The Martell Method: How Top VCs Evaluate AI Startups Fast

"RAISE CAPITAL LIKE A LEGEND: https://offer.fundraisecapital.co/free-ebook/"

Are you frustrated with countless AI pitches that sound great in theory, but fail to deliver the goods? Learn how top investors at Martell Ventures cut through the hype, spot real winners and avoid costly mistakes. This episode is for serious deal makers only. Here we go. 

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[THE GUEST]: Cooper Simson scaled a coaching and lead generation business to $2 million in revenue before losing it all in a partnership breakup. In the aftermath, he started a million-dollar-per-year jewelry business with a friend and co-founded an AI grant writing SaaS startup where Dan Martell was a partner. Once that wrapped up, Dan and I teamed up to start Martell Ventures.

[THE HOST]: Ryan Miller is an Angel investor, former VP of Finance, CFO of an insurance company, and the founder of Fund Raise Capital,  https://www.fundraisecapital.co where his strategies helped emerging fund managers and deal syndicators to report raising over $1B following his strateg

Transcript

Ryan Miller  

My name is Ryan Miller, and for the past 15 years, I've helped hundreds of people to raise millions of dollars for their funds and for their startups. If you're serious about raising money, launching your business or taking your life to the next level, this show will give you the answers so that you too can enjoy your pursuit of Making Billions. Let's get into it. 

Ryan Miller  

Are you frustrated with countless AI pitches that sound great in theory, but fail to deliver the goods? Learn how top investors at Martell Ventures cut through the hype, spot real winners and avoid costly mistakes. This episode is for serious deal makers only. Here we go. 

Ryan Miller  

Cooper, welcome to the show, man. 

Cooper Simson  

Yeah, thanks for having me, Ryan, huge fan of the show in the Making Billions world here. So happy to show a bunch of other people I can do with AI now too. So really excited to be here.

Ryan Miller  

Yeah, and I'm excited to have you. Obviously, I love Dan, and I love Martell Ventures and the things that you've done, and we've been very fortunate to be in, I think we're number three or four in the world for private equity shows, and top 10 in venture capital. So we've been very fortunate, and it's all because of amazing guests like you. So let's jump right into it, man. So everyone thinks that raising capital is really about pitching investors, but from your experience, on just running Martell Ventures with Dan, what's the biggest myth about raising capital that founders need to unlearn immediately.

Cooper Simson  

Yeah, I mean, I'll speak specifically in the AI context, because that's what we've been living in. And nowhere have I ever seen somewhere like in the AI space, where the technology now lets basically anybody create whatever the heck they want. And there's pros and cons with that. I mean, there's a lot of amazing companies that are going on to raise tons of money. There's a lot of amazing companies that are doing insane numbers, but there's also a ton of other founders that are just using AI to build stuff because it's now viable with AI. And a lot of them, in my experience, will kind of really lose sight of who is this product, or what is this tool actually solving, and what's the problem that's being addressed with it. And the amount of demos I've seen, even in the last three, four or five months from founders, where there's a really cool new feature that they're able to put together. But two weeks later, I mean, I bought probably like 10 or 11 stories of just companies this year, I've seen where they'll pitch me, seems cool on the surface, and then three weeks later, the open AI, or anthropic, or name Big AI company down in Silicon Valley releases a feature, and all of a sudden they're just gobbled up, and their company, their company is relevant. So I think the biggest thing right now is founders are just getting really married to like, what AI can do, as opposed to what the actual problem they're trying to solve is and if you really just hyper focus in on that, it also is nice from an investor's perspective, or somebody who's looking to help support these founders. Because if you know what the problem is, you can actually everything else is a byproduct of that. So I think that's probably the biggest thing right, the biggest thing right now, is just getting too swept up into tech, losing sight of the actual problem that's being addressed.

Ryan Miller  

You know, you're spot on. I been fortunate enough to be pitched as well, and the ones that nail it and versus those that maybe struggle to, here's the thing, and I'd love to get your take on it Cooper, some people, they get so excited, like you mentioned, they so excited about this product they've built, or are going to build. It could be real estate, it could be AI tech or something in between and they go through talk about, we'll say real estate. We got best countertops in the shiniest kitchen sinks, or whatever it is that they're pitching, and they lose sight to say, I mean, that's good. Yes, have a good product, obviously, that's a given, but it's we're not buying a condo or subscribing to this AI technology. We're buying a security that those assets will drive the value of and so missing the mark of saying, hey, here's the product, like, obviously you got to talk about it, but over emphasizing when you're raising on how great your product is might be missing the other half or the other side of that coin, which is to say, hey, I'm asking these guys to put money, and I'm giving them a security, right, a stock in my business, or whatever it might be, let's talk about that. And so a lot of that when you just focus on product and you miss talking about the problem you're solving, the security that they're getting. And so when it's too product centric, I find a lot of people start to stumble when investors ask non product questions. Have you saw anything like that?

