TRANSKRIPTIO 🔗
Charlie O'Donnell: All right. We are live and it's always fun for me to talk to Rob. So, Rob and I met through our respective blogs in 2005 when they were called blogs and now they're newsletters, I guess. And met in person for the first time a couple of years later at the South by Southwest that is most known for putting Twitter on the spotlight and showing everybody what it would look like if everybody was on Twitter. And then two years after that, Rob was the founder of the first company that I ever invested in as a VC, a company called Backupify, which was sort of an offhand idea that I had thrown out there on Twitter. that Rob very casually picked up and decided to build into a company that sold to another company and then that company sold for a couple billion dollars and he became an investor after that and still continues to be a builder. So Rob, thanks for making the time. I appreciate it.
Rob May: Yeah, always fun to talk to you, man. We've got such a long history, so glad to be here.
Charlie O'Donnell: So you were one of the first people to talk to me about AI. And you were like reading research on like neural nets and you went pretty deep on this pretty early. And I'll just kick it off with a couple of questions. And by the way, for everybody watching, Feel free to throw your questions in the chat. I want to make this as interactive as possible, but I just kind of want to set the stage of when you first started looking at this and then how it has impacted a founder's ability to build. did it play out as you thought it was going to?
Rob May: Ooh, so yeah, so I got really interested in 2015 in AI. And let me take your second question first. Did it play out as I anticipated? Yes, but on a different timeline is what I would say. So some things happened faster and some things happened slower. And the difference between those was you can look at an AI technology as does it meet some minimum bar? And then is it good, right? So like GPT-3, GPT-2, if anybody was using it back then from OpenAI sucked, wasn't very good. GPT-3 was the first thing that crossed the minimum bar where we were like, wow, this can actually like write a blog post or something. have been, things hitting the minimum bar have taken longer typically than I anticipated. Once they hit that bar, they typically progressed really good, faster than I anticipated. So. You know, we think of these things as like, uh, you know, going like this or even on an escort, but they're kind of the step function of like, not there, not there, not there. Now it's here and it takes off. Right. Like, um, so that was interesting in terms of, has it made it different for founders to build? Definitely. And I, but I, but I do think, I think it makes it more competitive. So when you lower the barrier to start a company, or lower the barrier. Like I think of AI as lowering the barrier to executing on things, right? Because there's stuff like, gosh, particularly like PowerPoint slides. I hate, it's my least favorite thing in the world. Cloud can whip up decks for me, like in between me doing emails and then I just give some feedback and you know, after an hour of that, I've got something pretty good. Like that's awesome. And so I think it's good for the economy as a whole. when you lower the barriers and you get more startups and you get all this kind of stuff. But for any individual startup, it just means you got more people to compete with now because more people are doing it. You know, people that couldn't write code had like, you probably saw some of these people over the last decade, Charlie, where they're sort of like, I'm a business person. I know how to sell. I've got a great idea. I can't find a developer to like be my co-founder and build it. Or like those days are gone, right? Unless you're building something super complicated. So
Charlie O'Donnell: And you know, what's interesting about that is if I think about, I was investing out of Brooklyn Bridge Ventures from 2012 to 2023, and about 50 % of the companies that I had backed had not launched yet. That would not be the case today. Like, I don't think I could back somebody that didn't have some semblance of a product today because the bar is so low to get to something usable.
Rob May: Yeah, I mean, even like, like, think about even do you remember for a while, maybe in like, probably around the time you're getting started, there was a website called like rocket launch or something. It was basically like, set up a page to collect interest in your thing, right? Like, and they made that easy. But yeah, today, I mean, you should be able like, definitely, if you're a programmer, you should be able to get out a prototype of a decent app in a day or two or three, even if you're not technical a week or two, like, so why would you you know, you remember these times when people would come in and be like, Okay, we talked to 100 potential customers before we wrote a line of code. You're like, why would you do that now? Like build something and go show it to them, right? It's way better feedback.
Charlie O'Donnell: Yeah, I still think it's useful to talk to people, but I'll actually sort of push back on that in that if you built something because you just talked to a hundred customers versus over the last few years, your career has brought you in front of hundreds of people that you have talked to and you actually know the customer this well, then you're really well positioned. The idea of just like, starting from scratch and just be like, let me go find 100 people to talk to. Like you're probably not as well positioned as somebody else is to go build.
