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Making capital allocation decisions in low information environments and with alot of uncertainty is hard. This show talks to people who do this every day and teases out how to be good at it.
Martin Tobias (00:01)
Hello, hi, this is the first bet. Every successful person gets interviewed about how they won and nobody takes them back to months before they knew that it would work, when the information was thin, when the money was real, and they push their chips in anyway. That's what we do here on the first bet. I'm Martin Tobias and I've bet money three ways as a CEO, as a pre seed investor, and as a poker player.
And today, my guest today has 15 years inside the machines at Apple, Google, BlackBerry, Toyota shipping hardware that ended up in billions of pockets. He looked at the factory floors still running old paper and ERPs before the iPhone and decided that's where the money was going. not after the AI manufacturing moment has arrived, but before that. And that's what I want to talk to about.
today. Simon Lancaster is the founding partner of OmniVentures, self-branded as a manufacturing VC. He's also co-author of Unlocking Alpha, The Rise of the Niche VC, which I've read. I really recommend it. The bet we're here to talk about is the first one, you know, leaving the logos and raising a fund in a sector that the market had kind of written off or not thought was too small and writing a check before it looked it's inevitable.
Simon (01:20)
Mm-hmm.
Martin Tobias (01:22)
He recently announced last week a thirty three million dollar fund. Simon, welcome.
Simon (01:30)
Thank you so much, Martin. Really appreciate the the warm intro. And I'm really happy to be here. Excited to talk to you.
Martin Tobias (01:35)
Yeah.
Yeah, thanks. And I've enjoyed, you know, we were at that dinner with Michael Dying that one time and we hung out in Sundance in and got our cowboy hats. That was a lot of fun. so I wanna talk about that that the the bet that you made of leaving the safe safe companies and deciding to start a fund before it was
obvious and I think even in their your announcement of your fund last week you noted that even a year ago it was a little counterintuitive to do a pre seed fund. There were big funds putting big investments in, but the idea of a of a of the first check into some of these manufacturing ideas was a little counterintuitive. but you had some conviction. Maybe talk to me about before the market agreed. how did you get conviction and and and and how did you think about
Simon (02:13)
Mm-hmm.
Mm-hmm.
Martin Tobias (02:32)
putting your own capital in to a fund that early in that sector.
Simon (02:37)
Sure. Yeah, that's great, great talking point start. maybe I'll just start with kind of like a tidbit, which I I still find quite interesting even today, is what when we bring up the thesis of our fund being manufacturing tech, people are like, you mean like building factories? And I say, well, if I were to say fintech, would you say building banks?
Martin Tobias (03:05)
Ha ha.
Simon (03:06)
And and you know, and and so so you can take that same analogy with with biotech, fintech, construction tech, etc. There's really this I guess left behind mentality around manufacturing where people just don't associate technology with manufacturing in the least. in in especially Silicon Valley technology, you know, capital light software.
centered or technology centered bets. So that that's kind of I think the the current day point still. But to your question, going back a couple years, you know the as you as you mentioned, there there had been some some larger investments into capital intensive deals. But as we
Martin Tobias (03:44)
current day right still that's your question going back a couple of years. you know as you as you mentioned there there have been some some
Simon (04:06)
Started the firm, we actually initially thought, okay, deep tech hardware, and realized that venture capital was was kind of becoming a little bit commoditized, both in good and bad. And I touch on this in the book. Like it's becoming democratized. Anyone almost anyone can start a capital efficient venture capital firm. and that led us to think, okay, well
Martin Tobias (04:16)
Right.
demonetized both in gym and death when I touched on this in the book like becoming democratized if anyone else anyone's concerned capital efficient venture capital firm and that led us to think okay
well if we just took to that ability to be capital efficient ourselves to the degree where everyone needs focus where is our alpha where is our own civilization
Simon (04:36)
If we just took that ability to be capital efficient ourselves to the nth degree, where would we focus? Where is our alpha? Where is our own differentiation?
And where can we see ahead of the curve and around corners where others couldn't? And we just kind of kept double-clicking. hardware, deep tech, the next level was manufacturing. And when we looked at manufacturing,
Martin Tobias (04:58)
So that's the best.
