Todd Gagne:

Mikey v. It's good to see you, brother.

Mike Vetter:

Todd, it's good to be back.

Todd Gagne:

Yeah. It is. It's been a while. Yeah. It's been a while.

So it's nice to have you on the podcast as we're kinda close out the year. And, it's it's been a busy 12 months. There's no question about it. So

Mike Vetter:

12 months, you've been busy, making content, so it's been fun to fun to see that.

Todd Gagne:

I have. It's been good from the standpoint of, I probably gotten a little bit more religious about writing, and then not writing just, simple stuff. I think, you know, as the year went on, I think just getting into the practice of writing a couple times a week, I had never done that before. I'm not a writer, and I think over time, figuring out how to do that and then adding higher quality stuff. And so I would say, you know, it's getting better.

I think finding topics and then finding stuff that's interesting has been good, but the response on SubSec has been really positive. I mean, I think we're we're definitely growing. You know, we started this thing at the beginning of March, I think, and I think we're up to, like, 84100, you know, subscribers on the on the substack. So that's pretty cool. And I think you were looking at some of the stats over 250,000 views, for the year.

So, that's pretty cool. That's how I've had it.

Mike Vetter:

Year. Those numbers are more than 10 x what they were last year, Todd. So what a and it's just great to be able to help founders, not only founders that are in our program, but one of the things I've noticed is just the number of founders who are engaging with our content that are at various stages in their build process and are running into some of the same issues. And it's been really validating to see some of those things turn into real, products that are that are growing in the market.

Todd Gagne:

Yeah. And I think just the network of people you get to meet, which is kinda interesting. You know, I've met folks from all around the globe, that have reached out as well as people domestically and just building some new connections. And so, it's probably one of the better things personally I've done is just writing online. It's, it's it's you gotta you gotta put yourself out there.

And, but once you do, it's it's been kind of interesting. So that's been positive. You know, we probably weren't as consistent on the podcast as I would like. We didn't get as many. And so, again, I think the theme of this whole discussion is really using AI tools to basically accelerate some of the work that we're doing.

I think, our team has done a great job of helping me, a, find people to to get on the podcast, vet them as far as, their their ability to, like, really add value to our, audience. And so I think we've had some really good successes where somebody sends us an email, and within 30 minutes, we can tell them, hey. Do you wanna get scheduled or not? And so that's pretty exciting for me as we go into 2025.

Mike Vetter:

That that's an example of, like, a 10 x improvement. Right? I mean, if you look at the amount of time you pick up to find a podcast guest, reach out to them, I mean, it was more than 10 x. And, it's amazing how you can go from no podcast to a podcast to improving the speed by 10 times on, on on adding guests. That's amazing.

Todd Gagne:

Yeah. And maybe we just, like, took 2 seconds to, like, talk about, like, that workflow because before somebody would I mean, we were getting inquiries, you know, maybe 5 to 7 a week of people that wanted to be on the podcast. That's flattering. But on the flip side, are they a good fit for us? Right?

And so I think the next thing I have to do is I go listen to a bunch of podcasts. I gotta go watch, a YouTube video or something that they're on or look through their social media, and that just takes time. And I don't care if it's, like, listening or if it's, reading a script. Like, it just takes time. And so now I think with their process in using LM, notebook LM from Google and basically putting all that in there and then doing some queries, very quickly, you can find, is there a good fit and a match for some of the unique, experiences they have, and does it fit for our clientele?

So, like, just that and the tools that we've been using, has made a huge impact. So, appreciate, you know, Priya and the team for this doing this.

Mike Vetter:

Yeah. You bet.

Todd Gagne:

So, you know, I've been pretty busy, but you have been busy busy as well. I mean, I think, we've added some full time staff. You wear multiple hats. But, like, what would you say are some of the things that you've really kinda focused on, as being key to kinda growth for this year?

Mike Vetter:

Well, one of them is actually just really in line with what you're talking about using AI in in some of the the front end stuff that you're doing. We've been putting AI into, almost every corner of our program from generating content that uses best practices to actually assisting founders with using AI, throughout the process. So even right at the beginning, before they even get into wildfire, we're we're doing differentiation analysis using AI to help them to make sure they have a highly unique idea. And then once they get in the program, you know, no longer do they need to design screens with, you know, one of those WYSIWYG editors where they're dragging buttons on the screens, but using, using AI to to generate layouts, to using AI to build their apps. And then once you get into go to market, it allows, founders to much more rapidly iterate on their go to market content and then test different messages in the market.

And so, you know, AI is not only in the products that our founders are building, but it's it's worming its way into every aspect of how they design, build, and launch their apps. And, it's something that, you know, I think we're really on the in the early stages of right now. And the the the speed at which we're able to evolve the wildfire program to help founders to use AI as they build and how they build is becoming, I think, key because I think speed is everything when you're doing a start up. And, you know, saying to a founder, go use AI without embedding AI into every step in your process, I think, is a real missed opportunity. So I think, you know, even a year ago, I I sort of didn't see all of the different places that we could add AI into our process, and it wasn't until we started to experiment with every single piece of our process embedding AI into it do you realize how much faster.

And there's there's multiple things that are 10 x faster when you when you look at using AI to make them happen.

Todd Gagne:

Yeah. And I would say it's not perfect. You know, for a lot of our stuff, it's okay. Like, I mean, even some of the stuff we're doing, you know, whether it's social media or marketing messages or any of that sort of stuff, I do think that and it's only gonna get better. Right?

I mean, I think that's the part is this is the worst. We're probably gonna see it, and it's gonna go forward. What I think is interesting too is we're stitching a lot of stuff together where I feel like we're you and I keep talking about, like, we need a framework to hang all this stuff off of. Right? Where it's like, you know, there may be 25 things in our business that we want to automate, and we can use these tools to get better at it, but stitching them altogether so that they go from, you know, like, you know, step 1, step 2, step 3, and there's some workflow and there's some Boolean equation or there's some if then statements in it.

Like, that stuff is hard today, but you would hope in 2025 we'll see more of that being stitched together or frameworks that'll allow us to do that.

Mike Vetter:

Yeah. And and and just the the chain reasoning, you know, technology is pretty young. I mean, you saw Yeah. Try GPT add that this year, but, you you know, it's it's still pretty young. So I think combining that chain reasoning with some of these workflow layers and even just having AI agent to agent communication, figured out, there's a bunch of attempts at doing that right now.