Rob May: Yeah. Well, it raises an interesting point on the two types of entrepreneurs that I don't think we distinguish enough in the market, right? There's people that are entrepreneurs because they're like, I'm an expert in this and I saw an opening because it's my industry and everything else. And then there's a smaller pool of people that are
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just like, I dig into spaces and I see gaps that should be filled because I understand how markets play out and what kinds of things people do and how technology evolves. You know, and I think the latter group that I mentioned is maybe a little closer to the VC side in terms of how they think about the world, you know, where they see patterns between all these kinds of things. So yeah, and it's crazy because AI is just accelerating all of this.
Charlie O'Donnell: It's interesting that you bring that up and it's, you kind of brought us a slightly subtle point, but I think it's interesting and worth noting that people who decide they are entrepreneurs first, who can see patterns across industries, I do think they might be better at talking to VCs versus somebody who's like, I just happen to be in the radiology lab and I noticed an opening for this space. It's probably unlikely I built any other company but this unless it's literally in my same space. It's
Rob May: Yeah.
Charlie O'Donnell: sometimes harder to generalize that to an investor who literally has never thought about radiology.
Rob May: Yeah, yeah, no, that's a good point. it's also, you know, it's so, so we're in the business of finding unique insights, right? Things that aren't obvious to everybody else yet. And sometimes that unique insight comes from the fact that like, you know, you're deep in something and you understand something other people don't. But sometimes it comes from the fact where you're like, no, no, I understand where this we're in step one of this phase. I know where it goes. likely goes in step two, three and four, because I've seen this type of story play out, you know, many, many times. And so it's like, let me give you an example that's really, really interesting is like, I remember Bijan from Spark Capital talking one time, he'd invested in Runkeeper. He was on stage with Jason Jacobs and they were talking about how consumer companies get built. And he's like, look, man, when people don't do consumer, they don't realize that you always have, it's never just a rocket ship. You have these periods of flatline, flatlining. And he's like, When that happens and your growth slows down, we tell companies focus on engagement and retention for a while until there's a new lever for growth to take off or whatever. And so he's like, we saw this with Twitter, we saw this with Marni Keaton, they saw it with all these companies. He's like, people freak out and they're like, my gosh, growth is slowing. And they're like, yeah, this happens. And there are these patterns you learn about how infrastructure markets work and financial markets work and all these things that are super interesting. But again, to get back to one of your first questions. is compressing all that, right? mean, AI, don't know that it can give you the unique insight yet, but it can help you come up to speed and explain stuff. Here's what's really interesting. The web has been full of primarily mediocre content and introductory level content. Why? Nothing, no, that's just
Charlie O'Donnell: I mean, not the content that we write, but everybody else's. Yeah.
Rob May: it. it's because most people don't produce content. for the love of producing the content or to share their expertise. They do it to get ad traffic or sell it or whatever. And the audience for entry level content, by definition, there are always many more novices in a field than there are experts. And so there's always this bigger market for novice content. And so if you wanted to get really in depth, so let me give you an example. When I was a VC, when I was at PJC, I wanted to learn, I wanted to see if you could take a, excuse me, package up startups in like an ETF. So I needed to know the technical characteristics of how an ETF works. Like when I buy a share of an ETF, what happens? That is hard information to actually find. I had to go to a textbook. had to buy a textbook and read it. But that's the kind of thing that chat GPT or Claude or somebody could walk you through today. Right. And so it's actually made, it's actually made learning about industries a lot easier. Again, still can't generate that unique insight of like, wow, what if you flipped it on its head and did this, but can help you come up that ramp much faster.
Charlie O'Donnell: Yeah, and think there's a certain amount of expertise that comes from seeing a bunch of stuff. I was actually looking a couple of different developer resumes and comparing them against each other. And the analysis that Claude had done was very superficial. And having seen a bunch of resumes and helped my portfolio companies with recruiting and all of that sort of stuff, I was able to of poke at certain things in a way where Plod was just sort of reading on the surface level. And then I sort of gave it some guidance. like, actually think about it in this way. And then it sort of picked up what I was doing. it's good to know that some well-earned insights from being around a while still count for something.