Simon (05:04)
under the microscope, I I guess you could say, we realized a few interesting things. One is it it really had been left behind. one of the one of the major talking points that we have in our in our funds thesis presentation, our pitch our own pitch deck, is that all the major sectors of the GDP take finance with fintech, business services with SaaS.
Martin Tobias (05:05)
Microscope, I guess you could say we realized a few interesting things. One is it it really had to have you. one of the one of the main sort of talking points that we have in our in our funds presentation, our pitchback, our own pitch deck, is that all the major selectors of the GPT that you can find against the students and business purposes with staff.
Simon (05:34)
IT with you know search and and the web the list kind of goes on they've all been digitally transformed and manufacturing is essentially industrials and manufacturing is essentially the the last bastion and and this was twenty four twenty three-24 and we and we said okay well it's not gonna be like that forever it's impossible it cannot it cannot continue to be left behind
Martin Tobias (05:35)
IC the first and and the web of this kind of fun they've all been digitally transformed and manufacturing is essentially enough with manufacturing
And then that's where the one he needs to w twenty three, twenty four.
used to be left
behind and undigitized according to the paper and stuff on the email remembrance. So R2 a big point outside of really the the the the point of of the big best for this term. Okay. And so when you say digitization, because you started with sort of deep tech and and and and hardware,
Simon (06:03)
and undigitize and run on paper and excel and email forever. So are we at the tipping point? That that was kind of really the the the point of of the big bet for this firm.
Yeah.
Martin Tobias (06:26)
Is that what you're investing in, or is it more the software? Like for example, I invested in factory.app, which is a lightweight ERP for small manufacturers like CNC shops. And my insight there was that most ERPs were big Oracle for, you know, Ford and GM, but the the the small manufacturers where 80% of the capacity is had been left out and there was no cheap, easy sort of mid-market thing, you know, except Microsoft Dynamics or whatever. Were you thinking more software transformation or were you thinking
Simon (06:28)
Mm-hmm.
Mm-hmm.
Martin Tobias (06:54)
you know, har hard manufacturing hardware that could be reinvented with AI or something or monitoring or y what what part of the digital transformation are you talking about?
Simon (06:56)
Robotics automation, IoT, yeah.
Mm-hmm.
Yeah.
It's great question. Initially our thesis was just broadly software automation. At the end of the day, software reduces friction and makes things more efficient. And you know, you can take that, you can you can build software with whatever the latest web one point two point three point zero or AI. you know, you wanna be building businesses that are software centric with with the latest wave of technology.
Martin Tobias (07:17)
Yeah.
Simon (07:36)
when we started, it it was really SAS, yes, and what you described would have been our our part of our core to our thesis, because yes, we are still lacking in capital efficient software for small, medium, medium-sized businesses and large businesses in in manufacturing. but as part of that digital wave, transformation wave, we are also starting to look at physical automation, physical AI and robotics.
Martin Tobias (07:44)
Yeah, you are spelled by
Simon (08:05)
And you know, we still consider those to be capital efficient and and digital transformation as part of this digital transformation wave, as long as they are tr actually relatively capital efficient.
Martin Tobias (08:19)
Yeah, yeah. I I've seen a lot of deals lately that is software around enabling of the robotics, not necessarily the the robotics themselves, like how to do the actuator and the arm and stuff like that, but how do you give that robot better spatial awareness, better yeah, understanding of its physical environment, safety, not you know, whacking pr human as they walk by and stuff like that. So
Simon (08:35)
Yeah. Insight sensing. Yeah.
Mm-hmm.
Martin Tobias (08:47)
you're you're looking at a a lot of those software things for robotics in the manufacturing.
Simon (08:54)
Yeah, hardware enabled,
sensing enabled, robotics enabled software. the the the challenging thing with these solutions, like you mentioned, Martin, these could be incredible new, you know, let's say ultrasonic sensing to let robots see through through walls. And and you know, even if we see that it's very useful for whatever spatial awareness, person detection, s security.
It's the who is the customer it becomes the challenge with this one. And and you know, can it be venture scalable? and what we have kind of realized from talking with thousands of customers, many of which are LPs and founders, and from our own experience, is that
The the the the full stack solution tends to be the easiest to show ROI. And and customers in the industrials and manufacturing space, they are it's an old industry and they're relatively impatient. so they they like to see kind of not not necessarily proof of concept, but more like proof of ROI through through actual deployments.
