Transcript: Mike Fridgen: Seattle based Startup Incubator Madrona Venture Labs

Host: This episode of startup Project is brought to you by bear. tax. Bear. tax compiles all your crypto transactions and makes it easy for you to file your taxes. Check out bear. tax, that is b. tax, bear. tax.

Host: Hey Mike, uh welcome to the show.

Guest: Thank you so much for having me.

Host: So, I mean I want to talk a lot about, you know, Madrona Venture Labs and what you're doing there, but before getting there, can you talk about your career before joining uh Madrona Venture Labs?

Guest: Yeah, you bet. Uh so I grew up in Seattle. I went to all local schools uh in the area.

I went to University of Washington for as an undergrad and and that's kind of where the passion for startups started in the in the mid 90s as an undergrad at Udub in the business school there and getting a tremendous amount of support from the faculty and the different, you know, emerging programs.

You know, the internet was on the scene.

That was the, you know, kind of our version of of what today's generations seen with Web 3, I think, kind of the the opportunity to kind of reimagine, you know, so many things uh in that time, but really exciting explosion of innovation and and opportunity.

And and so started my first company as an undergrad that was venture funded. So that was my also just a huge learning curve around, you know, venture back startups and the expectations of scaling and growth.

And so for the first 15 years of of my career uh as a founder builder type, my background was really in product and and go to market and and the business side of things.

And I was really been fortunate in the three venture back companies that that I was involved with prior to Mona Labs to work with incredible technologists, data science, engineering, designers, always look for those complementary partners, co-founders in companies.

One company I did uh of note called Faircast uh where I was a founding product leader was sold to Microsoft.

That company used data and technology to predict future airfare pricing, helping consumers know when to buy an airline ticket and it was part of that acquisition was rolled into Bing and the launch of Bing the search engine uh around this promise of decision engine, helping people make smart shopping decisions and for our product specifically travel decisions.

Went went from there to do another company called Decide, which was like a next generation data driven consumer reports. ran that company as the founding CEO with an incredible group, actually other undergrad team out of the Udub and an incredible professor uh with, you know, deep, deep background in machine learning AI to the Udub and and uh sold that company into eBay and from there uh came to Mona Venture Labs and happy to share a little bit more about what Mona Venture Labs does.

But my background up until up until that point was as a founder operator builder type.

Host: So uh you've been part of uh two acquisitions, right?

So and acquisitions are, you know, one of the interesting topics we would like to, you know, talk about in the podcast and we had Kirby previously on the podcast as well who was also part of, you know, a bunch of acquisitions and I was asking him the same question.

Do you see certain key factors that probably, you know, pushed or gave you an edge in terms of, you know, uh companies acquiring, you know, both the companies whether it's deciding.com or faircast.com.

Guest: Yeah, you you bet.

I mean one common thread with both of those companies in particular and actually that all three companies I was involved with were acquired and it in all cases the same thing was true, which was like we had established long term relationships with the acquiring company.

I mean the initial conversations were about product or distribution or a way to work together. But then after building a history, you know, it evolved into an M&A conversation.

I mean with with Microsoft specifically, um, you know, Faircast, the company, the startup had a had a deal, a distribution deal with MSN travel first. And and so that relationship was multiple years in development.

I think for for their teams to be able to see how, you know, we would present an ambitious road map and we'd deliver and they said, okay, here's this small startup team who has all this ambitions around, you know, evolving their product, adding new categories, went from flights to hotels, to other categories and he said, wow, we've got all these resources here within our group at Microsoft.

But look at how they perform. Look at how they execute. look at how they innovate in these unique data driven, really cutting edge types of features and capabilities.

So I think that that relationship through kind of them seeing our journey and and and then that relationship that distribution relationship kind of had a natural evolution into an M&A conversation.

That same could be said for Decide with eBay, you know, there was a a partnership there before it was an acquisition.

There was, you know, pilots being done and and discussions and with product teams and real relationship uh developing over time and and trust on both sides because it's it wasn't just the, you know, acquiring company looking at the startup but the startup saying, hey, is this a platform that we could realize our vision?

You know, I I remember, you know, and and in both cases, I think that was true to some extent that the product that we built in the startup, reached a level of scale we could only have dreamed about at the acquiring company.

I know for a lot of us I'll just to take go back to Faircast, you know, when we were joining that, the idea of predicting airfare pricing, kind of solving this problem of knowing when to buy a ticket, that seemed like to a lot of people, you know, friends who discouraged us from taking this crazy risk like a pipe dream, right?