Rob May: Yeah, definitely.
Charlie O'Donnell: So, okay, if I'm a founder, we've got a couple of founders around the table here, and feel free to ask questions along the way. How should I be thinking about the speed of change around me, especially as it pertains to, let's talk competition,
Rob May: Mm-hmm.
Charlie O'Donnell: what things are defensible, and also in particular, how do I convey that to an investor? You're still making investments.
Rob May: Hmm
Charlie O'Donnell: I feel like there's nothing that I can say. that only I can build these days. And so the defensibility of what I'm doing is like a big question on behalf of founders.
Rob May: So yeah, so the way that I think about that, one of the things that's changed in the startup market is as funds have moved earlier and earlier, you've been able to take bets on markets that maybe weren't there, right? So, you know, I think you used to have to be say like, hey, this is an unsolved problem
because there weren't enough companies, there weren't enough entrepreneurs. you go back to like 2007, 2008, there were a lot of unsolved problems that you could just find and go do. That's all saturated and that's hard to find. but you could anticipate problems coming. So for example, you could say drones are a thing. People are going to buy more drones. People are going to need to control multiple drones. It's not an issue yet, but I'm going to start working on a swarm operating system for drones. And that would be a very viable thing to go try to do. And you could probably get funding for stuff like that. And so I think we're in a phase where you're going to have to place more bets like that. So you have to think about Where is the world going next? And how do I want to be positioned? I mean, look, we did this with Neurometric, right? So my company makes small language models. And there's a couple of reasons to use them. One is they're lightning fast because they use less memory and they're smaller and everything else. But the other one is they're very, very cheap. And the big labs have done a great job of branding and people are like, but the models aren't very good. Wrong. On a per task basis, they typically beat the big models. They only do that one task. So we had this insight where we're like, wow, the first wave of AI was about conversational search. That's really what chat GPT was. And if you're building a conversational search engine, you need a giant model that knows everything because you don't know what you're going to ask it. But if you're building an agent that has to do very discreet work tasks, you know, a task like here's QuickBooks, here's our bank statements, reconcile the two. Here's an email, summarize it, right? These are perfect tasks for just a bunch of little SLMs that are fast and cheap and whatever. And as we move to an agentic world, which is where I think we're going, that is this. So we started building this at a time when it was really hard to raise money. I mean, definitely a year ago, but even like really four months ago, it was still hard to raise money because people were like, Rob, people don't care about inference costs. like, you know, first it was people don't care about inference. Then it was people don't care about inference costs. Then it was like, but the big models blah, blah. And I will tell you like in the last two months, it has been like a deluge of people that are like, I get emails from people that are like, my gosh, we're spending so much on inference. Isn't this what your company does helps with it? I'm like, yes, yes, yes. And like investors that we talked to six months ago coming back. So I think you have to take bets on where the world's going. And the way you have to think about is, think there's two, two key mindsets. Number one is open AI and anthropic can do whatever they want to do. They have enough money, they have enough talent, they have a lot. You have to think about what are they unlikely to do because they're not incentivized to do it. So a very smart investor was telling me the other day that like, When people are building platforms, there comes a point in the development of that platform where you're like, Ooh, I could go deeper over here, but if I do that, it would actually not be worth it because I could take more of this vertical, but I would lose some of my generalization. That's appealing to people. Right. you know, and so, so that's when companies go to, you know, ecosystems, add-ons, you know, all that kind of stuff. So you think a little bit about what they're less incentivized to do and how you might be a good ecosystem partner for something. And then the second thing is from a defensibility perspective, I think you have to make some predictions about where the world's going and kind of like, you know, it's almost like the road is being built and you're sort of navigating it. And there's a couple of crews up ahead and you're like, which crew do I think is going to have the road done when I get there? know, so, so you got to do that. So I would say it's, it's while some of the execution stuff has gotten easier. The dynamism that that's created in the economy has made it a little bit harder, I think, to figure out where the world's going to go. And is somebody going eat your lunch?
Charlie O'Donnell: It sounds like as a founder, you need to be like a little bit of a student of markets and you need to be understanding how markets develop over and above your understanding of like a particular problem.