Martin Tobias (10:02)
maybe other it's in the whole industry.
patient. Would they they'd like to see kind of not the process trade on that?
Mm-hmm.
Simon (10:19)
So how do we thread that needle of being relatively capital efficient, having a novel technology, and a
reasonably timed commercialization, not ten years, but two to three years, that's what we typically look for, while still having a big bet r hopefully right, a big bet for venture.
Martin Tobias (10:42)
Exactly. So one of the things you noted in your announcement last week of the King of the of the fund is that when you started raising this fund, which was what, about three years ago? you know, it was really hard to get meetings and a lot of people were saying maybe this is too small and whatever, but something seemed to have changed like a year ago. can you dig in a little bit more to that? Like how did the first meetings go? And was it a change in your thesis or was it a change maybe outside of of the
Simon (10:51)
Yeah.
Exist.
Mm-hmm.
Martin Tobias (11:10)
environment of people saying, you know, finally the AI intelligence layer is there or was was it an unlock that was had to do with how you were pitching your your thesis or was it an unlock maybe that was outside your control that happened in just the awareness of you know LPs and things like that. maybe this thing, you know, maybe there is an opportunity here. Because there frankly haven't been a lot of really great exits
Simon (11:16)
Mm-hmm.
Mm-hmm.
Martin Tobias (11:39)
in startups for manufacturing tech yet, but your bet is they're going to be enabled by something, right?
Simon (11:47)
Mm-hmm. Yeah, I I would I would argue that yeah, there have not been a lot of flashy ten in exits in the tens or hundreds of billions. There have been a lot of significant unicorn around unicorn exits. The the main difference is many of these exits, if not the vast majority,
are exits to publicly traded companies, deep-pocketed publicly traded k companies. And those tend to be not as prominent, not as picked up by the news. but okay to to answer your question how did our thesis change? How how have pe people's mindsets change over the last couple of years.
Martin Tobias (12:20)
But also I need to be
Finds it has changed over the last couple of years.
Simon (12:39)
We pretty early on we said, okay, this lack of digital transformation is has to be solved. Is the time now. and we felt like it was it was now a few years ago. We felt like it was coming in the la in the next few years, which is basically now. and I'd say that the main factors for that
Martin Tobias (12:48)
Existence.
Yeah.
And I think that the game factors for that
was
Simon (13:08)
was
talking with LPs, like big big customers who are LPs and and families that own businesses in this space. And most importantly talking to the to the next generation. So the the the up and coming executives or the sons of the current owners and essentially realizing that they were all extremely frustrated with with a couple of things. One is just the lack of
Martin Tobias (13:17)
And most important stuff is to the to the next generation. So the to the often companies are actually those.
Simon (13:37)
basic automation, whether it be it software or you know this combination of of software and hardware that that you mentioned. and then the the other one was fear of of labor shortage and the solutions around that. And then lastly I would say which is related to just
Martin Tobias (13:38)
That's great.
Mm.
Simon (14:06)
th this this population that we were talking to in general, the fact that this is a old industry, all the owners have been around for a while, the businesses have been around for a while. These are the customers of all of our portfolio companies that I'm talking about.
They were going through a generational shift in in in management. Like these up-and-coming executives or owners were about to take over because all the baby boomers that have been running the businesses are now retiring and you know will be retired in the in the next few years. And the next generation just didn't want to run the businesses the same way. and
Martin Tobias (14:31)
Yeah.
Okay. Yeah.
Yeah.
Simon (14:52)
I guess we we got that insight from just pitching our fund and talking to lots and lots of, you know, prospective LPs and the ones that just got it the quickest were were this persona of man, this this fund solves a real pain point in our operations. Like the fund thesis being able to bring our industry up to the same level of, you know, fintech, for example.
Martin Tobias (15:21)
Yeah, yeah. I I I've seen that in in other categories too. It there there it's it seemed like about a about a year ago, a a whole bunch of these second generation people just said, Hey, I now the combination of things happening in AI or software development. I think I think another thing that I've seen in my portfolio, I was gonna ask you if that if this was you know something that triggered people too was
Simon (15:40)
Mm-hmm.
Martin Tobias (15:46)
The increase in coding capacity given by Clawed Code and all these other things. You you could now write, whereas a lot of the reasons these industries were left behind is that it was so hard to write software that people were like, we're gonna use Excel or some general purpose fucking software because writing software is hard. But the minute writing software became easy, then they're like, Well, maybe I could use
Simon (16:00)
Mm. It's true.