A lot of them are still academic. Yeah. When you start to see those turned into real frameworks where you can plug in APIs to them, I think a lot of that stuff will get smoother. So it it's exciting to see, like, all these sort of desperate things we're doing in our process come together into one automated process. I think that's gonna be essential for founders to build into their businesses early on as they scale because it allows you to scale with a lot less friction, because you can scale a process without having to add people to it.

And help, they just get increasingly difficult. I know some people are worried that, you know, AI is gonna remove, you know, jobs, but I think it's gonna create tons of jobs because, you know, you gotta go figure all this stuff out. So I think that's pretty exciting too. So on on that note, the second big thing we did this year is we added masterminds to our program. We've

Todd Gagne:

Not AI. Not AI.

Mike Vetter:

Not AI masterminds. Not AI. You there's there's a human element of this that is super important. And so a lot of why we use AI so that we can spend more time with people because, our founders are at the center of what we do. We've just seen over and over and over that, entrepreneurs helping entrepreneurs is just us.

And so masterminds are way another way that we've added where every 2 weeks, founders sit down with other founders that are in the exact same build stage that they are. So, whether they're in customer interviews, build, go to market, or scaling, getting into a group of of other founders who are, you know, really trying to master those same problems has been, super rewarding because it allows us to knowledge share in real time, and I think it's helping us make the program better, faster. But it's also allowing founders to, learn from one another and their own strengths and weaknesses. Every founder has a technical background, a product background, or a sales background, and these masterminds are giving founders a community where they can grow in their areas of weakness and also share best practices. Todd, you've been involved in that too.

So it's been fun to see your mastermind that you've been building to, you know, start to see some of those companies really grow. So you've got some founders that are starting to really hit it, in in your your mastermind. So tell me a little bit about that.

Todd Gagne:

Yeah. And maybe just add a little more color to it too. I think, every founder knows that there's just 50 number one priorities. And I think what we're really trying to do in the mastermind is say, what is the 1 or 2 thing that you really need to do? And I think sometimes it's not always clear.

Right? It's not always clear that saying, you know, like, I got tons of things coming at me. Are am I picking the right things to focus on? And so I do think that's part of what the mastermind is able to do is to create some focus on the most important thing and then some muscle gets us a memory of, like, just executing. Because if you did what you said 2 weeks ago and it was the number one priority, you're going to make traction in your business.

And if you start compounding that after 1 month, 3 months, 6 months, lots of positive things happen. And I think that's where you just basically started. Right? Like, it's like we've got a bunch of founders that are in our program, in the mastermind that are starting to progress. I think you said something to the effect of we've probably gotten 10 different states, founders from 10 different states in our program this year, which is great to hear.

I mean, it's not just a regional South Dakota type of thing. It's about getting more people from more locations to come to South Dakota to build, which is exciting. And then, you know, like, we've had, companies that graduated fairly recently, like Journeyman, local company, in the wildland fire space. So very nichey. But on the flip side, they have a ton of domain expertise.

These are guys that have been doing it. And I think they're kind of, some of the demographic we're looking for. Right? You don't have to have a ton of product ex or, you know, development experience. You don't have to have a ton of sales experience.

They're just good people that understand, a problem and that domain expertise deep, and they're able to bring a bunch of expertise into, what does my industry really need? And we can wrap some of the tools around them. And so it's exciting to see them go from graduation to now I think they're about a 1000 users on their platform. And so, you know, that that's pretty cool that we're seeing some of that stuff come together. I think there's a theme.

You know, these masterminds, at least in mine, from a go to market standpoint, are going from 0 to a 100000, a 100000 to a 100000, and a 1000000 to 3,000,000. And what you're finding is if you're in that 0 to a 100000, there's some serious same core problems that you're facing, and it's really just trying to find that first handful of customers. And so optimizing the tools and the experiences, and the talk track around that to focus on it is basically creating, better execution on getting your first 25 or 50 customers or whatever it is in your in your industry. So I think it's it's pretty cool. We have another one in sign up sports.

That was one of our early ones that came through our program. They're starting to raise capital. We have, AgSense is another one that's that's raising capital, and they're all getting ready for a growth in, in scale in 2025. And so that's pretty exciting to see. This is not about, us finding people.

It's not about them getting through the program. It's about them generating revenue and really creating some real jobs in our local community.

Mike Vetter:

So so one thing to note, we we did this last year about this time, and we were we spent all of our time trying to figure out how to get them through the program. There's, like, a different set of challenges here we're talking about here because I think that part is largely checked out. Right? If you if you do the work, if you go through those stages, you can get a product with a market where customers are gonna pay. But now we're talking about a different set of problems, which is how do we get those customer those companies that are really starting to to scale up to that $1,000,000 mark quickly?

And we're really trying to compress time with that. Todd, have you seen some changes this year in those companies that have helped them to get to that $1,000,000 faster based on some of the stuff you're working on with them?

Todd Gagne:

Yeah. I mean, some of it's a continuation of what we preach in the program. Right? It's, really understanding your customer, ICP. It's really picking a beachhead and doubling down on it.

It's, also about running a series of experiments around marketing, about how to reach them, what's valuable, and, you know, and not about spamming them. You know? I think almost every single one of the customers, people that we come in is like, you have to add value. If you're going to send email, if you're gonna call, you have to add value. And I think and it's and then again, the second piece to that is you're not throwing up on them about your feature set.

You're basically trying to discover what the problem is, and really validate that they have this issue so that then your your solution makes more sense. So I'd say those handful of things are very repeatable, very consistent in almost every startup that we touch in this kind of 0 to a $100,000 range.

Mike Vetter:

Yeah. I totally agree. I think that one of the things that I did wrong when I started my first company is I I I tried to anchor on the solution and on why my little widget was better than the other widgets, and I didn't anchor enough on the problem. And I think that the the most valuable thing that I've seen come out of that mastermind is, founders who are really defining the problem that they're gonna go solve, getting the customer to agree during the sales process that that problem is solved using their app, and then selling becomes easy. And so, I think that's been really valuable.