Rob May: Yeah, so like, and I give people a lot of examples about market entry. So there's a there's a great book called competition demystified. And it was written by Bruce Greenwald. And he talks about how we you know, he talks about how he's like, anybody here that's like maybe over like 3738 might remember there used to only be like three TV stations when we were kids. And, and when Fox not the news channel, but just the broadcast company came along. It was sort of like, how do you enter this oligopolistic market? And the way they did it was they're like, they sent this signal to the big three that they weren't a threat, right? They were like, we just run reruns of shows you guys don't run anymore. And that's all they did for a couple years. And so the big three didn't try to fight them, didn't worry. Like, like if they had come in and they're like, we've got new programming and like, it would have been a big bad. And they're like, Hey guys, we're just, we're just making money showing the stuff you guys don't even want to show. And they were like, yeah, that's fine. Right. And so, and then they started and they got into some of the early cartoon stuff like the Simpsons and
Charlie O'Donnell: and
Rob May: Yes. And they were like, so now we're gonna run stuff that you wouldn't run because it's too edgy or you know, cartoons are for kids, we're gonna have an adult cartoon. And then, you know, and they did weird
shows like marry with children, which was a little bit like, to risque. And the next thing you know, they had a viable, you know, after 15 years of that, they had a viable competitor where they could launch a crime series or law series or whatever was the new thing. And so you kind of have to
Charlie O'Donnell: competing on local news. had their own.
Rob May: You kind of want to sneak up on people when you do that. You want to send these public signals like we're not a threat. not trying to take your business. And then you take their business. yeah, so I think it's hard. I think you've got to think about how markets develop and where you want to position yourselves and the incentives people have. dude, the other thing that's changed, the big tech companies, 15 years ago, Cisco didn't understand the innovatist dilemma, right? Facebook does. Google does, and they defend really well against it.
Charlie O'Donnell: So if you are, oh, this is a question that popped up from Kevin. How do you think about motes in this environment? And do you have a framework for evaluating which types of motes are truly defensible long term? Or I'll just add on to that. Is anything defensible?
Rob May: So I think economies of scale is always defensible, but that's not a moat you can start with, right? That's a moat you have to build over time, either through going super horizontal or super vertical on something. I think Google on the AI side has economies of scale over inference because they have chips, have models, have talent, they have all that kind of stuff. So that's one thing to think about. And so you can try to build a path to get there. I think... You know, I think brand is going to become a moat more so than in the past. It's always been a consumer moat because you know, when you're going somewhere and you don't know, like you just like that trusted thing that you know, that stands for something. and it's been less so brand matters, but less so in B2B sales. I think it's going to start to matter a lot because people are going to want to like, you're going to be overwhelmed with choices. Everybody and their brother can write a CRM in two weeks now with Claude code. So, you know, having a brand around, you know, uptime or service or support or privacy, like, I think those things are going to matter. I think some of your brands that are around, we have great design, like, I don't think it'll hurt Apple because Apple's got a different business with a bunch of network effects with the apps and the iPhone and everything else. But I think a lot of your traditional B2B companies that were like, we are the great design company. you know, we just hire the best design. I think that's going to go away because that's going to get a lot easier for people to test lots of designs and do lots of designs. I think it's going to be, but I think branding around things that tie back to services you deliver, right? That would be reflected in your income statement. like we pay support
people more and we get the best and we have this automated system that still has humans in it. Or we invested to have, you know, more SLAs of uptime or for AI models, know, latency or throughput or you know, low, low cost inference, stuff like that. So I think those are still modes.
Charlie O'Donnell: It was just interesting you bring up the service model because, was it Anthropic? That, them and a whole bunch of other folks just put about $4 billion into essentially the Accenture of AI, if you will, like,
Rob May: Yeah.
Charlie O'Donnell: like a, a, business that is deploying forward deployed AI engineers to sort of help people build on top of their, their stuff.
Rob May: Yeah, and I don't know how that's gonna play out, right? I think the thing that people forget is I'm not sure Anthropic and OpenAI, like they have some idea where they're going technically, but I think they're trying to figure out the same thing, which is like, what is defensible long-term? And I think they're doing so much, they're trying to form these competitive cooperative relationships with like, Because people are like, is Accenture going to die? Is Deloitte going to die because of these business models or not? And so I think they're trying to find, I think they're doing a lot of experimentation. It's just happening on a really, really big level. So we'll see. I think they want to make sure that they don't lose the, there's definitely going to be a segment of businesses where you still want the human touch at the end for various reasons. Yeah, I'm sure they don't want to miss out on those. So they need to build those relationships as well.
