00:00:00 David: Welcome to Massive Signals, a podcast exploring the companies defining the next inevitable deep tech industries and the key inflection points that got them from lab to market. Hosted by me, David Mandell, and my co-founder here at Massive, Ari Newman, along with future potential guest hosts from across the ecosystem. We spotlight the journeys of founders, investors, and researchers driving breakthroughs in evolved energy systems, quantum, AI, defense tech, cybersecurity, and the new space economy. Each episode looks to uncover the insights, risks, and hard-won lessons that move deep tech from vision to reality. This is Massive Signals.
00:00:40 Ari: Hi, everyone. Welcome back to Massive Signals. Today, we're speaking with Aziz Gilani, general partner of Mercury Fund, a Houston-based early-stage venture firm with over 750 million assets under management. They're focused on disruptive technology startups outside of Silicon Valley. In addition to his investing career, Aziz serves on the board of the National Venture Capital Association and has been a member of the National Advisory Council on Innovation and Entrepreneurship at the U.S. Department of Commerce. In this episode, we'll dive into Mercury's deep tech investment thesis, how they evaluate founders before writing checks, and the emerging industries and opportunities they're tracking. Let's jump in.
00:01:19 David: Awesome. So we're just going to jump right in. Aziz, I think I have known you for well over a decade at this point. If I'm remembering correctly, I think we originally met at TechStars in 2012, and Nicole introduced us, Nicole Glaros.
00:01:36 Ari: That sounds about right.
00:01:38 David: Sounds about right. So that was quite a while ago. I think at the time, even though you had been at Mercury for quite a while at that point, you were kind of a new partner. You hadn't been a partner for too long.
00:01:50 Aziz: Yeah.
00:01:51 David: You were kind of just jumping into your partner position as a deal owner, leading deals with Mercury, which is a fairly well-known, well-respected fund. Give us a little bit of background about how it felt starting as an intern, working all the way up to partner, and then how that partnership dynamic was, and some of the emotions involved in that.
00:02:09 Aziz: Yeah, sure. I mean, I first entered the VC industry in 2008, 2009, which was prime time for someone to learn. Maybe not the best time in terms of market dynamics, but holy moly, did I get to learn a lot. I was looking at some old NVCA yearbooks, and that was the low point in terms of number of active venture capital funds in the US. There was a trough. If you think of like ‘99, 2000, 2001, you're like way ascendant. And then you had the long decline as funds hit end of life. And so it was a super interesting moment because we were very much a cottage industry at that point. There was only a few hundred venture capital funds on Earth. The average size of a venture capital fund was about 3 people and an associate.
00:03:00 Aziz: That was typical VC back then. So you're talking about an entire industry that was maybe 2,000 people. And holy moly, has the world changed since then. I think the last time we tried to make an estimate over at NVCA, I think we said the industry had grown by 16X between that low point and then when we hit a high point around 2021 in terms of number of operating funds deploying capital. But it really gave me this weird and amazing and awesome backstage pass to see how everything operated because I'm entering into this industry when everyone is running out. And so I'm like, Hi, I'm a new venture capitalist. What can we do? And people are like, Oh, come meet my full partnership and let me tell you everything that we're up to. And so it was a fantastic time to be entering into the industry.
00:03:49 Aziz: I made my first investments in 2009, 2010. As you mentioned, I was the first non-partner at Mercury Fund. And so I tried to rectify that as fast as I could. And the way I did it was I just acted like a non-partner as soon as I showed up because there was no other modality to treat anyone. From that standpoint, it's like when people ask me my opinion, I just tell them my opinion. And then when they didn’t asked me for my opinion, I still told them my opinion. From that standpoint, I just didn't know any other way to behave.
00:04:22 Aziz: In the early days at Mercury, we were still figuring out what we were good at. And so to a certain degree, we spent a lot of time thinking about different business models in wildly different verticals. So if you look at that first 2005 vintage fund, you see a wide variety of different investment types that we were looking at before we focused more in certain areas of specialization. And that was just us just trying to hone our craft and figure out where lessons were learned and applying them as fast as possible.
00:04:53 Aziz: I describe my job here as an investor as, man, our job is to make every mistake exactly one time and then to distribute that knowledge as fast as possible. So it's like I get to absorb all the scar tissue across the portfolio so that you don't have to as an entrepreneur. And so it was very much like share learnings as fast as possible, get them distributed across the portfolio as fast as possible, so that we could all figure out how to play this unfair game together.
00:05:21 Aziz: And I describe it as an unfair game because if you look at the math, startups are not supposed to be successful. We try to take our unfair advantages in terms of our experiences, our technology, our markets, and our customers, we try to figure out how to play this game so that we can all win. And so, man, if we don't use that knowledge across the portfolio, we're not doing it right. So I always looked at my role… it didn't matter when I was an intern or an associate or a partner or a general partner at the firm. It's always been the same game, which has been take the lessons and communicate them across to as many people as possible as fast as possible. That always is the job. Now, portfolio construction, stuff like that, that all comes as you progress in the evolution of the fund. But the core job has always stayed the same.
00:06:09 David: Yeah, I think that's great. Ari and I refer to that as runtime and pattern recognition. Old guys have a little more pattern recognition and runtime than some of the newbies in the industry. And that super helps you frame your context for how you make decisions, why or why you don't invest, and how you drive those things forward and how you can add value as an investor, which is always one of the biggest questions. Like, oh, why should I let you invest? And well, because we've made all the mistakes, we know what not to do. And we can kind of help you avoid those mistakes yourself.
00:06:39 David: So you guys had some real runtime, obviously, as a fund. And obviously, you answered at an interesting time. Markets went crazy. I think we've seen kind of a little pullback now on them. I'd be curious to see what the NVCA data says now about the number of investors in the market. But here's the real question. So the real question is, what was the runtime and the data that you guys used? Or what was the key inflection point?
00:07:01 David: Because Ari and I like to focus on inflection points. What was the key inflection point that got Mercury to, I want to say this right, kind of renew your focus on deep tech? Because I know you guys have a real big background in enterprise SaaS, a lot of interesting industries, you know, not Silicon Valley based. You'd like to be early investors. So like, what were those key inflection points that got you as a firm to kind of renew your focus on the deep tech industry?
