• 31:16Shayle Kann?

  There's nuance to this, right? I mean, it's sort of a similar, Full Stack is similar to vertical immigration, right? Like, but it's not exactly the same thing.

• 31:24Speaker 01

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

• 31:33Shayle Kann?

  Yeah. I think the key thing for me, actually, more than like defining Full Stack, 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.

• 31:51Speaker 01

  Right, right.

• 31:52Shayle Kann?

  Sell to the end customer of the thing. Whatever your technology makes better, figure out what the end customer, who the end customer is for the thing that that made better, and then sell that product.

• 32:02Shayle Kann?

  But that is expensive. Like, let's be clear about the trade-off there, right? Like, because I think it is, it's like definitionally more capital intensive to do that. Do you disagree with that?

• 32:14Speaker 01

  No, this is clearly the downside of going Full Stack is that you typically need a little more money to do it. And like, 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.

• 32:55Speaker 01

  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.

• 33:13Speaker 01

  Then then treat them as pure trade offs.

• 33:16Shayle Kann?

  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?

• 33:27Speaker 01

  Yeah, so I mean, the a great example is mining. And there's a few companies in that in this space. Full disclosure, one of our largest investments is Earth AI.

• 33:37Speaker 01

  But you also have Cobalt, which is rates a lot of money and for AI. And there's a couple of 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.

• 34:19Speaker 01

  And it turns out it was very hard to sell that technology into mining companies. And 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, like, how much is it to acquire these mineral rights? How much is a drill? Like, 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.

• 35:03Speaker 01

  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 like, if you had taken the typical startup path of just selling software.

• 35:20Speaker 01

  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, you know, a mining SaaS company.

• 35:40Shayle Kann?

  The other category that I think of, as you describe this, that I think it's equally applicable to is the like 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 gonna 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

• 36:21Shayle Kann?

  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.

• 36:31Speaker 01

  Yeah, totally. I mean, one of the, one of the, 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, and it turns out it's not just the technology that, that improves. Every single time we've invested in a capable

• 37:10Speaker 01

  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.

• 37:29Shayle Kann?

  You mentioned even commodity thing. Let's talk about commodities for a second. A lot of the world that I treat, I'm like, you know, focused 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, you said in here, even commodities. So like, what is it that makes a commodity, a company who is going to end up, if they go full stack, they integrate downstream, they're going to sell a commodity.

• 38:14Shayle Kann?

  What is it, what does it take for that to be attractive to you?

• 38:17Speaker 01

  Yeah, I love, I love commodities. Like 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, and taking a step back, like 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, there's technical risk, there's execution risk and there's market risk. And you, you always have execution risk. So let's focus on the other two. In hard tech and deep tech and the physical world,

• 39:00Speaker 01

  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.

• 39:15Speaker 01

  If we're taking more technical risk and we are on balance, basically paying the same prices at seeds, 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. Like, these are the physics of finance, right? 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.

• 39:59Speaker 01

  I love when, like, in my memo, I can just look at the spot price of something on a liquid market. And I know 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.

• 40:28Shayle Kann?

  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,

• 40:36Speaker 01

  Yeah, but he invested in Impossible Foods for kidding that there was market risk there.

• 40:40Shayle Kann?

  Yeah, I mean, many things have... I think nothing is as simple as that makes it sound, right? Like, there is 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? Like, 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 indifferent to time and place. And that additional factor matters

• 41:25Shayle Kann?

  in terms of 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.

• 41:34Speaker 01

  I don't want to go into too much of a tangent, but like, there's an interesting corollary here to the type of real world full stack business that that we both like.

• 41:45Speaker 01

  And sort of decentralization of infrastructure, like i- if there is advantage to

• 41:52Speaker 01

  defy economies of scale and co-locate your your product, your, you know, behind the meter, energy generation, whatever.

• 42:02Speaker 01

  Then you are 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, um, 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, um, 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.

• 42:41Shayle Kann?

  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. So let's

• 42:59Speaker 01

  What do you mean, like, yeah, give an example?

• 43:01Shayle Kann?

  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 mined Bitcoin. That's that's a commodity, right? Bitcoin's clearly a commodity.

• 43:22Shayle Kann?

  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.

• 43:53Speaker 01

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

• 43:57Shayle Kann?

  No, it's no, it's different. I mean, CoreWeave 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

• 44:08Speaker 01

  Everything is computer.

• 44:09Shayle Kann?

  Yeah, 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 differentiated input, right? It was flare gas was their input to create Bitcoin and that's cheap energy.

