From VC to Founder: Building RedpineAI and Thinking 100x Bigger | Anders Hammerbäck

What changes when you stop investing in startups and start building one yourself?

James Johnson is joined by Anders Hammerbäck, Co-Founder and CEO of RedpineAI, to discuss his journey from venture capitalist to founder.

After spending six years backing early-stage startups at Antler, Anders left the world of investing to tackle one of AI's biggest challenges: unlocking access to high-quality data outside the public internet.

Together they explore:

• Why Anders left venture capital
• The realities of founder resilience
• What investors often misunderstand about entrepreneurship
• Building AI companies in a rapidly changing landscape
• How founders can stay ahead of technological change
• Why thinking 100x bigger creates different decisions
• The role of people, teams and AI agents in future businesses

This is a conversation about ambition, resilience, technology and what it really takes to build at the frontier of AI.

New episodes every week.

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Connect with James on LinkedIn or at peer-effect.com 

Transcript

SPEAKER_01 0:05

Hi, I'm James Johnson, founder and CEO coach. Welcome to Peer Effect, the podcast where your peers will tell you what's unlocking their 10 million plus business. My guest today is Anders Hammerbach, co-founder and CEO of RedPine AI. They're an AI company building infrastructure for financial data intelligence. They recently raised a 6.8 million euro round, and we're going to talk about switching from being a VC to a founder and what are the learnings for both. Remember to hit the subscribe button before we get started. And now on with the show. So Anders, welcome to the show.

SPEAKER_00 0:42

Thank you so much, James. It's great to be here. My pleasure.

SPEAKER_01 0:45

Now sounds like we've got something in common. Like you yours is more of an active skill, mine's more of a a long-dead skill. But you you now speak fluent Mandarin.

SPEAKER_00 0:55

Yeah, I used to speak fluent, now I think near fluent, at least at you know, good conversation level and some business level as well in in certain settings. So yeah, it's it's languages are so important, I think, even with translation being very, very improved now. But I I think in a real person-to-person language communication, just showing that you make the extra effort has for me been very important through my career, and and I'm happy to speak uh you know Chinese.

SPEAKER_01 1:21

Yeah, I've read a little test before before the sh the show, and I can I think I can confirm that you you do.

SPEAKER_00 1:28

Yeah, likewise. I think you're humble as well, but very impressive that you've managed to maintain your level from school and onwards. So so very impressive.

SPEAKER_01 1:38

Well, today we're gonna talk about sort of shifting from building a fund to building a company. But I'm curious, what's what's your origin story? What got you to this point?

SPEAKER_00 1:48

Yeah, let's see how how deep back we go. But foundationally, you know, I come from Sweden, Stockholm, Sweden, which is nowadays known as uh sort of an AI city with a lot of great companies coming out of it. But growing up in the the 80s myself, I did a lot of sports, a lot of ice hockey, football, especially. And I think that uh led to my competitiveness also growing up with a family of four brothers. I was the oldest. I think that's some sort of foundational and formative element for sure. But then, you know, in in that period as well, computers started really booming on the global level, and so also in Sweden. So my interest shifted from the ice hockey rink towards computers and the world wide web. And that's also a big, big chapter in my life, starting to build websites and starting to code and and so forth. And that remained a strong interest and passion throughout, even though I took more of a business route uh in in different companies. Yeah, I always sort of stayed at the intersection between business and technology and really using technology not just for the sake of it, but also what's the opportunity, what's the benefit of using this technology in various settings, and had a you know privilege to spend to be part of my career abroad as well, both in through McKinsey, where I was traveling a lot doing projects in remote places such as Congo, DRC, Nigeria, Lagos. I spent some time in the US, Europe, of course, and also in Asia, including China and other countries. So, you know, I think those are some of the elements that sort of led me to this route. Data has always been a core bloodline, you can say, throughout my professional time and working with data, seeing the value of data across industries within a company, outside of the company as well, and really drawing value out of data. And that's definitely come to fruition now building Red Pine AI.

SPEAKER_01 3:31

And I think sort of what we're going to look at is like this the shift from sort of going in Red Pine as a as a VC to RedPine as a product. And so the shift from sort of the portfolio approach, investment being hands-off to being like really hands-on. So what what what led to that shift?