Charlie O'Donnell: Somebody brought up this idea, and I'll get to Krista's question on patents in a moment. The idea of like you corporate buyers in particular always need somebody to blame and it can't be an LLM. Like the example they gave is that the language translation business of outsourced third party translation companies has actually grown in the last. 10 years, which is the exact opposite of what you think it would have done because clearly computers are better at trans or just as good, if not better at translating across different languages. But what has happened is the cost of doing those translations has gone down. So it is worth it for people to translate more stuff. But because it is worth it for people to translate more stuff, there's more liability around it. And whether it's like contracts or terms of service across international
Rob May: Yeah.
Charlie O'Donnell: websites and whatever. And ultimately there's a decision maker at a corporate who's basically like, can't the buck is going to stop with them if they're like, I screwed up this contract because I had, you know, chat, you BT translate this into, you know, Armenian or whatever. And it actually messed up the contract. So they're still outsourcing it if for nothing else than liability reasons.
Rob May: Yeah. And I think that's going to continue to, think people are
going to still want, like how many businesses are going to go install their own server somewhere, even though they could rise. This is why people use cloud stuff and, uh, cloud hosting and all that. So I do, I think that's going to be a good mode as well, which is, we, we bear the risk for your business at the end of the day. And
Charlie O'Donnell: So.
Rob May: then get good at managing that risk, right?
Charlie O'Donnell: So Krista asked the question, now that we've got LLMs, I can furiously apply for 100x the number of patents that I could have done in the past and create a, know, potentially create a moat around myself with various patent applications. Do you think that that is like, What is AI going to do to the patent market and is that going to change the nature of startup competitiveness?
Rob May: Yeah, I think things like that are going to get regulated in a different format. And I'm not sure what it'll look like, but they're going to have to be or else. mean, think about this. You could just build a bot that would, and then you could replicate it with as much money as you're willing to spend. in parallel, you could file, I mean, a hundred thousand patents a day. It could come up with just random stuff and like, you know, as long as it makes sense. So somebody's gonna start doing stuff like that. I mean, you already had one-off lawyers that would do that, right? They would just patent stuff that they think people might invent. And so there's gonna be some, I don't know, legislative way that that's gotta be dealt with. And I don't know what it'll be, but I'm sure it'll be tackled.
Charlie O'Donnell: One of the things around defensibility, and I'm actually somewhat surprised that this hasn't, that more of this isn't out there. I should, I'll probably pitch this to the team at Harmonic because I think this is where you might get some amount of defensibility. I think some of these applications are better when they help people collaborate, especially across companies. And so take VC and the Harmonic case. I can go out and use Harmonic to source a bunch of startup opportunities.
Rob May: Mm-hmm.
Charlie O'Donnell: I can use the public data from Harmonic to see who my co-investors might be on such a thing if I was going to share a deal. But effectively, that's all backward looking. because it's based on things they have already done in the past. No one is keeping intentionality as a saving what people want to do in the future across my network. And I think the moment that any VC investor logs into Harmonic, Harmonic should say, hey, what are you thinking about? What is your future thesis? We'll hold it here. And by the way, we'll make compelling introductions to other investors so that, you if some investor at NEA is like, you know, this is where, you know, the drone swarm thing is going to come into play. It should pop up, say, hey, by the way, have you talked to Rob May about this? Because Rob's also thinking about this and he hasn't made any
investments in it yet, but he keeps his future theses here.
Rob May: Yeah.
Charlie O'Donnell: And then you essentially like would be the default tool for searching scraping because everyone was keeping their stuff there.
Rob May: Yeah, I think that's a big opportunity because again, everything that's backward looking is just going to become ultra competitive. And yeah, this is the direction things are going to have to go is you're going to have to be creative about what's coming next. And you're going to have to be good at figuring out when to jump on that. Right. I, a lot, a lot of industries have an initial false start.
Charlie O'Donnell: What do mean?
Rob May: meaning the first company or two that launches doesn't really win, doesn't do that well. It just creates awareness for people to come along later and do it better when they've run out of money or whatever, right?