00:07:24 Aziz: Yeah, I mean, so deep tech, frontier tech, you know, however you want to describe it, we're talking about taking big swings at very large TAMs with new paradigms. That's the game. And to a certain degree, I feel like that's always been something we as venture capitalists have done. But the verticals that they're applied to, based off the technologies in the markets, that's always a fluid situation. And so when you think about where to apply those learnings, and where to apply your investment capital, you have to kind of play the game that's on the field in front of you.
00:07:56 Aziz: And so when I think about the game that's in front of us right now, I mean, we're just in this magical moment right now, where you have, and I apologize for using maybe some disparaging language here, but you've got some really interesting incumbents out there that have pretty brittle business models that are particularly challenged to dealing with new technology and new innovation. Man, you know, you talk about incumbents, take like the defense industry right now, where you have like these very large stayed and set in the way incumbents that are super focused on making quarterly profit numbers. And that just takes away the ability for them to invest in that new technology.
00:08:40 Aziz: And so with these brittle business models, going against what is the most dynamically changing technology landscape ever, with all kinds of advancements all across the board, it's like the magic time to disrupt these incumbents that frankly looked pretty untouchable a decade ago. And so it's just a super exciting time to go after. In certain degrees, it's like we're elephant hunting right now. I don't know if that's politically correct to say, maybe a big game hunting. Is that better?
00:09:09 Ari: I don't know. I don't think you can do that anymore either, but like, let's not touch that one. Yeah. Hold on. I want to back up a little bit cause – Like there's two big questions I have for you here. One is, you know, Mercury has spent a lot of time in enterprise and SaaS and you're doing more in deep tech again. So you know, it's easy in the industry to say, oh, this VC is a tourist or they're like hanging out in some hot new industry. And David and I have certainly heard our share of stories in the last, even like 90 days of XYZ fund is now like interested in deep tech, like, which is great.
00:09:45 Ari: But let's like unpack it a little bit. First of all, where is Mercury's interest? Why is this a renewed area of focus for you? And then what the hell was going on in SaaS and enterprise over the last like 18 months? And the AI thing that sort of got you guys as a partnership to go, Hey, wait a second, we want to be deploying more capital into going for these giant bets in these other sectors that are very different than where you were playing before. Like what is going on here?
00:10:14 Aziz: Yeah. So, the first thing I'll say is that if you look at the backgrounds of all the partners at Mercury Fund, what you'll find is that our vertical focuses are pretty darn similar to where they've always been. Like, if you look at my partner, Adrian Fortino, he's always been an industrials guy. He's Mr. Michigan, went to that school twice, has always, you know, you know, has done like, you know, two and a half startups in the industrial space. I was talking to him the other day and I was like, Oh man, like, you know, these big swings you're making land, like, you know, industrial tech.
00:10:49 Aziz: And he's like, Aziz. Whoa, I've started more companies in industrial tech that you can like, you know, list out. I'm like, okay, fair. And so, you know, it's like when you look at like what he's doing there, I mean, you know, when I think about how I started my career, a funny story about me is, is, you know, before I could drive a car, I used to ride a bicycle to the first startup I worked for. It was called Access Multimedia Technology. And we were pioneering OCR engines, if you're familiar with those things. Object character recognition engines, which at the time was considered a really big swing.
00:11:22 Aziz: We were trying to figure out how to take like, you know, printed letters on paper, and turn them into some, you know, digital characters that we could actually like utilize and do stuff with. Now, because the technology stack was so immature, it was frontier tech at the time. But you know, that's always been kind of like baked into the DNA of kind of like how these things work. And so when I think about like the market dynamics that make us say, hey, like, what's going on right now, I would say that incumbents across all industries have never been more susceptible to new entrants.
00:11:57 Aziz: And so if you look at like the last decade, our industry had a fantastic run, basically using a tried and true, almost cookie cutter approach to kind of launching SaaS startups to kind of gobble up incremental market share in a pre-existing technology stack. And that was because the cloud computing technology stack was one of those amazing wealth creating devices that we had to take advantage of. It was right there for the taking. And so you had to do it.
00:12:29 Aziz: But in a world in which those technology stacks are now being fundamentally disrupted by new technology, the name of the game is not use those pre-existing infrastructure stacks to kind of build end user facing use cases. That's not the game anymore. The game is use like, you know, start from a fresh sheet of paper now and build net new companies to go after the available space. And the available space right now, it's all about… you know, my partner Adrian talks about first order versus second order type problems. And the first order problems that I think about are, hey, do we have the technology to solve the problem? And two, are there people willing to pay for people to solve the problem? Okay, great.
00:13:18 Aziz: If you solve those two questions, it's just a question of execution now. And so let's take on these massive incumbents that frankly, you know, we didn't… you know, folks didn't have the risk appetite to take on over the last decade. And let's go straight after them and kind of disrupt the game. And that to me is what frontier technology investing is all about. It's taking bigger swings against bigger incumbents.
00:13:39 Ari: It's all… I think what you said earlier is really important. Like it's always been that way when we were building internet 1.0, that was frontier tech at the time. Right? And is there something that's going on with enterprise or SaaS or cloud business models where from a venture perspective, you just don't believe, or still do believe that the returns are there or the ability to truly differentiate and create billion dollar companies is changing? I mean, I think what you said earlier is important. Like so many of these ideas were just incremental variations on a theme, like the incrementally better version of something.
00:14:17 David: It's easy to do. Everyone can do it. And they're trying to do it a little bit better. Right? And I think that's kind of building on what Ari's saying. I think that's one of the keys to deep tech now, as opposed to kind of the software revolution is that most of the challenge in deep tech now, it's actually a combination of software and hardware. Right? It used to either be a hardware company or a software company. And now it's a combination that you have to nail both. So, you know, like it's not as easy as it was where you can just spin up a new software version and kind of take on, like – so I'm sorry. I’m ranting. I think that's the question.