SPEAKER_00 3:49

Yeah, no, great question. So I was a VC investing from a company called Antler for six years, working with really early stage startup companies focusing on European tech founders, and in the last few years were almost only focused on AI companies. And that was of course exciting seeing the whole shift of AI going from predictive models towards more generative models as well. But for me, having worked in different industries, I always had the one question: what about the data? How is how can data be a competitive mode for you as a company, the companies we're looking to invest into? You know, knowing out there there must be a better way to use other types of data than just internet data and worldwide web data. So eventually I realized this is a difficult problem to crack, how to really unlock the most high-quality data sources out there in addition to web data. So after, you know, six years in total, I decided I need to take a stab at this problem myself and really build a company that does this at scale on the global level, that really builds the data platform for the most ambitious AI companies out there. And yeah, that became the kind of starting point when the coin drop moment, so to speak, I realized this seems to be a problem that most of the companies I looked at had in common, and and no one was solving it in the way I thought it should be solved. So yeah, then I decided let's just do this.

SPEAKER_01 5:19

With that educative view, it feels like AI gives you access to a lot more data just by nature of what it does. Like you ask any question, it goes out from sources. So what what what is the problem that you are solving from a data perspective?

SPEAKER_00 5:33

Sure thing. You know, you're right. So internet data is a massive amount of data. The quantums are somewhere between 20 to 50 trillion tokens, which is of course a lot of data out there, but it's far from all the data that exists, and in fact, there's you know up to 100x uh of more data outside the public internet. So there's more both in terms of quantity of that data, but also some of the best data exists outside the public worldwide web domains. So in order to make AI truly powerful and really perform and perform accurately and compliantly for that sake, we need to access that data which sits outside the public internet. And that's what RedPy insets about. And I think you know, with my co-founder David Ostadal, who used to work early days at uh Spotify for a good number of years, you know, cracked also the new distribution model in that case for music for other types of media, when it came from you know a new type of distribution into digital distribution into people's streaming software. And Spotify did that, you know, managed that transition well, including the licensing piece of music. Now, what we're seeing in the world of AI and with the data, uh, a lot of data has been used and scraped, internet data specifically, but also some books by by AI companies, because the speed has been the key priority. Now we need to move to uh situation, also that's the second problem, where the data owners and the data creators get compensated for the data being used for AI, both one-off deals, but also an ongoing way. So I think that's the second problem that we see as critical to solve, because that also creates a flywheel for new data to be created if there are incentives to do so. So both the access to high quality data, but also the compensation to data owners. Those are the two main problems we're solving, and of course, AI agents, a new type of users here in this world, which we're just welcoming on board across functions, across companies, and also in our personal lives. I think most of us are dabbling around with AI agents to some degree. These agents will need to tap into various forms of data streams and data sets. And this is just a new type of market opening up, which we are leading.

SPEAKER_01 7:49

So is is is it a bit reductive to say a Spotify for data?

SPEAKER_00 7:54

Is that it's there are definitely similarities between you know creating a licensed model for AI data and creating a smart technical access model for doing that as well. So I think there are definitely similarities in those regards. And you know, the Spotify Amazing, another Swedish company, is more of a B2C product, whereas we are solidly a B2B product. Also, payment and pricing are somewhat different, but there are similarities and differences for sure.

SPEAKER_01 8:23

I can see how that's that's super helpful. I sort of joke people that if you were to persuade the best thing to do if you were an AI genius would be to go back in time 10 years and invent the idea of influencing. We get everyone to give up all of their best content out of their head and write it down into an easily discoverable format. You can then you can train your model, so I don't think anyone was thinking that far ahead, but it would have been genius if someone was thinking that. But I can see how there's also all this other data that's just sitting behind either it's not connected or it's sitting behind different paywall, or it's and if we don't have that data, we're only making a decision with like you say, 1% of what we need.