And so the idea of like not only did we build it, we got it to tens of millions of users per month through Microsoft's, you know, distribution, that was really cool.

That that felt like, you know, we had ultimately delivered against the vision and and promise.

Host: Yeah, I think uh I mean the reason I like to talk about our questions in the podcast is because often founders miss is uh most of the exits in startups happen through M&As and it's not not IPOs or you know, spack or anything else, right?

Um I was just looking at the quarter one report of you know, venture capital and almost like we had 1900 acquisition.

So you're essentially more probable to get acquired, that's your good exit probability rather than, you know, doing a uh spack or an IPO. But moving on uh even just if I can jump in on that.

I mean, I think that's right and just to break that down a little further there. There there are I kind of see it as three different flavors of an acquisition too. There's a full talent acquisition. They're really just it's all about the team.

There's talent and technology. You usually get, you know, you get more for that, right? There's there's not only talent but there's there's real underlying tech that's unique, differentiated, valuable.

And then there's a business acquisition where it's like you have a real business throwing off revenue and and that's the the strategic rationale for the acquisitions. This is going to add to the top line, add to my business, add to my valuation.

And I think, you know, depending on the level of traction a startup gets, it can be in the talent, talent and tech or the true business product phases of that.

So, um that's another way to kind of even break up that class of M&A for early stage startups even even a bit further.

Host: Yeah, that that's a good way of analyzing, you know, where you're where you fit in the valley chain of acquisitions as well if you're a founder.

But talking about Mona venture Labs, obviously, you know, uh Mona the venture group is uh you know, pretty iconic and pretty famous in Seattle and you know, uh has, you know, some impressive companies in their portfolio like Amazon, Redfin, Snowflake, Upath and others.

But you know, what is Mona venture Labs do?

Guest: Yeah, happy to go in more detail about that.

So as you said, yeah, Mona venture Group, the VC firm, 27-year history investing in seed and A in the Pacific Northwest with some of the companies that that you mentioned, you know, deep relationships with the anchors in in our communities of University of Washington and Amazon and Microsoft and just a a special ecosystem that's been built around Mona. and I think a really incredible founders who've built really meaningful companies in partnership with Mona from you know, what Mona would call or what we'd say is day one and for the long run.

I mean from from day one and through, you know, certainly ups, downs and and and and ultimately uh successful outcomes for many companies. Mona venture Labs is an incubation program.

So we're working with founders literally like day one, day zero even sometimes of an ideas and like really kind of ideas on a whiteboard that need to be validated, built early traction, then ultimately funded.

And where we're we're unique and that in a couple ways, one this tight relationship and alignment we have with Mona. Um but two like our entire team are former operator builders type.

So I've got a product and a go-to market background, but you know, my partners have data science, engineering, design, completely different competencies uh but they've been in those founding roles and been in the trenches building.

So it's kind of an interesting combination. We've got the Mona connection, but we have a different capability and skill set as operators.

So you kind of marry up the operating experience of the lab with, you know, 27 years of investment judgment and pattern recognition uh from the venture capital firm and and that's a real balance between the two, you know, styles.

And you know, I know for us, you know, we're optimist, we're we're creators, we're builders, it's super helpful to have the judgment of the Mona investors to say, hey, let's take a lens towards venture scale.

Let's let's have a lens towards, you know, what we can really get behind from an investment investment standpoint.

So, that's a little bit about the differences and you know, I've been at the studio for six and a half years, um super inspired working with, you know, founders who, you know, don't always fit the common mold.

I mean part of what we do and our our model is that we're trying to derisk and fast track getting from an idea all the way to a seed check.

I mean usually right now we're talking four to seven million in a in a seed uh round that really helps um move the company forward or just bring on resources to develop, you know, product, serve customer, really move the company forward in an accelerated rate.

And you know, for all kinds of reasons, people can use support in that early, early phase. I mean right now, you know, a lot of people we're working with, they might have a personal burn rate.

So they they can't spend two years iterating, validating in the garage, you know, working through their savings, that's just not an option or they have families or all kinds of reasons that, you know, working with a team like ours that can take that, call it 18 to 24 month process of of bootstrapping idea and compressing that into a few months where they have a team, an experienced team with them, oftentimes a vetted idea already in place and certainly a line of sight to venture funding.