Mm-hmm.
Martin Tobias (16:12)
some custom software for this because software is easier to write. That seemed to have been an unlock about a year ago.
Simon (16:17)
Yeah. It's it's for
sure. For sure, for sure. Yeah. And I would say to double click on that kind of the result of that is two things. Now you can build vertical tools, like not like Oracle and Salesforce Salesforce that serve everyone but poorly. You can now build these highly integrated, highly, you know, specialized tools very efficiently, essentially as you're describing.
Martin Tobias (16:33)
Yeah.
Simon (16:45)
And the other thing it enables is it enables much smaller teams and teams with founders of deep technical background of that field to build the b business versus a team of software engineers, which typically, you know, they wouldn't go after this industry, they'd go after something bigger, more lucrative, more flashy type of thing. But but the but the founders that have experienced the pain point firsthand.
Martin Tobias (16:56)
Yeah.
Simon (17:14)
And are like, I I'm this is what I'm solving. This is the this is the biggest pain point of my career, are now able to and and therefore serve the customer a a lot better. Right?
Martin Tobias (17:16)
Yeah.
Yeah, yeah, exact exactly. I'm I'm
I'm seeing that a lot too. It's that people who understand the business problem very well now have an easier path to create a technical solution versus, you know, trying to hire outsource developers in India or anything like that. yeah, so that that that that's good. So let me go back a little bit more to, you know, w what was the case sort of against doing this?
Simon (17:34)
Mm-hmm.
Mm-hmm.
Martin Tobias (17:54)
I mean, I maybe you could identify two or three of the reasons in the first two years that people were saying no. I think part of it was probably you know, manufacturing moves slowly, long fucking sales cycles, these people don't change, blah, blah, blah. Maybe you could steel man, you know, the the case, you know, that was against it at the time.
Simon (17:55)
Mm-hmm.
Mm. That's right. Two niche. Yeah.
Mm-hmm.
For sure.
I yeah, I would say, you know, the the financially focused LPs that didn't come on board, almost all of them said too niche, which you know we can talk about. I I'm I'm now adamantly opposed of any, you know, and any venture fund being too niche. I've I'm now an LP in like several sub five million dollar funds, and arguably, you know, as early angels, I think it's it's great.
The the other one is is certainly the long sales cycle. and you know, what we saw essentially was that the majority of our great founders that got early traction w were essentially showing up with with almost like r ready-made tailor-made solutions, like very quickly. that
had very short return on investment. Right. And and and like you c as an executive or an owner, if if you're if you're being presented with something that has a very short return on investment, it it's you're gonna you're gonna you you have to you have to try it. Right. Yeah, you have to try it. Otherwise you're you're dead in the water.
Martin Tobias (19:20)
And like
That it was something that has a very short return.
It's you're good you're good that you you have to be.
Okay.
Simon (19:39)
So so really focusing not not
on again, not on concepts, but on you know solutions that provide value that that can work very quickly and that provide value that leads to return on investment very quickly as well.
Martin Tobias (19:59)
Okay, super. And talk to me also about how you came up with the fund size and how you decided, you know, appreciate I pr I think probably one of the other, you know, cases against it was, you know, manufacturing's hard, you gotta build manufacturing. It's all capital intensive. Like how can a small fucking fund do anything in in in a capital intensive business? Now you're g going, you know, for software which is more less capital intensive and so on, but how did you end up with about a thirty million dollar
Simon (20:14)
Mm-hmm. Mm-hmm. Right.
Mm-hmm.
Martin Tobias (20:27)
a fund size and why do you think that's the right thing to catalyze the founders that that you want to catalyze?
Simon (20:36)
Probably probably the you know one of the most controversial topics in the in the industry in general. and I think you know I've had great debates on our own podcast, Beers with VCs, on this, you know, spray and pray versus concentration. And different LPs certainly prefer one way or another. Typically, you know, what what we found is
Martin Tobias (20:53)
Yeah.
Simon (21:06)
the the LPs that want to deploy after you, like this the strategics or the fund of funds, they want you to have higher concentration, likelihood to have prorata, but no pro rata, follow on budgeted. but you know in in our case we
Martin Tobias (21:22)
You know, in in our case.