I think, you know, when when you start something like wildfire, you look at what are the problems that founders are gonna run into. And this is the one that it feels like solving it once you get to the go to market. Whether you use AI or other things, you have to do that. And if you do it well, scaling gets really fun. And and, specifically, with signed up sports, they're starting to do the beginning of figuring that out, and it's been just awesome to see them start to close business.

So it's been fun to watch.

Todd Gagne:

Yeah. And it's not as linear as we'd like to think. Right? A lot of it is, you know, these guys are just kinda going through the guerrilla warfare of, like, hand to hand combat. Right?

It's like, I don't I have some ideas, and I think of what messaging is gonna work. They're trying to use kind of a gate structure and anchor. They're trying to use some of the techniques and tools that we've taught them, but it's messy. And, you know, I think what you find is, you're trying a bunch of things, and you don't really get to some sort of, consistent methodology until 80% of the time, it works the same thing. Right?

Like, there's always some variation, but, like, you're start you have to get creative. You're saying that didn't work. Why didn't it work? Let me try something else. Or they're not returning my calls.

What can I do to, like, add value to them? And so I think a lot of what you're trying to do is just be scrappy. Be scrappy. Know it's a hand to hand comment. It's not some big go to market strategy.

It's basically understand as much as you can about this prospect, and then go figure out how to get one of them done. Because if one of them is done, then maybe they can give you a referral to somebody else. Right? And so and it's just this kind of chain reaction. So I think sometimes, founders come to us and they wanna, like, boil the ocean.

I got this, like, wonderful, go to market strategy, and you're like, okay. But you can put that aside for a second. You just gotta go find the first couple of customers, and then you can start to, you know, basically reapply your learnings to that go to market strategy as it scales.

Mike Vetter:

Yeah. The the number of experiments you have to run is way higher than you think when you do this. And the founders who run the experiment quickly and then get data back and then and then adjust and pivot their message are the ones who do really well. You know, trying to come up with some big monolith marketing plan and then run it for 3 months, it just doesn't work. Like, you can be the best, most prepared founder, but until you get out there and start talking to customers and running a marketing funnel, you just have no idea.

So that's been another valuable thing about the masterminds as well, have been to have a sounding board when you conduct an ex you know, you run an experiment, you do a marketing campaign, and your click rate is really high, but then your your or sorry. Your open rate is really high and your click rate is crap. Like, what do you go do? How do you fix that? And then having a place where you can go figure that out together has been really fun.

So,

Todd Gagne:

so, Mike, we talk a lot about, adding value in a sales process even if you're not gonna buy. What do you think that means? Like, I think it's easy to say. It's a totally different thing when you're starting out and you have no customers. You know, so you don't have a lot of collateral.

You don't have test cases. Like, what do you think, is a way where founders can start thinking about adding value so it doesn't come across as a spam?

Mike Vetter:

Well, I think with a lot of founders, they have knowledge of the market or the industry that they can share with their prospects in a way that adds value to them. So, you know, for example, how how do you run sports camps, and how do you grow sports camps at a high level? How do you market them? How do you, how do you build loyalty in your your parents and your schools around you? That's an example of of a best practice that is not necessarily hooked to buying an app, but you can share with your, you know, your customers in a way that adds value to their lives whether or not they ever buy your product.

It also invites a conversation to say, how how could it how could we help you do that better, or how are you interested in doing that better? And that obviously, if your solution is at the end of that or the best practice of how to go go build your camp system, that's an example of how you would do that. So, I think that you have to look at the value proposition from the customer standpoint. It's like, what is the customer's problem? How do I help them to begin to solve that problem, by giving them some piece of collateral or a survey or even a a tool that they could use for free, but it leads them toward the product in a way that isn't, like, pushy or salesy, but still kind of paves the pathway for a product to be really, really, you know, useful to solving the rest of that problem.

Todd Gagne:

Yeah. So I think, even if they don't buy, they learn something. I mean, I think that's the takeaway. And I think if you wanna learn more about that, I think the challenger sale book is a good one. I mean, I think, like, a lot of the principles that we're talking about are there.

I mean, we all get inundated by email. And if it's not something that's value add, I just unsubscribe. Right? And so I just I think you gotta figure out ways to do this in a creative way, even when you're just starting out. And I think, you know, maybe to build on your last point was, you you have a vision for how something should be done differently.

I mean, that's why you're a founder. Right? And so sometimes even a voice mail that's that compelling maybe is the thing, right, that people would say, alright. I'll give them a shot. Right?

Like, I just you know, we've been doing this the same way for a long time. Maybe there is a better way. Maybe I'll talk to them. And so just don't, underestimate the level of passion that you have and and trying to translate that to prospects.

Mike Vetter:

Yep. I totally agree with that. Alright. Well, let's take a step back, Todd. And, we we talked a little bit about AI and sort of what happened this year.

I I feel like 2024 is actually a little slower than 2023. So, you know, what what are your thoughts on that? Like, there wasn't a there wasn't a chat g p t, you know, generation that happened this year.

Todd Gagne:

Yeah. I mean, it's weird for us to say that it was slow, but I just think it's slow in comparison to 22 and 23. Right? You know? And so, I think the incremental gains in the technology seems like we're running out of data to continue to train and basically, you know, basically, make these models, continue to better.

I think we're finding less hallucination in some of these. I think the chain reasoning, component that you talked about, with 01, with ChatGbt from OpenAI is good. I think we're starting to see some computer vision stuff, from Claude, but a lot of it was, almost proof of concept. I mean, at least the computer vision component of that was kind of proof of concept. I don't think it's ready for prime time.

And so I guess what I'm starting to feel like is, and and as I talk to other people that have industry knowledge, these things are large, and they're and they're horizontal, and they've sucked up so much data. But, like, what's interesting is if you go into precision ag or you go into manufacturing, there is so much more domain knowledge that is not included in these large language models. And so what it's starting to lead, I think, to is this idea that maybe, we're getting to more vertical ones down the road. And I know you're gonna talk about this here in a second, but I just think that there's a movement from, these large language models that are commercial to looking at some of these open source ones, meta in particular, and then saying, how do I skinny these things down so that they're maybe, not as expensive to run, but then have more domain knowledge? And so I don't know if you feel like that, Mike.

I mean, it just seems like there's a there's a movement in this direction for a lot of them. But, like, what do you think from a verticalization standpoint?

