Brian Smiga: Hi, this is Brian Smiga of Driving Alpha. I’m the co-founder of Alpha Partners. We’re the pro-rata growth fund that works with early-stage funds like Ben here to monetize their growth rounds when they get to $10 million and greater in revenue. So, Ben, welcome. Ben of 2.12—now, soon to be Blue Moon. Let’s hear about that renaming story.
Ben Orthlieb: Thanks. Sure. First, thank you for having me. The renaming story is fairly easy. In fact, we used to be called 2.12 because it’s a nod to our process for founders. However, it turned out that, A) nobody spells it the same way, and B) it made a strong association with New York—which we have nothing against—but we actually invest all over the place. I know, I know—we didn’t try 917 either! But it was a tough name and hard to keep going with it. So with the new fund, we decided to change our branding, renaming the fund to Blue Moon, which is launching later this week. So by the time the podcast is out, it will be official. The new website will be bluemoon.vc.
Brian Smiga: Fantastic. I think there’s a lot in the name. So quickly unpack 2.12 because everyone I’ve ever told about your model—including many, many founders—really finds it very smart. So there is meaning under 2.12, and there’s even better meaning under Blue Moon. You want to unpack those two?
Ben Orthlieb: Yes. 2.12 was the clarity of our process for founders. We do small checks, so founders cannot expect—or should not expect—to do multiple calls and not know when we’ll respond to them or follow up. 2.12 used to stand for two Zoom meetings and the answer the next day at 12. That’s our engagement process with the founders. We do a lot of research—and I can explain how, with a lot of AI—to get to those meetings. So it’s a quick engagement with founders where we evaluate their business in the first call, and we evaluate them and their co-founders as people in the second call and give them an answer fairly shortly thereafter.
Brian Smiga: That’s very founder-friendly. Okay, we’re going to get back to that. But now I know exactly why you’re called Blue Moon. Tell us why.
Ben Orthlieb: Oh, you know exactly why we’re called Blue Moon?
Brian Smiga: I want you to tell the story.
Ben Orthlieb: Well, I think—so one of our mentors is James at NFX, and he’s the one who effectively gave us the green light that we need to change the name. We spent time with him to think through archetypes, what we wanted to stand for. We noodled on this for a while and tried many combinations. We landed on Blue Moon in part due to the expression “once in a blue moon,” which is a little bit the type of founders we’re looking after. But also for the imagery that it evokes, because it’s very related to creators—which is effectively the founders we are trying to back.
Brian Smiga: I totally agree. As a reformed entrepreneur turned VC—and really an innovator on the VC front—I think Blue Moon is exactly right. I mean, whether it’s Peter Thiel or Outlander or you—we’re all looking for that blue moon. Now, there’s a method to your madness. This is one of the reasons I wanted to have you on the show is because this show’s about driving alpha, introducing VCs that have a unique edge in how they drive outperformance—without bragging. Tell us the origin story of what you observed and what you put together three years ago. Give us the essence of your edge and how it has evolved.
Ben Orthlieb: So where it starts is really when my co-founder and I became scouts for Emergence Capital. We started playing the game the traditional way—if you’re a scout or if you’re an angel. And quickly, it’s been a topic of conversation for many years—but once we were in the game, we quickly realized that the traditional game doesn’t work. It works if you’re a top brand. You’re Sequoia, and if you’re already established, it works. But for some reason, the model that everybody else tries is a very similar model. Whether you’re a star angel—will you ever have a bigger name than Elad Gil? Unlikely. Or whether you’re a spinoff of a fund—a good fund—those don’t turn out to be particularly great either. And so it’s a brand game and a network game.
The traditional path is to do larger checks, big ownership, and frankly have a portfolio that is concentrated at seed. It works for a few funds, but our name is not Sequoia. We’re building a brand—so in 10 years, maybe we can be there. But we don’t have that brand today. So we quickly realized that if we wanted to generate alpha and build a firm to win over the long term, we needed a different approach. And that’s what we’ve built over the last few years through our first pilot fund, and we’re continuing now with our new fund under the name Blue Moon.
Brian Smiga: Yeah. And that approach—using AI, using sophisticated data analysis algorithms—was controversial maybe four or five years ago, but now everyone’s doing it. But are they really doing it? And tell us what you have built.
Ben Orthlieb: Yeah, maybe we’ll start with the fundamentals, because the AI is a means to an end. As opposed to what you’ll see a lot of people do, which is, “Oh, I need to now have an AI angle”—which makes sense. Every company, including VCs—even though VC itself is a very low-tech business—everyone is getting excited about sourcing and effectively adding a little bit more deal flow.