00:14:48 Aziz: No, but I mean, another way to look at the problem is every aspect of that legacy business model that you're describing is under threat right now. First of all, it's very hard to find a moat. And what I mean by finding a moat is in a world in which thanks to a lot of the tooling that we built up over the last decade, building a software application is almost trivial now. So, take that to the extreme. Anyone can build any software for free. Okay. Man, that's super hard to build a moat around.
00:15:17 Aziz: Number two, customer discovery has completely gotten turned on its head. I don't know if you've been looking at like Google search traffic, but one hits, which is where someone just types in something, gets an answer through Gemini and then never clicks on a link has exploded. Okay. So customer discovery is broken. So now all your CAC costs are all kind of, you know, shot to hell. So, then what are you left with? I guess, like maybe like a unique channel strategy?
00:15:41 Ari: Distribution, right? So that's the story now is that if building is free distribution is everything. But if you can't control distribution because Gemini is controlling the search results, then you end up with like a Monday.com situation. Right?
00:15:55 David: But I think the real advantage is, and obviously, you know, Ari and I believe this together, right. And so it's because it's so easy and the moat is virtually non-existent anymore so when the startup costs for company are zero and the moat is virtually non-existent, right? What are the new moats that deep tech are really representing? And Ari and I think about this a lot. Is the moat your deep technical insight into a very specific technology or application that can truly change the industry much more than an incremental way that no one can just read up on and be as good as you are? And is that really where the new opportunities are in deep tech? Like that's certainly, if we look at our past several investments, right?
00:16:37 David: They've been in founders and companies that have such a deep background in the space that they're building in. Like this wasn't just some person with a problem, an idea, right. These were founders that have been thinking about these challenges that they've been working on for years, either a doctorate or scientific level and spinning up truly novel solutions that their background really is the moat.
00:17:00 Aziz: Yeah. I mean, we at Mercury, we talk a lot about a founder's right to win and the right to win comes from the fact that they're not tourists in this industry as you know, you know, to borrow a phrase. These are folks that have spent a good chunk of their lives building up the expertise to have that unique insight to win. We talk a lot about folks who understand the ins and outs of an industry with amazing fluency that gives them a unique market insight.
00:17:30 Aziz: So technology advantage, market insight into what will actually turn this market. And then it's our job as investors to make sure that we've got [inaudible] wins on our side. And if you can kind of put that constellation together of unique advantages and unfair advantages to win, then I think you've got an investment to pursue here. But you got to get all three of those lined up.
00:17:56 Ari: I think maybe there's a fourth. I'm curious for your take on it, which is how important is clear commercial traction or market pull when you're evaluating a company, especially in deep tech.
00:18:06 Aziz: Yeah. I mean, it's super case by case. I am personally a person who, because of when I entered into this market, I am uniquely traumatized by the clean tech boom of 2008, 2009, 2010. And so like, you know, let me just speak for Aziz for a second here. But I lived in a world in which we saw potential for technology and I saw large noises about potential market demand. And we as an industry… I mean, at one point it was the biggest vertical that VCs were investing in. And then, you know, our reward for that over the subsequent years was we watched one by one by one, a lot of these deals just kind of go belly up.
00:18:53 Aziz: And so in trying to deconstruct those lessons learned from that window of time, I've been a lot harder in terms of what the true market looks like for some of this stuff. Because if you look at what we were able to accomplish during that initial clean tech boom, we did a lot of the things that we set out to do. Like, if you look at like the cost of solar on a kilowatt basis, we really drove those prices down. If you look at like, you know, like, the total demand for electricity, that definitely went sky high. So a lot of like the elements kind of like, you know, held true, but the story for some reason, like didn't come together.
00:19:27 Aziz: Now you can point out like potential external competition. You can point at like injections of capital from state actors and a bunch of other stuff. But at least I've been a lot harder in terms of making sure that I can think about the entire investment process from a capital need point of view, because you need to make sure that your company is funded throughout its journey. But then also making sure that there are hard dollars available to the startup as it kind of goes down that path so that we can actually get like customer traction.
00:19:57 Aziz: Now, does that mean that we've got like a hard rule here saying like, Oh God, like we won't invest in anything unless you have pulled in like $10 billion of NREs from external customers? Now, I just don't think you can be prescriptive like that here, but you have to be truly honest with yourself about what that capital flow looks like, or else we might run into making those same mistakes again.
00:20:17 Ari: Interesting. All right. So I have a follow on question then. So one of the things you said, which is it's case by case basis when it comes to traction, right? And then when we're dealing with deep tech and nuanced technologies, where there's a convergence of software, hardware, deep IP, and a lot of tribal knowledge required about the industry, as you said, the founder has to have the right to win. You put all of that together, trying to get a partnership to understand in a deal review meeting, why this is the company we have to invest in right now… it can often be near impossible because the amount of nuance and detail that goes into the diligence process. How do you overcome that? And, like, what is the process of Mercury did to… as you guys dive into these deep tech companies?
00:21:00 Aziz: I mean, you got to trust your deal champions here. So a little inside lingo within the venture capital spaces is the person who kind of finds an opportunity and champions that opportunity you refer to as a deal champion. We also at Mercury, we try as much as possible to pair up on deals. In fact, for a while, I still have to double check with my partners, but for a while, we had an official designation of someone as a skeptic to kind of like push back internally, you know, just saying like, Hey, like, you know, is this assumption really true? Is this really true? Like, like that sort of a thing.
00:21:32 Aziz: But you're totally right. I mean, you can spend a month immersing yourself in a vertical and understanding the ins and outs of a piece of technology. And your reward for that is you're barely fluent with your founder. And then to expect to pull up the rest of a partnership up with you is, you know, man, that's super hard to pull off. And frankly, you know, you'd grind the operation of a firm to a halt if you required everyone to intricately understand the ins and outs of every deal. Like, that's not how you run a partnership.
00:22:02 Aziz: The way you run a partnership is you get together periodically to make sure that you're all looking for like similar types of proof points. So we do regular offsites in which we talk about like our core assumptions. We're very transparent and vulnerable with each other about like, Hey, for this to win, this needs to work, but this falls apart if this doesn't happen. And you have to be very transparent about what those things look like. And then, you know, and then you trust each other to kind of make like really smart decisions here. And when we think someone is, you know, making one too many assumptions, we tell them pretty, you know, candidly. And when we think someone is making the right type of risk, we say, let's go.