Like that's the that's the proposition we're putting out there for founders. that that derisking and and fast tracking to get that that company to that next level of scale.

Host: So there are different ways to create companies, right?

You could create companies just, you know, you know, create some small MVP, go out and, you know, raise a fund whether a pre-seed or a seed round from VCs and you know, start company and sort of iterate that process or you you can you can join an incubator and you know, work closely with incubator or you can join an accelerator like a YC or text stars and you know, work with them.

What do you think is the right fit in terms of like a founder incubator fit? Like what are you guys looking at in terms of, you know, this is the right type of idea/ founder combination we are looking to derisk.

Is there a specific type of things that you prefer to work with or uh because there's a huge spectrum of industry sectors thesis that you can, you know, choose to work with, right?

Guest: Yeah, we definitely have a thematic focus when we could talk more about that.

So we have the types of ideas generally that we're attracted to are ideas that have a deep data, technology underpinning to create a unique value for for customers, unique value in the product and um so that's that's how we think of the world.

So we have a data lens on everything we're doing. And most of what we're doing is in this category of intelligent application focused on a vertical. Uh in terms of in but we also experiment with other categories.

I mean we're doing a bunch of experimentation around Web 3.

We just had a event we held called Launchable whereby we brought 18 startup teams together from all over the world actually to a week of building and ultimately pitching investors of which MVL and made an investment and Mona is even, you know, had follow on conversations with many of these companies.

So thematically that's how we think about things uh data driven, AI ML driven around ideas. But then in terms of founders, we're looking with founders who have really a few things. One, deep domain expertise.

They've really lived a category, have unique insights about how to serve customers, how to think about a unique differentiated product. So that's that's one important element, deep domain experience.

We call it founder idea fit uh at the stage that we're operating at. There's also other components this idea of a rate of learning. Oftentimes we have founders coming in and it's the first time in a startup or first time as a founding CEO.

So this ability to be open, synthesize new information, use good judgment around using all those inputs to make smart decisions.

But also this rate of learning of just having this two-way door, I'm going to use a, you know, an Amazon term mentality of let the early stage, it's a lot of experimentation. So most decisions are two-way door.

If you make the wrong decisions, come right back, try it again and that rate of experimentation and learning, that's another thing we look for in founders. so they have that type of mindset.

And and then underpinning all of that at the heart is, is there a uncommon drive, ambition, some call it force of will that will kind of carry this person through all the challenging learning moments along the way.

And and usually that also is tied to this idea of passion for the problem and really believing in a in a mission level around what they're trying to achieve.

So those are the I think I hopefully I got to your question and and if not please tell me, but you know, kind of thematically what we look for and what do we look for in founders.

Host: Just to focus on that, you know, thematically what you're looking at.

I mean looking at your portfolio, you're obviously looking at, you know, AI companies, you know, heavy data science companies and you know, what we call as advanced ML companies, right?

One of the curious things, I mean uh just observing what is happening in venture is like five years back every tech probably had AI for this, ML for this, right?

And that probably you can say now it is, you know, Web 3 for this and Web 3 for that, right? Like it completely transition and no one talks about AI right now.

Just looking at the value chain of what is happening with you know, data first companies essentially. Uh what do you see where we are in that, you know, curve of evolution? Like is is the AI revolution done?

I'm sure it's not, but uh you know, I'm curious to hear what your opinion is in terms of where we are in that spectrum.

Guest: I mean, I think one thing that we're seeing in this evolution is this focus and we've done some companies that are of automation.

So not just the data element, the data, you know, and there's so many things that go into building a an AI company around the quality of the data, even as much as the algorithms themselves sometimes, the quality of data.

But then, you know, you kind of think about these phases of of the insights and then the automation around that into the, you know, workflows within an organization and that's where I see a lot of this moving to.

If you kind of look at the last set of companies we've done a company works around process discovery and automation.

A company called Strikegraph, which is around compliance automation, making that more repetitive and systematic and and building automation into those flows. Uh those are two good examples.

I mean at a later stage for for Mona, obviously UI Path, that an investment that was made uh on the Mona venture Group side and and UI Path.

So I automation is a natural evolution of the right systems and infrastructure and data and algorithms in place to then create more value in for companies and kind of this next phase of how to use data and and technology to create value.

Host: I think one takeaway from me was looking at, you know, the hype cycle uh even with Web 3 or, you know, what we are now calling as Web 2 and AI and ML is, I think we almost like when we talk about in popular culture, we almost imagine AI is this, you know, one single probably, you know, very intelligent creature talking to you like Siri or Cortana, but in reality what happened was we got embedded AI.

