Visionaries' Sarkadi Nagy: Industrial AI vs Legacy Sectors

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Hello and welcome, everybody. This is Joe from StartupRate.io,
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your startup podcast and YouTube blog from Germany, Austria and Switzerland.
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And today I do have Martin here with me. Hey, how are you doing?
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Hi, great to be here.
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Totally my pleasure. I usually give a little introduction about the guests that I do have here.
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And we may tell our audience up front, you are not per se an entrepreneur,
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but you're working on the investment side.
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You are with Visionaries VCs. You're based in Berlin.
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And you have been the former growth lead at tier during a hyper growth phase.
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I think you have one or two stories to tell from this time.
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You also have been a competitive athlete.
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I'm sure we'll also talk about that. Plus, you specialize in BASAS,
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AI, cybersecurity, and deep tech, where you're exactly at the right place here at StartupRate.io.
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You have a strong belief in operational experience and radical accountability
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in VC. We'll talk about that, I think.
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And you lead investments that solve real-world industrial problems via applied AI.
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I also got some names here of investments, not you personally did,
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but visionaries, including Lovable,
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the Unicorn Personio,
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Miro, Pigment, Tacto, Apron, Choco, Pivot, and Central.
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And of course, we link down here in the show notes interview with Central.
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So that was already a lot. Take a deep breath.
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So let's talk a little bit about your journey and your vision.
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How did your time at Tear for everybody that that's one of the e-scooter companies,
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the hyper growth e-scooter companies during its hyper growth phase influence
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your approach as an investor?
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Yeah, that's a great question, Jörn.
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And just for background, I was with Tear pretty much from its pre-seed stage until Series B,
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which meant that within a very short period of time, within one year,
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we went from zero to 400 people, reached 100 million annual revenues and similar
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number on the funding side,
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which I always refer to as a little bit of a positively chaotic scaling journey,
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because there was a lot of positive elements and there was also a lot of chaos.
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And one thing that was definitely very, very clear in that short period of very intense time is that.
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The people you work with really, really define of what you can achieve.
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And exceptional talent will find a way to own the outcome and really build something
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that will move the needle in some context.
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And this is one really interesting conversation we always have with founders
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that are building very early stage teams, especially investing in pre-seed and
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seed, is that who you should hire and how do you know that person actually performs well?
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Did you hire the right person for the right role?
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Yes or not? And if somebody is underperforming, is it because they are not doing
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the right responsibilities or not in charge of the right responsibilities or
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whether ultimately it's just not a fit for the company?
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And one key learning that really, really shapes the way that we are trying to
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work together with founders is this perspective of how we look at talent and
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ultimately how you can hire the type of people who you can use as Swiss Army
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Knives in very different situations.
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And just to be clear, those people, Swiss Army Knives, they don't necessarily
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need to come from just a handful of really big Berlin-based startups or a handful
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of consultancies, right?
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Absolutely not. these type of people can come from pretty much any types of backgrounds.
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Very often, in the majority of the cases,
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they have at least some level of unconventionality in their life story,
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which doesn't mean that they went to some Ivy League schools,
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but very often they might end up coding in their parents' basement at the age
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of 12 and just cannot stop reading books about building things.
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And I think that's something that just comes up again and again.
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Uh with these people um.
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You i assume you had quite a lot of fun at here but what motivated you to to
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to be to become really from an operator turned into a vc um
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did you think at the beginning it was more relaxed job and how did you end up at visionaries club
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Yeah it was not a very conscious decision at all when i was with tier i had
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a friend who was running entrepreneur first batch in berlin and we went into
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a couple of conversations.
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And we were talking about when i personally thrive the most and i also realized
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in that conversation, which I didn't know about myself, is that I thrived the most.
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The more I look outside of my regular day-to-day environment, so to say.
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And I think there are different types of people here. I definitely fall into
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the camp of really thriving in the environments where I get new impulses,
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not just from a topic perspective, but also individuals' perspective.
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And then this friend of mine told me, hey, I actually have two friends who are
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actually founders, former founders, and they are launching a fund.
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And it sounds like that since they are building this venture fund from scratch
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and you get to spend your entire day speaking to people who are thinking how
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the future should look like in a different way, changed by technology,
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sounds like a very good intersection of your operator DNA, building something
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actually as in a venture fund.
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So being kind of like an entrepreneur in VC and also being able to have this
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very outward-looking way of working.
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And I pretty much just took that introduction, not expecting too much.
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And I think a lot of things resonated with me.
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And the things that came together, the different DNAs of Visionaries Club, made me very excited.
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And that's where I have been in the last six years.
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Um you often speak about radical
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accountability what does this mean when you work with founders for example let's
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let's think um i'm one of your investments and currently it's not going well
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what what would you expect in terms of radical accountability um
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Radical accountability is a pretty broad term, I would say, and definitely don't
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only use it in the relationship of VC to founder, but also the other way around.
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And this is something that we also, most importantly, encourage founders that
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we back use within their own environment, so to say.
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Radical accountability is a little bit of a stolen term, I would say,
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from radical transparency from Ray Dalio, switching the word out,
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transparency into accountability.
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But it's very simply put, radical accountability means that especially in environments
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where there is a lot of change and just as I told you earlier, there is a lot of chaos.
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The one thing that you can only go back to and always can go back to is owning output.
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And that's really what radical accountability means, because everybody has ideas,
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everybody has comments about how things should be done.
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But what really differentiates the top 0.01% of startups from the rest is that
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this sense of radical accountability is pretty much soaked into the culture
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of how people think and get stuff done.
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And this is something that pretty much everybody is accountable,
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both on a positive and rather consequential negative side, when things are either
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executed very properly or not executed properly.
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We're now going a little bit into market insights and your investment thesis.
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And we may tell our audience because I do believe most of our audience are founders
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and they somehow have an idea they had heard Visionish Club before but we should
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tell them that you're around the data that I found around 600 million years
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assets under management.
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Your last fund was, I believe in 2022, 400 million.
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That's correct. Yes.
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And so you're one of the bigger VCs and therefore, um
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is of interest to me. But some of the things that first stood out is that you
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guys have a very unique base with limited partners.
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For everybody who's not familiar with the term, it's basically the institutions,
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the people who give you the money to invest them as VC, legacy industrialists,
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and modern digital entrepreneurs.
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How does that shape your portfolio strategy? Because It sounds like you have
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two magnetic poles and they always pull you in different directions.
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Yes. I'm happy to give you a little bit of background because I do think that
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this will help also scope the conversation a little bit.
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I just want to tell you and the listeners a little bit about the origin of Visionaries Club.
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So we have been around for some six years. And one very important theme that
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we have all across the investment team is that everybody is a former operator or founder.
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Pretty much really everybody in the investment team. And this is something that
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we really wanted to incorporate into the very DNA of how we set up the fund ultimately.
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And back then when we set up the first fund generation, one very important decision
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we made was, as you said, that we only raise capital from entrepreneurs that we know well.
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And if you look at who these entrepreneurs are, as you mentioned,
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it's two very different group of individuals, but it's always the private people
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behind these companies.
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But on the one hand, we have a collection of some 30 Unicorn founders.
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If you look at, for example, Andre from Miro or Daniel from UiPath from Eastern
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Europe, Ilka from Supercell or Miki from both from the Nordics.
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If you look at Fintech, for example, Peter from Adrian, Guillaume from Checkout.com,
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but also a lot of Dach entrepreneurs such as Get Your Guide,
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Flixbus, HelloFresh, AutoEyes.
