Todd Gagne:

Dan Hofer, welcome to the podcast, man. I appreciate you making the time.

Dan Hofer,:

Thanks so much, Tom. Appreciate the insight.

Todd Gagne:

Yeah. It's been good. So why don't we start a little bit about how you got to your position today? So today, you wrote a fund. And so you can talk a little bit about that.

But more more, I'm kind of interested in just your journey. Right? So you've had kind of an entrepreneur's entrepreneur journey, and I think it's kind of you got a bunch of interesting stops along the way. So why don't we just start from an intro standpoint and give people just a high level overview of kind of how you ended up here?

Dan Hofer,:

Yeah. Thanks. So I I feel like I've done all sorts of different things in my career. I I someone someone once described me when I was younger as as a seeker. And and so I I just love, you know, learning new things and having new experiences and kinda moving around.

So I've been a management consultant. I've been a a product executive for a number of years at at multiple companies. And and, Todd, that's actually where where you and I met Right. Back back in the day at Concur. Yep.

And then I've also been a corp dev professional at a couple of companies. And then over the last decade or so, I've been a partner at at venture capital firms in Silicon Valley. I've also been a founder and CEO of a global global travel website, which was venture backed. And so I've I've had experience on both sides of the table as an operator, as a founder CEO, and and as a venture capitalist.

Todd Gagne:

So what do you think? I mean, is there any theme in that besides curiosity? You know, you've taken multiple roles and multiple dimensions of the whole ecosystem, but is there any theme that basically kind of stitches any of that together?

Dan Hofer,:

Well, I I I love I love learning and growing, but I also love growing companies. And and the key reason that I became a venture capitalist was because I was having a ton of fun as an adviser to venture backed startups. And that was after I had been founder and CEO of my own company called couchsurfing.com, which is a global travel website. And and I I learned a lot of lessons as a as a founder. Couchsurfing, by the way, has raised $25,000,000 from from Benchmark Capital and General Catalyst and Nunlow Ventures and Point Nine Capital and some other folks.

And and so, you know, we we did a number of things right. And and candidly, we I made a bunch of mistakes along the way. And after that experience, I wanted to share my learnings with other founders and help them grow and avoid the mistakes that I had made. That was a lot of fun for me to be that kind of coach. And so I was taking on these advisor roles while I was working at big companies like Concur, which was publicly traded, and even Symantec, also publicly traded.

But my hobby was to work on on helping founders. And my my wife said to me, well, you know, why don't you just become a full time adviser? I was like, well, I don't know if I can make a living as a full time adviser, but it turns out that as a venture capitalist, founders tend to listen to you. Maybe maybe because they just have to, you know, to get to get your money. But at the same time, it was being a venture capitalist has always been an opportunity for me to contribute and and hopefully in a positive and constructive way always to to help these founders grow both personally and also their companies grow in in all the domains and and tackling all the challenges that that companies face.

Todd Gagne:

I'm curious on just that transition from founder to adviser to VC. What are elements of that you think that you've had to kinda tweak along the way to basically be good at each one of those? Right? Because I think, the founder role in a lot of cases is a lot more operational. You know, a mentor guidance is basically looking for areas that are maybe blind spots and helping them scale or, you know, pinch points that they have problems with.

And then, you know, the VC lens is is really a combination of those things, but it's got a much more financial and fiscal bent to it too. So I'm I'm curious on as you've pivoted through those things, were there things that just worked out easy? Did the skill adaptation kind of come naturally for you?

Dan Hofer,:

Yeah. Well, I mean, some of the some of the easy things are are, you know, sharing your network. Right? You know? So you over time, you build up a network of of of investors and and service providers and, you know, good people to work with.

So so, you know, that that's always applicable whether you're a a founder or an adviser or a VC. But but as a as a VC and as an adviser to multiple companies, you start to develop a a pattern recognition engine and and start to see themes and and patterns. And so I I feel I I personally feel that now having worked with, you know, dozens of companies over my lifetime, been on, you know, over a dozen boards, that I'm frankly, I just have a more valuable perspective than than when I was just getting started and Sure. Only work with a couple. So at this point, you know, I've I've seen, you know, for example, one one trend that I've observed sometimes is certain profiles of founders really love to build.

And and you can see it oftentimes in in their board decks, what they choose to talk about. They they they talk about in in great detail the products and and Yeah. And they'll go into, you know, the individual costs of of individual features, which is not really a board level discussion. Right. Right.

And and I've also seen some of those same founders simply avoid the discussion about revenue and sales pipeline. And and so you you start to notice these patterns, and you're like, oh, you know, this is a this is a builder kind of founder. And and this person, you know, that's great because, obviously, you need a product in order to have a company. But at the same time, you also need a a strong sales orientation so that you can have revenue, which you also need to have a company.

Todd Gagne:

Yeah. I think in preparation, we were talking about just maybe your skills in evaluating leaders and decision making. You kinda, like, hinted at some of this, but is there more of a a like, a philosophy or some guidance on on that as you've kind of accrued all this information, you've seen some of this pattern matching. You've given it a good example of somebody who is deep in product, maybe somebody who's not as strong in sales, but is there other trends or other ways you evaluate founders, especially from the VC perspective?