Simon (21:26)
W we weighed a few factors and and I'm gonna credit my my co GP Sabrina Passman for running, you know, an insanely detailed fund model where we looked at essentially every single exit in the last thirty years in the industrial space and we kind of filtered them down by okay, you know, essentially
Martin Tobias (21:28)
That's indeed credit.
It's anything like a double.
What's that? Essentially every single text to take five or three years of Interesting.
Simon (21:55)
regression analysis would we have invested in in these based on our thesis? what was the fund what was the fund sorry, what was the exit of that startup? And then what would our ownership need to be at the beginning given various simulated number of bets and a fund size that we thought we could raise based on being first-time fund managers with with limited
Martin Tobias (22:09)
beginning to give it various stipulated number of tests and one size that we thought we'd do raise
Simon (22:27)
institutional investment experience. And we felt like we, you know, also we went through Cool Water Capital and and we got allocator one to anchor our early close, both of them, you know, very, very professional, pseudo-institutional fund of funds, meaning they're just emerging still, but I think I think highly of all of them.
Martin Tobias (22:30)
And because like we you know, also we went through what our capital
Simon (22:54)
And we at the end of the day decided to go for the approach that that we talk about in the book unlocking alpha, but it's essentially a specialist approach. Assuming that we with our focus and and mastery were able to see ahead of the curve in our vertical. Sorry, I I reference mastery and focus like the three things in in the book that
Martin Tobias (22:57)
Yeah.
What does it do?
Simon (23:23)
that we double that we emphasize mastery focus and network being generators of of alpha.
Martin Tobias (23:26)
Emphasizing after your focus network is about.
Yeah, maybe we could talk a little bit more about that because you did write a whole book about how to generate alpha from emerging managers. And can you go a little deeper on those three things, the three things you think that these smaller emerging managers get or have or can have that differentiate them from the bigger funds? Because I know
A lot of people think about venture and they're like, it's Andreessen Horowitz, it's Sequoia, and and but I mean these smaller funds are a completely different asset class and they need and and they have completely different advantages over these bigger funds. These bigger funds you know are are really a completely different business. What what have you did you identify by talking to lots of other emerging managers as frameworks?
or things that emerging managers can use to pick and generate alpha in in ways that maybe some larger funds cannot or ha or do not.
Simon (24:27)
Mm-hmm. Mm-hmm. I think essentially as an emerging manager, likely to be focused on pre seed with a smaller fund, you have limited options. Option one is you do, you know.
pray and spray approach and you get exposure to many deals and you you hope to hit on a on a big bet on a big outcome as one of those deals. The other approach is to do less deals, get higher ownership, and earn your way into the deal through essentially your your focus or specialization. I think there are
Martin Tobias (24:49)
and you can have exposure to any deals and you can be focused a bit on a on a big that on a big applied.
This is more special information. I think the
repart S one managers that have actually managed the
Simon (25:18)
excellent managers that have actually managed with both. And
even in in the generalist approach, you can compensate for your lack of background and expertise through having a a really insane network network effect essentially. And the approach that we chose having having come from industry and being
Martin Tobias (25:42)
from the industry and he
Simon (25:45)
having double clicked through the layers of deep tech to or hardware to deep tech to manufacturing was essentially to be very, very focused on on a single stage pre-seed and to bring value to founders through our industry expertise and and also just as importantly our industry connections. And that's really where we've seen ourselves getting the
Martin Tobias (25:47)
And to bring value to the boundaries.
industry expertise and and also just as important in our industry connections. And that's early where we've seen ourselves getting
Simon (26:15)
very high quality deal flow and and being able to win deals in in competitive rounds. And and yes, also to your point, successfully raising a thirty three million dollar fund in arguably one of the toughest environments,
Martin Tobias (26:15)
very high quality yield flow and being able to win deals in the bag and grounds. yes also your point to successfully raising 33 million dollar fund in arguably one of the toughest environments.
Simon (26:32)
toughest times, right, in the last twenty years.
Martin Tobias (26:35)
So what are those three things again that you mentioned for a a focused?
Simon (26:38)
Yeah, so
so so in the in the introduction thank you for for for for asking in the introduction of the book we we essentially define alpha as MFN mastery, which is a you know deep domain expertise and you know maybe you could call that specialization. focus. Focus is kind of two things. It's
Martin Tobias (26:54)
Okay.