00:22:43 Aziz: The other thing is, is we are proudly a non-consensus fund, if that makes sense. Man, if every one of us thinks a deal is going to win, that means that it's so obvious that it's not the contrarian play anymore. It's so obvious that everyone's going to chase that. So, those are almost like… that's almost a sign that maybe you're playing in the wrong space. So the last thing I'll say on this is as a partnership, we're really proud of ourselves that like… just because one person has a strong opinion saying this isn't going to work, doesn't mean that we're not going to do the deal. If anything, it makes us more confident about the deal because it means that it's less of a… it's more of a contrarian pick, which is where you find like a lot of your biggest winners.
00:23:23 David: Got it. So I imagine there's a lot of group hugs going on. [crosstalk]
00:23:30 Aziz: It's like, you know, the sign of a good relationship is bite marks all over your tongue.
00:23:38 David: I don't think I've ever heard that one. [inaudible] So you guys have added a few partners recently, right? Like you guys have been growing as a fund. What's the process like bringing them up to speed on how you guys really work from our culture, how you think about deals and you know, and most importantly, like how are you getting them to think ahead of you guys? Because the assumption is like you want them to really drive the next wave of investments. So what are you doing from a cultural perspective when you bring them on as new partners to get them to think?
00:24:13 Aziz: I mean, I feel like this is a pretty tried and true playbook, but what I've learned is like, Hey, like, you know, in a pretty dynamic industry, what I think is tried and true may not be tried and true. But you know, it's like I do things the way I always learned how to do them, which is you get folks to shadow you on boards. You basically have like an open door meeting policy. So, you know, everyone comes to the investment team meetings and kind of hears us kind of go back and forth.
00:24:38 Aziz: We try to get a lot of reps through. For every investment we make, there are several investments we don't… we're pretty transparent about like how that process works. And we use a lot of Google Docs with a lot of commenting on them as they kind of progress down the pipe. What's it called? I don't have one handy next to my desk. That's kind of a shame. We actually have flow charts that we have all around the office that kind of talk about our investment process and everyone kind of like talks about them on a pretty regular basis. Very regular meetings, lots and lots of collisions.
00:25:06 Aziz: You know, I think some people think we're a little insane, but like we're very much in the office collision type partnership here. So we're always spending physical time with each other and we're always kind of bouncing ideas off each other while grabbing coffee and like sitting in physical rooms with each other. We've tried to embrace technology as much as possible at the same time. We have Zoom rooms all over our office. We try to use like as many of these presence tools as possible to make sure that we have more of those spontaneous types of collisions.
00:25:34 Aziz: But it's all about building reps with each other around a common process in which you try to build up trust over time. And as you kind of go down that path, what you quickly discover is that old fossils like me stop being the source of like the new ideas and they end up becoming the source of new ideas. And that's actually kind of a good thing. You want them to be doing more investments than you, especially because I'm like old and senile at this point. You know, it's like if I have an option to kind of sleep in my own bed, I kind of try to do that. But you know, I'm still clocking in my 100,000 miles a year though. So I'm still not doing the job completely right. But yeah.
00:26:14 David: We see all the pictures.
00:26:18 Aziz: I'm very famous for Instagram selfies on airplanes.
00:26:22 Ari: Do you have a preferred seat? Like do you always try to get the same spot?
00:26:25 Aziz: Man, you know, so I actually have a plaque here from the folks over at United after I crossed a million miles. So they pretty much let me sit wherever I want now. But usually I'm taking a windows. If it's a window versus aisle, I always kind of take window. I actually think that it's a foolish thing to get a meal on a plane. So I never eat on the plane. I'm always on my laptop because that's like my best downtime. The crappy internet I actually think is a feature, not a bug on those things.
00:26:50 Aziz: If there's something that I'm really a fan of, I got a SIM put in my laptop. So it's always online now. So like, so you know, it's like when you fly enough, they let you preboard and like, man, that's 30 minutes of prime email time. And I got time for anyone to, you know, put up a hotspot or anything. So I use the SIM on there. And now, if you're a T-Mobile customer, T-Mobile resells Earthlink. So they have the T-satellite service. So you're always online now. It's pretty great. So I'm a huge fan of that.
00:27:14 Ari: Here's a question for you. So based on what you just described about your partnership and trusting the deal lead, when it comes to you as the lead investor or the one championing a deal, especially in deep tech… like one of the things I've struggled with is, is I can have conviction about the market or the opportunity or, you know, like in our vernacular, Massive, we know this thing is going to be inevitable. It's this market's going to happen. Someone's going to win in that category in some way. But how do you build conviction sometimes with these early stage deep tech companies where like there's infinite vectors of risk?
00:27:50 Ari: There's so many vectors of risk, even if the founder knows what they're doing. What are some of the things you've gone through around this as you look at these companies to get to the place where you're like, I believe this is the company that's going to win in this category when they're still in the lab and they haven't actually proven that they can make the thing work in production yet?
00:28:09 Aziz: So, if I could just amend the setup to the question just by a hair, it's not just that you have to believe that they could win. You got to believe that they can win now. And there's a nuance there, but I want to make sure that we put some timescale on this. And this is because, again, you know, maybe this is the trauma that I'm experiencing from having lived through 2009, 2010, 2011. It's not just about like having that vision for the future, but it's the immediacy of that vision.
00:28:37 Aziz: And so, when you force yourself into the constraint of thinking about the immediacy of a vision, suddenly, you don't have like five years to wait for a market to figure itself out. Because you throw that five years of waiting on top of the scale up of a technology, coupled with like figuring out like a lot of market dynamic – I mean, suddenly, you're in like 10, 15 year territory. And so, for a world that's kind of bound by like certain time-based return profiles, that just doesn't work. It's not very compatible with institutional funds. So, you have to kind of always have in the back of your head the time constraint factor here. And that forces you to think about stuff that's closer to kind of getting there. The immediacy forces you to kind of shortcut your way through a lot of those different types of risk factors.