Like AI is everywhere and you know, with small features, right?

You know, right now on Zoom you're, you know, AI is being used in different forms whether it's for security or just compression algorithms or, you know, different purposes whether you're listening to music comes Spotify you're getting recommendations, you know, based on collaborative filtering, right?

So it's actually the product is not the end product, right? Uh the end product is not visible as AI or as product uh especially on the consumer side. So for the consumer, it is not actually a visible AI ML. It's only like what is the effect of it?

Like that is only visible. So it's what we are getting mostly is embedded AI and ML which is not generally travel to the customer as AI and ML. It travels us a better quality product in some sense.

So I think that's what and even I feel like Web 3 also transitions, right? We'll not look at like which token, which, you know, which chain you're using, right? What it helps me to do is the only thing that the customer at the end of the day cares.

Right. So I think we'll almost travel towards that phase probably in the next five years where I don't care if this is Web 3 or Web 2 or Web 2.5, right?

It's just that as a product what am I enabled to do and uh what it will actually help you know the users um to do.

Guest: I think you're right though and the the kind of the curve of the hype cycle or as as new technologies are adopted, there's a an initial fascination with the technology itself.

And a lot of the the energy is around the technology itself versus, you know, really when it's successful, you don't see it.

You know, you shouldn't see the technology, it shouldn't it shouldn't be about the technology, should be about end user experiences and enhancing the experience, uh the products where the technology is in the background.

You know, and and I think I think you're right. I mean I think AI is more at that. You you see the the value of smarter algorithms, whether it be uh for Netflix or or Spotify or those are in the background.

You just see the output of that, which are better recommendations or a better overall user experience.

Um so I I think I think you're right in terms of what you're saying about where the ML AI cycle is in terms of real product value versus Web 3 is more focused on the the novelty of the technology be in in that's taking maybe center stage and and over time we'll get to truly 10x better experiences, but we're not there yet.

Host: So since you also spend a lot of time, you know, exploding these ideas and incubating these ideas around AI and ML. What are some of the ideas you think still are, you know, unexplored?

Guest: Well, I'll tell you some of the categories we think are are are fascinating. You know, the future of work is a is a specific category that kind of sits underneath.

I mean we again, we're thinking about AI driven applications, but then how do you apply them to improve work.

This is a category that's been so radically transformed in recent years and I think people's minds have changed around, you know, what is what is work look like? What is their day-to-day flow in in their personal operating approach to to work.

So that's anytime there's that kind of radical behavioral shift, I think there's opens up opportunities for change. And I so I think we're just at the beginning of that.

Even Zoom, I think a lot of us are surprised two years later this is still the the baseline experience. there hasn't been, you know, like radical uh innovation here even yet, but it's coming certainly.

Uh there are a lot of startups have been funded to attack this.

They it's not it it'll take some creativity, it'll take um some iterating through it, but I I do believe that we'll see a lot of new and compelling um future of work companies built and new product experience delivered uh in the coming years.

Host: Yeah, if you've talked about, you know, obviously what you guys are doing with Web 3, uh what is your overall, you know, uh sort of uh understanding and you know, take away from what is happening right now in web and like where do you see primary value output coming from?

Guest: I think there's a lot of the main thing that attracted me to the category more recently is the amount of high quality, ambitious, early career talent that's entered the category.

And I I tend to think, you know, smart products and innovation will follow that over time. It won't happen immediately.

Um but there are a lot of brilliant people who are, you know, throwing themselves into this category as founders and builders and creators.

So I that has my attention personally and I think well, I mean obviously, there's a lot of attention broadly, but I mean that's that's personally why I'm I'm motivated to dig in and and learn and experiment from a, you know, Mona venture Labs point of view.

I mean that's generally our style too that we get in and build as a team. I mentioned this launchable event, you know, launched an NFT. that NFT was the onboard mechanism into a community Discord for the event.

You know, we built other products to build, you know, onboarding uh capabilities in terms of connecting wallets to to different elements of the experience.

So, you know, this is these are prototypes and this is experimentation and and kind of learning, you know, more and more about how to add value as as builders and and co-participants in this.

Um in terms of ideas that emerged, so we had, I think I mentioned this this particular event, 18 uh different teams.