Dan Hofer,:

Yeah. I think I think the you know, most people have a vision for, you know, a product. That that's what get gets them going. Yeah. But but sometime some founders are light on their go to market capabilities.

Sometimes they can imagine a go to market path, but then they don't, for example, do the financial analysis around the customer acquisition cost Yeah. Because maybe they're small sales and and one person, maybe even the CEO is pursuing a lot of small sales, but they don't run the numbers to say, okay. Well, that's actually not going to cover the cost of the sales at scale. And and so there's kind of a a go to market gap. So there there are a bunch of different, you know, kind of patterns and things you look for, you know, certain certain, obviously, CAC LTV ratios are are pretty well known within the industry, but also thinking about, you know, help helping founders think through in detail.

You know, what what are the what's the cost of your Salesforce? What what are what sales approach are you taking? How much are you doing directly versus indirectly via channel sales in some cases? And and helping them run that analysis is something that some founders can do, but but a lot, need some need some help with.

Todd Gagne:

So one of our philosophies is no black boxes. Right? You don't need to be an expert in a lot of these areas, but you do need to have a working knowledge of all of them. And, you know, it's interesting because some people will come in and they'll have a super strong technical bent, and getting them to, like, understand the business becomes a challenge. And then you have other folks that are basically like, I'm a product person, but but I'm malleable enough to understand what goes on in dev, I'm malleable enough to listen to what goes to like, what I need to do from a go to market standpoint.

Any insights on on how how adaptive or how you help people get more well rounded when they have a super strong area and they focus on it, but then sometimes there's an a propensity to kind of overpronate and saying, this is what I'm really good at and I but yet, like, my business is gonna die if I don't have a strong go to market strategy.

Dan Hofer,:

Yeah. Yeah. Well, one of one of the sayings that that people have in in the venture industry, which I'm I'm sure you've heard is, you know, invest for strengths, not for lack of weaknesses. Yeah. And so it it's fine if if someone is weak in an area so long as they are prepared to hire to augment their the team's capabilities in that area.

With my investor hat on, which is a little bit different from my adviser hat, with with my investor hat on, I'm I'm looking for people who are really extraordinary in certain areas. Mhmm. And then and then I'll I'll and then the question is, are are you open to hiring somebody else who's extraordinary in areas where you are not as strong? Hopefully, answer is yes. And if so, then you can build out a a quality team overall.

Todd Gagne:

Yeah. I you know, I think we're in the Midwest, and so I think a lot of our stuff is pretty capital intensive or or pretty capital efficient is what we're trying to get to. And so, you know, we had a guy that basically started a company, and, you know, he probably did the first hundred sales calls. Technical founder. It was a technical product, so, you know, it kinda fell with the technical sales.

But, like, the growth that he got from understanding those sales engagements to, like, make the product better, but he also understood basically what he needed to hire for. And so I I just I think pivoting too quickly to just, like, I'm gonna outsource this and find somebody that's super good in this, I think can be a real mistake early on. And so I don't know if you've seen that too, but, like, we really caution people from saying, let let's let's you know, until you get some pattern with what you're seeing in the sales cycle, you gotta own it. You gotta own it when you're small.

Dan Hofer,:

Well, the the sales role is is a particular and specific role, and and I agree with you. A lot of a lot of founder CEOs look for that VP sales as an as an early hire, which is typically the the wrong move. Yeah. Because even if they are weak in sales, and some of them are, especially some of the the deep tech folks, they the the sales conversations are a conduit to insight into the customer. And customer insight is something that is, you know, super valuable and key and foundational, and the CEO should absolutely have that.

Even if they're not, like, the ideal salesperson

Todd Gagne:

Right.

Dan Hofer,:

The the the process of talking with customers and seeing what resonates and what doesn't and all the nuances of those conversations is absolutely critical. So so over time, you can you can hire for a VP sales. Probably, you know, series a stage would be Yeah. Think the earliest where where that makes sense in most

Todd Gagne:

cases. Yep.

Dan Hofer,:

But but in other areas, you know, product or or or partnerships in some cases, engineering, you know, you can augment your your skill sets with with a key hire earlier than the series a.

Todd Gagne:

Yep. Totally agree. So maybe let's pivot a little bit to kind of like angel investment and the roles of advisors and that I mean, I think I'm kind of curious on, it sounds like you've done some of that. It seems like your fund is actually positioned for kind of pre revenue in a lot of cases. And so how do you evaluate some stuff when it's super early, right?

I mean, it's it's a it's a concept. Maybe they gotta prototype. In today's day and age, it's super easy to prototype something to at least get the concept across. But what do you really look for to make a decision on that? And what would you encourage people that are starting to raise money?

It's a very different environment today, at least in my world, from an angel investment standpoint than it was, you know, when interest rates were almost zero.

Dan Hofer,:

Mhmm. Yep. Yep. And and for me, my my lens and approach is a bit different as an angel investor and versus a professional VC. I'm I'm a little more risk tolerant with with my own money, but I'm also not really actively pursuing angel investments right now.

Yep. More focused on on my fund and and, you know, potentially some some advisory support. So but that said, you know, you you're absolutely right. You know, when when a company is just a couple people and a and a napkin, you know, the sorts of metrics that you dig into at a series a stage simply don't exist. It's it's all it's all about the the team and and the vision.