Mike Vetter:

Yeah. So I think I agree with that. And what you see also happening is is the, you know, the big LLMs are sort of running out of data. You're hearing a lot of that. They're they're like, where do I where am I gonna get my next chunk of data to make this LLM better?

And they're so big and expensive to train. There's just a limit to how much you can do with that. But in verticals, there's a whole bunch of nonpublic data that is only understood and sort of used by people in that industry. And you can take a horizontal LLM, and if you verticalize it with data that's specific to that vertical and you combine that with the knowledge that those people have in that vertical of how a process goes. Now you go from an LLM to an agent.

And and that agent is, I think, way more valuable than just a horizontal LLM because you have that unique data combined with a really defined process that is a problem in that industry. And that that knowledge, though, is actually less technical, and it's a little bit more and I'll get we'll get into that in a little bit, but it's it's actually in the minds of the people who are in that industry that understands how that industry works and what the problems are. And I think what's what's gonna happen is I think this is gonna be bigger than mobile apps and bigger than a lot of the recent, you know, innovations because it will change how those industries work because there are fundamental processes that are in those industries that AI can automate in ways that you just couldn't do anything with with traditional technology.

Todd Gagne:

So maybe, like, I'll just use an analogy. Like, today, you can build a, open AI chatbot that basically is unique for you. Right? So it's got the underpinnings of the horizontal, and then you can basically say, I'm gonna make this chatbot, and I'm gonna do customer discovery or whatever we decide to do because we're adding a whole bunch of unique information specifically to it. So I I get that part of it.

But then, like, if you took an open source model, how do you vertical vertical vertically ize it in going forward and making, like, taking the same concept, where, like, do you have to change the weights? Do you have to do anything to, like, make it, efficient for the problem you're trying to solve and then optimize for a production environment?

Mike Vetter:

Well, I think it's gonna depend on the problem. I think some of it, you can just load up all of the data from that industry and use it as inference to put out, you know, more specific outcomes. And And I think that's sort of like a vertical LOM. Right? If you just add a bunch of data from that industry.

And we we do that already. Right? Like, the notebook l m example you were talking about. We we loaded in, like, what is our podcast about? What are we looking for for topics?

And so that's kind of an example of just loading some industry data into a a large language model, and now you've got sort of a vertical LLM. What I think is is actually more interesting is some of these chain reasoning and layering on, like, a workflow or boolean engine on top of an LLM with local highly, highly, specific industry data, and then use chain reasoning to to actually go through a process that a human would normally have to run, and then using the l l the LLM with that industry data to solve the problems. Like, I was just thinking of, you know, manufacturing production scheduling is this notoriously difficult time consuming problem where you have all this data for your work orders. You've got a whole bunch of information about who's, you know, available on the floor. And you take all that data, you put that into LM, and you say, okay.

I wanna, like, actually go through the process of scheduling work on my production floor. I think we're not that far away from having a a vertical agent be able to do production scheduling, which is an expensive, you know, job where people get it wrong a lot, and it changes all the time. And I think AI is gonna be a better solution for doing that.

Todd Gagne:

So do you think for us and Wildfire and the founders that we're having, we will continue to use commercially available LLMs and then try to verticalize them, or do you think that we'll end up start to use Meta and some of these other ones, and they'll you know, either we host it or they host it?

Mike Vetter:

I think I think at some point, our start ups are gonna wanna have their own, their own AI framework. So there's another kind of opportunity for innovation in the next 5 years, which is actually building AI infrastructure inside of a start up so that they're not necessarily going to need to subscribe to, you know, OpenAI API limit because I think that that gets really expensive. And, you know, some of the llama models, for example, are pretty darn good. You can run them on your own server, and you can load them up with some of your own data. And, you know, you've got your own AI infrastructure that scales really efficiently with you.

Todd Gagne:

Yep. Cheaply too. Yep. So that's good. Yep.

Well, I think it's pretty exciting. We're in a it it it just seems like we're starting to operationalize some of these tools, into kind of workflows and and and starting to build product around them, not a bolt on to an existing product.

Mike Vetter:

Yeah. And also not this vaporware stuff where people just build a chatbot and they load something in it and they call it a product. Like, there's real value, I think, that can be a lot. But it's gonna take a lot of discipline. So, you know, Todd, how do you feel like that's gonna affect our start ups in the upcoming, you know, years?

Because there's some there's some real trends, I think, that will make it you know, they can build faster potentially than they have ever been able to do before.

Todd Gagne:

Not potentially. It is true.

Mike Vetter:

It is true.

Todd Gagne:

So I think, you know, if you think about where, we were even a year or 2 ago, you know, we talk about an MVP, and we're talking about 40, $50,000 of of money to, like, go hire a dev team to full stack development, whether it's Microsoft, Java, or whatever you you you're gonna use. But you're it's gonna take you some time and some money to go do it. I think then we had this kind of no code, low code solution, and I think it got a bad rap where people were like, yeah. You can build something. It's essentially a prototype, and it doesn't test you know, it doesn't stand the test of time when you actually work with customers.

And I think we've even had some experiences, with, like, Journeyman and some of the other ones in our program where, that really hasn't turned out to be true. They've spent less than $15,000, to get an MVP, and then it scaled relatively well. And so, you know, if you can build an MVP for 1500 $15,000 and get a 1,000 customers on it, maybe that's a pretty good return. And I just wanna be super clear. Our goal is not to build the Taj Mahal with any of these tools.

I think what we're trying to do is say, we had in a series of assumptions. You did some market research. You validated with the client on what you're trying to do. Now we're gonna build you a product that is not the end all, be all, but it's gonna prove out, is there value in what your in the problem you're trying to solve? And so I think these tools are getting much better.

And I was, there's an there's an interview I did just recently with, a custom development shop in San Diego. And, basically, they're kind of, like, looking at it too, saying, they're they need to start building these using these tools to drop the cost down, and it's exactly what we're talking about. You build something to validate the idea. You validate the idea, get some generate some revenue, and maybe you end up rebuilding it on a more established technology stack that basically allows you to scale. And so you and I have been talking about, you know, do you use Flutterflow with some sort of AI engine on the front end to to do almost Figma like, prototyping, and then it turns into HTML and JavaScript for you?