Charlie O'Donnell: What do you think about, before I let you go and I want to make sure that everybody gets their questions in beforehand, is the current fundraising environment. And let's put aside the raising it a trillion dollars and all, because that's a whole other market itself. But even just the world in which you've been investing for a while, where an interesting team coming out of Y Combinator that hasn't accomplished much yet is a 30 pre. anybody who's gotten to revenue is priced higher. literally, it feels like no single digit priced rounds. The rounds are getting quite large. And so it's If you're going in prices that high, isn't it going to tank venture returns or are we just hoping that all the returns are 100X what they were?
Rob May: I think it is, right? And it's one of those situations. I mean, I think you've already seen it. SaaS kind of got that way where, I mean, think how many SaaS companies got, you know, 15, 20, 50X revenue. And now you're having the SaaSpocalypse where those companies that raised at $700 million are gonna have to exit at 125 or something. So I think you're gonna, I think this is gonna create a similar dynamic because, yeah, mean, entrepreneurs just forget they shouldn't want this, right? You don't want it. The difference between having somebody sit on your board every company that I've ever been a part of across 135 investments is not always up into the right. They all have moments where they slow down, where they go sideways or whatever. And when you have a board that's like, that's okay, this is normal. We got in at a fair price versus like, everything has to go right and you have to nail it perfectly. Like it's just a different level of stress on you as the CEO and the team. And then macro conditions can change the market. Like, do know what really sucks? Being the CEO of a company that raised that $150 million valuation over the next two years quintupled your revenue and is now raising a down round because macro conditions change. And you have to explain that to your team. Like that's, you know, you just should try to be a little more reasonable. And I think it benefits you in a lot of ways as an entrepreneur to raise it reasonable valuations. But I get it. It's a vanity metric that people measure themselves against even though they shouldn't. And so that's why it happens.
Charlie O'Donnell: How do you defend against that? Are you literally telling founders, don't raise it 30, even though somebody's giving it to you, raise it half that, take double the, like what should a founder literally do?
Rob May: There's a, somebody just wrote a post on this. One of these companies that does shutdowns, this guy basically wrote a post and was like, hey, I see the data from all the mediocre outcomes. Do you know how many companies would make it if they raised it reasonable valuations?
Charlie O'Donnell: Brendan just wrote that it's a sunset.
Rob May: Yeah, yeah. And it's true. I spoke to, when the last election was going on, you remember there was this whole thing of like, There's no &A because the FTC is blah, blah liberal and what are like not true at all. If you talked to, corp dev heads at big companies, cause I had this conversation several times and I was like, yeah, you know, you're hoping for Republican administration that'll be, and they're like, we don't care. That's not the problem. They're like, the problem is all the investors and founders want ridiculous outcomes that we're just not going to pay. we'll, we'll, wait. They'll be forced to come down. And that was the issue that was holding it up. the press didn't report on that, didn't talk to those people. And so I think there's a big difference. People forget when you raise it at a six post or a 12 post or even a 20 post, there's a lot of exit opportunities. A lot of companies can get acquired for 40, $50 million. In fact, if you have a good tech and million bucks in revenue, somebody might pay 50 million bucks for your company just because they know if it's at one, they can take it to 20. Right. So but if you you know, you
Charlie O'Donnell: And by the way,
Rob May: you raise
Charlie O'Donnell: if you own the vast majority of that company and you've raised appropriately, that's a really nice outcome.
Rob May: Yeah, know, somebody, I forget who said this, but seven or eight years ago, I remember reading a blog post that somebody had written where they were like, hey, we'd gone through one of those phases that tech goes through sometimes when people like bootstrap, bootstrap, you should bootstrap. I don't know, some companies you can, some companies don't, it doesn't make sense. But this guy was basically like, in my experience, a bootstrap company and a VC backed company that both exit in the same industry, the founder ends up about the same. He either owns, you know, 70 % of his company that sells for $100 million or 9 % of his company that sells for $700 million. Either way, it ends up being roughly the same outcome for the founder, different paths along the way. so I just think people have to, yeah, people should be
Charlie O'Donnell: So,
Rob May: reasonable.