So at that point, you're you're evaluating the market and the team effectively. And and you can do those things. And and so, you know, on the on the market, you can look at the the players in the space, the competitive landscape, and and try to figure out how differentiated this offering is likely to be. On the on the team side, you know, you're you're looking for people who can scale ideally to, you know, people who you can imagine running a hundred plus person company, ideally a a thousand person company as you know, if if things go well. So, you know, I I always prefer not to replace the founder if if possible.

Yeah.

Todd Gagne:

How what do you look for then? Right? I mean, like, let's say it's two people. They've never done it before. What are some of the characteristics or some of the insight you get that says this person's probably gonna go to scale?

Right? Because I I always look at this and say, at the beginning, you're basically just doing. You're you're kind of a freak of nature. Right? You're creating create this vision, and you're doing a lot of it.

And then you kinda get a couple people, and then maybe you delegate. And then so there's this kind of continuum of kinda leadership growth that happens, but you don't get to see that from the very beginning. Right? What you're really trying to get was, can you actually get other people excited about your idea, and can you actually execute on it?

Dan Hofer,:

Yeah. Yeah. Yeah. I I think it's it's you know, there there are a few things you look for, and and it always helps. I mean, typically, some of my best angel investments have happened when I had started out as an advisor then gotten to know the team over time and you don't always have the luxury to do that.

But it's a preferred way to operate when you do. So I think, you know, tenacity, resilience and and hard work, you know, are are all absolutely critical and key and, you know, table stakes, frankly. And and obviously, you know, intellect, you gotta have smart people. You gotta have people who can talent. Yeah.

Yep. That's that's one of the most important things. So so one of the the mental checks, you know, that I I make is, you know, how would I want to work for this person? Do I respect this person enough that I I could imagine myself as, you know, COO reporting to them? Mhmm.

Because, you know, if if if I respect them that much, then probably other people will will also respect them that much. They'll be able to build a a quality team. And so so those are a few of the things that that I look for. Then, of course, you know, they need to understand the market deeply. That's that's the founder market fit concept.

Yep. And and have a vision for it and then simultaneously be very committed to their vision, but also receptive enough to feedback that they're willing to pivot and and not hold unreasonably to anything. So also showing that kind of, you know, intellectual flexibility and, and adaptability because things always change.

Todd Gagne:

So what do you think is, you know, with the role of kind of AI and stuff, it seems like, or at least our world, you know, it's being inserted into every step in the startup process. Right? From a from a good standpoint, I think, things that used to take us six months to a year now are starting to get crashed even further. MVPs are coming out in four to six weeks. And they're not something that's gonna be the Taj Mahal, but it certainly can get you something to understand, get it in front of customers, validate it.

And that's getting introduced at almost every step, whether it's marketing, whether it's aspects of sales. And so I'm curious about how this process, maybe from your standpoint in evaluation, has changed. Has the bar gone up about what people are expected to have at that level of kind of angel investment because of the tools are getting easier to and lower cost to actually get something out?

Dan Hofer,:

Mhmm. Well, I think I think the concept of AI will probably kinda disappear from from the the public discourse in in a few years. And and the reason is that, you know, I've I've been around the block long enough at this point that that I've seen, you know, as as as you have cycles come and go. And so I remember, for example, you know, fifteen years ago when mobile phones were getting popular, smartphones, and people were talking about a a mobile company and they were starting a mobile company. And now there's no such thing as a mobile company.

It's simply just something you do on your product road map. And so, like, likewise, AI, you know, a few years from now, I don't think for the most part, there will there will not really be any AI companies more companies anymore except for the most deep tech kind of AI companies. But otherwise, AI will just be everywhere. And so and as you said, we're we're starting to see that. And and people will not lose their jobs to AI.

People will lose their jobs if they become so inefficient because they're not using AI. But, ultimately, you know, AI will just be everywhere as as you've said. So so I I I think the the AI landscape continues to evolve, but in a way that makes it just totally ubiquitous.

Todd Gagne:

So maybe say I'll say something a little bit different and maybe bring it back to the original point. I just think it's a level up. Right? Like and I and I think what's interesting a little bit, Dan, is it's maybe one of the first technologies that I can think of in my timeline that basically benefits people with mixed experience. Right?

So the older you are, the more of an enabler it is in a lot of cases. Right? Because you understand where to go from here to here. There's all these steps. And what you're doing is you're plugging in all these elements to make sure it actually happens.

And so I'm curious, as people are younger and they're starting out with this, do you think that I I think that this level up is gonna happen with everybody. I mean, I think that's what you're kind of saying. And the people that basically just say, hey, I just wanna do a job and I want input and output, those are the people at risk. And so as it goes back to scaling and starting startups, don't you think the people that are starting to grab those and scale it that much quickly, I mean, I think that is the skill that will kind of enable you to have a great career or, you know, continue to be effective in this new environment?

Dan Hofer,:

Mhmm. Yeah. Absolutely. And and the art of prompt engineering, which which I think is is increasingly important, and and by the way, may favor some some younger folks who who just have the natural aptitude to to play with technology in a way that that older folks tend to do a little bit less of, you know, that that's that'll be a a key skill. But but, yeah, it's interesting to reflect on the ecosystem of AI agents that are emerging and how those are going to start to interact both with humans, which is the point, but also with each other.