SPEAKER_00 9:07

Absolutely. And that's the opportunity, right? I'm uh I'm very much optimistic about what AI will do for people, for companies, for the world in general, you know, focusing on that part of the equation. And and that's what we're trying to unlock the the kind of massive potential of uh you know, towards people talking about AGI, ASI, singularity, whatever we call it, but just higher potential of AI to solve the biggest and most important problems that we do face. And that's what we're focusing on, including healthcare and solving for new drugs, treatment methods, new materials, for example, from chemical discovery and material discovery using new combinations, which is very important, but also across other fields in the future, you know, education, for example, which is underpinning all the other industries. So there's so much potential to be unlocked and to be diffused into all sectors, and and we're focusing on the data aspect of doing that.

SPEAKER_01 10:03

Very nice. And and it was it was this clarity and this problem that pulled you out of VC into the U.

SPEAKER_00 10:11

Definitely. I mean, both seeing that the big problem to be to be cracked, but also the pure excitement of building again, you know, starting up in the VC, I came on board very early stage and got the opportunity to launch this VC platform and the first funds uh in Sweden, focusing on northern Europe. Early days, that was also building, but building in the fund structure. Now I I love building early stage 0 to 1, 1 to 10, and those kind of journeys, you know, setting up the early team, creating the mission, creating the culture, building the the early plans and the frameworks and getting out there, validating those towards the market. I just thrive in that context. So it was time to do that again, especially seeing the master mega trends of AI really starting to take the world by storm five years back, four years back. It just felt like in the sporting metaphor way. I needed to be on the playing field playing that game. And being a VC is fantastic and exciting in many ways, but in some ways, I felt like being on the sidelines, seeing where the game was happening on the field. And yeah, oh, I need to get back on the field. And then, of course, you know, having a great co-founder is so important as a VC. That was one of the prerequisites to invest in. And and getting to work with David as the co-founder of Red Pine, and he decided to you know start building this company around the same time. And we all both came together and said this is it. So I think that serendipity was also very important in making that decision.

SPEAKER_01 11:37

Yeah, that's definitely been a theme recently on the podcast, just the importance of the right co-founder. But so let's let's let's continue the sports analogy of sort of getting off off the onto the field. What did you learn as a VC that has do you think that's helped you as a founder?

SPEAKER_00 11:54

I think what learned I I saw so many, you know, we had hundreds of companies in portfolio, and I see up close in person how much up and down, how much roller coaster life as a founder really is. Because you're often the first call of the founders when they bump into challenges or problems, you know, picking up the phone call, call the first investor on board, and both as a sounding board, but also getting some some practical advice. So seeing so many scenarios and situations where it goes up and down, and I think that mental readiness is very important to know before you start a company. And and to me, I think the also the second step of that is knowing that you know how much your your grit, perseverance, and as the the Finns say, the Sisu, that's another word for it, just powering through with a clear objective and clear motivation, how far that can really take you when it's getting when the wind blows you know towards you and when it's getting tough. I think that's the same in sports. When you're down a few goals, you need to tie it up and then you know win. It's a lot about that mobilizing that inner energy and optimistically feeling this can be done, you know, we can get through this. I I've seen that and how much that as a VC, I saw that in in some of the best founders, how they managed to do that. And that's also something I I truly take to myself every day here building a red pine. I think that's that's the key one.

SPEAKER_01 13:18

Is that something you can prepare or work on? Because you you saw that in your background with iTalkie at a professional level. I mean, that is that's probably fewer tougher sports than that. Yeah, but it's just so that's a pretty tough sport. I'm wondering, like you you saw this trend of the founders, but other founders listening. Is there stuff that you think that you've done or can do to help bring up that resilience or C2, if I'm if I'm saying that correctly?