Back to maybe the founding principles—or the first principles. Acknowledging that we wanted to play a different game, that we needed to build a brand over time. The first one is: at the early stage, at seed, where we play, 90% of what matters is really the founders. There’s been research at LinkedIn and other places that clearly states that there are very few signals that are useful outside of the founders at seed.
Second, you actually need a pretty deep portfolio. That’s just the math. AngelList has done some wonderful work on this. But it’s the math of seed returns. You need a pretty deep portfolio—which for us means about 15 investments per fund. You need to avoid adverse selection. The top founders want the top VCs, and vice versa. If you are leading a round and you’re not fighting with top VCs—why are you leading this round? Of course, there are exceptions; there are plenty of stories around that. But on the aggregate—and we have sort of in-sample data that proves this—when you invest, just the pure presence of a top VC in a round effectively doubles the chances of success of a company.
So, we want to co-invest with top funds. And the way we do this—how it translates into the strategy—is smaller checks and actually being highly collaborative with top VCs. So if you turn these first principles into our strategy, it becomes clear, and it explains why we need so much tech. One, we want to see every potential team that is building something in B2B North America. At the seed stage today, we source about 9,000 teams every year—95% through data, various data signals, and data pipelines, if you will. But top of the funnel, 9,000. We see three to four times as much deal flow as most of the top funds. It’s impossible to analyze with associates—and we don’t.
So the second part of the strategy is to analyze everything, which means analyzing every team. We use machine learning to screen founders based on their backgrounds, their history, and their personality—personality inferred outside-in. We don’t use questionnaires or anything like that. This helps us effectively focus on the 300 to 400 companies or teams that have the most potential, according to our algorithm, to go from seed to Series A.
Brian Smiga: Let me stop you there real quick. So you start with a top-of-funnel of 9,000, and your analysis of the teams—I think plural is important here.
Ben Orthlieb: Yes.
Brian Smiga: The artifacts that they leave on the web—where they’ve gone to school, what they’ve built, what their domain expertise is, what they’ve done in social—the combination of multiple founding members of a team…
Ben Orthlieb: Yes.
Brian Smiga: That cuts the herd from 9,000 to 300.
Ben Orthlieb: 300 to 400, yes. That we engage with.
Brian Smiga: Right away, you’ve got to tell us—we’ve got to cut to the chase. That 300, starting there as your starting point—what kind of results are you generating with this? I know there’s something that happens between the 300 and the ones you invest in, but just give us a peek at what this method enables you to do from a graduation rate in your fund.
Ben Orthlieb: We overperform not only the market—that’s not the goal—we overperform the best VCs. To give you a sense, our investments from 2021: 50% of them have graduated through to Series A. For 2022 and 2023, that rate is at 44%. If you take 2022 for example, the average graduation rate from seed to Series A from top VCs is 28%. If you marry top VCs plus our score, you get to a target of about 35%, and the rest of our process adds another 10%. So all in all, we get to a graduation rate in the 45% to 50% range for the last three years—which is much higher than the market, much higher than top VCs that we follow, and not surprising.
Brian Smiga: What is the market compared to your 45%?
Ben Orthlieb: Market is 14%.
Brian Smiga: Just explain why this ratio of graduation rate is important—I think it’s obvious, but more importantly, the speed from seed to A is important as a measure of success.
Ben Orthlieb: The graduation rate is important because it’s effectively the Moneyball story. You cannot become an IPO or a unicorn if you don’t get from seed to Series A. That’s the first proof of traction. The component of speed is important because—again, research from AngelList, who sees 50% of the data on their platform—shows that graduation rate from seed to Series A within a specific time period at a fund level is actually predictive of future results and tends to stay constant fund to fund. Meaning, the funds that do well on that ratio continue to do well, and the managers who don’t continue not to. It’s a reflection of brand and picking ability effectively.
Brian Smiga: Fantastic. Now let’s go backwards a little bit. This is great—I see the results, they’re impressive. In fact, they’re the best I’ve seen.
Ben Orthlieb: Okay. Thank you.
Brian Smiga: And I’m a growth investor, right? So I’ve got no horse in this race. We work with folks like you and it’s great to know you, getting to know you over the last two years. But the question is, how do you crack the round open with a small check of, say, $250K to $500K, as you’re going to do in your next fund?
Ben Orthlieb: Yep.