Is there a middle layer with your business logic that's in, you know, build ship or some other tool? And then Supabase, for the for the database component of it. You know, really, it's just a Postgres component. So I think, like, we're the tools are getting easier to use. You don't have to have nearly as much technical knowledge, and I think the speed to market in validating your idea is getting shorter and shorter.

Mike Vetter:

So the other thing that's interesting about this is you're talking about low code earlier in Flutterflow. So the problem with these low code tools is that they they design, you know, decent front end logic. Right? But once you get into something complex or you have, you know, some specific business cases you need to go you you need to go abide by, they start their their user interfaces start to break down. So then you'd have to, like, hire a developer, and they'd have to fill in all the gaps.

And it was it ended up just being a, you know, a development project, plus you had, you know, maybe some low code stuff that doesn't look really nice. Well, the what's happening now is you can use AI to write all that intermediary code, and it knows the framework. Right? It already knows what the low code layouts are gonna be. So you can you can further compress time by doing all of the, you know, design work in a low code tool and then use AI to fill in all the gaps.

Yeah. And and now you've sort of compressed almost all of the sort of manual work of building out of the system. Now, again, we're in the early days, so there's a lot of, like, holes in this and problems in this. But you can see where this is heading. Right?

Over the next, you know, 24 months as these apps get better and more integrated, pretty soon, the the idea we're already seeing this where you can develop an entire app just using an AI prompt. There's a lot of kind of early pain points with that where it doesn't write good code or you can't do revisions without it falling apart. But, I mean, the the the sort of convergence of low code, no code, and AI is is just rapidly gonna remove some of the technical barriers to launching apps. And and and the time is just is falling. I mean and and it also it also is taking down the barriers to somebody who just doesn't know all the back end technical stuff to go and to go and build something like this.

Todd Gagne:

I think the other one too that you haven't really hit on is just code portability. Right? A lot of these no code solutions basically basically try to get lock you into a platform and an ecosystem. And I think what we've been talking about is these tools that allow you to rapidly prototype and then and then your code's portable. And so, and I think what we're trying to do is find a technology stack that has the maximum reuse, with more traditional enterprise type development tools.

And so, and I think that's a big part of this. Right? So if we can do that, it's not throw away and rewrite. It's basically port over and improve.

Mike Vetter:

Yeah. And you're starting to see startups that have tens of thousands, even 100 of thousands of users on these sort of, like, you know, low code apps because the infrastructure also scales so much more efficiently now. So it's and it's it's a good time to build. Like, I get jealous a little bit of these founders when I when I first started my first company. I mean, I mean, Todd, you and I were, like, working with devs and hacking away at some Bush league code that we didn't have any business writing for, you know, months on end.

Like, all this stuff now. I mean, I was playing around with Cursor, and you can, like, rewrite, like, 16 different files with, like, you know, a 25 word text prompt. It's just incredible.

Todd Gagne:

It is incredible. Yeah. Which I think brings me down to, like, the the the point of, what we look for in founders. And I think if I if I go back to our founding principles of of how we think about interviewing founders for our program, we look for people that are coachable, right, that want to understand a good idea. We talk about people that can execute, and, you know, not only once they have a good idea do they actually deliver on what they're saying because we think that's a good kind of thing.

But the last part of it is is always been about some domain expertise. So basically making sure that these people actually have some information about the problem they're trying to solve. And so I'm kinda curious. Like, it feels like that, emphasis maybe has changed in 2024, going into 25, but I'm curious on your thoughts on that, Mike.

Mike Vetter:

Yeah. So so I I would say that the domain experts are in the driver's seat, full stop. With all of these tools, we kinda talked about them when we were talking about AI and and low code and and also some of these other, you know, just ways of compressing time. The the technical piece of this is becoming less and less important to solving these vertical problems. So if you understand a market, you understand the problems that that market has, and you gotta have a little vision.

Right? But if you have some vision of how some of these new tools could be used to make life better at those companies, I think that you you you could be a founder of of a really high scale startup that can scale incredibly fast. And it it also takes the pressure off of some of those, nontechnical founders, the domain expert founders, to to know all of the technology and tools. And and we at Wildfire are able to help complement them with some of these frameworks, tools, methodologies that just rapidly translate that knowledge about our industry into the tech stack that can make that happen. It really takes the pressure off them to figure that out, and and and they don't need to build this big expansive dev team.

And that we've got founders like I think you you mentioned Journeyman who aren't necessarily needing to hire devs at all, getting to market into revenue and and in a position to raise before they even they even bring their first dev team members on, which is which is incredible. I mean, it used to be you couldn't even start a startup without at least a few a few developers.

Todd Gagne:

So that's pretty cool. I guess one of the things that, I if I was a founder listening to this, I'd be saying, cool. I'm it feels like we got the technology figured out, but what about the go to market? I'm a domain expertise. Does that mean, like, I need to be a sales guy and a marketing guy to go figure this stuff out because now you've figured out my, you know, coding solution?

Mike Vetter:

Well well, so that that's kinda comes back to a little bit what you're talking about with your your go to market, mastermind. So, you know, this this go to market, process and methodology is still the same sales funnel that it was, you know, that's always been. Right? People need to be educated on their problem. They need they need to get value out of the interactions that they have with you as as a start up, and then they need to see that your your problem your pro product will solve their problem.

What's different now is that a lot of those tools, you know, a, they're easier and more accessible, less expensive. And secondly, you can use AI to build a lot of those assets. So, you know, combined with, you know, better tools that we have at Wildfire and and AI to make those things happen, it it really does also compress the amount of time that you need to go to market and the amount of money you need to go to market. So I think the traditional way that a founder would raise money is they would they would go to investors prerevenue, and they would raise their 1st round of capital to go and and test their go to market thesis. What we're seeing is that founders are getting to revenue.

I think you mentioned, you know, where where a couple of our our start ups are at. They're already into revenue. And and at that time, they're raising money. Rather than raising money to go to market, they're raising money to ramp their go to market up. And so I think that it also means that the, founder who doesn't necessarily need to have all that expertise in sales and marketing coming to us, we can put that in as a part of our process and teach them those principles and then provide the tools to help them go make that happen.

So, you know, used to be you'd have to have those three things. Right? You have you have to have domain expertise, you'd have to have technical, and you'd have to have go to market. And now you really just need the beginnings of the first one, which is you you need to have the domain expertise, and then we can add those other two pieces as we go along.