00:29:26 Ari: Yeah. I think that's really true. And you know, that brings up like a lot of my own scar tissue too. Like I've been investing in deep tech and frontier tech for ages. And one of the things that happens in some of these sectors is they start to capture the imagination and they get a little buzzy. And then the first wave of companies, they all think that they're at these early inflection points because they think they've got the right signals coming to them.
00:29:53 Ari: But the truth is that what often happens is that the industry or different verticals have curiosity about how to apply new technologies to their business. And so, there's all these sort of essentially false flags and actually head fake situations where the company thinks what they're getting is market pull. And the CEO will stand up and say, we're raising the Series B. We totally have product market fit. I need to raise a giant round. And then you find out that all of these companies were really just kicking tires and had curiosity. And that there were some internal mandated, a large corporate to play around with some new technology to learn. And the bottom falls out on the revenue growth. And everyone that thought they were going to do a pilot and turn that into an enterprise license, they never get past the pilot.
00:30:37 Ari: And a lot of the venture community backs up this wave because everyone's chasing this next sector. And the next thing you know, you've got an overfunded sector that's under-delivering on commercial revenue. And now all these companies are over their skis. This has been why we have so much wreckage in hard science and deep tech industries that can't really get to commercial product market fit. And so, we've just seen it over and over again. What do you think about that? And how do you navigate it?
00:31:06 Aziz: There are a lot of facts that you're conveying there that are hard to argue with. The trial problem is always going to be a problem that we run into in any net new technology. You can't get to recurring revenue without having some kind of a trial and pilot phase, especially for a net new technology. That's always there. But there has to be a forcing function to make sure that you stick with the product. And man, it's like part of the industry keeps on running into these problems is because, man, it's just so hard to tell the difference between what's going to work and what's not going to work on a recurring basis. And making sure that those market dynamics that made everyone eager to trial, we'll make sure that they stick with it.
00:31:52 Aziz: There's a fun cartoon that I reposted this morning about that. I think Dave, you actually gave it a laugh symbol. But it was like every CEO in America is like, I need to use AI. What are we using it for? We're not sure yet. I don't know. But we got to use it now. But it's those types of ambiguous crowd, wisdom of crowd type moments that, frankly, are the false positives that you think about a lot. If everyone's chasing the thing, but they can't tell you why they're chasing the thing, they can't put actual economic rewards around why they're chasing the thing, and there's no real advantage to chasing the thing, then why are they chasing the thing? It's a lot less clear and it's pretty hard to get to a real proof point there.
00:32:40 Ari: I feel like the place I always come back to with this is that you've got to look at real market signals or you got to go interview the CFO at a company and understand what their top five problems are. And if you're not solving one of the CFO's top five problems, you're probably a nice to have.
00:33:01 Aziz: Let me just double click on that. I'm from a place called Houston, Texas. If you don't know Houston, Texas, it is the energy capital of Earth. And if you know anything about the oil and gas and the energy industry, man, the mother of all capital intensive industries. These are folks who spend a billion dollars getting an offshore oil rig up and running. And every now and then, I hear about some nifty little software solution for the space. And the pushback that we always have on stuff like that is we're like, man, the problem with the energy industry in particular is the ratio of capital intensity versus the reward for using a net new technology. And if there's too much of an imbalance there, you're never going to get the customer's attention.
00:33:49 Aziz: And so in a multi-trillion dollar industry, saving a billion dollars just isn't on anyone's radar. What's on everyone's radar is securing cheap acreage at the right time using the right upstream techniques. And in that world, maybe tightening up your supply chain by like 2% never was going to move the needle. And it was never going to be considered the thing that anyone wanted to focus on.
00:34:12 Aziz: Applying that lesson to a lot of these other industries really jives with what you're saying there, Ari, which is effectively, hey, if this isn't enough to get the CFO's top 5 priorities, you're never going to cut through the noise of getting them to actually switch to the net new technology. It's just never going to get there. And so the sense of urgency is so critical. Because the act of a customer switching to a new technology is disruptive. It takes work. And so you have to… It has to be top of mind or it's never going to happen.
0:34:49 Aziz: And this is maybe a big difference between what we were seeing with some of the more incremental software businesses versus some of these more important frontier technology businesses. Those things work hand in glove. It was like a slightly better answer that had no switching costs associated with it. And it gave you that incremental improvement. Great. God bless. We did a lot of that in the 2010s. And folks made money doing that. But for these bigger swings, for these bigger changes, you have to be top of mind in terms of the problem that you're solving, or no one's going to put up with the switching costs of moving over to the new paradigm.
00:35:26 Ari: How much do you look at these... Let's use the tailwinds or headwinds analogy, right? How much are you looking at market, regulatory, technical, or even press headline and zeitgeist? How important is that to you? Or do you look at these first principles issues of… Energy is a great one. AI data centers need way more energy than we can produce. We're way behind on the energy production curve. It actually doesn't matter whether we drill or burn atoms or collect solar rays. We need all of it. But then there's all this regulatory stuff. So how do you stack rank those signals as you think about investing in these kinds of companies?
00:36:09 Aziz: Yeah. By the way, fun aside, I'm from Texas. What regulations? We got this thing down here called ERCOT. We have our own power grid down here. But look, when I think about these types of very obvious, call them demand-driven signals, and how do you try to solve against them? Man, I still ask myself the same basic questions I've been asking myself for 20 years, which is, what is my unique market insight? What is my unfair advantage to win? When I think about unfair advantages, if it's a technology-based one, it's like, how long is it going to take someone to figure this out once I figure it out?
00:36:49 Aziz: These sound like super glib, super simplistic approaches to it. But I feel like those are still the right answers. The regulatory risk one is a weird one. And look, I've been a side software investor since as long as I... I mean, a side healthcare investor since as long as I've been an investor. And when I think about and talk about regulatory morass like no other, imagine investing in healthcare, especially around insurance and reimbursement policies and God knows what else.