Yeah. So you can imagine a bunch of AI bots having long conversations with each other, trying to convince each other of things. And, you know, it's a it's a brave new world.

Todd Gagne:

It is. Are you seeing any, like, technology that's you know, like, whether it's LangChain or some of these other things that are starting to be almost a workflow and and, you know, decision making engine? I mean, I think that's where things are going. I haven't seen a lot of people have a lot of success with it. But, you know, you feel like in 02/2025, we have all the tools.

We should be headed in that direction.

Dan Hofer,:

Yeah. I I think things like that are starting to emerge. It's it's interesting from a start up and investor perspective, you know, how important is something like revenue? You know? Because a lot of these technologies that there's not it it's kinda like, you know, in in in in crypto, you know, when when you're when you're having digital art that with with a unique digital signature, you know, how is there a ecosystem that truly supports that, or is that kind of a a speculative opportunity?

And and so, you know, how much can you actually build a solid company with with revenue and margins based on some of these technologies, or is the ecosystem not quite mature enough yet to accommodate something like that?

Todd Gagne:

So let's keep going on this thread. I know this wasn't kind of on our theme, but, you know, I guess we kinda think of, you know, a lot of development, at least short term development, could get commoditized over time. It's getting easier, and you're getting more throughput through engineers, right? So people that are full stack developers, you layer these tools on, they become more efficient. And I think what we're seeing even in the folks that we accept is a lot more verticalization, right?

So taking those problems and building applications with deep domain expertise. And I just I'm curious on It just seems like the tools are enabling smaller and smaller swaths of problems to go be solved. And if you have that domain expertise, then that is opening up a lot of different aspects. And so it's just crazy to me. Like, we had a guy that we just recently talked to, civil engineer in the construction industry.

His firm was tired of getting hit with some of these fines about water runoff from storms around construction sites. And so, you know, their Department of Natural Resources and their contractor, there's laws on the books. They come out and expect, and then all of a sudden, they're giving him fines. And so this guy's got, like, a whole design of what to go do, and you're like, okay. Well and that's different state by state.

Right? And and he was looking at Minnesota, and he was saying there was 480 municipalities in Minnesota that works. And you're like, cost $10,000? That's pretty interesting. And so I'm just curious if you're seeing more of that and if you kinda feel like some of the development components of this gets democratized over time as the tools get easier to build simple simple applications.

Dan Hofer,:

Yeah. Yeah. I think well, you know, the term vertical SaaS has been thrown around for for many years. Obviously, now it's it's a vertical AI enabled SaaS. Yeah.

And and in in many cases, the degree of differentiation and defensibility for an AI company is driven by the data the the training data that it uses and the access to data that the company has. That's that's arguably an increasingly form increasingly important form of of defensibility for for the entire company. And and so, certainly, you know, taking some some broad broadly trained and applicable AI engines and and providing them with particular data that's relevant to particular market niches can create some some outsized opportunities.

Todd Gagne:

Yeah. I think I I just I really believe that that domain expertise that's not sitting in a horizontal LLM is really the value. Right? And so if you can build vector databases with that in it, do inference training on horizontal, that's maybe an open source model, your cost can come down. You could probably simplify that quite a bit, and really, that's where the value, because it probably never gets put into the horizontal LLMs that are, you know, API driven.

Dan Hofer,:

Yep.

Todd Gagne:

And and I think, you know, you think about large corporations, whether it's Concur or Symantec or any of these other ones, I think that's the challenge for them over the next twenty years, right, is like saying, I have all this domain expertise and all these silos. How do I basically do that and then leverage it and then build tools for all the people across my organization to actually do it? And so, you know, that'll be the next twenty year cycle. You're already seeing Accenture and Deloitte do these types of projects. Right?

They're kind of on the tip of the spear doing it. But I think that is the differentiation where they start to amplify that, and it's just sitting in silos and and websites and stuff internally.

Dan Hofer,:

Yep. Yeah. I I agree with all that. And and the one thing they all have in common, and and this was this was really the breakthrough. The the in in some ways, the the mass market breakthrough of of ChatGPT was was the the language interface, you know, the easily accessible language interface that that everybody wants Yeah.

For for all sorts of use cases now as as the front end. So, yes, you know, the the power is is a combination of that, you know, easy to use front end ease of use and combined with, you know, the powerful back end integration with with proprietary training datasets and proprietary information on, how to how to leverage those datasets to to to drive business value.

Todd Gagne:

So do you think that OpenAI just becomes, more of a consumer brand like Google or somebody? I mean, they've got almost a first mover disadvantage, right, when you think about what happened with DeepSeek or any of these other ones where they're basically forging the way. It's an expensive process to go do it, and then people can kind of follow, use their model to train. And so, you know, having a consumer brand seems like you know, I I mean, I prefer Claude, but in but, know, the number of people that have used Claude in comparison to ChatGBT is is huge. Like, drop off is huge.