Cooper Simson  

Yeah. I mean, it's also, it's back to the whole thing. I mean, it's funny, my mom used to be an architect, or still is an architect, interior designer, and half of her battles with clients is always getting to envision the space that she's putting together and building. Like most people, most people say they're really good imaginations, they don't really. So you kind of have to spell it out as clean and simple and neat as possible, especially if you're a founder. Because at the end of the day, if you can't articulate how, especially if you're talking, yeah, if you can articulate how you're gonna get a return, or how you're gonna drive value, or where the underlying benefit of the company you're actually putting together is. It's very difficult if you're just product centric, and just going too much down that side for people actually envision how is this going to look 2, 3, 4, years from now? And I think if you can just spell it out nice and clean to be like, hey, here's the exact problem. Here's how our tool solves this problem, different from how maybe it's been able to be done in the past, or maybe different from how people are currently doing it right now. Here's how it's more unique, and whatever your unique way of doing it is. This is why you should come support me, and here's the outcome we're shooting for in the future whatever your growth multiple or exit target looks like. Is just a better way of presenting it, rather than going, hey, you know what, new GPT rollout just came Look at this cool like now we can actually do X, Y, Z. It's like fascinating, but it's also hard for people to don't understand the underlying technology to really get a grasp on. Especially in the AI space, because it's growing so fast, it's moving so quickly, that's really easy, if you're not staring at it every day, to get left behind, which is just kind of like also what we really that's why we really focus on very problem heavy solving companies, as opposed to really cool tech heavy companies, because it's also easier for us to digest. Like we're not the even though we might say we're the smartest people in the room at the end of the day, we're also just trying to really find what's the easiest. Find what's the easiest, simple one plus one equals two solutions that we can really wrap our heads around. And if, if I can find out in the first 30 seconds who a customer is, what the problem they're solving is just way easier for everyone to strive towards a desirable outcome.

Ryan Miller  

And finding out what they have. It makes me wonder, could you walk us through the Martell method as it relates to the exact evaluation framework that you guys go through just when you see a new AI startup pitch, what are those first three things that you look for? 

Cooper Simson  

Yeah, I mean, for us, like, we were pretty specific. So the number one thing for us is we want to make sure that there's customer alignment so we know what we know, and that is small, medium sized businesses, we know AI can help solve a problem for them. And when you see some level of, like, traction without kind of getting caught up in a whole bunch of vanity metrics, which there's a lot of in the AI space. So for us, really what that kind of looks like is, we want to see a company that is coming in and disrupting, or at least trying to solve a very definable problem. And like, we've got a whole bunch of frameworks, if you want, we can dive into in terms of, like, what that actually looks like in terms of the problems. Second thing is, they gotta have some sort of traction. So we're not looking for companies that are already blowing past series A going off for crazy other rounds, like for us, it's any range of company kind of doing anywhere from like $500 to $3 million a year in annual revenue. So we're kind of just looking to see that there is a little bit of validation here. And then the third thing is, we're looking for people that, again, can really clearly articulate how this product is adding value to the customers that they're looking for if they get caught up too much in, like, hey, here's how, if they start talking too much about what models they're using, or how efficient everything is from a back end, or, like, just the different token usage and just getting way too nerdy into the tech on it, it's kind of a bit of a signal that there might be a little bit of a missing gap somewhere. So those are kind of the things that we look for at a high level before we dive deeper.

Ryan Miller  

Yeah, it sounds like you're talking to the engineers behind it, so they're like, look at what I built. They're like, cool, but does the market want it, right?

Cooper Simson  

Exactly.

Ryan Miller  

So yeah, that's really good. I know you talked about it, but for the benefit of the people listening around the world, you said, I remember when we were speaking offline, that you could tell in about the first five seconds that there's a little bit of something that kind of is a, I don't want to say red flag, but maybe a green flag or an orange flag. What is it that that first five seconds, is that first thing that you really can pick up on if you're onto something, or if the founder is onto some what is that? 

Cooper Simson  

Yeah, I mean, there's a bunch of them. I think one of the really clear, definable ones that we look for as well is just how painful would it be, well too, how much is somebody going to use the product, and how painful is it if you take it away from them? So if someone's coming to me with a product or an idea or some sort of concept, and is it something that they're going to check in on once a month, and they might use it, they might not use it, but like, hey, it's going to be there, living in the background. Kind of hard to really get on board with that being a tool that I can see a lot of stickiness with especially when things are moving so quickly, someone's just going to come out with something that are a little bit cheaper, a little bit faster, a little bit more in your face, and just take them over. So that's a big one is like, how frequently someone's going to use it. And then the second one is just, how painful is it like, if I can see myself, like, if it's a huge problem, such as, like, recruiting or accounts receivable or something where it's like, it's a daily kind of in your face problem that someone in an organization or business is facing, and they're going to be like, hey, you know, if you we just installed it, we're using it now, if you take it away from them, there's like, a lot of pain and just yucky feeling on that. That's a really big way that we can kind of look to assess and there's some, there's some, like, funnier ones as well, that we that we use, but those are kind of like two of the easiest, biggest ones.

Ryan Miller  

Brilliant. This year I read Dan's book, Buy Back Your Time, and what I've learned is Dan's known for systematizing success. How did you and the Martell Ventures team build a repeatable system for filtering through hundreds, if not 1000s of AI deals? 