Charlie O'Donnell: so I want to, and we'll end on this. and I want to ask this question in a, a way that, um, cause I see this a lot. Um, so one of the founders is asking about a million dollars in revs. They're in a big market. I have some pending IP. They're raising a seed round, trying to raise around 20, uh, trying to raise at 20 rather. And. I would love for you to comment on the comparability of startups, because this is a question that VCs get a lot. And they'll give you a couple of details and they say, what are you seeing for companies like this? Like, where is the market for companies like this? What do you think is the best way to answer that question for founders? Because I don't necessarily think it's, you have a million dollars in revs, so that means... you should expect X valuation because it's a little more complicated than that. But why and what should founders consider?
Rob May: So I think there's two vectors. One, there is this macro vector of what is the market like at the moment. And markets are what they are, for better or for worse. They're the summation of a lot of people. They are often wrong for short periods of time. So it's very likely as a founder, you're going out to raise for an idea that in six months may be the hottest thing in the fucking world. But like right now, people
Charlie O'Donnell: This is not.
Rob May: just don't like your space for whatever reason. And so that's reality that you have to deal with, which is sometimes like, FinTech valuations are compressed or like, can you imagine trying to do a pure SaaS company, you know, earlier this year? I mean, it would have been terrible. And so, so you have to think about that. On the flip side, I think the key thing for founders is I, I, I don't like the whole like, yes, there's patterns. But successful companies are rare. They're fundamentally idiosyncratic. They're fundamentally, there's a fit. And sometimes it's a really tiny thing, right? It's like your business model allows you to offer a package, a pricing option that nobody else did. And that was your wedge into the market that made it Or you tried a channel early that didn't work for most people, that most people didn't think would work, that actually turned out to work for this market. You know, there's a lot of weird things that you, you you, you had a novel feature that became really popular because I said, those are the things you have to think about. Figure out what that is or what you think that is likely to be and focus on that. Right. And don't, and so, I, and so I'll tell you our, favorite sales tactic. And this comes Charlie from our mutual friend, Todd Earwood would taught me this. Um, it's called feel felt found. And what you do is you don't confront people and push back. you acknowledge, but you explain why it's different, right? So what you always say when somebody says, yeah, but you know, we don't like FinTech companies, we don't like SaaS, whatever you go, I understand why you feel that way, right? So that's the feel part. Understand, acknowledge. In fact, most of the people we talked to, they also felt that way until they found out that, so you kind of go, yes, I agree. Most people agree with you, but you know what changes their mind is when they learn this idiosyncratic thing about our company that's different. And I think that's what you have to figure out and lean into and make them feel like they're being led in on a secret.
Charlie O'Donnell: Gotcha. And I think the other thing I'll add to that is anything about what revenue you have now doesn't necessarily tell you the story of where you plan on taking it. so, you know, I've said this a million times. It's like fundraising is a reward for the past. Oops, sorry. I'm going let it in a package. Fundraising is not a reward for the past. It's selling a ticket to the future. And so the fact that you have gotten up to a million dollars in revenue up to this point does not, does not let tell me like, you know, that you are going to take it to 10 or 20 or 30 or whatever your future path is for this company. So Rob, listen, thanks for making the time. I really appreciate it. And, by the way, I just also wanted to point out you were talking about companies being too early to stuff and then the market sort of figuring out like, I think this is what this person does. That actually just happened to me because I had listened to the pre-QL, did they pronounce it pre-QL? Leah and her companies, all in the AI in New York podcast. And
Rob May: yeah.
Charlie O'Donnell: somebody had posted looking for a company that like, however they described it, like cleans up data and all this sort of stuff. And I had heard them pitch before and I left in the comments, I'm like, I think this is what these guys do. then Leo was like, yeah, this is totally what we're doing. And they were very early to doing that data cleanup stuff. And like now the market is like coming around to them. So that happens all the time.
Rob May: Oh, dude, that's great. So I'm going to add that to the AI and NYC show website. Come in and just type and search and we'll do we'll just plug it in chat GPT and we'll index all the New York companies and you can find a New York tech company that does what you need.
Charlie O'Donnell: There you go. All right. Thank you, sir. Appreciate the time and hope to see you around in person soon.
Rob May: Yeah, thanks, Charlie.
Charlie O'Donnell: Okay, no problem.