SPEAKER_00 13:46

That's correct. Yeah, I think everyone can find their source uh and channel of strengths, right? Either it's being from the sports or from you know having mentors around, maybe and balancing that with. So one of your previous podcast guests talked about you know using AI as a form of mentorship as well. I found that to be quite interesting. So I guess that comes down to who you are as a person and where you find your source of strengths, whether it's you know from a competitive mindset or you know, getting energy from other people around you or or uh you know some sort of meditation approach. So I guess that's a little bit personal. For me, it's definitely that winning mindset that helps a lot, and knowing that no matter what, we're gonna you know win in this this space that motivates me a lot, and knowing that just a sheer willpower will get you very far. No matter if it's you know building the best company you can build, winning the the sports game that seems tough, or learning a difficult language like Chinese, or you know, doing something very tough. And doing that a few times over and over in different domains, I think shows to yourself what you are able to do. And to me, that's been a core theme, like doing difficult stuff and pushing myself uh over tough, tough edges and and seeing that okay, it can actually be achieved. That's been helpful for me, and I think for most founders that's something they have to have as a resilience, as a kind of yeah, inner strength somehow to face challenges when they hit, because they definitely would do.

SPEAKER_01 15:18

I wonder just how much that's trainable, how much it's just innate. I was having a chat with another founder earlier this week talking about how the things we sign up for as founders to most people are ridiculous, whether that's extreme sports events, whether it's like the hours that you work, it's like you just you just agree to do things that people abnormal people would probably think are ridiculous. And I wonder whether it's something that whether that's just something that you have and build up over time, or whether it's something that you can even train.

SPEAKER_00 15:52

I to me, if you ask me, James, I think it's trainable. I think that's like a muscle you train, like any other muscle almost like and and doing it over and over again makes you realize you know how to build that that muscle's strengths over time. I think many of the founders, you know, that that start their own the first companies in the you know late teens or early 20s, for example, and nowadays are you know decided corns and even more very impressive. And I I think did they were they born in a different breed? My take is that uh they're not, but they're exposed to so many situations, and over time gives them resilience as well. So I think you know, not stopping the first times around when the challenges hit will create more resilience next time, and over time that compounds into uh superpowers, you know, entrepreneurial superpowers. That's my view at least. I've had a chance of you know studying with some of the fantastic founders of Klarna, Swedish fintech giant, you know, amazing guys, and and big congrats to their achievement. And I said in another podcast, Danny Liek, the Spotify founder, I think European Europe's biggest tech companies by some metrics, went to the same high school as I did, a year behind. And this is a small ecosystem, so I think in Sweden, as in many European places, you get to see some of these people and how they operate and so forth. And and my view at least is that you know the what sets them apart is of course many things, but one is the the decision to start that company, that's number one, and decide to make it big. And then I think that a lot comes along the way, the training, the situations that you're exposed to, and the people that you meet, all of that compounds into superpowers. So yeah, that's that's my view.

SPEAKER_01 17:37

It's kind of exposure therapy in some ways. And I someone's joke, like for me, I used to business turnaround the start of my career, and like what other people think as like a nine out of ten crisis, it's probably like a three out of ten. It's like unless the company is about a week away from running out of cash, that's a nine.

SPEAKER_00 17:54

Yeah, exactly.

SPEAKER_01 17:55

Sort of a key person leaving is probably like a two. Yeah, it's like you you are kind of exposed, you know, your mentality does shift over time when you see that the world doesn't fall over, or you can deal with a lot more than you probably think you could do when you start out.

SPEAKER_00 18:11

And I think it's also, you know, building onto that, it's all relative. I I try to think like that. Everything is relative. Um, you know, what's the worst thing that can happen? That was one of my early mentors said something like that. What's the worst thing that can happen based on your decisions and your actions, both as a founder and working inside companies? Maybe in most cases it's about, you know, maybe you get fired, or maybe you know, something like happens, some people might lose some money, which is terrible, of course, in many ways. But is that something you can over time overcome and fix and solve? Yeah, probably, both for the for the kind of people around you and yourself. So I try to put in perspective and and at least focus on the upside, focus on the opportunity, and put it in in perspective to think about other things that are meaningful, you know, family, health, and those things to be grateful of. And doing that, I think the the kind of the negative stress and so forth feels a bit lighter to carry, put in a different perspective and balance. That's at least my one of my coping mechanisms.

SPEAKER_01 19:10

I agree. I think having the right mindset towards it, working on the mindset, thinking about mindfulness, having the right support network. Like, I think these things help. What what so coming in back to sort of this transition? What is something that you feel you might have got wrong as an investor that when it came to founders? Like now that you're back into founder, go, oh, if I was if I was a VC again, this is something that I've learned that actually maybe I was I I got wrong when I was a VC.