00:37:19 Aziz: But I always think about like, hey, I still lean back on my old MBA training of looking at Porter's 5 Forces. And I'm like, hey, whoever had the thrust around the initial sets of regulations here, are we on their team or are we on a different team? And I try to figure out whether or not we're fighting on the force of where the market is headed versus not. And man, like in my life, as long as you're on the same side as the market, you tend to be pretty okay in terms of where the demand ends up being. Sorry, that's a super rambly ranty answer.
00:37:53 David: Let's take the ramble and the rant and let's turn it maybe in a little different direction. You kind of touched on these points, but let's focus a little differently. Let's talk about it from the founder perspective for a second. You're an investor. You've seen a lot of founders building a lot of interesting companies. Obviously, we already talked about the fact that this new deep tech wave is a little different than the software wave that we lived through 10 years ago.
00:38:14 David: And so when you're talking to founders, you're looking at early stage investments. What are the key things that you are really focusing on from their perspective? Because a lot of these founders of deep tech, they're very scientific, they're very data driven, but not a lot of them have built businesses before for a lot of different reasons. And so how are you counseling them or what are the things you're thinking through from a key pattern recognition perspective, key inflection points? How are you talking or thinking about, can they actually turn this into a real business from an early stage perspective?
00:38:48 Aziz: Man, I got to tell you, we've looked hard at this problem. And I'm not giving you a law. I'm not giving you a rule. But second-time founders are so good. Folks who have dealt with dealing with trying to get customers to buy a product for money and have lived to tell the tale, there's something different about a second-time founder versus a first-time founder. It's such a beautiful thing.
00:39:18 Aziz: And so man, it's super hard to bet against the second-time founder because they've been through that valley, because they've been through that process. There's something super special about that. Now, sometimes you can fake it. And what I mean by fake it is, I have a founder that I'm on the board of right now. And his father was a repeat entrepreneur in the restaurant space. And so he watched… Basically, from age 12, he was working in his dad's restaurants and had to deal with that. That gave him a lot of founder DNA. And so that helps.
00:39:51 Aziz: But man, there's something special about having struggled through customer acquisition and having to honor a P&L. Super hard to replicate, super hard to teach. Some schools do a really good job of putting this into their students through accelerator programs and stuff. I advise down here in Houston. Rice has this thing called OWL Labs. And I was like, man, if there's only one takeaway, I want them to learn that this is really hard. And I want them to go through the reps of watching it not work. It's like... So when I'm looking for things in a founder, it's like that… I sound like a broken record. But unique market insight that comes from deep technical expertise. But man, if I could… If there is an entrepreneurial DNA to have there, man, that makes this so much easier.
00:40:35 David: Yeah. I talk about this a lot. Too many people start startups because they're sexy and they just want to start something cool. But when you look in their eyes, you understand the people that know how hard this is actually going to be. And that's not something that people understand initially. You and I, we've done a lot of talks at Techstars and for early stage companies. And one of my favorite situations in that early stage conversation is when you're talking to a first time founder and cool company. And they're making good progress. And then you just get to see you on the room and they look at you and they're like… And you see those eyes and they're like, when's it going to get easier? And you have to slowly explain and say, it never gets easier, only faster.
00:41:19 Ari: The problems only get bigger, right? The problems only get bigger.
00:41:22 Aziz: Have I already told you the hot dog story?
00:41:24 David: Which story?
00:41:26 Aziz: The hot dog story. So I went to high school. I went to high school in Houston with this guy named Yasir Salem. Very easy to Google Yasir. We're very dear friends. So Yasser is a competitive eater. And he invites me. He used to be at that final table at Coney Island every year for that hot dog eating contest. And he's super proud of himself. He's like showing off. And he's like, he's like, Aziz. Because I'm at the final table, I can walk into any Nathan's hot dog chain and I can get free hot dogs. And I was like, okay, so I just want to make sure I got this straight. Your reward for eating all these hot dogs is more hot dogs.
00:42:07 Aziz: And so this is like a shorthand I use with my entrepreneurs now. Because I'm like, you know, running a startup is just a hot dog eating contest. Your reward for solving this problem is more problems. Your reward for scaling to this point is you have to scale to this bigger point. It just never ends. You're just going to keep on escalating up the chain.
00:42:26 David: One of the things I used to do, you need like this is, you know, when you look at a founder, you're like, bring it on. Like they want the bigger problems. And it's those people that think it's just going to get easier once they get off the ground. And especially in deep tech, when like the challenges are so big, the valleys are big, the capital needs are so big, right? The time to market, even though it seems small, like it's still like the barriers there. If you're a defense tech, it's understanding how to navigate the government. Your energy is like, it's…
00:42:54 Ari: One of the patterns we see in deep tech over and over again is relatively senior person at giant company gets fed up with giant company, leaves and start something in the sector that they know. So they check your first box for deep technical expertise, domain expertise, a right to be in that market. What they don't know is all of the other things. They just know that they want to go do their own thing because they're fed up with the way that the big guys were doing.
00:43:19 Ari: So it's funny. One of my quick, like my fastest, like no button filters when I was doing a lot of Techstars screening for founders, which oftentimes were first-time founders was the very simple question. Why do you want to start this company? And whenever I heard the answer of, well, this is a big market and I wanted to do a startup. It’s a no.
00:43:46 Aziz: You know, my quickest no’s are folks that have always been at a Fortune 100 company. It is so different trying to work in the context of an existing machine versus building your own machine. It's just so different. You know, in a former life, I launched a new division of a public company versus… what's it called? I was the executive chairman at a startup that was just a true startup. And the problems you run into are just so different.
00:44:21 Aziz: I mean, you know, because, because your primary success factor for launching a new division in an existing company is basically being really good at bureaucracy. It's like, how do you get money out of this budget? How do you get this manager to sign off? How do you get this facilities rec fulfilled? Like, how do you do this? How do you do that? Versus like in startup land, it's just like, do a now and like, and like what is a one-week project in the first example is like, you have 30 minutes to do this now in the second example. And there's no… it's just totally different.
00:45:01 David: It’s totally different.