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Who build these very successful hyperscaling tech companies.
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And as you mentioned on the completely other side, we have this collection of
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family business entrepreneurs who are a little bit less conventional entrepreneurs
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because they didn't start these companies themselves, right?
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They inherited these multi-decade old family businesses from the what we call
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old economy or industrial economy that have been operating pretty much offline
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for a couple of decades, very often in manufacturing, logistics,
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distribution, wholesale.
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And what's really interesting about them and about Europe specifically,
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is that 80% of the European economy is owned by family businesses.
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So when we were thinking about bringing this entrepreneurial DNA into how we build the fund,
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we felt that if we look into the next decade and we look at the intersection
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of what we have to work with in the European economy and what technology can
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bring and unlock, this is really the intersection that we are looking into.
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This is very digital first entrepreneurs and this is very non-digital entrepreneurs
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who are incredibly important of how we think about the economy.
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So this is how we really bring this group of people together.
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And over the last couple of years, we scaled this one to some 600 million.
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And ultimately, if I really want to sum it up in one sentence,
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the single biggest leverage that we bring into the relationship we have with
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our founders that we back is that we,
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bring in these people and really connect the founders that we back with the
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right people at the right time across all this network.
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This can be about potential customer introductions. This can be about integration
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partners, hiring go to market.
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But based on our experience, instead of coming in with a high-level VC advice,
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we just take a step back and really execute on those introductions that are
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strategically important.
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I also do have a theory, maybe you also have an opinion on that.
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I'm now doing startup interviews with the project in Germany that I did before
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since, let's say, 13 years.
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And over time, I've seen a lot of
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entrepreneurs maturing, getting bigger businesses and so on and so forth.
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And when they're running the company for long enough, there is barely a difference
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between those people and the more traditional entrepreneurs,
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how they view their life, how they view the company and their outlook on the
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company. Would you agree to that?
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I would say it's really interesting, especially if you contrast industrial entrepreneurs
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with really, really large corporates.
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One thing that we made a very conscious decision on taking on these industrial
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entrepreneurs and how I would say they think about actually digital entrepreneurs
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is that since they own a very significant portion of the company and they are
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also in a very active strategic role,
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they can take decisions much faster and they can take risk with a much higher level.
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Again this is not a guarantee that they will suddenly all adopt highest you
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know the most advanced software and end-to-end agentic ai automation tomorrow
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but at least you can get an answer from them very very fast whether this is
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the right timing for them to speak to a certain software company or not i.
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See um we're not talking tvc and i would be interested maybe except for ai Hi,
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what sectors are you most bullish on right now, especially in early stage investing?
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Yes, this is a really good question. I would say that given our very DNA and
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kind of history, over the last couple of years, we built a relatively lean team.
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So in total, we are six people in the investment team. And that means that for
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us specifically, it doesn't make sense to split up the team by sector, right?
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So even though we have certain interest areas, for example, I personally look
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into a lot of topics on the, let's say, more technical side when it comes to
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data, infrastructure, architecture, AI, cybersecurity.
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These are all areas to love to look into.
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We are incredibly focused on founders and pretty much picture them within the
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bigger realm of what we find exciting, right?
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So if you look at the way that we work usually and work together with founders,
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we spend, I would say, 80 to 90% of our time on the ground in ecosystems because
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Europe is incredibly fragmented and you have absolutely no idea which ecosystem
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will produce the next really exceptional entrepreneur. You pretty much have to be there.
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Really try to find these founders, sit down with them and really understand.
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Why the timing of what they want to build fits into the broader market.
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And this can be in very different industries.
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For example, I personally have been looking into and working with a lot of founders
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in procurement, but also back teams in cybersecurity.
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Security, it can be about engineering, it can be about pretty much pure data,
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it can be about really, I would say we are very sector agnostic from that perspective.
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And which ones are the most interesting right now?
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Sectors yeah you can also speak
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from personal perspective because i do understand from from uh such broad company
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it's always difficult to speak like about this or that but your personal experience
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in your area of responsibility is totally fine um it's it's
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It's a really interesting question because we are now at
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a very interesting shift between cloud
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software 1.0 versus the next type
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of let's say software you can still call it software and i know you didn't necessarily
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want to get an ai answer but i would say one very clear shift that we are seeing
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at the moment is that traditional software as a service will very likely cease
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to exist in its current form in a very short period of time.
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And almost these models around services and software is emerging.
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Because if you look at, especially, for example, the industrial economy.
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One very interesting theme that we have been looking into, and maybe one thing
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to pinpoint very concretely, is how we are thinking about the automation of
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back office work, right?
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And this traditionally, for example, in software has been very much tied to sectors.
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So for example, you had to think about a very specific procurement software
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as a service that had, I don't know, an underlying database,
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some type of a user interface, maybe integration with legacy systems.
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And then you try to pretty much
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take these companies and then target these companies and roll them out.
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Now, what we are seeing is that if you look at some of the back office work,
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Let it be, let's say, insurance, procurement, sales, quoting, construction.
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You have these massive back offices where people are just sitting in front of
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their computer and have been doing the same repetitive tasks they have been
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trained to do for pretty much 10, 20 years.
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And in my view, this is going to be exactly the absolute first type of use case
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where full level of automation will be achieved within a very,
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very short period of time.
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So we absolutely don't see any scenario where these tasks won't be 100% automated
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within a couple of years of time.
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And this is especially relevant because this is exactly the type of talent also
00:18:54.411 --> 00:18:58.131
in our economy that is retiring fast and there is no supply of it.
00:18:58.131 --> 00:19:02.971
Because you have to be somewhat educated in order to execute on this task,
00:19:03.191 --> 00:19:06.551
but it's actually not something that needs incredibly sophisticated,
00:19:06.551 --> 00:19:11.371
you know, qualification that cannot be taught in certain areas.
00:19:11.651 --> 00:19:17.811
Why do you believe Europe is positioned to lead in the application layer of AI globally?
00:19:18.991 --> 00:19:24.691
The reason for that is that Europe is in a very special position.
00:19:25.931 --> 00:19:32.471
If you look at the talent in Europe, it's very clear, speaking to entrepreneurs
00:19:32.471 --> 00:19:35.571
from a global scale, speaking to investors from a global level,
00:19:35.751 --> 00:19:37.831
that Europe has absolutely zero talent problem.
00:19:38.211 --> 00:19:41.651
This is something that is sometimes a massive misconception.
00:19:42.431 --> 00:19:47.171
Europe has incredible engineers, incredible entrepreneurs. it's a very fragmented
00:19:47.171 --> 00:19:53.451
ecosystem, but from a very fundamental perspective, I think this is just one
00:19:53.451 --> 00:19:55.871
thing that is, I think, very important to get right.
00:19:56.211 --> 00:19:58.991
When it comes to the application layer of AI.
00:20:00.707 --> 00:20:03.607
And especially if you look at the European economy and getting back to,
00:20:03.687 --> 00:20:08.027
for example, how many of these industrial companies, well, for what it's worth,
00:20:08.147 --> 00:20:12.007
you know, non-industrial companies necessarily, have been working with traditional
00:20:12.007 --> 00:20:14.747
software like SAP and others.
00:20:15.287 --> 00:20:19.527
You know, some of these existing software stacks have been around for 30 years, right?