• 44:25Speaker 01

  Right.

• 44:25Shayle Kann?

  If you could take advantage of it.

• 44:26Speaker 01

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

• 44:33Shayle Kann?

  Right, right.

• 44:35Speaker 01

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

• 44:40Shayle Kann?

  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, the would not have happened, certainly would not have happened in that timeframe, or they're wave riders, right? They correctly predict a trend a few years ahead of time and they time the development of 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

• 45:23Shayle Kann?

  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 the onus on the, you know, 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 your needs. I think it'd be similar in the full stack, deep tech concept, right? Like it's it's harder to do. You need more money. You have to do more things.

• 46:04Speaker 01

  Definitely.

• 46:05Shayle Kann?

  Right? And so what do you? How do you think about like the archetype of the founder that can do the full stack deep tech thing?

• 46:10Speaker 01

  Our preference for this type of business has also increased the onus on the entrepreneurs.

• 46:21Speaker 01

  And you know, when we thought that you just needed incredible technology and you know, sort of good enough business sense, I was not, um, not that we were lowering our bar for entrepreneurs, but I was sort of looking for different things. And now we flesh it out. Um, we actually have internally like a way 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

• 47:03Speaker 01

  you would 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 that I'm on this side of the table, not operating a company is I know I don't have those qualities. Um, 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. Um, and to do so, you probably need to raise, you know, nine figures of capital, probably ultimately billions of capital, um, across equity and other forms of capital. So the, um, the type of person you need to make a wave is like you said, like, you know, bends the

• 47:44Speaker 01

  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. Um, and if we don't get that sense, we sort of say, okay, well, maybe this isn't a wave maker. Um, 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, of understanding, communicate it to an expert, communicate it to the general audience and get people so fired up that they.

• 48:25Speaker 01

  Bend the fabric of spacetime to their will.

• 48:28Shayle Kann?

  Yep. All right. Just to close out, the other category of things that you do look forward to invest in, which I also share, you describe as weird N of one, 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, like, how would you articulate, why are the weird N of one, never seen anything like it before, ideas, good venture investments on balance?

• 48:55Speaker 01

  To continue the astrophysics parallel, like, if you're in a, a area with other astronomical bodies, you're sort of like competing with their gravity to pull in talent and capital and PR, then that's harder than if you are the, 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, we saw, we saw an early stage company recently that I thought was weird and interesting.

• 49:37Speaker 01

  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 a higher and higher prices. And, and I thought that was really interesting. I'd never heard, I mean, I've been doing this for 10 years. I see like a thousand startups a year, more. I'd 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 then. She's going to build like the company. And when people think of dinosaur fossils,

• 50:19Speaker 01

  they're going to think of her company. Whereas if you've got, you know, you and I have both invested in long duration energy storage businesses, but if you've got like the 20th LDES business, it's going to be a little harder to stand out. And the venture capitalists that 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.

• 50:40Shayle Kann?

  Yeah, but I want to separate two things. I mean, there's a part of this is 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 like if the narrative, if the story, if I can tell myself the story of what this company is trying to be, and like

• 51:25Shayle Kann?

  my eyes light up as I'm trying to do it, because it's like so interesting and so weird or so impactful, if it would have such a big impact on the world, I'm drawn to it. And that creed, that's a part of the magnet system that we were talking about before, 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 tagline, I don't know anything about them, apart from that they're trying to bring back the woolly mammoth. Like, that, that's interesting.

• 51:51Speaker 01

  But it's weird.

• 51:52Shayle Kann?

  Yeah.

• 51:53Speaker 01

  It's cool.

• 51:54Shayle Kann?

  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.

• 52:05Speaker 01

  Right. It's not valuable just because it's weird. For us, weird is a filter for might be unique. And, and, and unique in a valuable way. Look at this.

• 52:16Speaker 01

  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 Anduril weird in the beginning. Maybe I would have like now it's sort of hard to look back because it's so big and it's spun off all these other defense tech unicorns that, um, 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.

• 53:00Speaker 01

  And if you're not comfortable doing that, then it's going to be difficult to build a weird, unique end of one company.

• 53:08Shayle Kann?

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

• 53:14Speaker 01

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

• 53:17Shayle Kann?

  That's right.

• 53:20Shayle Kann?

  Ian Rountree is a partner and the founder of Kantos. 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 and theme song by Sean Marquand. Stephen Lacey is our executive editor. I'm Shao Khan and this is Catalyst.