00:45:03 Ari: I learned my lesson the hard way. [crosstalk] You only learn the lesson once. I ended up learning it twice at the same time because I made the mistake twice at the same time. So I had two pieces of data, right? I was literally on the board and had led the seed round for a company where the executive came from large enterprise, like SAP. Right. And then I had backed somebody else in a different category, similar deal. And I was getting the same lessons coming at me twice at the same era. And I was like, okay, well, got it.
00:45:33 David: My car alert, that whole conversation is in all the companies that I started, I always paid MBAs less. Because it took them so much time to unlearn what they were told, what was going to actually happen versus what actually goes on. And you know, once they actually get it, they can be amazing, but the unlearning curve cost me time in [inaudible] because they were taught, this is how things work. And if you're going to go to a Fortune 500 or a Fortune 100, yeah, absolutely. But if you're going to go to a startup, a whole different world.
00:46:02 Aziz: So, let me ask y'all a question because I'm super curious on this one. What do you think about consultants becoming founders?
00:46:10 David: So as a consultant that became a multi-time founder, I will tell you, kind of thinking back to our initial conversation, it depends on the person. It's all about the person, right? Like if they're in the consulting business because they think they're smarter and they just deserve to get paid more and they don't want to actually do the work and they want to come in and tell you, this is what you have to do. Just, you know, lower cost, increased revenue. That's all they have to do. Right.
00:46:37 Aziz: I started my career as a consultant. I started at Ernst and Young way back when. I was talking to someone who is at EY Consulting right now. And they're on their fourth iteration now of having a consulting practice now because they keep on spinning it off, selling it off to somebody. But man, I tell you, it's like unlearning the mentality of charging yourself by the hour is so hard. Yeah. It is so hard.
00:47:02 David: The outcomes are not [inaudible]. When you're building a startup, it's about objectives. Where can I get the company? That's the value prop. It's not how much time I put into it. No one cares how much time you put into it.
00:47:17 Ari: It's totally the person and how they're wired. Like you end up consulting for experience, but you get this broad, you know, this broad set of instructions. And the CEO of my first company in the nineties was an ex-consultant, but he saw five steps ahead of everyone else and was able to go execute against it.
00:47:34 Aziz: Yeah. I mean, I tell you, you know, it's super interesting. It's like, there are certain types of fields that people come out of and become entrepreneurs. And I feel like each one of those fields has a unique insight that comes with it, but also comes with a super obvious blind spot to everyone but themselves. So like, I've noticed this with consultants and I say this as a former consultant myself, this is the hours put in versus value blind spot because you're trained as a consultant to do something, get something called a utilization rate. And that's the goal is to put in effort.
00:48:09 Aziz: With lawyers, what I've noticed is an over-focus on whether or not you can do something from a legal or from a contractual point of view versus whether you should do something. That's super hard log jam to kind of get past in their heads. With doctors, because there's a structural shortage of physicians in this country, they have no concept of customer acquisition cost is what I've run into.
00:48:34 Aziz: Because again, America has a structural shortage of physicians and that's because we gave them an antitrust exemption. But because of the constant shortage, no doctor knows how to actually acquire a customer. They just say, I'm a doctor and people start showing up. And so they never can think through the CAC problem correctly. But every field has its own unique, weird challenge associated with it as they try to go down this true entrepreneurial journey.
00:48:59 Ari: Interesting.
00:49:00 David: So we want to start close wrapping. So I'm going to ask some interesting kind of fire forward questions now. So based on that, different industries have different perspectives, right? They play, they bring different value props and blind sides to each, to the startup world. Let's kind of flip that a little today. As Mercury, as venture investors, especially as you renew your focus on deep tech, right? So what are you seeing or thinking about as some of the next emerging trends in deep tech that are going to drive massive markets?
00:49:30 Aziz: Yeah. I mean, so look, I live in Houston, Texas, as I've reminded you, I think five times today. There's a lot of space here.
00:49:37 David: That little state in the Northeast, right?
00:49:39 Aziz: Yeah. Yeah. Yeah. Tiny little state no one's heard of called Texas, but you know, so space is always something that's always top of mind here. Aerospace is always super top of mind here. So, you know, it's kind of like, you can't go to an evening spot here in Houston and not talk about like aerospace space. And so, man, like, you know, like I went to Clear Lake High School, which is where all the astronauts kids go. And so, you know, it's like… I'm confused why we don't have cities on the moon right now. But it seems like something imminent always all the time.
00:50:11 Aziz: You know, that's part of the reason why we've invested in like low earth orbit satellites. That's part of the reason why we invest in aerospace companies. But because for us, you know, it seems like one of those obvious things. And man, there's a lot of dollars now kind of getting allocated to the space. And we think there's some imminency there.
00:50:26 Aziz: We see the same thing around like, you know, next generation industrial type applications. You know, Dave, you and I were co-investors on the quantum side of the equation here. I think that's super interesting. You know, the running joke is quantum has been five years away for the last 20 years. But there are so many redundant paths to finding something kind of happen there, whether it's on the locational side, whether it's on the quantum computing side, whether it's on the networking side. But there are lots and lots of paths to success there.
00:50:56 Aziz: Robotics is super interesting right now. I think that something that folks kind of overlook is that AI changed the equation on how to train robots on net new use cases. I don't know if you saw the same optimist demos that I saw, but the ability to like have like, you know, basically throw a camera in front of a human doing a problem and then having a robot replicate like the same motion within like five minutes is super game changing. You can do some super interesting things.
00:51:24 Aziz: We have portfolio companies that operate in the logistics space that do stuff around like distribution centers and supply centers. And robotics are just kind of changing that real time. But there are so many of these like hardware/software/new technology use cases that are just there available for the taking in which the incumbents are so old and are so bad at what they do that it's really, really a fun time right now.
00:51:53 Ari: This is the convergence that David and I keep talking about, right? Like the robotics unlock is really coming from computer vision and AI.
00:52:04 Aziz: Yeah. Robotics to me feels a lot like what smartphones felt like, like, you know, in like 2010, 2011. Man, there was this restaurant app in 2011, 2010, sorry, that just kind of blew my mind. It was like, you know, because for the first time you had like this mobile computing device that was like in your pocket and it was able to take advantage of like the social media reviews that were all crowdsourced.