Brian Smiga: You’ve got these founders—we’ve already established—they may be top quintile. Then through your two-meeting process, maybe you get to top decile. They don’t need you. They’re with a top-tier investor. In fact, you won’t invest unless they have a top-tier investor. So how do you crack open that round and win?
Ben Orthlieb: It’s a combination of things, really. But maybe I’ll read you actually an email from a founder that we had the second meeting with yesterday, because that’s what happens: “Hi Ben and Omar, it was a pleasure to meet you today. We’d love to have you on our journey to disrupt the way…” (from their product). “Not only did we enjoy our conversation today, but we believe that you can highly contribute from your experience to Bagel’s success. We’ve also never had a call like this one with other VCs.”
Brian Smiga: What is it? A love letter?
Ben Orthlieb: So, no—it’s a very personal conversation. So here’s why we win at the various steps. First step is to actually get in front of them, right? I find 400 people that I want to talk to. The average VC outbound talks to one in three people. We talk to three in four people that we meet. That’s a combination of things—we use machine learning, and we have effectively, at this point, an AI associate that helps analyze companies. It helps me write a cold email. Between cold email and introductions, I get a three-quarter graduation from “I want to talk to Brian” to actually talking to Brian. Pretty hard. Unheard of.
Before the first meeting, I send them a complete analysis of their company—which founders very much appreciate. I tell them an AI found them. I tell them, “Here’s what my AI thinks of your company,” and all of them say, “This is amazing,” because this is a reflection of how we come across on the internet, and nobody has given us that mirror.
We have a first meeting. The reason they talk to us also at first is the clarity of process—it’s a small check, so the stakes are a little bit low. Where we really win is in that second conversation. If you go back to the first principle, which is what matters the most is the founders—everyone agrees with this. Nobody acts on this. For us, the screening with machine learning is all about the founders. But for us, the alpha of the process is a deep conversation with the founders about basically why they are founders. It’s irrational to be a founder. What drives you? It is—I mean, every founder knows that it’s irrational. And they know that at seed, what matters is them. You know they’re going to pivot. And so we just had a couple in the last few days. Those conversations are: Are you the first entrepreneur in your family? Your sibling runs the company that your dad started—how do you feel about this? Or, what choices did you make in life that led you to this? What other choices would you have made? What’s your relationship with your siblings?
So it’s a deeply personal conversation.
Brian Smiga: Very interesting. Very interesting. So now, where does the science come from in asking these kinds of personal questions of the founding team? Would you say you can share…
Ben Orthlieb: There’s research on traits and motivators, and you’ll find that— I guess not surprisingly in hindsight—the traits that top founders, not just people who become founders, but top founders with performance, are actually fairly similar to those of Olympic gold medalists. Effectively, it’s irrational. You’re signing up for 10 years’ worth of pain, and the odds are not great. And so, why are you doing this? That’s the conversation we’re having.
Brian Smiga: Excellent. And this is with, like, four or so of the founding team—it’s not just with…
Ben Orthlieb: So it’s all the founders. All the founders are on the call.
Brian Smiga: And the way they interact—is that important too?
Ben Orthlieb: Yes. In fact, that’s often one of the things that we see and can lead us to not invest: when we capture on this call that there are red flags around dynamics. So we’ve moved away from a few deals because of observing dynamics in the calls—as opposed to the individual answers from the people themselves.
Brian Smiga: Okay, so now you’ve had your two meetings. You decide you want to make the investment. Does that conversation happen? And what are the terms?
Ben Orthlieb: We join a round where there usually is a lead. So for us, because of the adverse selection first principle, we need a VC who’s what we call a signal VC. They don’t have to be the lead, but we need other top VCs in the round to be able to join that round.
Brian Smiga: On that list of top tiers?
Ben Orthlieb: About 50.
Brian Smiga: Okay. We do the same thing at Alpha. Sounds good.
Ben Orthlieb: Yeah. And we use in part that metric that I mentioned—the graduation rate within a certain time period—to evaluate people. So sometimes there are new funds; you can go check their prior investments, things like that.
Brian Smiga: Great. And now, if they’ve recently raised, you maybe get into that round—they open it up for you. But if not…
Ben Orthlieb: That’s right.
Brian Smiga: Are you then in line, and they’ve reserved a place for you?
Ben Orthlieb: That’s another place where we prove our worth, right? So our value proposition is a number of things. We pay for services. We take from our management fees to invest in services to help them: an executive coach who has three exits, a CTO, an engineering team, a mentorship program, sales coaching, and support. So they get that as part of the package—which is also part of why we win.