And so I'm curious on how you think some of these large commercial models, is it a good business? And then, you know, the amount of money they're talking about spending from a capital expense. And, you know, there's some questions whether how much incremental given the you know, we've talked about ChatGPT four, five, and five, and they're really struggling to get Orion out. Just, you know, is there enough incremental gain for the money we're spending?

Dan Hofer,:

Yeah. Well, there there's actually a a parallel that I've considered with the the database industry in the nineteen nineties. And so I realize I'm dating myself here, but

Todd Gagne:

That's alright. You're not on the same page.

Dan Hofer,:

You you remember those days.

Todd Gagne:

I do. Yes.

Dan Hofer,:

So if if you think about, you know, Sybase and Informix and Oracle as Yep. Corporates and then and then, you know, MySQL and Postgres and and so on. So you you see some similar dynamics of, you know, these large expensive corporate platforms and then open source opportunities as well today. And so if you're a new startup or a new customer of AI, you can choose which platform to use and some will go for that. You know, Oracle remains a big business.

Sybase and Informix, you know, obviously

Todd Gagne:

That's much.

Dan Hofer,:

So so there there is a there is a market opportunity to to have that, you know, commercial infrastructure and establishment on on the on the AI front, but but there's also an opportunity for some of these open source offerings to to build the followings. And then, of course, you know, just like, you know, Red Hat Linux, you can you can build, you know, commercial offerings around an open source foundation and so on. There's a so there are many different business models for for the ecosystem. With regard to, you know, OpenAI specifically, I think, obviously, there's there's a lot of brilliant people there, and and they they're very visionary. So I I wouldn't wouldn't wanna speculate on on their future, but specifically, but but you're you're right.

The the costs are astronomical to do what they're doing. And and and so I I think right now, we're at an interesting stage in the market evolution where people are it's still a a growth stage, people are not really thinking about margins yet. They're focusing you know, they're valuing companies based on top line growth and and and hype and excitement and things like that. And and so OpenAI's opportunity, which I'm sure they're acutely aware of, is is to expand beyond a, you know, just a consumer brand. And and, obviously, they're they're already building out lots of infrastructure for on the enterprise side, and and that that already exists.

But, but having, you know, private capabilities per enterprise to with proprietary training datasets, and and making it leverageable across, you know, many many, applications is, a big part of their future as well.

Todd Gagne:

Yeah. I'm kinda curious on if you have any thoughts to it. I mean, the one thing we haven't been talking a lot about in the industry is just the robotics angle of this. Right? Where, you know, I think when you take some of the mechanic robotics that we have today and and have that with an AI component of it, lots of things get interesting.

Know, there's a power consumption, there's batteries, there's a bunch of constraints that are there. But you would think that, you know, you look at manufacturing, you look at all the different applications, our unemployment rates, like our unemployment rate here is 1.8%, right? And so we don't have enough, we have so many jobs that we just can't find people to go do. And so, you know, there is going to be a replacement strategy with some of that over time and you think that's a huge opportunity for them if they're you know, they have the right models and solve those problems correctly.

Dan Hofer,:

Mhmm. Yeah. Yeah. You know, from a from a business model and investment perspective, it it's interesting to think about where where robotics makes sense to to replace humans because, for example, at at my previous fund, we invested in a a startup called Verdant Robotics, which helps with farming and and essentially, depending how you look at it, it either replaces farm workers or augments them. Yeah.

But but given some of the the farm worker dynamics, you know, many of them are not showing up to work these days. Yep. And so there's there's simply a staffing shortage. So at at that point, it's it's a great opportunity for for robots to to come in and and help, you know, harvest the crops or or spray, you know, pesticides or or whatever. And and so that that's a you know, when when there's a staffing shortage, robots make sense.

The other dynamic is, again, this is kind of from a financial investment perspective, depending on the labor cost of some of these workers, which which is not always that that high, it might, the the robots might cost more than than Yep. Actually, the workers doing it manually. Obviously, you know, I'm I'm talking from a very intellectual perspective, not not focusing on the human element because, you know, these are real people with real jobs and and, you know, it it's a it's a complicated topic to to think about replacing humans with with robots. But but again, with with the with the investment perspective, you think, well, you know, does it actually even make sense for that customer to replace humans with robots? Sometimes it does, sometimes it doesn't.

You know, there's some some a bunch of dynamics around it.

Todd Gagne:

Yeah. And I I mean, part of that scale though too, right? The the more they produce, the cheaper the per unit becomes. And so then more opportunities look cost effective. Right?

And so there's just a curve adopting that. And so it just seems like we're still missing some of these elements. You can only do and replace high end ones that basically make sense. And as more of the technology around power, batteries, AI comes together, you would think that there's an opportunity to solve more problems. And with production, the cost comes down over time.

Dan Hofer,:

Mhmm. Yeah. Yeah. For sure. Yeah.

Todd Gagne:

Yeah. It's just interesting. It's and it just seems like it feels like we're in early innings. And, you know, I I I always kinda joke. I mean, I think, you know, I'm 54, and so you think about the evolutions of technology over our lifetime.

Right? You know, it's like I worked on an Apple 2C. You know, it was my first program. That's what I programmed in basic. And, you know, I used Fortran 77 in college.