Simon (27:05)
being focused on your area of expertise, the being essentially knowing to be focused on the your area of edge. And then the last one is network.
Martin Tobias (27:06)
Okay, it's not.
Okay.
Simon (27:19)
And network is
you know, it's it's a bit of a a catch-all, but it is a constant reminder that venture is is a person a people game, right? You you need to earn your way into rounds, you need to be liked, you need to people to want to take your money. and it's like MFN or Alpha, it's a product of those three. So you can score low on on one or two.
Martin Tobias (27:33)
Yeah.
Simon (27:48)
But not on all three.
Martin Tobias (27:51)
Great. And I I like that framework for emerging managers and I would I would agree with those three things. And we've talked a lot about how you you know the the con how you built conviction and and and what your edge was for for your particular fund. But I'd like to t to pivot a little bit and see if those three things are the same things you apply to founders or how do you think differently about low information decisions when you deploy capital
Simon (28:14)
Mm.
Martin Tobias (28:19)
into founders because it's very similar. You're gonna find somebody that hopefully has a lot of domain experience and this and that. But it is it similar or different, or how would you compare the capital allocation decision to write a check into a pre seed founder versus, you know, as an LP, your your p p you know experience trying to raise a VC fund. They're similar in some ways, but they're also a little bit different. Maybe you could talk about some of the frameworks that are the same or different about how you think about choosing founders in the pre seed.
Simon (28:23)
Yeah. Yes.
For sure.
Mm-hmm. You know, in in preparing for this podcast, I for the first time because of of the thesis of the podcast and the topic, I I made that comparison. But I've never actually answered this question, which is fascinating. Like, how do you evaluate founders using the same methodology? And no no, I I it's very interesting because we actually wrote the book.
Martin Tobias (29:02)
Okay.
Or do you use it differently?
Simon (29:18)
last year, which was two years after we developed the thesis for the fund. And the original thesis, like the founder archetype that we that we wrote, I still remember it quite vividly, was deep tech founders, so like technical founders solving the biggest pain points of their careers. And then we always looked
To see if they had spoken with 100 or more customers and how strong their go-to market network was. So arguably you could say, you know, deep tech, technical founders, that's the mastery component. Solving the biggest pain point of their careers, that's the focus aspect. And then, you know, the commercialization mindset and go-to-market network is their kind of go-to-market unfair advantage. Like how many.
Martin Tobias (29:59)
Mastery?
Focus.
Simon (30:15)
customers can you call up on day one and get them to try the the the product. That's the that's the network. So there is actually a very uncanny correlation which I never thought of before, but but certainly you know you bring up a really interesting point there, Marsha.
Martin Tobias (30:36)
Yeah. I I agree. There when when I read the book, I was like, this looks a lot like how I evaluate founders. especially that network thing, given that it is so much easier to build software. At at one point I might might put as a third thing, you know, do you have a technical founder? Can you build the product? Can you even build the fucking product? Especially in deep tech, a lot of times that's the question can you even build it? But if you're just building software.
Simon (30:48)
Mm-hmm.
Absolutely.
Yeah.
Martin Tobias (31:05)
likely you can build it. The the real question is can you sell it? Can you get any attention in a you know complicated market where lots of people are calling up your customers and this and that. And so I focus a lot more these days on what's your distribution wedge, what's your unfair go-to-market and stuff like that. And if the person is in an industry trade association or if they, you know, worked at a prior you know, you know, in how you're gonna get your first hundred customers.
Simon (31:12)
Mm.
Yeah. Absolutely.
Martin Tobias (31:35)
That's the real differentiator for me for most founders these days because it's so much easier to build whatever product you're you're building. yeah. Absolutely.
Simon (31:35)
Mm-hmm.
Absolutely.
Yep. Yep. I I agree.
Yeah. And when I look at, you know, out of the thirty odd investments we've done, the ones that really stand out are the ones that have an uncanny ability to explain technical problems and their solution and use this to quickly build rapport with customers and investors, right? Like not so much a technical savant, but someone who deeply understands the pain point.
Martin Tobias (32:10)
Instead.