SPEAKER_00 19:40

Yeah, great question. I think the and reflecting a bit ahead of this this podcast, I think as a VC, some VCs at least, and I think I probably was, was quite opinionated on what I thought was the right thing for a certain company, and maybe it was a bit too prescriptive about certain ideas or angles to take and advising founders about. And when in fact there's so many degrees of uncertainty in in the world, especially in the world of AI, things move so incredibly fast. So, you know, some founders might have appreciated that, but others might have appreciated more, more sort of just unbridled, constant sort of encouragement no matter what they're building, you know, just giving them the full degrees of freedom of support. And I think many investors maybe take that approach of of thinking they know exactly what's going to happen in the world in a certain field. And maybe some of them, you know, get it right, but most probably don't. So I think that that humility is probably something that benefits the the investor community as well as other fields, even more and not sort of pushing hypotheses too hard onto founders. That's probably something I I would do more if I at some point in the future went back into the investor role.

SPEAKER_01 21:00

Especially for like the pace of change at the moment. Like I think like I saw my company in 2020, would I almost quite a lot of that experience is it's it's now I say worthless, but it's so different, like the environment's different, the tools you have are different. Like even coming from an operating background, if I was I do advise a company, I'd do it like it's still the game has changed so much. There are certain fundamentals that are still the same in terms of watching your cash, having good people, etc. But the hows, one of the reasons I do this podcast, I think the hows are changing so fast. I think it's pretty easy almost to be humble because you've just got like almost no one can know. I don't think anyone knows at the moment how to do it truly.

SPEAKER_00 21:44

No, no, no, it's moving so fast. And I agree with your operating excellence, you know, meant something five years ago, and it means something else today on how to set up an AI enabled theme and organizations and different functions and how to make them all come together, where to apply agents, where to apply. You know, people plus agents and where to simply have people and what tools to use and so forth. You know, how much should token cost be as part of your overall opex? Is it 20%? Is it 50%? Is it 80%? All those kind of questions. I think everyone's you know moving the pushing the the boundary here and trying to experiment and to find the right equilibrium for that company and for that sector and for that function. But again, investor founder mix and perspectives, tough to know what exactly it is. But I think what you can do as an investor, I guess, is you know seeing some overall trends across your portfolio and sharing them in the right way towards portfolio founders that that might be focused on on One Piece a bit more intensively, getting that you know 10,000 feet perspective could sometimes be helpful putting it in in perspective.

SPEAKER_01 22:48

Yeah, I think that'll share 10, 20, 50 portfolio stories, you're hopefully seeing some trends out of thought from macro perspective. Yeah, I guess. Where do you get now? So, like you're part of a big VC, you're getting that trend now, you're in it. How do you maintain say token? 20%, 30%, 80%. How do you benchmark what you're doing and sort of get those ideas?

SPEAKER_00 23:16

Yeah, no, I'm trying to get a lot of signals always, and you know, filter out the ones I think are important and and the ones are not so much uh removed. I listen to a lot of podcasts all the time. Being a European founder, I think it's important to also tap into what's happening at the front line, at the frontier, in Silicon Valley, especially, and understanding which companies are are leading the way, which founders, their advice. I think podcasts, you know, such as one you're building, James, it's very important from at least for me, from a thought leadership point of view, getting signals across industries, across people, and trying to make them as diverse as possible in terms of the input signals, but also reading you know some social media, X, LinkedIn, you know, viewpoints, again, trying to kind of filter in, filter out what makes sense. And also for me, speaking to founder peers is very helpful. Having some of the kind of trusted peers in your network, some of them might be building one or a couple of steps ahead, some are might be a step behind or at the same step. But you know, speaking to founder peers is is very helpful. Also, we have an amazing set of angel investors and now VCs as well behind Redpine. To me, that's helpful as well in advisor meetings and board meetings to also tap into what they're seeing in their networks to align what we are seeing, what we're building, to make sure we really get the right type of intelligence behind Redpine. At the end of the day, the North Star needs to you know rest on your compass as founders, for me and my co-founder and the team, but getting that you know signal from outside is very important when things move as fast as it does right now.