And then you think about the Internet, and you think about mobile, and and then you think about where we are today. And it's like, it's a pretty interesting fifty year period. Sure. And a lot of change, and it and it's cool to get to participate at at different levels. Really, you know, some of it you knew, and some of it you just accidentally stumbled upon.

Or at least that was my story.

Dan Hofer,:

%. And and I I also programmed in basic on an Apple two c Yeah. And and then an Apple two e. So Yep.

Todd Gagne:

Yep. Both of those.

Dan Hofer,:

As well. Yeah. But I I think, you know, go going back to kind of the the robot and and it's certainly a fascinating time in the last fifty years. Obviously, the the digital revolution is historic in its in its import. But but, again, even with robots, I think there's a dynamic of of training data as being, you know, critical and and foundational to to make a an AI driven robot successful.

So, you know, whether it's a a Roomba that's getting the lay of the land of your house or Yep. Or a autonomous forklift driving around your factory trying not to run over people. You know, the data that you give it is well, it makes a huge difference in in whether or not it it makes sense and will succeed in them.

Todd Gagne:

So you had some some I think you had a fund in mobility. Is that correct? I can't remember.

Dan Hofer,:

Yes. I I was a managing director at a mobility focused fund.

Todd Gagne:

Yeah. And so I'm just curious if you have any insight into kind of a lot of the autonomous vehicle discussion, whether it's Tesla or Weimu or, you know, like, I mean, there's definitely some competing technology approaches to getting to those. And so, know, and AI plays a huge role in that, right? And so, the self driving in a Tesla, I've never taken away mood ride that's independent, but those cars are running, I don't know, 200, dollars 2 hundred and 50 thousand with all of the LiDAR packages and stuff on By all accounts, it's a great experience, but that's not really a commercially available tool for me. But other people buy a Tesla and they're pretty excited, but that's a totally different approach where it's more software oriented and all the millions of miles that are coming into it.

And so I'm just kinda curious from your perspective if you have any insights or thoughts on who wins in that model.

Dan Hofer,:

Yeah. That's a good question. Who wins in that model? Consumers win in that model eventually. Yeah.

You know, it's interesting because we're in 2025 right now. We were all supposed to be driving self driving cars, you know, five years ago.

Todd Gagne:

Yep.

Dan Hofer,:

And and the the suite of technical challenges have been much more complex than than anyone expected. And and some of it is related to there's a whole bunch of things that have inhibited the mass adoption of autonomous technology is just one of them. Regulatory is is a big one. The the patchwork of of regulatory framework across The US that determines where autonomous drive cars can drive and when where they can't. In some cases, the connectivity dynamic because, you know, people always thought that five g was going to be the the huge enabler of autonomous driving cars.

The problem is five g does not exist everywhere in the country or everywhere in the world and so if you're an automotive manufacturer you know you need to build cars that can drive just as well and you know rural Alaska as in you know Downtown San Francisco. And so that that's been that's been an element as well. I think, you know, in terms of who wins, you know, at at scale and and eventually, like I said, obviously, the the the consumer wins, but but, you know, there is certainly a a place and and room for self driving cars. There are, of course, the nuances of different levels of of self driving cars, you know, level one through five and and as as as you as you work up that ladder, it it gets more and more and more complex. But I think the big risk from from an investment perspective is, you know, a lot of folks underestimated how difficult it would be.

And so they they invested into these, you know, even a billion dollars into a startup was willfully inadequate k. Yeah. For for for self driving technology. So, you know, I think, you know, some some of these companies like Waymo, you know, may may win the game in terms of, you know, market share technology. In terms of financial returns, it's not clear that they'll make a huge return on on the massive amount of money that has been invested into them.

So that that remains to be seen.

Todd Gagne:

So maybe more pointedly, I mean, do you feel like I mean, Waymo has taken like a hardware approach to solving the problem. And, you know, I would say Tesla in particular has gone more software, right? More data, more AI, more processing. And so do you have like a thought process on which one of those is better? I mean, it seems like in the short term, Weimu's doing pretty well and continue to expand, but it's got a high fixed cost where Tesla has a lot of data.

It consistently gets better. But the question is, does it get better to the point where you get autonomous four or five, you know, level driving?

Dan Hofer,:

Mhmm. Well, I I think I think there are many ways to look at it. And you mentioned earlier, you know, the first mover disadvantage in some cases, and especially from a technological perspective. You know, Waymo pioneered the way and and and the risk is that they now have, you know, legacy tech in in certain areas, and and they're, you know, bogged down by that, you know, tech debt effectively. And so so again but but they're also building the most mature and robust product on the market.

So so it just depends how you look at it. Yeah. So maybe they're winning from the customer experience perspective. Are they going to win, you

Todd Gagne:

know Financially.

Dan Hofer,:

Financially or returns to shareholders? Not necessarily. Yeah. You know, Tesla has been more more gradual in this adoption and kind of, you know, self funding along the way which which is, you know, good from a, you know, capital perspective. So, I mean, they're they're just there there are many ways to look at that.

The question of of who wins. But but like I said, ultimately, the consumers win because everyone continues to compete to to make us all To get there.

Todd Gagne:

So how long do you think this takes? I mean, is it another five years? Is it another seven years? Or no idea?