Simon (32:12)
and is able to build a business to capture that that pain point through a solution, but more importantly, clearly communicate that and and in so doing, build rapport and trust with customers more quickly. And this to your you know to your point, it's becoming more and more important, I think, now.
Martin Tobias (32:16)
Okay.
This you're you know, your point is becoming more and more important, I
think. Yeah, absolutely. well that's interesting. We discovered maybe a potentially more portable rule that your alpha thing for emerging managers fits a little more for founders as as well. how do you think that it might change you know for founders in in the next five years? It does seem like
You know, this faster software development has unlocked a lot of new applications. you know I I I I I've talked to a lot of people that are trying to bundle hardware and software now with these managed services type things. if you're putting on your forward looking hat, how do you think it's gonna be different being a founder five years from now in this manufacturing thing versus today?
Simon (33:19)
Mm-hmm.
Mm-hmm. Yeah, I think one a couple a couple things that that are kind of top of mind but but nascent. One is the willingness to pay for recurring fees is is is actually
Martin Tobias (33:47)
Software.
Simon (33:53)
Improving, I would say, in in the manufacturing industrial space, but it's it's not like SAS. It's more like what we're seeing is more akin to maintenance or guarantees of service packages tied to a human interaction. So almost like AI-powered.
Martin Tobias (34:20)
Yeah, the passage it's a little more.
Simon (34:26)
services where where the where the the company has someone at you know the customer has someone that they are imagining that service coming from but but that it's it's very much moving at the speed of AI. that's maybe I I don't have like a a you know a clean verbiage for for wrapping that up but that that's one thing that we've noticed.
Martin Tobias (34:35)
Not one that's a
Okay, problem. But but that is very much moving to the screen that AI. that's maybe I I don't have like a
I I had
I I don't really either, but the the trend, you know, I I was watching Jensen Yang talk a couple weeks ago and one of the things he pointed out, which I hadn't tracked yet before, is that the pace of improvement in AI is an order of magnitude faster than the pace that was following like Moore's law. Basically all of software and all of computing followed Moore's Law. Every eighteen months the CPU
Simon (35:16)
Mm.
Martin Tobias (35:21)
density doubled and then you know the cost halved and this kind of thing. And that was fairly predictable for about 25 years. But it was an 18 month innovation cycle. And in AI, you've got like a three-month innovation. You've got intelligence doubling every three months to six months instead of every 18 months. So then when you go forward a couple of years
I mean, I've even seen people saying, you know, we started three years ago with a chat bot and we now have agents that can complete c full tasks. I think that three years is probably faster than people at the beginning of chatbots thought it would be because of the compounding that we've seen. Right.
Simon (36:03)
Absolutely. Absolutely.
Martin Tobias (36:06)
So it it's gonna be kind of interesting. we are in the, you know, what's it gonna be like in the future business? But I I I I feel less confident in my ability to do that. But what's what what I feel confident in is you know, making the bets in in teams that really understand their problems and are AI native. One of my portfolio companies last week sent me an update and he's like,
You know, a year ago I had fifteen people, today I have two and I'm doing twenty percent more revenue. So in one year they got way more capital efficient with their business. and I think you're gonna see more of that in in in every business is capital efficiency. That's kind of kinda kinda kinda interesting. so let's go back I we're getting close to the end of this here.
Simon (36:44)
Wait.
Easy, easy.
Martin Tobias (37:00)
What are some of the things, you know, that were the the gremlins in in this decision, you know, for you? What were some of the people, you know, when you were when you had this conviction, what were some of the things in the back of your head that said maybe this this isn't gonna work? I mean, what what were some of the things that you were worried about you know, committing your life to to to do to doing this, new fund?
Simon (37:28)
Yeah, I you know, I I briefly mentioned it earlier, but I think it's worth bringing up and discussing a little more was this concept of the fund being too niche or too focused, too small, too niche. It does the does the thesis allow for enough follow on investment? and you know, especially
Martin Tobias (37:40)
Too niche, okay.
Simon (37:57)
prior to any big follow on investors having having invested in any of our portfolio companies, like are there even big follow on investors to to take these companies to be to be huge? you know, we we took we took a multi pronged approach to dispelling that. I would say one was looking at the
Martin Tobias (38:10)
Yeah.
Simon (38:28)
the outcomes and and essentially determining that, hey, even if even if we only have a $1 billion outcome or a $800 million outcome, could we could that somehow be an advantage to us? Like if we got in early enough and if the exit horizon was short enough, could we make that work and and built out models around around that?