Cooper Simson  

Yeah. I mean, it's kind of funny, but one of the easiest ways is you can kind of just ask chatGPT, which is, I don't know, like the best answer the role, but like, there's this whole concept that people in the AI world use called, like, master prompts and system prompts. So essentially, what you do is take whatever your current process is, now ask chatGPT, Claude, whatever you want to use, you can use Google eavesdrop, doesn't really matter. Start there and say, hey, I want you to help me make my processes more efficient for X, Y, Z fund here's what we're doing. Ask me as many questions as possible. Help build a master prompt about how my organization runs. And you go, cool, set aside like, two hours, because you're gonna get legitimately, 100 questions from the AI. And you, like, kind of lock yourself in a quiet room because you will look a little insane just talking to your computer. Also a pro tip, there's a bunch of these tools out there, my favorite is called Super Whisper, we don't have any affiliation with them. It's just a really good tool and I wish I had some affiliation with them, so if the founders listening, I'd love to get in touch. But there's, there's a number of these tools that will let you talk to basically, you can use voice to text essentially, and way better than dictation, way better than the out of the box, chatGPT features and yeah, just sit down, answer the questions. Go into as much detail as possible, leave no stone unturned, and you'll what you'll end up with is essentially this master document that outlines your entire operational process, head to toe, and you go, bang, okay, where's my inefficiencies? Where am I wasting a bunch of time? Where am I maybe spending, where can I automate processes that are currently, right now, being done manually, and each person is going to be a little bit different. It's like for us, we essentially have it where we have new inbound applicants come in. We have as bunch of prompts that essentially evaluate each one of those candidates and applications based off of like a pretty detailed, super in depth grading rubric of how we assess and how we want to view deals. It goes through that initial pass through all the ones that kind of show through as promising, then go on to, like, a quick manual review, just to do a quick double check. So instead of us filtering through 100 applications a day, we're filtering through 5 to 10, so it's a little bit easier to kind of digest. 

Cooper Simson  

Then once we kind of move them through, basically we just slide them across in our CRM that then fires off a bunch of other automations to schedule in the meeting. Have that person join, have that person basically join in on a quick, like quick demo call requests, all the information that we need to see from them. Basically, essentially automates the entire process of like, managing that founder, so to speak. So that way, all I need to do is take 10 minutes out of my day to assess and evaluate all the highest probability deals we should be looking at, hop on calls with the ones that we do want to talk to, and then we have a bunch of prompts on the backside that actually take the transcript from the calls we have with the founders, runs them through a whole series of additional prompts and other kind of AI processes to, again, extract more information from them to see, okay, does this kind of fit the objectives that we're looking for? Matches it through to see if there's any like conflicts, goes through the entire grading process again in more detail, and at the end of it kind of grades, it scores, it posts it across all the channels, where everybody who's involved that needs to make a decision can see it to make a decision, and then preps all of our diligence docs, all the diligence process, everything else on the back end. So it's a pretty crazy it's a pretty involved deal, but all kind of starts, if anyone wants to do it at home, all you need to do is, like I said before, talk to your chatGPT, go in depth, give it the information, run through the process, plug the holes, and before you know it, like our entire process now maybe takes 10-15, minutes with just a little bit of formatting on some of the social media, there's not so much on some of like the slack or internal messaging posts, but it's, uh, it's pretty remarkable. And you be every time I almost do it at once, every once a month, just to be like, how can I make this even better? And like, you'll find the upper limits pretty quickly, of like, where it's good or where it's not good and then you can kind of like, dial it back or go deeper, if you want. But what you all I can say is with confidence, at the start of the year, what used to take probably three to four hours is now taking probably 20-30 minutes and just buying back a crazy amount of time? 

Ryan Miller  

Yeah, you certainly did that. Do you have a because a big part of this is doing due diligence. When you're at this phase, you're doing that is there, do you guys have an in-house thing or do you have any AI DD support, are there any that you personally like?

Cooper Simson  

For the companies that we deal with? Most of the DD is kind of done in house just based off the size the companies they don't usually don't have the amount of information that we need to, kind of, like, go through a huge, a huge due diligence process. I mean, we definitely have our checklist and our markers and everything else to make sure that we're making good decisions, founders are making good decisions, so that nobody ends up with a bad deal. So, I mean, for us internally, we we have a bunch of, kind of, like, our own internal due diligence that we run at all these to make sure that we're making good decisions and that the founders making a good decision. I mean, we don't get enough information from these companies to fully run it through a much more crazy diligence process. But if we were, there is one tool I've seen called Termina, which is pretty, pretty wicked , again, no affiliation on our end from it, just a cool tool that we've come across that, yeah, definitely, if you are doing more involved diligence is definitely worth a look. 

Ryan Miller  

Yeah, well, hopefully everyone's involved in due diligence who listens to this show means something's going horribly, right? So, yeah, the power of AI and wow, you guys, you just blew my mind, man. So this is what we're talking about. The new age of venture capital is a lot of it is not just cutting checks to AI. It obviously is that what we're saying is also using AI to make better decisions, both from risk management, covering your downside, also covering your upside, and so hopefully, with the power of AI and as it matures, that this will also affect investors as well. Man, absolutely love it. What would you say is one red flag that kills an AI deal instantly, no matter how good it looks on the surface, what's, what's one red flag that you see?

