Catalyst with Shayle Kann - The VC case for 'full stack deeptech'
Episode Date: January 8, 2026For “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 gua...ranteed 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.
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Latitude Media covering the new frontiers of the energy transition.
I'm Shayle Khan, and this is Catalyst.
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I'm Shale 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 ex post or whatever you want to call it, but I'm in the business of exceptions.
So here's one.
My friend Ian Roundtree is also an early stage investor.
He leads Cantos, which is a pre-seed and seed fund that's been doing deep tech since long
before it was cool.
I think he may have been part of coining the term deep tech and the same.
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 Campos.
One, full-stack deep tech,
selling an end product or even commodity,
not selling technology.
Or two, weird end of one,
never seen anything like it before.
Selling technology to incumbents,
pass, commercializing science,
pass, and the company doing the current thing, pass. I've been hung up on it because it
resonates so strongly with my experience and for the past 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, Shale. I'm excited to final.
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 ex-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 could not agree more
strongly with it. And 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?
Well, I've learned this like many things the hard way.
You know, I started Kanto's.
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're going to use this amazing technology
and we're going to like productize it in the simplest way.
And that'll make it easy to,
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 we can address that later.
It's more that it slows you down when speed is so.
critical to a startup.
I think speed is actually the key point about this.
Because 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.
Yeah.
Faster, cheaper, et cetera.
So 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.
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.
Yeah, and 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
owe debt. 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 are understandable reasons for this.
You know, the stakes are very high. In some industry's lives could be on the line. The customer
wants to do their diligence. And they're using something good and
enough today, question mark, and 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 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.
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,
before, 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 perspective you get.
Well, sometimes they're literally different teams.
Like, 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, sometimes quicken the sales cycle or assess whether you are pursuing a sales cycle that is compatible with your startup in the first place.
I will say I've learned this lesson in 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. 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, 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.
Yeah.
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.
Yeah.
I mean, speaking less to the value capture and more to the timeline thing, I think I'm thinking about a company like Cila Nano, which is run by a friend of mine, Gene.
Burteshevsky, I'm not an investor there, but Kosoachene, 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 OPMs 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?
Yes, definitely.
Okay, let's move on.
So selling technology to incumbents is hard for all the reasons we described.
Second category that you said as a pass, commercializing science.
I guess I want to hear what you mean specifically by that.
Yeah, I mean, without getting to the semantics of like, do we call it hard tech or deep tech, frontier tech or whatever, there was 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 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 if you were like 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.
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 I've lost a lot of money just waiting for a startup to advance through technology readiness levels.
So I feel like there's two pieces there to what you're describing.
One piece 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 think about things like fusion, for example, nuclear fusion, right?
Which is like anybody who's investing early in nuclear fusion, even if they were doing that 10,000,
years ago or today, like, it's sort of inherently breakthrough science that hasn't been commercialized.
I don't. The short answer is I don't. That's just not the time 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 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 expressly the type of science that we at Cantos do not invest in.
Yeah. Although I really hope for humanity's sake we pull it off.
And then on that first one, the sort of hammer and 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 ended up
incubating a company called Voia 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 in, 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 a question.
Like, are we missing something?
Why is that the way that everybody is doing it?
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?
Oh, man.
I should start by saying,
we're doing a lot less of it now,
having more than hard ways.
Times have changed, yeah.
We do very much believe
that, like, in our lifetimes,
the intersection of computation
in 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. Yes, I find this to be
frustrating not being in the farmer world, right? Because I look at the farmer 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.
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 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 farmer 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 investors for biotechnologies, it has been a really tough area for public and private companies.
For a while, like a third of publicly traded biotex 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 debt.
decades, it's sometimes still not enough to weather certain storms.
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 solugent, right? If you had looked early days to what solugent 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?
No, I mean, well, in Soligen'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 the, 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 commercial.
There wasn't like a long roadmap to first dollars of revenue.
And so it's just been scale up.
Like that, I would define, you know, they had this cool science out of their PhD work at MIT.
And then it was just like scale up from there.
It was more engineering after the seed round.
And 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 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.
Which we see a lot of.
And occasionally works, right?
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.
Okay, so that's two sort of tough categories,
selling technology and 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,
endth 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. It's harder to attract talent. It's harder
to separate yourself from the pack, basically. Well, 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 our type. We're the best, because
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.
Yeah.
But sometimes you do legitimately have something that is better than the incumbents.
Like, you know, I'll pick on 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 ABC 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 have a lot more capital,
and they're landing contracts with the government left and right.
And my hope is, because we've invested in a much better technology,
we can cash up.
But, like, I've seen this movie before,
and sometimes having the best technology doesn't win your race.
It gets back to the old trope adventure of, right,
like a combination of Team Tem, 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.
Yeah.
When 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-sufficiency.
styled intellectuals to sit and think that like, oh, I've just outsmarts at everybody.
But like, the market can afford to be wrong longer than you can afford to be right.
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, you know, the heady days of all the solar technologies and the thin film
technologies predominantly in the like late 2000s, early 2010s.
And, you know, 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 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 that crystal and silicon is, even.
out of silver 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 may have been right, at least some of those folks,
may have been right. But, yeah, it means nothing, essentially, in the grand scheme of things,
because they were never able to prove it. Yeah, I used to kind of think that you could, like,
if you had an amazing enough technology, you could, 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 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,
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 actually like startups that start small. And they,
And they just get that little compounding and learning every little like sales motion, getting know your customer better and internal operations.