SPEAKER_01 25:00

So just practically, what percentage of your time do you think you spend sense checking with like these whether it's through podcasts or connections or just that external data just to benchmark and check you're on the right track?

SPEAKER_00 25:15

That's a great question. It probably varies from week to week, but on average week, including all of those different channels outside, probably say 10, 10 hours, maybe 10 to 15 hours, like in total. And that can be you know in transportation, in transit, working out, being at a VC mingle event or or something like that, which does happen occasionally, you know, speaking to founders, fireside chats, and so on and so forth. In I think also interviewing people is very important. Like as you're scaling fast, like we do now at Red Pine, you interview a lot of people. All those people you know have different backgrounds, different insights. It's always important not just to kind of validate is this person right for you, for your team, but also okay, where are they coming from? What do they see? I think that's an amazing opportunity to actually tap into signals, to input that you can then decide if it's relevant for you and maybe even hire the person.

SPEAKER_01 26:11

That's that's really nice. So there's actually lots of given we're talking about data as a as a business. What you're saying is that even even like to get the external data, there's lots of different ways to get that data, but it feels like 10 to 15 hours, it's a good amount of investment just to even if you're multitasking and doing it while working out or travelling, it is still let's say, 10% to 20% of your of your week.

SPEAKER_00 26:39

Yeah, yeah.

SPEAKER_01 26:40

It must be worthwhile doing them.

SPEAKER_00 26:42

Yeah, let's see. The future will show, but I definitely think that's that's important. It's well spent time for sure, at least you know, navigating in this amazing time that we live in. You know, so much opportunity left, right, and center. And there's an abundance of opportunity, I would say, even. So to me it's it's not so much about where the pitfalls here, but rather which are the really big opportunities and differentiating them from the big ones. That to me is the kind of navigation signal I'm trying to find. And that changes over time, sometimes week by week, as you said. New models come come on board and new companies launch. Yeah, it's just amazing the kind of force of the AI right now happening and how to navigate that. I I think the first year of Red Pine was very challenging in that regard because you know that simply that speed as a you know two-person startup as we were, just foundry led up to the point where we build a team. You know, you have to run very fast to catch up with that train. But now I think we're starting to really get some good speed and really to trying to see what's behind the corner in terms of what's happening. And I think also using the crystal ball from from the previous work, previous experiences and career that you've had is very important. And and drawing parallels from different shifts over time, which is still relevant, I think, by and large, and also looking at different industries, sort of across industry to industry, what is happening here. That's where I think the the more interesting opportunities appear. When you can say, okay, what happened here 10 years ago? Okay, now maybe this is what we're seeing in this industry, and start thinking laterally between industries over time, and that to me creates a more exciting playing field to work with.

SPEAKER_01 28:22

And we brought up a really interesting point there in terms of team size versus speed that I've just got to jump into. So there's there's a narrative slightly particularly on LinkedIn, like, oh, you can build a billion-dollar business as a single person operator due to agents and different communities. Your clear version space, you're speaking to VT, you're speaking to other founders, you're doing it yourself. What do you think is kind of the optimal structure slash balance between team size and use of AI to truly scale? Because you said like those two of you felt that maybe the operation was a bit slower, so you brought in people and now you're really hitting it. So what do you think? What do you see as kind of the optimal balance?