Cooper Simson  

Yeah, I mean for us there. I mean, there's, there's kind of like the usual suspects for us, though, one of the big ones is given who Dan is and, kind of his name being front and forward on our fund. One of the biggest ones for us is affiliation risk. So we'll purposely turn away deals if we know that there's risk with the founder who's involved, even if it's a fantastic deal, makes a ton of sense. But if the affiliation risk goes like, hey, this could actually end up hurting the brand of Dan at a high level, typically, what we're going to do is kind of look to move away from those like so for us, things are maybe a little bit different than some other funds or firms out there where maybe, like, the social facing element isn't as prevalent. But for us, that's, like, usually, pretty much one of the biggest ones, I mean, one is a bit more general, though, and this is for anybody that's looking at AI, is founders that brag about how easy building that products are. I can't tell you how many times I've been talking with a founder and again, this is back to just because you can build something with AI doesn't mean you should. But people now, anybody, and everybody that can articulate correctly what they want a product to look like can use tools such as Replit or Claude Code to build products now, and I've had founders number a number of times that'll come with, like, pretty decent traction, but they'll start bragging right off the bat that product only took them two weeks or one weekend to put together. And I mean, like, man, unless you are the industry expert with the biggest audience, or you are just the most knowledgeable, best operator on the planet, usually, if someone's bragging about how quickly they can build something, it's a bit of a signal that it's not very defensible in the long run. And also, why would we invest in that person if there's somebody that might have more defensibility involved in it? So for us, those are kind of like two really easy ones that we kind of look at that I go, ah, doesn't quite sit right if they're , they're bragging about how quickly something came to be.

Ryan Miller  

Yeah, that's, that's the thing they miss, I remember the early days, my first love was venture capital and angel investing. And one of the things that we always found to be an extremely good green flag is what you talked about before AI it was, I remember there was a deal that we loved, and they put in below this, they put in 10 years. They had like 60 patents. Instantly, exactly what you're talking about, instantly, we're like, okay, so for somebody to become a competitor, we're already 10 years ahead of them. There's no catching these guys, it's, it's a brilliant strategy. So if you're like, hey, I could pop up this app in, by the afternoon you're like, so then your competitors probably could too, and I'm gonna lose a lot of money. So I could see why you're looking at that to say, actually, if it's quite easy to build, that might not be great, we're looking for things that have some defensibility. I absolutely love it, and I'm so glad you brought that up. Now with that said, let's talk about the flip side, what's a green flag that makes you and your team lean in and just say, we gotta fund this guy?

Cooper Simson  

Yeah, so for us, I mean, back to the whole thing about AI, you can it's kind of taken non technical people and turn them very tech enabled now, which means people that, like the people who are gonna succeed in the businesses, are gonna succeed in the founders that are gonna really win in the next three to five years are the ones that just have such deep domain expertise in whatever solution they're trying to solve is like, I mean, from our perspective, I would way rather go fund or work with the guy who's worked in construction for 35 years knows every pain point down to like the nos is super well connected in space. And just you, you tell him about a process that you can point to, like, 15 reasons why is, or you point them in a project or work, the 10 reasons reasons it won't. That guy is going to be able to build a product that solves a problem for that ICP or that customer, so much better than some kid who is just understands how, like, all this product and how this technology works, like, so really deep understanding and, like, deep domain knowledge. I mean and what we kind of call is like founder market set. So it's like, you want to have product market fit, but if you can have founder market fit, especially with AI, you can do a lot of damage real quick. That's kind of the kind of like, the biggest green flag for us is just like, because if you know it, and you know how big the pain is, guaranteed, there's other people that have it too. And if you can help solve it, and it isn't already being done in a wide enough scale yet, let's rock and roll.

Ryan Miller  

Yeah. So would you say then, just carrying on that logic at Martell Ventures, are you guys more focused on product excellence, or how does the founder story come into play as you guys look at making decisions to fund or not fund?

Cooper Simson  

Yeah, I mean, product definitely factors in however right now, I mean, it's more important as it's less of an important thing, because you can get good product so easily now, like kind of gone. Are the days where you go raise a bunch of money, hire a crazy talented tech team, build up the product, then go to market. What impresses the living crap out of us is somebody who can actually go validate a problem first, go sell it to someone, come back to us and say, hey, you know what, I felt this pain myself, my friend saw this pain. I put this really janky duct tape and bubble gum solution together, but it does a specific thing for this person, and it's an expensive problem. I'd like to kind of go on forward with this, to us that's like the cherry on top, almost when we're looking at assessing deals. Because if someone's going to go out of their way to use these new tools that are available, or kind of use AI to solve problems that otherwise weren't viable From a logistical perspective before that, because, again, like AI has been able to make a bunch of old, boring problems sexy, again, all of a sudden, because there's things out there that you would have never built technology for. You would have never gone and found a software solution to solve it, just because the cost would have been insane, the return wasn't as high. But people I know going and saying, like, hey, actually, that thing that was too expensive and didn't make any sense to go do, I can go do it now. And as as it turns out, there's a ton of people that have that problem in pain point, so let's go sell it to them. And that, to us is kind of like one of the coolest things, is people I go scratch their own itch, understand it, come to us and say, hey, you know what, this just sucks so bad for me, went and solved it. Want to help go get this in front of more people, we're like, hell yeah. Let's rock and roll.