I think, you know, some of the things that really caught my eye, teams that are building smart analytics tools and capabilities to understand everything from, you know, wallet analytics, community analytics, help understand the value of of engagement within these communities.

That whole area is compelling. I think companies serving brands who are looking to experiment. There are a couple different companies doing things in that area that I I thought that was uh interesting and and I think again, you see demand.

I mean you see brands every day, it's another brands, you know, either, you know, engaged with an NFT community, running an experiment experiment in a metaverse, a virtual world. You know, there's demand.

There's clearly demand for those experiments and learning and and I think it's just the beginning of that.

So those types of ideas, I mean certainly infrastructure, I mean at this event we had some of the the emerging change, you know, polygon and Solana and and avalanche and others who who participated.

I mean I I think I mean I think that's a fascinating area as well. So, you know, lots of creativity, uh lots of new ideas.

I mean we are we take the attitude of let's get in and contribute and add value to the community, let's learn and and these ideas that, you know, will really emerge over time.

I mean one the winning idea that I think is was a pretty interesting one is a company called Stack. It's a Seattle based company. It's providing a platform to help teens invest in cryptocurrency.

But there's obviously there's a lot of complexity in enabling that, but it's it it's an interesting market that'll be crypto natives. I mean we'll really like grow up with this.

And I so I think that's a a really interesting company and and MVL made an investment in that company as part of the event and you know, I think uh that's just one example to point out.

Host: I'm still I I would say I'm rationally optimistic on Web 3 because I think there's so much of it right now uh in the popular culture and um I think I mean, when you're on the investing side, it is your job to figure out, you know, what is novel that is new and that is really going to effectively do.

Like for example, replicating something that's been very effective like a decentralized cloud, for example, like that might not be a great idea because we have very efficiency compute delivered to us unless it's for a different purpose.

But some of the things I do like is like identity, like uh I can almost imagine a new identity company that could replace, you know, all the one click identity that we have across web to like, you know, um, you know, Google's one click that we are using everywhere or Octa, you know, for B2B, uh you can almost imagine a identity first wallet. like you know I think probably the end vision for .h wallet is to become sort of like the whole identity layer which you can own and you know, it's interoperable across the internet.

The other thing I'm also interested is how tokenization can basically um change how we access every other asset.

Uh if we, you know, end up to existing assets, uh I mean the new assets are cool, but I think a lot of it don't derive value that much because today for me they look more like tickets, right?

You can have a particular event and you know, produce that event very highly and you know, you can bulk up the charge for the NFT. Those you're basically selling a ticket not an NFT, right? But you know, think about Dos.

I think Dos are interesting if you have, you know, legit regulation around it where everyone can participate and you know, you can make sure that whatever the new accreditation status for example is going to be and make sure that we can comply with that technology much more easily, simply and you know, you can also be compliant because everything is stored on blockchain.

I think there certain use cases are very compelling for me like, you know, identity and um the equity aspect of it.

Uh like for example what Worldcoin is doing with uh you know, capturing identity in underdeveloped uh countries uh which is again interesting and scary and ambitious all all at the same time.

But uh I think there's definitely something to it for sure.

Guest: I agree. I like the concepts.

I mean this idea of kind of web one, two and three, kind of the the read, read write, read write own. like the concept of Web 3 being about this ownership of phase of of the web and and you're talking about Dos.

I mean that's the idea that the right that the community owns it. Uh you think about kind of these some of these projects. There's uh professional Dos like developer Dow, there's investors that like flamingo Dow.

Um you have these projects that are going after making acquisitions whether it's an NBA team or the Constitution, um these shared interest. I think these are interesting ideas and concepts.

I think there's some still fundamental governance, voting, decision making, some real gaps to be better performing organizations than the organizations we see in today's world. I mean today most of them aren't set up.

I think in my own personal view to be more successful. Maybe some of them around philanthropic pursuits etc, but I think there's a long way to go and I do think this idea of like today there are more Dow tools than there are Dow.

I mean we've we've kind of seen that.

You know, as we've analyzed that space, true Dos that are out to kind of like almost kind of more builder type that there's value but we're not seeing kind of the I haven't seen yet the kind of a breakthrough scenario, set of examples of where it's a better experience than the current company designed.

So more to come I mean I think there that's what's so great about this there will be such rapid and widespread experimentation and learning and evolution here.

So I think like I try not to have any hard fast, you know, kind of future because that my views will evolve as the, you know, as the examples and experiments evolve.