00:20:20.907 --> 00:20:23.887
And there is an absolute clear reason for that. And the
00:20:23.887 --> 00:20:26.847
clear reason for that is that their lock-in is so
00:20:26.847 --> 00:20:30.367
incredibly high that challengers over
00:20:30.367 --> 00:20:34.147
the course of the last couple of decades absolutely failed to remove them because
00:20:34.147 --> 00:20:39.247
they are so ingrained and so customized to the local environment that it was
00:20:39.247 --> 00:20:43.807
just pretty much impossible to create a strong enough incentive for these customers
00:20:43.807 --> 00:20:47.167
to put effort into removing them and adopt a new solution.
00:20:47.667 --> 00:20:53.307
Now, the opportunity for Europe right now, where pretty much this ingrainedness
00:20:53.307 --> 00:20:55.007
is the highest, I would say,
00:20:55.727 --> 00:21:00.587
is that with the shift in technology when it comes to mapping,
00:21:00.747 --> 00:21:06.507
let's say, integration endpoints, when it comes to using new technologies around
00:21:06.507 --> 00:21:09.687
AI to facilitate data migration, data schema mapping,
00:21:10.307 --> 00:21:14.367
mapping out workflows, and pretty much ultimately automating these workflows
00:21:14.367 --> 00:21:16.627
is something that was not unlocked before.
00:21:17.367 --> 00:21:23.847
And from an application layer perspective, this is what we have context on.
00:21:24.027 --> 00:21:28.307
And I think the key word here is contextuality. And this is something that Europe has.
00:21:28.907 --> 00:21:33.287
The technology is there. We can use it pretty much from a foundation model perspective,
00:21:33.287 --> 00:21:36.207
which we don't have to be a winner in.
00:21:36.527 --> 00:21:39.887
And ultimately, this is exactly where the opportunity is, because you can match
00:21:39.887 --> 00:21:44.667
this level of contextuality and generate a new generation of challenges that
00:21:44.667 --> 00:21:50.707
can ultimately remove this absolute high locking of incumbents that have been
00:21:50.707 --> 00:21:52.347
dominating the industry for many, many years.
00:21:54.747 --> 00:22:01.067
As personally, I've been working in more SAP projects than I would like to admit here.
00:22:01.227 --> 00:22:03.307
I can totally see that.
00:22:03.467 --> 00:22:08.607
But when I now think about the logic that we used there back in the days
00:22:09.647 --> 00:22:14.107
and the teams you've been talking about doing their administrative stuff,
00:22:14.107 --> 00:22:21.587
which would be quite a picture book example of being replaced by AI agents.
00:22:22.187 --> 00:22:29.487
I get to think that you would not only need to re-envision the software,
00:22:30.067 --> 00:22:36.927
but you'll also need to re-envision at least in part the companies because there'll
00:22:36.927 --> 00:22:41.587
be a lot more of automation, especially in administrative duties.
00:22:44.156 --> 00:22:52.156
Yes, 100%. And I do not think that this is going to be a zero to one shift, right?
00:22:52.716 --> 00:23:00.016
If you look at, for example, a very clear example of the migration push of SAP
00:23:00.016 --> 00:23:04.296
on-prem to SAP HANA that SAP is pushing massively,
00:23:04.476 --> 00:23:09.536
some of these companies actually spend a very, very significant amount of euros
00:23:09.536 --> 00:23:13.276
and very significant amount of time, meaning years.
00:23:13.396 --> 00:23:19.556
To go from the concept of understanding what the existing on-prem setup looks
00:23:19.556 --> 00:23:24.116
like from the perspective of what's standard SRP code, what's customer SRP code,
00:23:24.556 --> 00:23:27.336
how, for example, the business logics look like,
00:23:28.096 --> 00:23:33.116
all of these things, hire a bunch of consultants, kind of try to map out exactly
00:23:33.116 --> 00:23:35.216
how this should look like in the cloud.
00:23:35.496 --> 00:23:38.996
It doesn't just work in a way that you buy a virtual machine and you just push
00:23:38.996 --> 00:23:42.336
it there within a week, but you actually have to go through this entire process
00:23:42.336 --> 00:23:44.876
And then pretty much you try to move the application.
00:23:46.276 --> 00:23:51.976
Now, from my perspective, technologies that can, on the one hand,
00:23:52.556 --> 00:24:00.236
speed up this type of process, as well as think about how these workflows can
00:24:00.236 --> 00:24:06.996
be fully automated from, let's say, an agentic perspective, will need to emerge in parallel.
00:24:07.396 --> 00:24:11.416
Because you cannot just throw an agent pretty much at an on-prem SAP instance,
00:24:11.596 --> 00:24:13.176
right? I think it's very, very clear.
00:24:14.056 --> 00:24:19.736
So you will need very different approaches. And ultimately, what will unlock
00:24:19.736 --> 00:24:23.516
the most value will have the most grip on the market, as we have seen also in the past.
00:24:23.656 --> 00:24:29.036
There is no absolute clear cut answer what type of approaches will win.
00:24:30.136 --> 00:24:32.296
But ultimately, I think it needs to be,
00:24:32.927 --> 00:24:35.187
game of parallel approaches, to be honest.
00:24:36.367 --> 00:24:42.007
And what you've been talking about is on-premise, basically more or less very simplified.
00:24:42.027 --> 00:24:45.407
You had a very big data center.
00:24:45.807 --> 00:24:51.527
You're running SAP there just for your company. And now it's moved on HANA into the cloud.
00:24:51.667 --> 00:24:54.607
Very, very much simplified. And that was already a big project.
00:24:54.847 --> 00:25:00.647
But the more I think about using AI agents in such a tool,
00:25:00.647 --> 00:25:06.627
I always get the idea that the most successful companies or the most successful
00:25:06.627 --> 00:25:11.487
software in the future may not be the fastest AI agent,
00:25:11.627 --> 00:25:19.207
but I do get the one who makes it the easiest to administrate those agents, control them,
00:25:19.707 --> 00:25:22.007
give them duty and keep them in check.
00:25:22.007 --> 00:25:28.267
Because if you do, what I have in mind are those huge Excel sheets where you track stuff.
00:25:28.407 --> 00:25:33.047
And then at one point, you don't realize that this agent is doing A,
00:25:33.247 --> 00:25:37.647
this agent is doing P, and they're basically just giving each other work.
00:25:37.787 --> 00:25:43.387
So there is a new way how you need to think about a company getting back to
00:25:43.387 --> 00:25:46.367
the idea of rethinking the company.
00:25:47.547 --> 00:25:51.787
But we've been a little bit intertwined already into AI.
00:25:52.007 --> 00:25:56.987
So I was wondering, we're talking to your VC, what is your framework to identify
00:25:56.987 --> 00:26:04.067
AI startups with like a real differentiation and they don't necessarily have just buzz?
00:26:05.867 --> 00:26:12.747
Yes, that's a really good question. So I'm especially speaking from the perspective
00:26:12.747 --> 00:26:16.347
of a pre-seed seed investor, which is a little bit of a cheat card sometimes
00:26:16.347 --> 00:26:19.407
because you can always give the answer that the founder has to be exceptional.
00:26:19.407 --> 00:26:23.267
Which in itself, on the one hand, can be a really good answer.