Ryan Miller  

Yeah, you know the info products and coaching and all that stuff online. I always fantasize with AI . How cool would it be if you can actually schedule a phone call with an AI coach who's trained on whatever methods, raising capital, startups, losing weight? It could be literally anything, how cool would it be to just have a scheduled phone call with an accountability coach, and it's just because we've got SDR dialer, we got a lot of these technologies that are circling, and I always thought that would be right, like to build software around that, that makes no sense, but now it can pop up, so fast, heck, I could, I mean, I'm a finance guy, and we could probably build something like that. But yeah, how cool is the market, it's turning absolutely, absolutely jaw dropping. So I love it, and you guys are right at the forefront for funding that. So let's peel this back another layer, can you share an example of a deal that you passed on later that just it validated your instincts, and then maybe one that you funded that proved you were right? 

Cooper Simson  

Yeah, so I won't use the name of the company that we passed on, but it's kind of back to what I was mentioning before, which is, like, cool. Which is like focusing on technology over actual core problem solving. So there's this one company that loved the founder, phenomenal guy, like what it would have backed him. Still would like to find a way to work with him, but he built a solution that basically, kind of helped. Essentially used AI to get ahead of every phone call that you would receive, and then screened it, saw if it was spam worthy of talking to, and like beforehand, would pass it through. So if you're getting a call, but like to basically sell you a cruise in Nigeria next summer for $10,000. It'll just have AI take that call, and then you don't actually ever see the phone ring, so that way never actually registers. Pretty cool thing, because it also kind of protected you from spam registrars and stuff, because you're technically never answering the phone. We were like, Hey, this is awesome. And then I remember, three weeks after we kind of started chatting with him, a new update comes out from Apple where that's, like, just baked into a new software update and I'm like, okay, cool. So there's, unfortunately, no more company anymore, because you're not going to go compete against Apple in that respect there. 

Cooper Simson  

There's also one other one I can think of, there was a company that before kind of in, like, of in like AI, moved so quickly, but kind of back a few months ago, there used to be this big concept around how you would prepare your data. So how did you get your data ready for an LLM to use, essentially? So seems like a pretty straightforward thing, but if you don't, yeah, if you don't have the right tags or if it's not structured properly, a had a hard time reading it. There's this one company that they said, hey, we actually built a whole system that will take all your messy data, turn it into clean, AI, visible data, and then that way you can get better uses out of it with AI and we're like, sweet, this is perfect. And then, quite literally, about we ended up not doing the deal. And then I remember seeing about a month afterwards, anthropic, who created quad and all that came out with an update that basically just said, yeah, it doesn't really matter what your data looks like, AI can read it. And I was like, oh, okay, so yeah, like, even, like, even if we had done that, there's just, you're, you're now just a core function of a larger product. So there's, there's a ton more of them, those are just two that kind of, like, stick out, I remember at the, at the top of my mind.

Ryan Miller  

Yeah, you dodged that bullet. What about ones that you had an instinct to focus a lot, depending on how early if you're seed or pre-seed, it's a lot instinct. But what about those that you did fund and then later on, you're like, I knew, I knew this was going to be good, you have any of those?

Cooper Simson  

Yeah. So one of the this is this one might be a little bit cheating, because it was kind of like a little internal incubated quartz project, but we had basically solved one of our own itches. So the company is called, this is, I will share the name on because we did do the deal. It's called Get Revio, but essentially, we were having a really hard time managing kind of social media as a sales channel, whereas kind of just an organized sales channel. Lots of reasons you've ever been in your inbox is linear, multiple people get in there, it gets messy really quickly and AI is really good at helping to clean all that up, but also give insights. Pull information from who you're actually talking to, predict what you should actually say to people in order to kind of help get them to move along in a sales process. So we actually had a guy on the team, his name is Viv, he was building out the product for us. It was kind of again, back to scratch your own edge, it was scratching our own edge. It was a problem we knew, and then, yeah, surprise, surprise, we ended up doing. We ended up kind of bringing that into Martell Ventures, and now he's often crushing it. So it's a phenomenal tool. I mean, if anybody ever is trying to use social media, Instagram, LinkedIn, Facebook, all everything to try and grow as a sales channel, it's really hard unless you're using something like that. So for us, that was one where we knew it was a problem we knew need to be solved, lo and behold, can't really go wrong when you start kind of coming at them, at things with that sort of frame. So that was like a little bit of one, because, like an internal Skunk Works project, but the, it's often flying right now, so we're super happy with that one.