Todd Gagne:

Yeah. I mean, I think maybe going back to your comment, it's never been a better time to be a founder. Right? The there's tools that we can put around you. If you bring that domain expertise, the technical parts, and the go to market pieces, there's things there's training wheels in both cases to help you scale, and let you focus on really solving the big problems in your business.

Mike Vetter:

Yep. So, Todd, we've got work to do with wildfire. So what happens next to us?

Todd Gagne:

Well, I think it's internalizing a lot of this. Right? I mean, I think we we talk about this. We see the trend lines, and then I think it's a lot of this is how do we build all these tools so that we can compress the time faster and faster and get people from business idea to revenue as quickly as possible. You know, Tamara is one that's come to our program fairly recently, And, you know, she's been in town maybe, what, 4 weeks, 5 weeks.

And so she's now running with her first customer and hopefully gonna have revenue by the 1st of the year. And so, I would love to, like, see that be more of the norm. We're we're we're seeing people crash the 6 month thing, and we can say we can do it even faster than that. But there's a lot of work for us to do to build these kind of reusable components, whether it's building more of the infrastructure in a technical standpoint or taking a lot of lessons learned that we have in the mastermind and basically making it and almost productizing it so that there's tools and and basically templates and, prompts and things that they can go do to apply and just kinda crash that so that they they don't make a lot of the same mistakes that you and I did.

Mike Vetter:

Yeah. And I I think a lot of this is going back to what you're talking about with just our value system of of running experiments, iterating really rapidly, incorporating our learnings. And that doesn't go for just our founders to live by when they build their start ups. We gotta live that too, right, at Wildfire. And I think that the faster we can do that, the faster and more efficiently we launch start ups.

And and I think that that's gonna give them, a competitive advantage. Now I think the same thing is true with the go to market tools. You know, you and I just talked briefly about some of the tools that we have today. But there's a whole bunch of, new AI tools that are gonna be used this year. Even you wrote that article on the AI sales agent or companion that's gonna be available to help salespeople.

I mean, the same thing is true with, you know, SDRs and and with, you know, going out and doing prospecting. Is there, you know, tools that we can use that are gonna help our our, founders learn more quickly, how to do that sort of challenge of sales methodology and help them level up on that faster, especially for the founders who have never sold before or never built a marketing funnel before. So we have a mix of we gotta add new tools to our program to help them do that faster, and we're going to need to, refine the methodology and just give them, know, preflighted, you know, better starting points on some of those templates and everything else to go work on. So I think I think there's as much to do with go to market as there is with product build this year. Do you have anything to add to that, Todd?

Todd Gagne:

I do, actually. I think one of the things that we over, or we're just kinda glossing over is just even let's not even talk about AI, but just, like, sending out email messages, to lists of people has gotten more difficult. Right? And so you and Priya had gone on a rabbit hole this year on just trying to understand how to build a current technology stack around marketing that basically actually works and scales. And I think one of the things that we're talking about doing is documenting that, productizing it for our our our our founders.

And I don't think that's trivial, and I don't think that's about a bunch of AI tools. That's about just some hard learnings and scraping our knees and going, don't do that again. And whether that's around burner domains and warming up domains and making validating lists, whether it's about making sure you have email addresses that go to Google versus, you know, Office 365. There's a bunch of best practices in here that I think if you, asked a founder just to go out and figure that out, they're gonna get they're gonna come back bloodied. And I think what we're trying to do is basically build something with a bunch of best practices that says, do it this way, and you'll probably have 10% that won't work, but you can deal with iterating on that 10%.

Like, do you agree with that? Like, do you feel like I just don't wanna lose sight. Like, this is not all about AI. There's some, like, basically just hardcore block and tackle that is important too.

Mike Vetter:

Yeah. So AI can automate and improve something that works, but what it can't do is it can't take a broken process and make it more broken.

Todd Gagne:

So so It can make it more broken. I don't know if it doesn't fix it. Yeah.

Mike Vetter:

You get more garbage. So Yeah. Cold garbage, you'll get more. And so, I mean, that that example of the cold email marketing is, like, it's a really defined process that we've had to painfully step by step go through. And this is back to the domain expertise.

Right? Like, we had to become the domain experts in doing effective cold email marketing before we could teach AI to do some of it. Now once you learn those tools, you learn the process, then you can use AI to improve your messages, to change when emails go out, all that kind of stuff. And then cloud computer use is pretty exciting. We like, you mentioned it before, Todd.

But we'd love for this whole machine of setting these up, getting them spooled up, and growing. We'd like to make an agent that does that using cloud computer use or something like that. So I think I think you're right, Todd. It's a good, it's a good nuance here that we we don't AI is not the panacea that will fix everything. It is really useful once you understand something deeply.

And so I think that comes back to just the domain expertise. Right? I I don't think that we're gonna win at this game by making AI bets in a bunch of different industries with smart, people. They actually need to understand the problem. So, Todd, tell me a little bit more about when we see we keep using this word domain experts.

What does that mean to you, and and why why does that gonna change this year at at Wildfire?

Todd Gagne:

Well, I don't know if it's gonna change dramatically. I mean, I think we'll just have a hard a harder look, on it. I think that, it just I think it kinda goes back to everything we've been talking about for the last 30, 40 minutes. We're trying to build an infrastructure around, people that are smart, that have vision, and wanna make their industry better. And so if you have if you're in an industry that basically has problems and that you know, like, every business has got problems.

Right? And I I wrote that article on kinda the heartland just recently. I think it went out this week. And it was really just talking about, like, there's precision ag, there's robotics, but the back office in a lot of these businesses is just shambles. Right?

It's post its notes. It's Excel spreadsheets. It's not very operationalized. And then there's a guy named Earl that's gonna retire in 18 months. And, like, he's been there for 35 years, and he's got all the tribal knowledge.

And so when Earl walks out after the big party, you guys are all gonna be, like, looking around going, like, what do I do? And so I think that's what we're looking for is, the people that have that domain expertise that are interested in making it better and then applying some of these tools and systems that we have around them to solving real world problems. These probably won't be $1,000,000,000 companies, but they're gonna be really good, nichey, vertical SaaS companies that are gonna provide jobs and and potentially good exits for founders in this process because you're not gonna have to generate a ton of capital to, like, go solve these problems. These tools will help you get to revenue. And if you need a little bit of capital to continue to scale, that's great, but you're not you're not raising 50, a 100, $200,000,000 to go solve these problems.