00:26:23.467 --> 00:26:28.107
On the other hand, I completely agree that if you look at many of the verticals
00:26:28.107 --> 00:26:30.467
you see right now in agentic AI,
00:26:30.867 --> 00:26:35.227
you do see an absolute red ocean of parallel approaches, let's say when it comes
00:26:35.227 --> 00:26:39.647
to the number of AI legal tech companies or the number of companies that are
00:26:39.647 --> 00:26:43.867
trying to build your AI SDR and so many of these different approaches.
00:26:44.687 --> 00:26:47.727
From our perspective, the two things we...
00:26:48.654 --> 00:26:53.314
Pre-seed, ultimately, and early-stage investing, in a really simple,
00:26:53.514 --> 00:26:59.934
simply put way, is a really, truly excellent founder building in an incredibly exciting market.
00:27:00.434 --> 00:27:04.894
And the incredibly exciting market is pretty much a given, in many cases,
00:27:04.954 --> 00:27:08.114
when you are looking at the opportunity of the technology and what you can see
00:27:08.114 --> 00:27:09.594
in many of these use cases.
00:27:09.594 --> 00:27:15.054
Now, ultimately, the exceptionality of the founder is something that we pay exceptional,
00:27:15.394 --> 00:27:21.454
like really, really big attention to, because that's where you can identify
00:27:21.454 --> 00:27:26.354
somebody who will be able to navigate the, let's say, the level of uncertainty
00:27:26.354 --> 00:27:28.834
that you will need to navigate in this space.
00:27:28.834 --> 00:27:33.794
And if you look at just the simple acceleration of the last two to three years
00:27:33.794 --> 00:27:39.394
when it comes to what capabilities, for example, AI can do, this is one topic
00:27:39.394 --> 00:27:40.874
we have been discussing with the founder,
00:27:41.174 --> 00:27:47.994
is that, for example, if you look at some of the, let's say.
00:27:48.754 --> 00:27:52.494
Features that, I don't know, some of these foundation models could do,
00:27:52.594 --> 00:27:55.974
for example, writing a poem or something like this that are absolutely not spectacular
00:27:55.974 --> 00:27:59.834
today, almost to anyone who has been natively using these AI tools,
00:28:00.074 --> 00:28:06.334
back then the amount of wow effect that you got from them was 100 times higher
00:28:06.334 --> 00:28:08.334
than what you get from now.
00:28:08.774 --> 00:28:13.574
So from our perspective, from a human perspective, human experience perspective,
00:28:13.894 --> 00:28:19.594
what we see is that we get used to the power of the technology incredibly fast.
00:28:20.274 --> 00:28:24.194
And we just forget how much progress has been made in the last two to three years.
00:28:25.214 --> 00:28:28.414
And I think personally that we completely underestimate
00:28:28.414 --> 00:28:31.314
how much this technology will develop in the
00:28:31.314 --> 00:28:35.434
coming years and because of that there is
00:28:35.434 --> 00:28:38.194
a very high level of uncertainty that a certain
00:28:38.194 --> 00:28:41.074
founder needs to navigate so ultimately as a pre-seed or
00:28:41.074 --> 00:28:43.794
seed investor trying to identify if you have a level of
00:28:43.794 --> 00:28:46.754
tech defensibility as a startup that just developed an
00:28:46.754 --> 00:28:49.694
MVP is not a
00:28:49.694 --> 00:28:53.094
very valid question right so for us the focus
00:28:53.094 --> 00:28:56.134
really really shifts very much to the exceptionality
00:28:56.134 --> 00:28:59.194
of the founder which in itself can lie into for
00:28:59.194 --> 00:29:02.314
example unique insights to a certain industry because as
00:29:02.314 --> 00:29:07.274
discussed already for example in europe when you still have the challenge of
00:29:07.274 --> 00:29:12.734
for example needing to sell to some customers um in person or do field sales
00:29:12.734 --> 00:29:16.494
for example let's say in construction tech or industrial tech a founder that
00:29:16.494 --> 00:29:19.414
is able to understand on the one hand the capabilities of AI,
00:29:19.654 --> 00:29:23.114
but also understands the particularities of the industry, is the combination
00:29:23.114 --> 00:29:25.134
that makes them exceptional, right?
00:29:25.334 --> 00:29:29.934
And this is something that we always try to look at from a perspective point of view.
00:29:31.874 --> 00:29:37.974
I see. We'll be back after a short ad break and then talk about how you do your
00:29:37.974 --> 00:29:43.234
investments, how, for example, you evaluate a founder, and so on and so forth.
00:29:48.771 --> 00:29:52.031
Hey, guys. Thank you for being back with us after the short ad break.
00:29:52.471 --> 00:29:58.491
I'm still talking to Martin Partner at Visionaries VC, and we are talking right
00:29:58.491 --> 00:30:02.151
now about how they evaluate the founders.
00:30:04.911 --> 00:30:12.451
What traits do you think define a genre-defining founder in your eyes?
00:30:13.211 --> 00:30:20.051
Yes, this has been an exercise we have been constantly thinking about and re-challenging ourselves on,
00:30:21.891 --> 00:30:26.431
especially if you look at the really exceptional founders in Europe and how
00:30:26.431 --> 00:30:31.851
serendipitously they came out of absolutely unexpected hubs, times, and setups.
00:30:33.111 --> 00:30:38.291
We definitely don't think that you have a very strong ability to put together
00:30:38.291 --> 00:30:42.391
a checklist and just tick boxes and give an average score.
00:30:42.611 --> 00:30:45.271
And if somebody hits that average score about a certain level,
00:30:45.411 --> 00:30:47.211
then you invest. If not, then not.
00:30:47.831 --> 00:30:53.051
So, for us, exceptionality can come in very different forms,
00:30:53.071 --> 00:31:00.011
and we have certain traits that we usually look into that can feed into certain
00:31:00.011 --> 00:31:02.671
exceptionalities in founders in very different ways.
00:31:02.671 --> 00:31:10.871
To give you an example, one trade that we are also looking into is a combination
00:31:10.871 --> 00:31:14.751
of a founder having pretty much very much like,
00:31:14.891 --> 00:31:18.251
for example, if you would look into, let's say,
00:31:18.611 --> 00:31:23.331
soccer, to come up with a very concrete example.
00:31:25.051 --> 00:31:31.471
What makes a good player shoot, for example, a ball in a good way? right?
00:31:31.591 --> 00:31:36.331
It's a combination of timing, it's a combination of power and accuracy.
00:31:36.611 --> 00:31:40.471
And these are the three characteristics and the combination that really,
00:31:40.531 --> 00:31:42.531
really exceptional founders do have.
00:31:42.711 --> 00:31:48.231
When it comes to timing, also interchangeably use it together with urgency or
00:31:48.231 --> 00:31:49.451
kind of like proneness to action,
00:31:49.611 --> 00:31:57.911
is the ability for the founder to very clearly articulate when to do what and how to prioritize what.
00:31:58.111 --> 00:32:02.111
It can be about hiring, it can be about execution, it can be about when they
00:32:02.111 --> 00:32:04.691
start building a certain product in a certain market.
00:32:05.171 --> 00:32:10.231
Power is pure grit. It's about how hard you work and pretty much how much you
00:32:10.231 --> 00:32:11.171
can commit to the company.
00:32:11.651 --> 00:32:18.531
And accuracy is ultimately the ability to identify the most important problems
00:32:18.531 --> 00:32:21.511
and really shortlist those on a daily basis.
00:32:21.711 --> 00:32:29.031
And this is something that we always try to evaluate on a recurring basis together with founders.