Dan Hofer,:

Well, it's gradual and and and my apologies if it seems like I'm kind of nitpicking on the question. But, know, if if you're if you're looking to drive in an autonomous car, you can do that today in Downtown San Francisco.

Todd Gagne:

Yep.

Dan Hofer,:

So in that sense, we're already there. If you want to drive in rural Alaska

Todd Gagne:

We're a ways away.

Dan Hofer,:

We're a ways away. Yep. And then there's the regulatory piece and the technological piece and then also globally, like, you know, I'm not sure if you're talking about just US or or globally. So they're they're just a and and for example, you know, navigating the streets of India is a very different experience.

Todd Gagne:

Different experience. Yeah.

Dan Hofer,:

You know, Google Maps doesn't really work there. There there are no addresses in some cases and and there's just a lot of chaos.

Todd Gagne:

Yep. Which is No lines on the road?

Dan Hofer,:

Yeah. No lines on the road. Yeah. So I think things like that. They're a bunch of corner cases that we don't deal with.

So, you know, the the companies that are pursuing this market have with with the possible exception of China, have been designing it for kind of a a US kinda infrastructure, but obviously, The US is just one of, you know, 200 plus countries.

Todd Gagne:

Yeah. But but the the

Dan Hofer,:

OEMs are thinking from that global perspective. You know, they're they're trying to make that one car that that can operate, you know, as easily and, you know, the the Toyota Tacoma can can go in, you know, the deserts of Egypt or or, you know, Downtown Minneapolis. So the OEMs would prefer to have that that one skew if possible.

Todd Gagne:

Yeah. Maybe one more comment on this. It's just interesting. You get into a Tesla and it feels like it was developed around the software and then the hardware, whereas a lot of ICE traditional Ford, GM, whatever it happens to be, they're basically bolting on software. And so to me, that's the inflection point.

I mean, you think of BYD or any of these other ones, I think they're taking a very similar approach. And so I have some concerns on, like, some of the tariffs and stuff. You know, if we can drive more innovation to get more closer to that, that experience over time, it seems like it's the right thing to do from a consumer perspective versus protecting an industry that maybe has been slow to adopt some of these new technologies. And so it'll be interesting to see. Mean, it's a fascinating space and there's a lot of evolution to it.

Elon, to his credit, he designed something that is, we haven't had a new car company in, what, one hundred years. And so I think whatever you think of him outside of those endeavors, that's still pretty impressive.

Dan Hofer,:

Yeah. Well, I I think definitely, you know, his vision of a a software driven car Yeah. Which as as you described is is is defined by software and not the hardware, was was revolutionary Yep. And and distinctive. And and that was, you know, the vision that I think a lot of Tesla's early investors bought into.

Yep. The know, because because it's it's not just another car company.

Todd Gagne:

Yep. Okay. Let's pivot away from AI and and some of this stuff. I I appreciate the tangent with me. You know, you've written in the past a little bit about just rightsizing kind of capital runway and just kind of understanding your kind of inflection point in your company's kind of evolution, how much money to raise.

So maybe talk a little bit about that because I think that's an interesting one. I think I think there's a knee jerk reaction in a lot of entrepreneurs. I just gotta go raise more money, raise more money, raise more money. And, you know, I mean, I think sometimes they don't think of dilution. They don't think of, you know, like, if it doesn't grow as fast and and you've got, you know, all these terms in your in your term sheet, it can really bite you.

And so maybe explain a little bit more about what you think about that from a rightsizing of of capital in your runway and just kind of lessons to be learned there.

Dan Hofer,:

Yeah. Well, in in my in my experience, founders do tend to think a fair amount about dilution in most cases. Sometimes sometimes too much about dilution because because they're trying to maximize their valuation Sure. Which is not not always the thing that they should be focusing on. It's it's dangerous to maximize valuation in in many cases.

Even when you can, you you shouldn't necessarily because you're you're setting yourself up for for failure down the road and and a down round which which is unpleasant for everybody. Yep. And, you know, they they they say that sophisticated founders will will look at will focus more on the terms than the valuation and their governance dynamics and and things like that. But in terms of the runway optimization, capital runway, you know, there there's this kind of conventional wisdom that you should raise eighteen months of capital. And I've always kinda questioned that and and thought to myself, oh, why why eighteen months?

What's what's magical about eighteen? Sometimes it's eighteen to twenty four. You know? But but still these numbers seem arbitrary. And and really the the point is, you know, obviously, founders don't don't wanna give away any more of their company than they have to.

And and my my advice, and and I wrote an article for for Forbes about about this, is to to to think about where where the inflection points of the value drivers are going to to occur in in the evolution of the business. So if you are if you have, you know, a year of of runway and and you can you can you can close a big sale, you know, six months in, then at that point, after that six months or or maybe a a big partnership or or maybe you've landed a key hire. You know, you've you've recruited Elon to be your, you know, your chairman or something. You know, events like that can can have a big impact on your valuation. And so so that's actually those events should be what drives when you raise money because at that point, your your valuation is just gonna jump up.

Otherwise, your valuation might kinda be flat for a very long time characterized by a big spike whenever something good happens or conversely when something bad happens. But but and, you know, it's easier to predict the good things, hopefully, than than the bad things. But in either case, you you wanna think about the trajectory of the business, what's likely to happen, and then try to structure your fundraising around those those individual points in time where a massive change in value is taking place.