Ryan Miller  

Well, we need to talk about that, because that's definitely an issue that I have. I mean, I do get a lot of offers to get a million followers in 30 days with no bots, so I was like, really? I like, you're full of crap. But working through that, all these offers and the social media, and often in the industry that I'm in, and while you and I are in, always talking about the best place to start is what I call quadruple F, friends, family, fools and followers. Used to be triple F, but in this day, there's a lot of followers, and managing that social media and building rapport, a lot of people put money and time and effort and their heart into growing a following, and then they get a message, and then they get a lot of messages, and what do I do, right, and so you've built this follower base that you can't monetize. So I can certainly see just from my personal experience, and I can imagine the millions of people around the world that would benefit from saying, hey, you put a lot of time and investment into this. How about you get the value that you intended to get in the first place. We have a tool. So I love it, man, hitting the easy button. I love it. So if a founder wants to build an AI company that actually gets fun from your experience, what must be in place beyond just the tech itself? 

Cooper Simson  

Yeah, beyond just the tech, I mean, I think the biggest thing is they need to actually be building AI first. So there's still a lot of founders I notice out there right now, they're building software products that are made better with AI. So it's not kind of a through and through full on AI company, if that makes sense. So I've even seen this where I'll talk to founders and their head of development doesn't like to use quad code or doesn't like to use cursor any of these AI development tools, bit of a flag if you're building an AI tool and you're not using AI to help build the process. So make sure that if you're building an AI company, you're actually building the whole stack with AI. That's kind of giving us kind of on the tech side, but it's also just good future proofing, because, yeah, I mean, you want to be these companies actually build so lean and mean, if you're not taking every advantage, it's a bit of a flag. The other thing is back to what we've already kind of spoken about a little bit, but I'll just reiterate here, maybe a little bit differently, but you need to make sure that your product has a very clear use case that you can quantify. So thinking at almost less of like, hey, here's what we're able to do, here's how it provides value, but thinking of it more like, hey, here's the repeatable process every single day that people are doing. Here is how we can use our tool to basically remove those tasks, like a good example is we bought another company our portfolio. It's called Atlas. It does a bunch of like call. Basically, there's a bunch of like AI dialing. So anytime a lead form gets filled out, an AI, basically voice agent will call. Do all the qualification very clear how that use case is definable. And I can take one look at that a customer can take one look one look at that and be like, oh yeah, great. So you're saying my receptionist now doesn't have to waste their time on 30 of these random calls a day, they can actually do more important tasks, two thumbs up. And then the third one is just again, kind of another thing we've already spoken about a little bit, but it needs to be sticky. So you need to find products that people are actually going to keep and want to keep coming back for. So ideally, it's an everyday workflow support tool. It's a back end kind of like system of record or tool that essentially just cleans up and manages a lot of processes that someone's doing very manually, things that people again, back to what we already spoke about a little bit. But just if it hurts to take it away, that's the sign that you've got something that's really gonna work here. If you just have kind of bit of like a you have kind of bit of, like a tech magic trick, you might want to reevaluate how durable your product is. So those are kind of the three big things that I would kind of put out there. 

Ryan Miller  

Brilliant man. And you know, with that, I'm curious. I have an add on question for you. So where do most since you focus on AI and dealing with AI founders, where would you say most AI founders waste their time when pitching investors, and maybe follow up with some advice on how to redirect that energy. 

Cooper Simson  

Yeah. I mean, I should kind of take a bit of a bit of a page out of your books here. I mean, I think the one phrase that you use is always like the BLUF. So it's like most founders, I still know I was on a pitch earlier today, literally did not get to the point. Like, the biggest thing that I think founders can do is just get to the numbers right away. Get to the meat and potatoes, skip everything else and just tell me what the deal is before you jump in everything else. Like, I don't know why I need to sit around and hear a life story, product development that, like all of it is, it's cool. We will get there, but within two minutes, I'll be able to determine if a deal is worth going on or not, if we just kind of get to, like, the most important information right off the bat. So I'll kind of, I'll kind of take a page out of the Making Billions playbook here, and use some terminology people might, might see, but that'd be, that'd be my biggest thing.

Ryan Miller  

Well, thank you, flattery will get you everywhere. Yeah, the Bottom Line Up Front, the BLUF, so for the benefit of those listening, I'll go through it, here's the science behind it. Let's talk about that because while that sounds good, bottom line, let me get framework we were chatting offline to be like we got to help people execute. And so the Bottom Line Up Front is, seriously, the first thing out of my mouth. It's on the title page, but we say it, and this from the context of a fund manager raising money, and say, we're X fund, we invest in Y assets, in Z sector. We're raising X amount of money, and we're targeting a Y return for our investors. That's it. So right out of the gates, I love that you brought this up Cooper, because right out of the gates now an investor is like, cool. I know who you are, what you invest in, where you invest, how much you're going to ask for and what kind of return should I decide to join you on this 10 year journey, or however long the funds the long one. And now the rest of the pitch is like, they're locked in. They're like, hey, yep, I know who you are, what you do, where you do it, now the rest of the pitch is just adding context to those first five or 10 seconds on the bluff. Could you imagine missing all of that and you're just get into and it's this, and we tried that, and we had this story, and the investors like, what the hell is happening right now? And so now you're able to really support a lot of the founders in their quest and the investors as well by just saying, like, here Bottom Line Up Front, this is who we are, this is how much we need. Here's what you can expect to get should we be successful and then let me, let me add context. I absolutely love that. Thank you for the BLUF, thanks for the shout out, so. 