And so the outcome and the control that you're gonna have, as you continue to scale is is gonna be an endiest position, I think, compared to some founders.

Mike Vetter:

Yeah. And the other thing is because some of these tools are adding so much in terms of efficiency to those businesses, the other thing I feel like is changing here is, you know, previously, in order for a tech accelerator or an investor to look at a start up, they had to have a huge TAM. Like, the TAM had to be, like, a large dollar amount to be interesting. But with some of these AI things that we're looking at now, the TAM doesn't actually have to be as big because the problem that you're solving is so significant. And like the IRRRL problem, you know, he's retiring.

Well, that's a person. That how how in the heck are you gonna replace that person? Well, if you've got a tool that can scale with you that doesn't make you reliant on that, there's there's a lot of value to that. You don't need to have as big of a TAM, to make to make a difference. The other thing is you actually need less capital because of all of the things we're talking about earlier.

So you don't have to have these giant payouts with these unicorn type companies to make it worth solving the problem for these smaller industries that are really big problems and, I think, make America stronger.

Todd Gagne:

Yeah. There's another one where I that I wrote that isn't out yet, that was talking about, like, what's how many people do you need, to get to, like, a $1,000,000,000 company? And, you know, I think like a decade ago, it was 2,000 people, were needed to get to a $1,000,000,000 company. And today it's 203. So by an order of magnitude, we've changed that.

Yeah. And so I think this goes back to your point where you don't need as much money, mostly because you don't need as many people. Yeah. Right? And so I think

Mike Vetter:

Because time

Todd Gagne:

As much time. Right? So not only are you compressing the time frame of it, but, like, the number of people you need to solve these problems, is just way more efficient. And I think the tools we're talking about throughout this entire discussion is just creating more scale and efficiency in that. And so I I think that's another pretty cool trend line for us.

Mike Vetter:

Yep. Yep. I agree. Alright. So, Todd, we're passionate about helping founders.

That's what we do. Right? So I wanna talk a little bit about, what what does this mean for founders? And I'll take the first one on this because, I'm I'm passionate about this. You know that I love to play with with tools.

Man, each gotta get in to play with this stuff. You know, the if the first time you load up, you know, whatever, clod or chat GPT and you get hallucinating or it doesn't give you, you know, the results you're looking for, that doesn't mean that the tools don't work. It means that, you might need to keep diving in deeper. And the other thing you need to remember is that we're in the early days. So we're in, like, the first iPhone, like iPhone version 1 or not even iPhone version 1.

And so a lot of these, apps and and systems are really disconnected right now. There's sort of one over here, one over there. This one does some of it. This one does some of it. And you've gotta just learn what the strengths and weaknesses are of of these of these tools to really get an idea as a founder of how could I change the industry I'm in using these building blocks.

Because, really, what those are, those are building blocks that you're gonna build, you know, the start up of tomorrow on as those as those tools evolve.

Todd Gagne:

Yeah. I think it's good. And I I I'd echo that. I think, you know, it's almost embarrassing. You just try keep trying it with all different things, and you see what happens.

Right? And so whether it's planning vacations or asking a question and telling you to explain it to, like, an 8th grader, you know, like, there was a I was talking to somebody, and they were talking about how they moved to a new location. They wanted to create a bunch of raised beds so they could raise all their vegetables. And he went through this whole process where he was, like, saying, how many, raised beds do I need? It's my wife and I.

We like we eat a disproportional amount of vegetables. We're not vegetarians, but we're close. And then it said, for our climate, what are the types of vegetables that'll grow all year in the different seasons? And then they said, what plants go with them to keep the bugs away? And he had blown out this whole plan within, like, 10 minutes.

And his wife was like, this would have taken us forever to go to library and research or do stuff online to come up with it. And they implemented it. And, like, literally, I think she was blown away. But it's just like the number of use cases that you hear are just interesting, and they're like, oh, I never would have thought of that. So Yeah.

Validate your point.

Mike Vetter:

I I was learning how to make it. My my wife got an espresso machine for me, for Christmas, and so I'm in the unfortunate or fortunate, job of learning how to run it. And, man, the number of quad conversations I had about what the heck I needed to do to make espresso that didn't taste like, you know, burnt charcoal was pretty incredible. But, man, like, the number of hours I would have spent, like, watching YouTube videos and doing Google searches to figure out, like, why my, espresso machine was backing up in the novel was incredible. So, I mean, part of it is just you gotta incorporate this into how you think and live and solve the problems you have in front of you to get an idea of what it what it can do.

But but I also think it's it's important to apply it when you're thinking about starting a company. So Yeah. One of the things that we tell all of our entrepreneurs to do is don't don't do a traditional market analysis by looking at, you know, you know, the the agencies that that publish market market data. Go look at who your you know, what your TAM is, who your competitors are, and then and then drill the heck into differentiation. We actually do that internally now where we review each start up.

We analyze their competitors, and we use AI to do that. It collapses the amount of time that I I feel like some of what we're able to do, you you'd have to have research analysts that we'd be employing. And that's what VCs have, and we're we're able to do that level of of research on a on a on an idea. And not only just so the founder can can have a better shot, but also to give them the best, information that they need to decide if this is something they wanna chase. But, you know, I think that if founders start to use these tools, not only in their product, but also how they think about their business and analyze the world around them, I think they get a huge advantage.

Todd Gagne:

Yeah. I I couldn't agree with you more. And I just think there's so many different ways. Right? We were talking about, I I was working with somebody on on just defining a pain tree and saying, like, who's our beachhead?

Like, what's the pain that they're really how do I get to them? What do you think the average cost is to reach them? What are the markets or the tools that could go do that? You're really having a conversation with somebody that, you know, like, has some interesting information. And I'm not saying it's all perfect and right.

That's I wanna be super clear that, like, we're not saying do all this work and then basically just pass it off and say it's good. I think, you know, it's good to, like, figure this out. And then once you feel like you've got something, then go validate a lot of those assumptions. Right? And so I do think that it's a a multistep process, but it does crash the amount of time that's taken.