00:32:29.531 --> 00:32:35.171
This is one very important aspect, obviously, that just comes up again and again.
00:32:35.997 --> 00:32:41.297
In certain founders. And I want to highlight this sense of urgency that with
00:32:41.297 --> 00:32:45.997
some of the most successful founders, when as an investor, you are in a meeting
00:32:45.997 --> 00:32:50.437
with them, you almost feel uncomfortable about wasting their time.
00:32:50.757 --> 00:32:55.917
And this is something that, you know, I definitely felt at tier with Lawrence,
00:32:56.077 --> 00:32:57.537
who is just a fantastic founder as well,
00:32:57.737 --> 00:33:04.437
is that their sense of urgency when it comes to coming to action and their sense
00:33:04.437 --> 00:33:09.817
to not waste time in instances where they absolutely don't need to is very, very high.
00:33:09.997 --> 00:33:13.277
And this is something that you can, I think, really sense as an investor.
00:33:13.837 --> 00:33:20.017
To give you another example, product and personal obsession is something that
00:33:20.017 --> 00:33:24.077
you definitely can identify relatively accurately.
00:33:24.517 --> 00:33:28.997
And it comes out in very different formats, in very different founder journeys.
00:33:28.997 --> 00:33:33.217
Because if you have a fresh university team coming out of uni,
00:33:33.357 --> 00:33:37.077
maybe a couple of months of internship experience, who have been constantly
00:33:37.077 --> 00:33:39.677
thinking about a certain problem and, you know,
00:33:40.037 --> 00:33:43.057
they were absolutely sleepless about it and now try to attack it,
00:33:43.377 --> 00:33:47.597
which was the case in some of our investments like Tacto for the listeners.
00:33:47.597 --> 00:33:53.097
It's a Munich-based procurement software company from some of the small and
00:33:53.097 --> 00:33:56.097
medium-sized businesses in the European economy.
00:33:56.277 --> 00:34:02.337
They have been obsessing over and over about how incredibly broken procurement is.
00:34:02.537 --> 00:34:04.077
It originally was their DNA.
00:34:04.497 --> 00:34:11.497
If you look at a seasoned entrepreneur, a seasoned operator entrepreneur who
00:34:11.497 --> 00:34:15.157
have been in the industry for more than 10 years, it's going to be a very different
00:34:15.157 --> 00:34:17.397
type of personal or product obsession.
00:34:17.597 --> 00:34:24.257
If, for example, somebody decides after six years of being one of the most successful, let's say.
00:34:24.837 --> 00:34:30.357
Companies or scale-ups, for example, companies like Klarna or Konto or Swile,
00:34:30.557 --> 00:34:35.377
to give you just some examples from our portfolio, to...
00:34:36.601 --> 00:34:40.841
Start from zero and start with a blank sheet of paper to start building something new.
00:34:42.201 --> 00:34:47.501
They often felt something from a market timing perspective and in a once in
00:34:47.501 --> 00:34:52.041
a lifetime perspective from an obsession perspective that they just have to make that step.
00:34:52.221 --> 00:34:56.661
And this is something that clearly comes out when you have a very open and transparent
00:34:56.661 --> 00:34:57.821
personal conversation with them.
00:34:58.761 --> 00:35:05.481
I was wondering can you give examples of painkiller versus vitamin startups
00:35:05.481 --> 00:35:08.601
and why that distinction matters
00:35:08.601 --> 00:35:17.721
Yes um it's uh it's something that we uh we really like using in the context
00:35:17.721 --> 00:35:22.161
of b2b software and that's the reason why i would personally be an absolutely
00:35:22.161 --> 00:35:26.221
horrible consumer investor, because for me,
00:35:26.501 --> 00:35:31.241
comprehending painkiller versus vitamin in that context is just very, very difficult.
00:35:31.621 --> 00:35:37.521
In B2B software, it's from at least a theoretical perspective, you know,
00:35:38.527 --> 00:35:43.667
It's something relatively simple to identify. From a conceptual perspective,
00:35:44.247 --> 00:35:49.487
a painkiller is something that can help your customer either increase your revenues
00:35:49.487 --> 00:35:53.987
or decrease costs, or will be absolutely mission critical for you to operate.
00:35:54.727 --> 00:35:57.747
If you look at, for example,
00:35:58.347 --> 00:36:04.187
some of the agentic AI companies that try to automate your sales team,
00:36:04.507 --> 00:36:09.507
that's a very clear, you know, impact on you being able to, for example,
00:36:09.687 --> 00:36:12.107
serve more customers or open your funnel up more.
00:36:12.287 --> 00:36:15.787
So really try to, for example, drive your supply. If you look at,
00:36:15.847 --> 00:36:19.307
for example, some of the agency AI companies that are trying to automate your
00:36:19.307 --> 00:36:20.227
back office end-to-end,
00:36:20.567 --> 00:36:25.107
you pretty much can replace very concretely headcounts in your back office at
00:36:25.107 --> 00:36:27.487
a fraction of the cost. So that's really doing that.
00:36:27.647 --> 00:36:32.527
If you look at companies like Stripe, for example, that's a very clear example
00:36:32.527 --> 00:36:37.287
of a company that is just mission critical for you to operate because otherwise you don't get paid.
00:36:38.267 --> 00:36:41.327
So this is pretty much how we try to think about it.
00:36:42.107 --> 00:36:47.747
One very interesting thing when we are thinking about peculer versus vitamin
00:36:47.747 --> 00:36:52.467
is that in reality, things work sometimes in a different way.
00:36:53.247 --> 00:36:56.707
If you look at the very concrete example of process automation,
00:36:57.087 --> 00:37:03.267
and I'm talking a little bit pre-AI era, there have been a huge wave of some
00:37:03.267 --> 00:37:07.447
of these RPA companies that were trying to pretty much automate anything that
00:37:07.447 --> 00:37:09.187
Zapier and UiPath couldn't.
00:37:09.187 --> 00:37:12.047
But yet they were not successful.
00:37:12.627 --> 00:37:17.807
Why is that? It's very obvious from a conceptual point of view that if you automate
00:37:17.807 --> 00:37:19.967
something, then you also save money.
00:37:20.247 --> 00:37:24.527
Yes, that is absolutely true. But if your customers don't want to automate those
00:37:24.527 --> 00:37:27.187
things and they are not in the business of automating things,
00:37:27.347 --> 00:37:31.867
it becomes often very difficult for them to convince that they need to give
00:37:31.867 --> 00:37:34.287
the extra upfront investment for those cost savings.
00:37:34.507 --> 00:37:40.567
And that's where we always try to match the conceptual understanding of what
00:37:40.567 --> 00:37:44.087
is a painkiller with reality of what actually is a painkiller.
00:37:46.667 --> 00:37:52.567
We've been talking in the introduction that you do have a background in competitive sports.
00:37:52.807 --> 00:37:58.067
How does this influence your judgment in high-stakes investment decisions?
00:37:59.107 --> 00:38:01.127
Competitive sports is a really...
00:38:02.068 --> 00:38:07.688
Interesting environment. And there are a lot of parallels when you're thinking
00:38:07.688 --> 00:38:11.948
about company building, because in competitive sports,
00:38:12.328 --> 00:38:18.308
in many cases, you have to prepare for one single event that might happen once
00:38:18.308 --> 00:38:22.868
a year, once every two years, or in the case of the Olympics, once every four years.