Brian Smiga: After you’ve invested?
Ben Orthlieb: No, no. We do that after an investment, but we share that with them—that’s part of our value prop. If they haven’t raised yet and I like what they’re doing, that’s where the social network we have with VCs comes into play. VCs trust our recommendations—top VCs.
To give you a sense, last year I made 278 intros between founders and top VCs because I met founders, I liked what they were doing, and if they were raising and looking for a lead, I shared them with a number of folks and made a lot of intros.
Brian Smiga: So you’re making friends—these 278 introductions.
Ben Orthlieb: Yes.
Brian Smiga: How many of those go to an investment? Like you make 278 introductions—how many graduate to an investment post-intro?
Ben Orthlieb: Over the last six months, NFX and Emergence have made investments that resulted from our introduction.
Brian Smiga: Okay, that’s how so much of VC works. It’s karma. It’s giving value to get value.
Ben Orthlieb: The interesting thing that happens in being this active network participant is we actually get private market read. What I mean by that is—I find Brian at Alpha, and I think you’re doing something super interesting. You’re raising. I share you with a few VCs. They tell me, “Oh, I’ve met Brian. Here’s what I think. Here are maybe competitors that I’ve seen of Brian’s. You may want to check them out.”
And so there’s signal in the feedback I get from VCs—even as simple as the number of introductions I’m being asked to make as a ratio—it gives me a sense of, is a topic hot? Is a founding team exciting?
So it’s easier, from a timing perspective, if I get in when the round is just about to happen or even a week or two before and we can do a quick SAFE. But I get strong signal and generate a lot of goodwill if I meet founders early—which we do through our approach—and nurture over time and can get signals.
Brian Smiga: Okay. More in the day-in-the-life of Blue Moon and you. You mentioned this AI agent that prepares you for the meetings and reflects what the company really is doing—better than most VCs calling up these founders. How did you build that?
Ben Orthlieb: Sure.
Brian Smiga: How is that agent getting better? What is that agent’s name? Can I borrow that agent? How much do you pay them?
Ben Orthlieb: All I pay is the tech costs—which still is our number one cost. But to give you a sense: so I’ve mentioned the machine learning for screening. That agent—if you want to call her that—is called Agatha, like the precog in Minority Report. Agatha helps me see into the future of founders.
After that, we’ve built an agent called Da Vinci. Da Vinci, under the hood, is an enterprise RAG—retrieval-augmented generation. We continuously build a knowledge base for Da Vinci of the best early-stage writing: all the top VCs’ writings, Substack, podcast interviews, founder interviews, industry analysis, and industry reports. We continuously ingest all of this to make Da Vinci better and more knowledgeable.
So Da Vinci, as of today, has about the equivalent of 200,000 pages of content that it analyzes and slices multiple different ways to best answer questions about industries. It’s also morphing into—giving you a peek into a future product—a full virtual board member for founders. But for my use, Da Vinci helps me understand a company.
When I go into a meeting with a company, I generally have three or four bullets on product-market fit, market opportunity, technology, and execution—and even a view on strengths and risks, with sources. So I can refer back to some of the articles it’s using to make this analysis. I didn’t use to do this, but now I share it with founders—and they absolutely love it.
Brian Smiga: Amazing. Okay, so this process you’ve built and invented, really—it becomes your edge. You’ve got the funnel, cutting the herd to the top founding teams you want to look at. You’ve got Agatha. You’ve got Da Vinci. How is it continuing to evolve? And how difficult is it to evolve it? And can you be copied?
Ben Orthlieb: I think it’s hard—partially because it’s a mindset, partially because companies preexist. We work very closely with a number of funds—some of them more or less advanced on this topic—and we try to help them if they’re friends. VCs obviously—people are not stupid—they’re trying to do things with data and AI.
Brian Smiga: Names of funds that you’re close with and that you…
Ben Orthlieb: Sure. We have some infrastructure in common with NFX. We’re close to Foundation—the person—we’ve demoed all our tools to the team at Foundation, actually pretty recently. Emergence also—back to when we were scouts—we’ve stayed very close. So we’ve demoed all our tools with them too, at different stages, sometimes to inspire a little bit of what they could build or where they could go next.
We’re close to Renata and Roseanne at Renegade, for example—stage after us.
Brian Smiga: So I’m happy. I’m happy. We need to now maybe put out to the audience why they should be in touch with you—Ben Orthlieb and Blue Moon. I think you invest primarily in North American enterprise SaaS; is that correct?