Martin Tobias (38:46)
Yeah, so we got it.
Simon (39:00)
and the other thing was just looking at, like you mentioned, some of the most capital efficient teams and the way they were building, and very early on seeing that that wave coming, and determining that hey, maybe we are able to build these businesses without mega rounds and have
Martin Tobias (39:08)
And very early on seeing that that waves coming. and just turning that same age.
Simon (39:27)
you know, billion dollar eggs. and you know, I think I I was one of the early adopters of the of the pre-seed or seed strapping type mentality. I'm not saying that's all we focus on, but certainly, you know, being a s a smaller and more capital efficient focused fund, we saw that as as an a attractive approach.
Martin Tobias (39:41)
Yeah.
Okay. Yeah, I I agree. well i thinking about all the you know frameworks that you use to make a decision to start a fund that was un un not obvious at the time, if there if you were to to s leave with one idea for somebody else that's thinking about putting a big capital decision in a low information environment today, you know, what would that be? How what would you tell a person that's trying to do that, either a CEO or another
investor trying to decide to put his own capital in in in a completely uncertain environment.
Simon (40:35)
Yeah, I you know, I I love this question because I think there's there's so many right answers. And there's probably so many wrong answers, but there's so many right answers and and what I love to do is find founders that are able to communicate a a large picture, a large vision, large enough, hopefully just large enough for our fund, but that have
Martin Tobias (40:41)
Yes.
Simon (41:05)
spoken with a hundred customers and have their finger on the pulse of the market today and what the problem is today. And they have developed a unique and capital efficient go-to-market, a unique wedge. Right. So, you know, a company that's I'll I'll give you a specific example. one of the only companies we've we've done a follow-on investment into is a company called Xenode.
Martin Tobias (41:13)
But let's make a pink and apple.
Right, so you know a company that's developing just as an example. one of the companies we have with a ball investment into
Simon (41:32)
Run by Brandon Bourne out of San Francisco, amazing electronic design AI company. While while everyone was going after this 10-year horizon
Martin Tobias (41:33)
is a company called Cino, Brandon Warren's electronic design AI company. Well everyone's going after this 10 year
Simon (41:44)
EDA, which is essentially like AI-powered electronic design of PCBs, and you know, they wouldn't really have a working product in gears, and even more importantly, the accuracy level that you need for for
Martin Tobias (41:46)
Yeah, which is essentially AI proper electronics design.
you they wouldn't really have the working product and the years and even more importantly the the accuracy level that you needed for for for
Simon (41:59)
For that type of product is so high that
Martin Tobias (41:59)
was actually
Simon (42:01)
you wouldn't be able to sell it for years. While everyone was chasing that, they looked at the market incredibly deeply from both a technical and commercial mindset and determined: hey, let's when everyone else is zigging, let's zag. Let's build something that's that goes after where the engineers spend the rest of their time when they're not in CAD.
Martin Tobias (42:14)
As the chairman.
Simon (42:27)
They're researching and looking at d data sheets and trying to digest data sheets and comparing, you know, forty different open tabs in their browser. And let's build a tool that penetrates the market there where we actually need much lower accuracy to be efficient and useful and create value to the customer. And and they're still tackling the same giant market, but they're they went to market with something
Martin Tobias (42:41)
Look where.
Yeah, because we get
And what's the same?
Simon (42:56)
That they can start selling almost immediately.
Martin Tobias (42:56)
They can start
selling multiple meaning. So yeah, so getting getting shorter term. So if you have it something you're uncertain if some people are gonna buy or that you can build, build something that can deliver value very quickly, and then you'll have your answer sooner than 10 years. I I I love that. Well, thank you for your time, Simon. Where can people find more about you, either socials and more about your book?
Simon (43:20)
Sure. LinkedIn is the the best way to get in touch with me or or follow me. very easy to find Simon Lancaster with the upside down profile pick. And then the book is on Amazon. It's called Unlocking Alpha, Rise of the Niche VC. And appreciate the shout-out for that and for reading it.
Martin Tobias (43:40)
Okay. All right. Thanks. Well I hope to invest a little bit more with you and s talk to you soon.
Simon (43:46)
Sounds great, Marvin.