I mean, if you think about, like, what it was like for us to build business plans back in the day compared to putting something together today, like, I was just, you know, mentoring somebody at a local business plan competition, and I gave her a bunch of prompts, and she just blew it out, like, literally, like, blew it out from start to finish. And I would say it was 85% good, and then we had to go back and and tweak the last 10 or 15%. But, you know, for what she was doing, perfect.

Mike Vetter:

But but I think you make a good point, though, that that AI in its current incarnation and probably in in the foreseeable future is not a replacement for critical thinking. What it allows you to do Correct. And you and I talked actually a bunch about this, about how do we take our time and reallocate it to higher level tasks. So when you use AI to do your competitive research, it doesn't mean that you spend less time doing competitive research. It means that you spend more time going into what makes you different and then drilling into that and really understanding that in detail.

That's something that, you know, AI is not gonna do for you, but it can take all of the busy work of collecting data about your market, competitors, and differentiation, and then at least distilling that into something you can drill into. And then that's where you start looking at your each of your competitors, looking at their websites, finding out what you can do different, you know, doing online searches even on Reddit. Like so it just all you're doing is shifting your time up into more of thinking

Todd Gagne:

Higher value. And less of

Mike Vetter:

thinking for data. Yep.

Todd Gagne:

Yeah. It's exciting. I and it I just there's an opportunity there. And maybe the last part of this, Mike, that we said, and we probably said it 15 times already in this conversation, is just domain expertise. Right?

I think the more of this that you have, and you'd be surprised at what you know, if you've been in the industry for 3 to 5 years, you know, maybe that's enough. Maybe you see enough of these problems and you understand it. Or if you've been in it for 10 years and you and you see all the struggles and you see Earl retiring, like, those are the types of opportunities that we think are really good. And, you know, I have talked to entrepreneurs that say, yeah, but I'm not a technology guy. Yeah.

I'm not a sales guy. I just know this stuff. And you're just like, well, maybe now is the time where where there's enough tools around you to make this successful. I think it's a time to take a look at it and say, how do I leverage this domain expertise that I do have?

Mike Vetter:

Yeah. I think really, like, clearly, if you are a domain expert and you have vision and you're willing to just grind it out, like, you can do a lot. And all of the other pieces around how to do sales, how to build product, a lot of those barriers have come way down. But you gotta have vision. You gotta have, an area of expertise where you know a lot about something so that you can add uncommon value.

And if you're willing to do the hard work, AI is making it faster to do this. It also is lowering the barriers, meaning speed is your ally. And if you can go quickly and you can use that knowledge you have to quickly solve problems, then it's it's an amazing time to be a founder. And so, I mean, 2025 could be incredible, Todd. I mean, there's just the barriers are coming down to do this.

I think there is gonna be people this year that start businesses that would have never been able to start a business even in 2024.

Todd Gagne:

Yeah. And I think that goes for us too. Right? It's, our success is predicated on, you, me, and the team executing on what we say. Right?

We can't do 50 things. We have to focus on the 1 or 2 things that are most important. We've outlined a lot of the themes that we think are important for us, but it's incumbent just like it is for any other founder to basically stay focused, to create accountability, and then continue to execute and deliver on the promises that they made. And so I'm pretty excited. I mean, I think you and I have got a good pattern of doing this.

I've been pretty impressed with what we've gotten done in the last couple of years. But to maybe close this out, I don't think there's been a better time. I I mean, I'm super excited about, like, the next 10, 15 years. Like, this is the through line. Like, there is so much potential and opportunity.

Mike Vetter:

Yep. I agree, Todd. And, it's again, there there's there's less of a barrier because the tools are so much better. But, and that and that, I think, for some people, that will cause them worry. Like, I don't wanna start a company right now because it would be easier easier for a competitor to, to to tend to the market.

But I think I think the opposite for our founders is true, which is that if you got a vision and you are able to think at those higher levels, you can go from taking something that takes years to build to months, and you can go build a business into a market at a speed that would have never been possible. And it also means that you don't have to raise giant amounts of capital to make this happen. And a lot of founders have come to me and said, hey. I have to raise my seed round or I can't even start building. And I think if you're disciplined about what you decide to build in your version 1 of your product or MVP, then I don't we have not seen where a really good idea, we can't make it happen Does

Todd Gagne:

it win?

Mike Vetter:

Will cap. Yep. Like Yeah. 5 years ago, I would've said yes. Like, there's definitely businesses where you just needed 10,000,000, $20,000,000 to make it happen.

But the stuff we're looking at, especially in these niches, vertical agent areas, like, capital is not the gating factor. It's execution and it's founder, product market fit.

Todd Gagne:

Yeah. Well, it's exciting. So, Mike, as always, man, it's, fun to spend an hour with you on in talking about this stuff. And, you know, this has been a discussion I think we've been having all the way through the year, and and now this is maybe a more condensed, version of it. Hopefully, a little bit more little more through line to it all and making sense.

But as always, man, I appreciate you coming to the journey and doing this with me. It's been a ton of fun, and I'm excited about 2025.

Mike Vetter:

Well, it it's an honor to be back on the podcast. I feel like the the stakes keep getting higher because the distribution is mushrooming. So, man, I'm gonna have to up my game on being a podcast guest because I'm gonna get caught in, like, that that funnel of podcast guest pretty soon. There's Right. The stakes are gonna get higher.

So, I mean, Todd, you know, in all seriousness, congrats on on the success you've had on the on sort of the podcast. The the quality of guests that you've been bringing to the to the podcast has been just outstanding. And and, also, Substack, you you make me think when I read those things. Todd asked me to, to proofread those and add value to them, and you're making it hard on me because you've been leveling up, and, you're gonna you're gonna cross a quarter million, views, before the end of It's kinda crazy. Year.

In fact, I think if I go and cut the stats today, you may be crossing that. So

Todd Gagne:

Yep.

Mike Vetter:

Todd, congrats on that. It's,

Todd Gagne:

Thanks.

Mike Vetter:

Like always, it's it's an honor to to do this with you. And, man, what a year it's been.

Todd Gagne:

I agree. Well, it's good. Let's go knock out next year, man. So I appreciate it.

Mike Vetter:

Let's do it, Todd. Thanks again for the interview.

Todd Gagne:

Yep. Bye bye.

Mike Vetter:

Yep. Bye.