00:38:24.428 --> 00:38:28.528
And you have to show up every day, sometimes every day, twice,
00:38:28.788 --> 00:38:34.568
training up to 14 times a week, give your absolute best and think about how
00:38:34.568 --> 00:38:38.748
you can be your better self every single day for that one single event.
00:38:39.328 --> 00:38:44.348
And sometimes you have an injury that comes in that takes you back,
00:38:44.448 --> 00:38:49.128
let's say, four to five months in your preparation and you cannot do anything
00:38:49.128 --> 00:38:51.008
with it. But there are a lot of crisis situations.
00:38:52.628 --> 00:38:58.128
And if you look at the most successful people in sports and competitive sports,
00:38:58.368 --> 00:39:02.668
they are able to deal with setbacks incredibly well.
00:39:03.668 --> 00:39:08.308
Keeping their cool in those events is something that is really exceptional.
00:39:08.528 --> 00:39:12.128
And if you look at some of the top athletes, there's just something that comes out again and again.
00:39:13.208 --> 00:39:19.768
When it comes to investing and having an honest conversation with a founder,
00:39:20.128 --> 00:39:24.148
this type of pressure test also, I would say, can be very much applied.
00:39:24.928 --> 00:39:29.588
And if you're having an honest conversation about the most,
00:39:29.908 --> 00:39:34.888
the highest heated crisis situations that they ever had in their life and listen
00:39:34.888 --> 00:39:40.588
to how they dealt with it, it's something that really shows how they deal with the situations.
00:39:40.928 --> 00:39:46.248
Because these situations happen. And as a founder, you just have to solve them.
00:39:46.908 --> 00:39:52.468
And this is something that we always have as a bit of an exercise.
00:39:52.468 --> 00:39:57.448
And what some of our best founders absolutely managed to do incredibly well
00:39:57.448 --> 00:40:00.808
is to assess the situation, understand what you can do about it,
00:40:00.908 --> 00:40:03.688
what you can't do about it, and act like that.
00:40:07.308 --> 00:40:11.828
Let's talk a little bit about applied AI and SaaS adoption.
00:40:12.288 --> 00:40:18.668
You said AI will be the biggest driver of SaaS adoption, particularly in industrial
00:40:18.668 --> 00:40:21.628
sectors. Can you a little bit expand on that?
00:40:21.748 --> 00:40:27.608
Because you also said the classical SaaS, how does this fit together here?
00:40:29.300 --> 00:40:37.100
So you mean the classical SaaS will cease to exist in the form that it has been existing?
00:40:37.600 --> 00:40:43.280
Yes, in the form right now. And where will it go? What will be the next iteration,
00:40:43.520 --> 00:40:45.040
the next form of classical SaaS?
00:40:47.460 --> 00:40:52.200
This is a really interesting topic. And I think everybody is to some extent
00:40:52.200 --> 00:40:53.900
still very speculative about it.
00:40:54.880 --> 00:41:00.900
But what we have seen already in the last couple of months or one or two years
00:41:00.900 --> 00:41:08.940
is that the ultimate application interface that people in these environments
00:41:08.940 --> 00:41:13.600
are using to execute on certain workflows is completely changing.
00:41:13.600 --> 00:41:19.080
If you, for example, look at very traditional software as a service,
00:41:19.420 --> 00:41:26.220
as mentioned, you might have some backend database, some features that people input data in,
00:41:26.640 --> 00:41:31.580
maybe the software application is processing this data, and then you have an output.
00:41:32.460 --> 00:41:37.140
That's something that, given the capabilities of what's changing right now,
00:41:37.380 --> 00:41:44.820
in my view, will really, really change just from the perspective that if you
00:41:44.820 --> 00:41:47.440
look at how traditionally workflow has been executed,
00:41:48.260 --> 00:41:54.380
especially in the case of knowledge work, 80% of knowledge work is just finding,
00:41:55.020 --> 00:42:00.340
some processing and summarizing information and maybe passing it on to the next person.
00:42:00.340 --> 00:42:05.720
This is something that can be done incredibly well using AI.
00:42:06.120 --> 00:42:12.240
And not only it's possible right now to remove some of the intermediary steps,
00:42:12.460 --> 00:42:17.120
but you can also completely rethink how the whole workflow is executed.
00:42:17.380 --> 00:42:22.180
Because if you look at this whole concept from a data perspective and data processing
00:42:22.180 --> 00:42:26.040
perspective, an agent or AI agent,
00:42:26.735 --> 00:42:32.075
does not necessarily have to process the data the exact same way as a human
00:42:32.075 --> 00:42:34.095
being would, right? Ultimately.
00:42:34.555 --> 00:42:40.635
And this is something where I do think that AI as an application layer will
00:42:40.635 --> 00:42:44.095
completely change the way that industrial companies work.
00:42:44.295 --> 00:42:47.375
Just let's take a very, I would say, concrete look at procurement.
00:42:47.695 --> 00:42:51.575
Ultimately, if you are head of procurement at some of these industrial companies.
00:42:52.635 --> 00:42:55.575
Your number one job as procurement leaders
00:42:55.575 --> 00:42:59.495
usually say is to keep your job because procurement
00:42:59.495 --> 00:43:02.635
is a bit of a loser game right you ultimately make sure
00:43:02.635 --> 00:43:07.695
that everything is procured on time at the best price and it arrives um if it
00:43:07.695 --> 00:43:11.595
does that then great you're doing a great job if it doesn't then then it's not
00:43:11.595 --> 00:43:17.155
so ultimately um if you look at how procurement leaders have been using software
00:43:17.155 --> 00:43:21.815
for example in the past is that um They had to enter, for example,
00:43:22.495 --> 00:43:26.995
their system or ERP system to look up inventory, talk to product,
00:43:27.095 --> 00:43:28.655
talk to product, engineering, sales.
00:43:28.935 --> 00:43:32.155
What do you need to procure? Ultimately, go up to your supplier,
00:43:33.315 --> 00:43:39.235
open some type of supplier database, look at some catalogs, submit some purchase orders.
00:43:39.475 --> 00:43:43.895
And it was all a little bit of a chaotic workflow from the perspective of what you needed to do.
00:43:44.575 --> 00:43:47.555
But if you look at ultimately what, for example,
00:43:47.735 --> 00:43:51.535
some of the AI capabilities can unlock when
00:43:51.535 --> 00:43:56.935
it comes to understanding need budget analysis and what you ultimately need
00:43:56.935 --> 00:44:01.915
to execute on at a given point in time and what you need to optimize for is
00:44:01.915 --> 00:44:08.755
something that is very different from how you would work as an individual human
00:44:08.755 --> 00:44:11.495
and how you would process this information and pass it on, if that makes sense.
00:44:13.895 --> 00:44:13.915
Thank you.
00:44:15.447 --> 00:44:23.187
Definitely makes sense, but it takes a while until it sinks in what this really
00:44:23.187 --> 00:44:27.007
means and how it actually applies to different industries.
00:44:28.327 --> 00:44:33.667
I don't claim I'm through with this thinking by getting closer and closer.
00:44:34.247 --> 00:44:40.307
You are also connecting AI startups with LPs to solve real problems.
00:44:41.007 --> 00:44:44.807
And how does a successful case for such a corporation look like?