Cooper Simson  

No worries. 

Ryan Miller  

And so for investors listening, what? What's the biggest mistake that they make when evaluating AI startups that just causes them to get roasted?

Cooper Simson  

Yeah, I think it's getting wrapped up in magic tricks. So this is this again. I'll just speak to the AI stuff, because this is where my life has been the last number of months. But the biggest mistake I see people making is they'll get pitched by founder, charismatic, all the energy in the world they build something that is cool. Like, I'm not gonna say it's not like, I'm not gonna say some of this technology being built right now isn't really cool. The trouble is, is that it's so cool because, again, you can build things that were never feasible before. So that way, it's easy to get wrapped up in kind of this vortex of irrationality, where you can kind of start to, it's kind of we all start to play, like, whack a mole with what's the solution for this cool tech? And you're just like, oh, hey, like, it's a little bit of smoke and mirrors. And I think the biggest thing right now is founders just get really caught up with a super charismatic founder and a really cool tech or product demo that doesn't actually have any substantial benefit to an end customer. So that's probably the biggest thing and I'd say a byproduct of that is, if you're going to be best investing or looking at AI companies, at least try and stay up to date with what kind of the status quo is with AI because, what is actually something that we're coming across more and more recently. There's a lot of founders making claims of what this tech can do, but if you know what the State of the Union is, it's actually not feasible for some of these products to be at the level they're talking about now. And so that's a really big one, like, if you don't know what the tech is actually capable of, you'll run the risk of getting overly impressed by kind of a walled garden scenario, and that's a quick way to get burnt as well. So be in the know and just kind of have your BS radar going off, because if it looks too good to be true, it probably is. So those are two, the two biggest things. 

Ryan Miller  

I love that man, and I'd love to carry on that logic. So for those investors, what would you say are, let's say, three questions they should always ask before writing a check to an AI company.

Cooper Simson  

Three that I would ask, one would just be actually see if you can talk to some of the customers that are using the product right now. That is a huge one, because the founder can tell you as much as they want to, but a customer will actually tell you how they're currently using it right now, and are they using the thing? Are they using the cool magic trick portion that they showed you or are they using for some other reason, or are they not using it at all and they actually turned away? Big, big one, right there. Another question that I would say is, yeah, just get a full breakdown of kind of everything that they are using. I mean, there's a bit of a running joke in the AI space right now that every product is just a chatGPT rapper and like, there's a little bit of, there's a little bit, there's shreds of truth in that. But because, at the end of the day, both there's no reason not to use chatGPT APIs, because they're phenomenal, but there's levels to it, like some companies are quite literally just a couple degrees away from chatGPT. So you want to really see, like, what is the tech stack that you're using, and is there anything somewhat proprietary or somewhat unique in how they've positioned their product around open AI or anthropic APIs, that's a really big one. 

Cooper Simson  

And then this one, I'd say, is a bit of a split, but I really understand and make sure that either they're kind of what I mentioned before, like a massive subject matter expert on the problem they're trying to solve. So you know that regardless if they're capable of doing if you can find a tech talent to put in there to help them solve the problem, they know, cool beans. Or make sure that, if they are a technical founder, that they actually know what they're talking about, and they're not just kind of coming to you as some vibe coating, tech bro that threw together a bunch of like Zapier or n8n automations, as there's a lot of that out there, and there's even tools that I've seen nowadays where you can essentially take Zapier or n8n or make.com workflow and put user a front end user experience on top of it. So you can match light at this point, it's getting pretty it's getting pretty murky why like is and isn't a product. So really make sure that if you're investing in something, it's not just a couple web hooks thrown together, because that gets you hurt pretty quick.

Ryan Miller  

Yeah. Back to the magic trick thing that you talked about the sleight of hand look over here, or whatever. And you know one thing I remember the first time you and I met, and you talked a lot like you have this domain expertise, and one of the things that really got me thinking, and I learned this from you, was, is there a question that you tend to ask as you're trying to make a decision and do right at Martell Ventures, is to say, does this get better with AI, or will this get wiped out. As AI, like the big one, Anthropic and Grok and these big models that most people are familiar with now, is it if it's a feature that uses it and then say, chatGPT added to that feature, now you're irrelevant. So I absolutely love that, and I do want to lose that, I do want to lose your brilliance that you do and that's something to really think about. And when I heard it, I was like, how is this not more obvious, of course, so it's absolutely brilliant, man. And so making sure that this isn't just a feature that could get wiped out, as say, chatGPT, they added agents and additional features so that wrapper of the models, there's a lot of things, and I can see why you might be a little skeptical and maybe take your time, or be able to sharpen your pencil a little extra sharp on due diligence. I think that's really important to be able to do that, to say, Could this thing get wiped out? Like, is this a feature that Grok or chatGPT could add if so may not, may not be for us, anything you can add to that?