Ben Orthlieb: Enterprise B2B, yes. B2B businesses in North America. That’s right. At seed.
Brian Smiga: And could your algorithm—I know your agents may not work as well in other sectors—but could your algorithm for cutting the herd work in any sector?
Ben Orthlieb: It works in any sector. Da Vinci probably also works across a lot more sectors, because we ingest things about healthcare—we don’t invest in healthcare, but Da Vinci is knowledgeable about healthcare, for example.
Brian Smiga: Okay, so if you’re a founder, you’re going to be found by Ben anyway. But how should founders interact? Great founding teams—how should they interact with you?
Ben Orthlieb: They can get in touch, because I will anyway put them into the scoring mechanism and engage if they pass my score. Ideally, if I’m doing my job, I find them beforehand. But of course, we always want to see more deal flow—that’s easy.
Brian Smiga: And unlike many of us, you’re very good at getting back to founders, aren’t you—even with a no?
Ben Orthlieb: Yes, because we have systems for that. My emails get generated. I don’t have a choice but to actually do it.
Brian Smiga: Oh, so your emails are generated.
Ben Orthlieb: It’s the same thing with the following companies. Actually, we capture information all the time.
Brian Smiga: So now, if you’re a top-tier VC that wants to explore more with Ben and Blue Moon, they just get in touch?
Ben Orthlieb: Yes.
Brian Smiga: If you’re an investor—I don’t want to do any solicitation here—but you are raising your next fund, aren’t you?
Ben Orthlieb: Yeah, we’re raising. But we’re also offering our tools to our close friends, which obviously includes our LPs. So if people are also themselves active investors, we can give them access to our tools.
Brian Smiga: A family office or an…
Ben Orthlieb: Yes.
Brian Smiga: …who takes positions in funds—as many do—that’s a win.
Ben Orthlieb: That’s a win-win. You won’t be surprised, but we’ve also designed our own LP portal because we didn’t think Carta was enough. So our LPs get access to real-time info about our portfolio. We also publish insights when we see trends in the market based on companies we meet. So we write a number of insights. For example, I saw a few companies in the last few weeks about AI governance, so we just wrote, based on those conversations, a summary of what’s going on in the space.
Brian Smiga: So I can vouch for how founder-friendly you are, how VC-friendly you are—obviously. I think also now you’re pointing out that you’re pretty LP-friendly.
Ben Orthlieb: Yes.
Brian Smiga: I think you’re making a real difference there. So that’s great. Where do you want to be next? What’s next? I mean, other people are chasing you to a degree, and they’re not exactly copying you, but every VC must now have an AI story. Let’s crystal ball in closing. Where do you predict things are going to go—for yourself at Blue Moon and for the industry—maybe in 2026?
Ben Orthlieb: In some ways, it’s helpful for us to have more VCs that are somewhat data-driven because it validates our approach. The VC, in fact, that we found the closest to us is CoTwo, which is led by the ex-head of AI at Atlassian. We have an edge, and we work with enough funds to know that people are doing things—but it’s hard because of the innovator’s dilemma.
Effectively, people do not want to change their core processes, and so they use AI and data at the edge—for a little bit of sourcing or things like that. The other problem that people face is that the people that develop those tools are not the GPs. They’re not day-to-day understanding how to interact, how to manage the process.
And we keep going, right? We didn’t have Da Vinci a couple of years ago. Da Vinci will be turned into a full board member—virtual board member—for founders.
Brian Smiga: Right.
Ben Orthlieb: Founder advice. It will help with recruiting, and it’ll help with finding your next clients. So we keep moving.
Brian Smiga: You also have a band. Isn’t that true?
Ben Orthlieb: That is true.
Brian Smiga: So what’s the name of your band, and where can we hear you play?
Ben Orthlieb: The band is called Marco and France, per my friend Marco. And you can hear me play in the North Bay of San Francisco.
Brian Smiga: Fantastic. I’ve got to leave it there because I want to finish in under 30 minutes.
Ben Orthlieb: Yes.
Brian Smiga: This has been Brian Smiga interviewing Ben Orthlieb, my friend from Blue Moon Ventures—Blue Moon VC.
Ben Orthlieb: That’s right.
Brian Smiga: Ben has a unique model he’s honed over three years, and I’m really impressed with you, Ben, and what you’ve built. Thanks so much for coming on to Driving Alpha. It’s been a real pleasure.
Ben Orthlieb: Thanks, Brian. It’s always a pleasure to see you.