Todd Gagne:

So do you think there's enough predictability in a lot of that? I'm sure you're just like I am. We deal with a lot of optimistic investors, right, or entrepreneurs, right? They basically think they're gonna get more green lights than they necessarily do. And so, you know, I think, especially if you're young and you've never done it before, I think that's, you know, you look at this and say, here's a huge TAM that I can go after.

I've had some early success. This is just gonna go to the moon. And and it's hard to talk them out of that. And so I'm kinda curious about, like, how do you how do you do that? Because I in in theory, it makes really good sense.

In practicality, I I I guess I'm just thinking through a couple of examples that I probably would have struggled with them.

Dan Hofer,:

Yeah. Well so I I mean, I agree with you. You know, life is not predictable, and and startup life especially is not predictable. And founders have to be irrationally exuberant.

Todd Gagne:

And That's why they get into it.

Dan Hofer,:

Yeah. Yeah. I mean, you know, no no one would no one would be a founder if if if they You

Todd Gagne:

can't change the world? I'm not doing it.

Dan Hofer,:

Yeah. Yep. Yeah. So, you know, founder founders are a certain breed of of people who are supremely optimistic and and self confident, and and you need that. Yep.

That's that's necessary even though it it can also kinda get you into trouble. And and, absolutely, some things are impossible to predict, but some things are possible to predict. And for example, if you're working on a partnership negotiation with a big company, that that might be a six month negotiating process or or or a major sale or your first pilot or something like that. And and then imagine there's a, you know, two or three month pilot, and then and then you're expecting that a a much larger contract will get signed, you know, after that pilot completes, and you figure that contract will take a month to negotiate. So so now you you're looking out four months and assuming it goes on track, then you're like, okay.

Well, at that point, the value of my company is gonna spike as soon as that as soon as that closes. So you can start to time your your fundraising around events like that. Also key hires if you're if you're recruiting a high profile, you know, member of the c suite Sure. Maybe even a CEO, you know, that might also take six months. And so things like you know, some things are not predictable, but some of those things, I think, you know, are predictable.

Todd Gagne:

And so I I that totally makes a lot of sense. So maybe put it in the context, though, what does that mean for when you raise? So, like, you get to these inflection points. Are you basically raising enough capital to, like, get you to the next one? So if the eighteen to twenty four months is kind of arbitrary, are you really trying to just fundraise in between these major events with some sort of, you know, margin of safety?

Dan Hofer,:

Yeah. Yes. Yes. I I think I think that's the right way to look at it. And and you're you're basically raising from one inflection point to the next inflection point.

However long that might be. Maybe it's eighteen months or or maybe it's not. Maybe it's more or less than that. Yep. But but, yes, from one inflection point to the next and taking into account also that it will probably take six months to race Yeah.

Depending on which round you're looking at and market dynamics and and so on. Yeah. Things that are specific to your company. But but, yes, you you need to take into account that conservatively, say, six months just as as that margin of safety so you you don't find yourself with your back against the wall.

Todd Gagne:

Yeah. You don't want that. That's not a good spot to raising capital. That's for sure. Well, good.

I mean, we've taken almost forty eight minutes out of this. I guess I'd try to wrap it up a little bit and maybe give you an opportunity to talk a little bit about your fund, Deep Venture Partners and kind of maybe what you guys look for, kind of where you are from a in the process of of, you know, what type of maturity you're looking for and the type of projects.

Dan Hofer,:

Yeah. Yeah. So Deep Venture Partners is is focused on pre seed to series a investments. We have a we have an affinity for deep tech as well as marketplaces and and consumer. And we my my cofounder of the fund was a former VP of AI at at Meta.

Okay. The founder of Google Street View, and and so and he's got a hundred patents. So, you know, he he's, you know, well suited to evaluate AI deals as as well as, you know, across multiple of of industries and and verticals because as as we've seen depending on the training data, AI can be broadly applicable. So overall, you know and and then we also have an advisory board with professors and key scientists from around the world who help us look at deals as well. So right now we're interested in those kinds of sectors and, you know, we're a young fund, but excited that at the opportunity because there's there's a lot of overlooked potential we believe in in the university ecosystem and it and and I personally enjoy investing at an early stage.

Sure. And some people are are better late stage investors. I personally feel like I'm a better earlier stage investor, and and that's also happens to be where where the most upside is.

Todd Gagne:

Yeah. That's good. Well, if people want to get a hold of you, what's the best way to do that?

Dan Hofer,:

Yeah. Through through through my website, deepventurepartners.com Okay. Or or deepvp.com. They both work. They go to the same place.

Okay. And my my email address is dan@deepvp.com.

Todd Gagne:

Okay. Well, Well, Dan, I really appreciate you taking the time to do this. This was a fun conversation. We covered a bunch of interesting topics that I think are relevant, and I appreciate just kinda sharing your wisdom.

Dan Hofer,:

Yeah. Well, it was a lot of fun to to chat about it, and and thanks so much for the invite.

Todd Gagne:

Okay. Sounds good.

Dan Hofer,:

Take care. Thank you.