SPEAKER_00 29:04

And and here I think the it might be contrarian or hot take so forth. I I really see a big value of people going forward as well. Some of the you know teams and founders that we want more agents and robots and so on and so forth. I love those as well. But I do see the the kind of Jevons paradox playing out here. As long as people are AI enabled and can make good use of agentic services and productivity tools, which everyone has to now. I think that should probably clear. Then I see that you know adding smart, good driven people to our team will continue increasing the output and thereby the scale of our company. So I suggest by way of showing that we'll we launched an internship for the summer 2026, where we are bringing on board between 10 people, maybe a bit more, as an internship program. And that's basically the size of our current team, you know, 10 people. I do see huge value of having 10 amazing interns to our company. And I think they can both deliver value from day one almost, and also we can deliver value back to them, give them an experience of working with a fast-scaling AI startup. And this goes across functions: tech, engineering, data science, go-to-market, data partnerships, legal, and so forth. So I think that's just a fantastic example to me of the belief in the capabilities of people here in the next chapter of AI's rollout and how we can work in good tandem and work in uh a good symbiosis between agents and people. So the optimal structure, coming back to your point, James, I think is really an interplay. Having you know great people that see the value of AI and creating systems around so that every person is enhanced and augmented by the potential and capacity. But there's also a lot of great things that that AI agents right now, still in the next few years, will not be able to do. I think that trust building between people that will then open up interfaces between companies, as they have been over centuries, as some of the sales motions, some of the partnerships and so forth still will happen between people, even if an agent-to-agent commerce is starting to kick off. So for that reason, I I I love the the notion of building a company which is still founded between the trust between people and then having AI adding value, you know, around that. That's that's how I see it. So we will continue growing our team, probably not as aggressively as had we launched 10 years ago. At the same time, there wouldn't have been an AI data business 10 years ago. But right now, there definitely can be. Yeah, definitely, definitely.

SPEAKER_01 31:51

As a sort of a final question, then to wrap up, like what is one thing that you think founders listening today, off the back of listening to this, could go and do?

SPEAKER_00 32:03

Yeah, super good question. I think they founders, you know, I thought about this question. I think you know, as a founder, it's easy to get bogged down into operational details and the everyday problems to solve and so forth. And yes, those are important, but I think the most successful founders do think 10 or 100x or even more X in terms of ambition and then shape the roadmap accordingly. Always thinking how can we do this 10 times bigger or 100 times bigger? What's the unlock to do that? I think that's a kind of mindset thought, kind of you know, a challenge to oneself that every founder can always think about okay, we're at this stage now, maybe that feels like a good stage or not, but what about 10 times or 100 times this? And especially coming from Europe, I think this is something we have to, or Sweden push ourselves even more to do. But again, it can be done. We've seen other companies do it, no matter if we talk about Klarna, Spotify, or so many other great European companies, to really become a global leader in the space. What does it take? How do we do it? Do we launch globally from day one? Do we launch you know an open platform? So on and so forth. So I think it's that sort of mindset unlock to do things 100 times bigger. That's like a concrete thing, a question to always have in the back of the head and bring forward sometimes and think what should we do? What concrete actions do we take? And that's number one. Number two, I think, is just getting knee deep into AI, if not already doing it, you know, testing the tools, productivity tools always, testing new services. And that's a different difficult thing for any team running in you know 150 kilometers per hour every day. Like, how do we find time to test all the new tools and enable our team to use all these tools? I think that's tough, even for the frontier labs. They say the same. We tested one thing last month, which I think worked really well, is to sort of allocate one day for a whole in-team hackathon, on-team hackathon. And we're gonna try to do that every every month or every other month. To do like, okay, we're taking six hours now, allocating to building internal improvement between the team, using those tools that we think about to really create that diffusion internally of the most recent tools and technology. That's something that everyone can test what works for them, but at least for us, that was a good AI enabler in the in-house ways of working.

SPEAKER_01 34:30

I think that's a really nice thing to take back. I've actually had a couple people say that. It's super as a coach, like I do not have the same operational sort of demands on me. And I still I still feel I should spend more time experimenting with AI. Like I don't, I haven't yet dedicated time in my diaries to do it. I've just kind of taken things on people. But it does feel like doing it as a deliberate diarising it, doing it with your team, however long you're choosing to do it for, does feel like the only way that you're gonna find the time to do it. So I love I love that as a takeaway.

SPEAKER_00 35:08

Sounds good. Just try it.

SPEAKER_01 35:11

Andus, thank you so much for this. It's been it's been really useful.

SPEAKER_00 35:15

Thanks so much, James, for the opportunity. Love the pod and and the keep up the good work, and thanks so much for inviting us.

SPEAKER_01 35:21

Remember to subscribe if you want more action insight from founders scaling now. Thanks for listening, and see you next week.