00:44:47.067 --> 00:44:50.367
Yes. So this is something that we talked about. And, you know,
00:44:50.487 --> 00:44:52.687
when we built the fund or started building the fund,
00:44:52.827 --> 00:44:59.187
we wanted to make sure that we have this unique ingredient of having the connection
00:44:59.187 --> 00:45:04.607
to these limited partners of industrial family businesses who represent a very
00:45:04.607 --> 00:45:06.367
significant portion of the economy.
00:45:07.767 --> 00:45:11.867
Because very often, if you look at B2B software,
00:45:12.387 --> 00:45:16.887
you know, AI, or call it pretty much any type of technology at the moment in
00:45:16.887 --> 00:45:21.767
Europe, if you want to build a multi-billion dollar outcome as an entrepreneur,
00:45:22.127 --> 00:45:27.187
it's very difficult to ignore this group of family business entrepreneurs and
00:45:27.187 --> 00:45:28.347
industrials in the long term,
00:45:29.207 --> 00:45:33.007
if you are selling to European companies. So our...
00:45:34.261 --> 00:45:39.001
Our idea was that, you know, when we build the fund is that we can connect these
00:45:39.001 --> 00:45:41.341
entrepreneurs that we back with these industrials.
00:45:42.281 --> 00:45:47.041
And, you know, as mentioned, the most important thing that we bring in as Visionaries
00:45:47.041 --> 00:45:50.741
Club is that whenever we invest with founders, and this often already starts
00:45:50.741 --> 00:45:52.421
before investment, it can be, you know,
00:45:52.941 --> 00:45:58.181
sometimes in the stage of ideation, is that we sit down together and figure
00:45:58.181 --> 00:46:02.661
out who from our industrial network is actually most helpful to talk to.
00:46:02.661 --> 00:46:08.661
From the perspective of the product that the founder is building and ultimately
00:46:08.661 --> 00:46:11.701
get them in front of the most important stakeholder,
00:46:12.141 --> 00:46:18.001
let it be a champion or an actual user of the product as soon as possible and
00:46:18.001 --> 00:46:22.821
really shorten this response time that they get from these industrial companies.
00:46:23.661 --> 00:46:27.641
And this is something we do think has a very fundamental unlock.
00:46:27.841 --> 00:46:31.581
And in many cases, some of these industrial companies might get back,
00:46:31.581 --> 00:46:34.821
hey this is incredibly relevant now we are in
00:46:34.821 --> 00:46:37.901
the middle of this massive i don't know erp migration so
00:46:37.901 --> 00:46:40.761
let's talk in six months sometimes they say this is
00:46:40.761 --> 00:46:43.701
exactly what we have been looking for for a long time let's set
00:46:43.701 --> 00:46:50.121
up a paid doc next week and sometimes it's no we will you know build this internally
00:46:50.121 --> 00:46:55.061
and this is not relevant but getting this response time versus trying to call
00:46:55.061 --> 00:46:59.441
it inbound some of these industrial businesses that are not on not even on linkedin
00:46:59.441 --> 00:47:01.861
is something that is very contrasting.
00:47:02.001 --> 00:47:07.621
In an ideal scenario, whenever we can connect these industrial businesses with
00:47:07.621 --> 00:47:11.361
the founders that we are working with, we can really shorten this cycle.
00:47:11.881 --> 00:47:16.701
In the most exceptional cases, founders can pretty much champion these companies
00:47:16.701 --> 00:47:20.281
as well as if they were, let's say, technology companies.
00:47:20.781 --> 00:47:23.021
This is where the magic of 3D exceptional founders lie.
00:47:23.961 --> 00:47:27.301
We don't guarantee any paid contracts.
00:47:27.501 --> 00:47:32.021
This is not the business we are in, But this kind of door opening function is what we've.
00:47:33.701 --> 00:47:38.141
Past success is no indication for future performance. The usual disclaimer in
00:47:38.141 --> 00:47:39.401
financial services. Yes.
00:47:39.821 --> 00:47:46.261
Let us go a little bit shortly into Europe's venture capital landscape.
00:47:46.261 --> 00:47:49.101
If you still have a little bit time. Yes.
00:47:50.221 --> 00:47:56.321
What are the biggest challenges European founders face today and how can they overcome them?
00:47:58.289 --> 00:48:04.769
The biggest challenge European founders face today is ultimately what everybody
00:48:04.769 --> 00:48:08.129
says, which is fragmentation of the European ecosystem.
00:48:09.029 --> 00:48:15.949
And why we think fragmentation is the biggest challenge at the moment is because
00:48:15.949 --> 00:48:21.909
various different ecosystems are in very different maturity stages.
00:48:22.229 --> 00:48:26.529
If you look at London, if you look at Paris, if you look at some of these ecosystems,
00:48:26.529 --> 00:48:32.949
they have a history of producing some really exceptional, you know, venture outcomes.
00:48:33.349 --> 00:48:37.369
And some of these venture outcomes started producing some really exceptional
00:48:37.369 --> 00:48:40.309
operators who might end up, you know, starting new companies.
00:48:40.509 --> 00:48:43.689
And for example, if you have a proximity of a university,
00:48:43.689 --> 00:48:47.889
you might even have the chance to bring some of these entrepreneurs or operators
00:48:47.889 --> 00:48:52.009
into some of these hubs that can really enable entrepreneurs not only to just
00:48:52.009 --> 00:48:54.049
pull the trigger and start something new and take risk,
00:48:54.049 --> 00:48:58.229
but also to be able to hire exceptional talent and start, you know,
00:48:58.429 --> 00:48:59.789
selling to the local ecosystem.
00:49:00.829 --> 00:49:05.849
Now, this is not the case for all ecosystems. If you look at some of,
00:49:05.949 --> 00:49:10.609
you know, other cities, the ecosystem are in very different stages.
00:49:10.969 --> 00:49:14.809
But ultimately, if you look at, for example, the example of Miro,
00:49:15.309 --> 00:49:20.409
Andrei started it from a small town in Russia called Perm that many people didn't even hear about.
00:49:20.409 --> 00:49:26.429
And through this big filter he managed to build it into a successful enough
00:49:26.429 --> 00:49:31.549
outcome that now is a globally leading company but if you put,
00:49:32.509 --> 00:49:37.129
yourself into the shoes of something like that, the amount of challenges that
00:49:37.129 --> 00:49:38.769
you need to go through and the,
00:49:39.672 --> 00:49:44.132
amount of pushback that you will get that will set you back in terms of timeline
00:49:44.132 --> 00:49:47.832
and how fast you can market your product is exponentially higher.
00:49:48.332 --> 00:49:51.552
And the more remote the ecosystem is, the more difficult it is ultimately.
00:49:52.592 --> 00:49:56.372
And this is something that is already changing, but ultimately this is the very
00:49:56.372 --> 00:49:58.812
reason why we set up Visionaries Club in the way that we did.
00:49:58.992 --> 00:50:02.272
That if we back, for example, a young entrepreneur out of Munich,
00:50:02.492 --> 00:50:05.432
who, you know, Munich is already a pretty advanced ecosystem,
00:50:05.652 --> 00:50:11.552
but if they want to connect to a wide range of entrepreneurs who either successfully
00:50:11.552 --> 00:50:14.852
navigated a certain landscape in a certain industry, traditionally,
00:50:15.132 --> 00:50:19.812
it has been incredibly difficult for them to get a meaningful connection with these people.
00:50:20.832 --> 00:50:26.252
But via our approach, we really try to work on that and facilitate that.
00:50:28.872 --> 00:50:34.172
How should European VCs adapt to stay global competitive?