Cooper Simson  

Yeah, there's actually a framework we use to kind of, like evaluate and kind of go down that pathway a little bit more. So, I mean, like, because this kind of actually happened at my previous startup, not it wasn't the reason why the startup wasn't successful, but it was definitely one thing that we had on our mind. Was my previous startup was an AI grant writing business and or an AI grant writing startup. And one of the things for us is, like, back in the prehistoric times of AI chain of thought and context wasn't really a thing. So for anybody that doesn't understand AI a ton, basically, you used to be able to ask a singular question and get a response based off that text block that you submitted. But if you had, like, say, 10 questions chained together, used to be very difficult to get a response to the question, one that you used to ask. That's no longer a problem and thank goodness, because it was really annoying when AI first kind of came out and all these chat bots came out. So what we did, you can imagine, for grants, so that's pretty important, because they're like massive documents you have to put all this information in. And I remember, literally one day, me and my other co-founders, we were just arguing because it was such a big annoyance for us, and it was literally stalling how many applications we could sell, because we had to build all this context in every single document that we put together. And I remember, like, one of my co-founders just said, like, there's no point in us building this, because in six months, it's going to be a standard, like, there's no way open AI anthropic and these other companies aren't already tackling this. So us putting any of our resources on it is pointless, because it's just going to come out. And so the framework that we kind of use now at Ventures to really evaluate this is, if you take everything else out of the out of play, is the core functionality of product of founders building does it get better, if the models get better? It's like a good example would be, say, voice AI, for instance. I don't necessarily think that OpenAI is going to have a feature that allows you to put a context, basically put a whole database of contacts into it, send out messages, and off it goes. And it's going to just go dial, call and message all of them. What I do think, though, is that you're gonna be able to use that model and the voice agent on the other side is gonna get tremendously better every single time there's new updates. So it's like the core functionality isn't really at risk, but the underlying engine, as it improves, the business improves and so we really look for opportunities like that. And if it feels like this is something that could become a part of your chatGPT, $20 subscription three months from now. That's where, that's where we kind of draw the line. 

Ryan Miller  

Brilliant. You know, my final question for you, brother, so you sat in Martell Ventures with Dan for a while now, been able to see what works at scale. What's one inside lesson that you've learned from Dan and this experience that listeners can apply immediately. 

Cooper Simson  

I think the biggest one is just attack problems, and you're probably not working as fast as you think you are. I mean, this might be a little bit of a wake up call because, I mean, it's definitely a bit of a culture shock for anybody new that joins our team. But the speed and pace in which we operate, and that kind of like Dan operates all of his companies at is just monumental compared to what I think most people really realize. And I think everybody who, if you're thinking about it right now, your upper limit of what you think working hard is probably 40% of the capacity of what you're able to do. And an easy framework to kind of instill with your team or even within yourself is, if you're looking at a task list of everything that needs to get done this week, really push whoever's responsible for that outcome to see how come the thing that's earmarked for Friday can't be done on Wednesday. And what you'll really find is that most people are just putting it off because they want to, not because they actually have to. And if you start kind of looking at everything you need to get done through that lens, whether that's in a diligence process, like, I mean, even for us, like, we'll, we'll attach deadlines to the founder that are working with to get this documentation. Like we'll set deadlines for everything, but it's just make sure that you set deadlines. Challenge how come they can't be done quicker and then really work, just make sure you're attacking whatever it is that you're working on with the speed and intensity you want to you want to execute and operate at. Now, full disclosure, that's for people who want to go do big amazing things. If you don't want to go do big amazing things, keep doing what your doing. Amazing things, keep doing what you're doing. But if you want to go accomplish really big things, which I think everybody listening to a podcast talking about how to Make Billions, probably is then I would assume, yeah, just kind of take that mental check and just follow up with your team and see push them to figure out why stuff can't be done two days sooner than when they say it's going to be done by.

Ryan Miller  

Brilliant man. So before we wrap things up. Where can people go to find out more information or if they want to contact you just to learn a little bit more, where would you send them?

Cooper Simson  

Probably the two easiest ways, you can either shoot me a message on Instagram, or if you want to go connect with me on LinkedIn, I'm pretty easy to find there just Cooper Simpson on LinkedIn. Or if you want to just fire me off an email, even it's just cooper@danmartell.com and, yeah, those are probably the easiest ways to get a hold of me. 

Ryan Miller  

Brilliant man. So just to summarize everything that we talked about, use AI to work faster. You can work at God-like speeds, apparently, especially at the Martell Ventures. Also avoid products that can get wiped out with AI updates on those larger models. And finally, the BLUF, get to the point, get to the bottom line up front, you do these things, and you too will be well on your way in your pursuit of Making Billions.

Ryan Miller  

Wow, what a show, I hope you enjoyed this episode as much as I did. Now, if you haven't done so already, be sure to leave a comment and review on new ideas and guests you want me to bring on for future episodes, plus, why don't you head over to YouTube and see extra takes while you get to know our guests even better, and make sure to come back for our next episode, where we dive even deeper into the people, the process and the perspectives of both investors and founders. Until then, my friends, stay hungry, focus on your goals and keep grinding towards your dream of Making Billions.