Host: So that's the paradox of you know, staying as an enter investor, right? Like you have to look for the optimistic side of things and not I mean, your whole goal is to find those good five things that really work, right?

So, and that means that you have to and when you're at the edge of evolution, you have to face those failures because you are accepting that they're going to be failures and you're making that bets uh accepting the fact that some of these will not work.

But in related topic, uh how do you see the, you know, recent, you know, in general because you're closely working with the startups and you're also closely working with Mona, the VC firm.

How do you see the venture ecosystem evolving and you know, especially, you know, valuations and general like how do you see the whole cycle evolved in the last couple of years and we are seeing probably a bit of slowdown uh this quarter, but in general, what is your vantage point, you know, being at the center of all this?

Guest: Well, I think what you're seeing is that at the later stages, there's some clear adjustments to the to the later stage rounds. You see some of the traditionally later stage investors coming to the earlier stages. Uh right?

Uh so there'll be more more competition at the seed and A. I think, you know, I'm I'm a believer that it's always a good time to start a company.

So even if there are corrections and adjustments, I mean some of the most interesting companies have been started in in downturns and when markets didn't look perfectly suited for for new companies and and we could talk about I mean I think you know those examples you talk about those examples everything from Google to to Airbnb kind of and in those kind of moments.

So, you know, I think I think it's a great time to be an an early stage company builder, a zero to one builder. And and I think that, you know, there have been more and more investors who've entered that pre-seed and seed uh stage of investing.

So I think there there there are more options and certainly that's a of the highest priority for Mona Labs but Mona in general in in the Pacific Northwest in particular, you know, being being a partner and a founder's um especially in the in the transitional times as as much as the is the heady times.

So, yeah, I'm I'm optimistic at at at the early stage.

I think, you know, if you're in if you're a later stage founder builder, I think being smart about burn and runway and and and all of that, you know, I mean that's those are the discussions happening at the board levels of these companies, right?

So so that's that's obviously got to be top of mind or you know, really being smart and giving ourselves room to, you know, maybe catch up to valuation, catch up to multiples that that had been there in in the in the previous cycle.

Host: How are you advising your own, you know, incubated companies through this cycle because we are clearly seeing some sort of uh you know, adjustment in venture and probably it might take more time than raising, you know, your seed or see if you say than it took uh maybe, you know, last year. How are you making sure that you are at least portfolio is set up for success?

Guest: Yeah, I mean I think it comes back to, you know, being responsible in how you manage burn rate and you know, and and and you're giving yourself room on on product market fit.

I mean, you know, focusing resources around product and customer and giving yourself time to to get that right. So that that means, you know, being you know give having giving yourself the runway to get through it.

And and that's a that's comes down to costs and burn and you know, prioritizing the right things, being focused. Those are the types of types of conversations that are that are happening.

Host: So I one last question, you know, before we end our conversation, I wanted to ask because, you know, traditionally whenever you talk to very young people in around Seattle area, there's always this criticism of, you know, Seattle investors or Northwest investors always invest in B2B companies.

How much of do you think is uh, you know, that uh changing or I mean obviously, you know, there's certain bias towards it because you know, Amazon exists here, Microsoft exists here, you know, other you know, B2B companies exist here.

So that bias is sort of inherently the nature of, you know, the people around. But how do you see the whole ecosystem evolving? Do you see more of, you know, other categories coming at the mix uh or do we have to do more to actually make that happen?

Guest: I think that there are some some really smart if you're talking about kind of the consumer category, smart founders in our market, investors in our market and consumer.

And we we could point to companies in, you know, Mona's portfolio like Rover or Redfin others, you can go beyond that, you know, companies like Expedia and Zillow and you can kind of go go down the list.

So I think I think Amazon, of course, you know, Seattle's had its mark on on consumer even though it is it certainly is a B2B enterprise heavy heavy market.

I think it's about, you know, these success stories, if we think about the future, you know, bringing more and more angel investments so that the the successful consumer operators having outcomes and then being there, supporting the next generation of consumer builders and founders.

I think that's I think what we're in front of us is I think another wave of of an of early stage investors and supporters of that entrepreneurial spirit in our in our community.

So relative to some markets, it might not be uh in the same place, but it's certainly a growing and developing one in in uh this is certainly a good consumer company.

Host: Mike, uh thanks for taking time and uh coming onto the podcast.

Guest: Yeah, really enjoyed it. Thanks for having me.

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