00:50:34.172 --> 00:50:41.172
Because I've seen in the past a few analyzers that, at least from the perspective
00:50:41.172 --> 00:50:48.232
of the LPs, the European VCs have outperformed over time their American counterparts.
00:50:48.332 --> 00:50:51.452
So they did have a competitive advantage.
00:50:51.772 --> 00:50:57.472
How can they keep pushing it in their increasingly fractured world right now?
00:50:58.352 --> 00:51:03.672
Venture capital traditionally has been and always will be driven by power law.
00:51:04.172 --> 00:51:08.332
So there will be a lot of winners. And it's very difficult to give,
00:51:08.472 --> 00:51:12.212
I would say, a collective formula of how European venture capital funds,
00:51:12.312 --> 00:51:14.292
all of them can stay more competitive.
00:51:14.612 --> 00:51:18.172
And when you say, you know, European venture capital funds,
00:51:18.972 --> 00:51:22.832
it almost feels like that, you know, you would need to move the whole curve
00:51:22.832 --> 00:51:28.172
in a certain way, which is somewhat tied to maker environment.
00:51:28.492 --> 00:51:30.152
But what I can say is that...
00:51:32.272 --> 00:51:37.272
In order for some of the European venture capital funds that can be successful
00:51:37.272 --> 00:51:40.432
is completely to be on the ground.
00:51:41.192 --> 00:51:47.152
Because if you look at the amount of time it takes for a certain ecosystem to
00:51:47.152 --> 00:51:50.852
absolutely ignite, it can be very, very short.
00:51:51.232 --> 00:51:57.912
And if you are trying to run this from behind your desktop, I think it's a very, very difficult job.
00:51:58.052 --> 00:52:02.512
And I think you see this story very interestingly playing out right now in the
00:52:02.512 --> 00:52:05.772
case of Stockholm, where a couple of companies, including Glovable,
00:52:06.792 --> 00:52:11.712
just absolutely demonstrated how you can get onto the path of building a globally
00:52:11.712 --> 00:52:13.892
leading company in a very short period of time.
00:52:14.592 --> 00:52:19.692
And taking that encouragement, many, many other really exceptional talent in
00:52:19.692 --> 00:52:22.252
the ecosystem had the courage to start new companies.
00:52:22.632 --> 00:52:26.812
And pretty much within the matter of six months it
00:52:26.812 --> 00:52:29.952
became from a really interesting ecosystem into
00:52:29.952 --> 00:52:33.272
one of the leading ecosystems i would say in europe and if you're a venture
00:52:33.272 --> 00:52:37.632
investor you just have to be there and see that for yourself speak to the founders
00:52:37.632 --> 00:52:43.272
because they will grow they will build very successful companies very fast and
00:52:43.272 --> 00:52:47.852
if you're an early stage investor and you're not there you you will miss a thousand a.
00:52:47.852 --> 00:52:51.912
Very last high level question what needs
00:52:51.912 --> 00:52:55.932
to change in how early stage capital supports
00:52:55.932 --> 00:52:58.832
technical founders in europe because we do have
00:52:58.832 --> 00:53:03.332
a lot of very good universities very good technical universities lots of stem
00:53:03.332 --> 00:53:09.872
talent but i do see a lot of them struggling uh to get out not only but also
00:53:09.872 --> 00:53:16.612
in terms of biotech and so on and so forth to really get the support they need And admittedly,
00:53:17.092 --> 00:53:21.692
Technical University Unique and Unternehmertum are getting very good at this,
00:53:21.852 --> 00:53:25.912
but they need more to change.
00:53:26.132 --> 00:53:31.012
Do you have a few ideas what needs to change in order to support them better,
00:53:31.192 --> 00:53:34.592
get them more opportunity to find a company right out of university?
00:53:36.351 --> 00:53:44.931
Yes, absolutely. The most important challenge is bringing back exceptional execution
00:53:44.931 --> 00:53:50.811
and commercial talents and connecting them with early STEM talent as soon as possible.
00:53:51.471 --> 00:53:55.671
If you take the example of Hungary and Eastern Europe, where I'm from ultimately,
00:53:56.091 --> 00:54:01.011
and this is a conversation I just had with a Hungarian VC founder that just got into VC.
00:54:02.411 --> 00:54:07.231
I'm now 29. He's, I think, also towards that age.
00:54:08.011 --> 00:54:14.571
Up until we finished our maybe second degree or master's or started working
00:54:14.571 --> 00:54:19.011
in the first position, we didn't have a clue about what venture capital is or
00:54:19.011 --> 00:54:20.991
what entrepreneurship truly is.
00:54:21.151 --> 00:54:25.611
We heard about the concept of starting a company, but the concept of what it
00:54:25.611 --> 00:54:31.591
means to take risk and pulling the trigger to build something massive was absolutely missing.
00:54:31.851 --> 00:54:35.611
And this is something, for example, You absolutely see in many business universities
00:54:35.611 --> 00:54:39.431
already happening in the West, in Deha, you have successful e-commerce founders
00:54:39.431 --> 00:54:42.831
going back and saying, you can start this company, you can start this company.
00:54:43.051 --> 00:54:47.311
And then you have students sitting there and having a conversation after the
00:54:47.311 --> 00:54:49.911
lecture about, hey, actually, we should start doing this.
00:54:50.051 --> 00:54:56.311
We are in a time of our life where pretty much we can take the most risks that we can.
00:54:56.511 --> 00:55:01.571
And this mindset is something that is very, very difficult to bring back very early.
00:55:01.571 --> 00:55:06.491
But the more early you can bring it, as soon as possible, pretty much start
00:55:06.491 --> 00:55:11.371
of university, ideally, the earlier you start a spark for these type of conversations
00:55:11.371 --> 00:55:13.131
and encouragement also across students.
00:55:13.131 --> 00:55:16.591
So I would say for all those different ecosystems that you have in STEM,
00:55:16.851 --> 00:55:20.631
you know, all across Europe, as you mentioned, you have TUM,
00:55:20.731 --> 00:55:24.391
you have ETH, you have Oxbridge, you have so many of these universities.
00:55:25.431 --> 00:55:29.031
The ability to connect students with those entrepreneurs that really,
00:55:29.111 --> 00:55:34.571
really made it there is something that is, in my perspective, is really missing.
00:55:36.051 --> 00:55:41.211
I see. Martin, thank you very much. it was a pleasure having you as a guest
00:55:41.211 --> 00:55:45.511
hope to have you back and for everybody who'd like to learn more we link of
00:55:45.511 --> 00:55:50.091
course your LinkedIn profile the website of Visionaries Club what's the best way to pitch
00:55:51.751 --> 00:55:55.171
Just pretty much send an email martin at visionariesclub.vc.
00:55:55.831 --> 00:56:01.491
I do have a game that's going on since I interviewed a few years ago Alex from
00:56:01.491 --> 00:56:04.631
Frankenberg from Hitech Grunafor and I was
00:56:06.251 --> 00:56:11.691
wondering if you get an email that only says the headline yo we should talk would you reply
00:56:14.811 --> 00:56:20.631
The headline i would say we don't i personally don't care that much about uh
00:56:20.631 --> 00:56:24.271
what's in the message is um is is a little bit more important.
00:56:24.271 --> 00:56:27.051
Okay great thank you very much
00:56:27.851 --> 00:56:29.531
Pleasure thank you so much for having me.
00:56:29.680 --> 00:56:59.477