And how does technology hand off with manufacturing and closing that designed for manufacturing loop?
And all those little things that like 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 got all this technical debt or something.
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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-scentral.
stack, deep tech, selling an end product or even commodity, not technology. So say more.
What is full stack? So when I say full stack, I'm sub-tweeting a 2015 post from Chris Dixon
at Andrews in 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 Airbus.
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.
And 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 also some
physical component.
There's nuance to this, right?
I mean, it's sort of a similar,
FullStack is similar to vertical immigration, right?
But it's not exactly the same thing.
There's heavy overlap, but it connotes the combination of technology
and non-tech product or services specifically.
Yeah.
I think the key thing for me, actually,
more than 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.
Right, right.
Sell to the end customer or 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 tradeoff there, right?
Because I think it is, it's like definitionally more capital intensive to do that.
Do you disagree with that?
No, it 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 added 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, then treat them as pure tradeoffs.
Can you give me like a canonical example for you of like a company either you are or not
involved with that is full stack in a category where they could otherwise be selling tech
to incumbents?
Yeah.
So, I mean, 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.
But you also have cobald, which is rates 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 defense tech, 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,
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 EarthA.I.
And I believe Cobold may have had a similar journey, although I won't speak out of turn,
I 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.
You've seen COBOL to 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,
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 route.
And that's a lot more interesting to me as an investor than, you know, you know, you.
a mining SaaS company.
The other category that I think of, as you described 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 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 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.
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, could we just, like, buy a failing general contractor?
Like, just do this better.
And it turns out it's not just the technology 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.
You mentioned even commodity thing.
Let's talk about commodities for a second.
A lot of the world that I treat it, I'm like, you know, focus in energy and industrial.
And like, when you boil that world, the energy in particular, down to its core constituent
parts, it's mostly commodities, right?
Electrons or MMBTUs or whatever.
And notoriously, commodities are difficult market.
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, like, 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?
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, 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 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, in deep tech, in a 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 C,
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.
I love one, 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.
I've heard Van Gogh, 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.
Yeah, but he invested in impossible foods forgetting that there was market risk there.
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 like electrons are commodities.
They're kind of not, right?
Like, yeah, an electron is is a fungible thing and it's similar to every other electron, except where and when it is delivered is very, very, 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 a
from an investment perspective.
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 we both like
and sort of decentralization of infrastructure.
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 invested in some of those,
but you just have to be clear about whether the counterparty
is going to slow your sales cycle down.
Yeah, there are also interesting examples
that are like companies in a commodity space
with a differentiated input
and or companies of commodity space
that their execution and ability to learn
in that market allows them to enter into a new market
that's non-commodity.
So let's take a given example.
Crusoe, right?
So Crusoe was flare gas to Bitcoin.
That was the start of the company.
They went and locked up assets that were methane flaring,
it's wasted energy.
They turned that, they put little data centers there and mine Bitcoin.
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 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 now they're building, you know, Abilene Stargate Campus
for Open AI and Oracle and a bunch of others,
and they just raised money at a $10 billion valuation.
Now they're a totally different company.
Yeah.
I think Corrieve started mining crypto, too.
I don't know if it was because they were flaring, but...
No, it was different.
I mean, Corwave was just doing crypto mining.
A lot of crypto mining companies are now, you know, AI data center companies.
That pivot is not unique to Crusoe, but I think they've been being able to particularly take advantage of it.
What's interesting to me about it is like 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.
Right.
If you could take advantage of it.
That's what I mean.
If you have a structure.
advantage in producing a commodity, that's like the holy grail.
Right.
Like if I can make dollar bills for 70 cents, I'm a trillionaire.
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.
time frame or their 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 that time frame 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 a 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 were swimming against the tide and you have to bend the
arc of the universe to meet your needs. I think it would be similar.
in the full-stack, deep-tech concept, right?
Like, it's harder to do.
You need more money.
You have to do more things.
Definitely.
Right?
And so, how do you think about, like,
the archetype of the founder
that can do the full-stack deep-tech thing?
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
scoring founders along six axes and how we tease out each of those.
And a lot of them are around the qualitative.
It's sort of, you know, it's talent gravity, 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 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.
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 advantage.
incumbent and to do so you probably need to raise you know 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 waifemaker. And we've just found ourselves looking
for people that are both incredible technologists and also have this ability to communicate
things in a hyperfluent 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.
Yeah.
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 end 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 end of one never seen anything like it before ideas?
good venture investments on balance to continue the astrophysics parallel like if you're in a
area with other astronomical bodies you're sort of like competing with their gravity to pull in
talent and capital and 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 our early stage company recently that I thought
was weird and interesting.
We ultimately didn't invest where a woman 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.
I've never heard.
I mean, I've been doing this for 10 years.
I see like 1,000 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 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 have both invested in long-duration energy storage
businesses, but if you've got like the 20th L-DES 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.
Yeah, but I want to separate two things.
I mean, there's a part of this is just the flip side of endth 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 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 magnetism that we were talking about before
that 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.
That's weird.
Yeah, it's weird.
So, yeah, I guess I just 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.
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 Andrew.
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 it's 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.
All right, Ian, this was unsurprisingly a lot of fun for me.
Thank you, again, for joining.
Of course, yeah. Well, this is just one of our normal conversations
so we hit record this time. That's right.
Ian Roundtree 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 Lacey is our executive editor.
I'm Shayal Khan, and this is Catalyst.