00:52:32 Aziz: And like the funny thing was, the way it would work is when you wanted to eat, you would shake it and it would make like a little cash register sound. And then it would tell you like the nearest restaurant that had like a reservation available. And it just blew all of our minds. We're like, you can do that now? But that was a combination of like five technologies stacked on each other that kind of gave you like this friction-free experience. And you're seeing that now with robotics, which makes it so much fun. Man, it's just a fun time to be here when all of the things stack on top of each other.
00:53:01 Ari: All right. So on the flip side of all of that goodness and hype and excitement, what do you think is the most like overcooked thing going on in deep tech right now?
00:53:11 Aziz: Man, I tell you.
00:53:12 Ari: And you can't say AI, that doesn't count.
00:53:16 Aziz: Man, I love AI. I don't know about you.
00:53:20 Ari: We all love AI too, but aside from AI, what is the most overhyped, overcooked thing that you think is not going to materialize as a market?
00:53:28 Aziz: Man, every 18 months, someone tells me they finally figured out cold fusion. It's like the perennial Charlie Brown in the football. They keep on telling us they figured it out, and then it keeps on not happening. I think the latest one was one that came out of South Korea a few months ago. They even published papers on it in peer-reviewed journals, and it still ended up not being quite right. So cold fusion is like a pretty perennial one that we keep on missing out on. So that's a real one. I don't know.
00:53:58 Ari: So you don't think Commonwealth will get operational?
00:54:00 Aziz: Man, look, there are... You know, by the way, the first rule of VC is you never make fun of a startup, because holy moly, you'll look like really, really dumb really, really fast in this industry. There are really, really smart people chasing stuff that know stuff that you don't. So man, I'm not going to make fun of anyone in particular. But talking in generalities, that one seems kind of far away. Talking in generalities, I don't know.
00:54:28 Ari: All right. So related to that, is there a one that got away, an anti-portfolio company where you thought you made the right call and you regret it deeply?
00:54:39 Aziz: So this is a true story. I tell this in a lot of public forums. But the first pitch I've ever listened to as a venture capitalist was when I was in Chicago, going to Northwestern. And another Northwestern student pitched the firm I was interning at that I will not name on his idea called The Point. And so he comes in, he pitches this thing called The Point. And as he walks out of the room, everyone at this firm is just making mercilessly fun of this idea.
00:55:13 Aziz: The Point was this idea. It was actually built on the shoulders of another crowd-sourced business in Chicago called Threadless, in which you would get people to vote on ideas. The Point ends up becoming Groupon. So that was the very first pitch I ever heard. And we obviously did not do that deal. And I know the people who did that deal. And they're very, very happy that they did that. That was the very first pitch I ever heard.
00:55:38 David: That's a great story. I think we all kind of have stories like that. We could keep going forever on this topic, but we do need to wrap. So, Aziz, I just want to interrupt you. I want to say, when people ask me about you, I describe them as, aside from being an amazing investor and an [inaudible] personal good friend, I describe you as being like Tigger without the ego problem. And you have 100% lived up to that today. And we are deeply, deeply grateful for your time with us today and being a guest on Massive Signals. And I hope I see you very soon.
00:56:08 Aziz: Yeah. I mean, I'll tell you, it's like... The thing I love about this industry is that you only get to survive in this industry for any prolonged period of time if you end up just being... It's very hard to be successful in this industry if you're just a jerk. Because...
00:56:25 David: But they're out there. But they're out there.
00:56:28 Aziz: I mean, look, look, look. We are not an industry of saints by any stretch. But it's like the longevity of friendships like yours and mine, Dave, are the reason why I love this job. And they're the reason why I love these relationships. I love running into you on the beaches of Aruba. I love… Yeah. I love riding Shinkansen with you for milestone birthdays. I love harassing sushi chefs at the counters at hard-to-get-into restaurants. These long-standing relationships that really make this industry work for me. And thank you for being a huge part of it.
00:57:06 David: By the way, I'm honored to be a part of it. And thank you so much for today. And I hope I see you soon.
00:57:13 Aziz: Good to see you guys.
00:57:14 Ari: Thanks for being on. See you soon.
00:57:15 Aziz: Thank you.
00:57:17 David: Thanks for tuning in to Massive Signals. If you enjoyed today's conversation, be sure to follow us on Spotify, Apple, or YouTube. And share the episode with someone who cares about the future of deep tech. And subscribe to our substack at massive.vc to stay in the loop on all of our current investments, thinking, as well as upcoming events like our quarterly deep tech table dinners, and the second annual Deep Tech Summit May of 2026. Find it all at massive.vc. Until next time, keep listening for the signals that are shaping our future world.
00:00:40 Ari: Hi, everyone. Welcome back to Massive Signals. Today, we're speaking with Aziz Gilani, general partner of Mercury Fund, a Houston-based early-stage venture firm with over 750 million assets under management. They're focused on disruptive technology startups outside of Silicon Valley. In addition to his investing career, Aziz serves on the board of the National Venture Capital Association and has been a member of the National Advisory Council on Innovation and Entrepreneurship at the U.S. Department of Commerce. In this episode, we'll dive into Mercury's deep tech investment thesis, how they evaluate founders before writing checks, and the emerging industries and opportunities they're tracking. Let's jump in.
00:01:19 David: Awesome. So we're just going to jump right in. Aziz, I think I have known you for well over a decade at this point. If I'm remembering correctly, I think we originally met at TechStars in 2012, and Nicole introduced us, Nicole Glaros.
00:01:36 Ari: That sounds about right.
00:01:38 David: Sounds about right. So that was quite a while ago. I think at the time, even though you had been at Mercury for quite a while at that point, you were kind of a new partner. You hadn't been a partner for too long.
00:01:50 Aziz: Yeah.
00:01:51 David: You were kind of just jumping into your partner position as a deal owner, leading deals with Mercury, which is a fairly well-known, well-respected fund. Give us a little bit of background about how it felt starting as an intern, working all the way up to partner, and then how that partnership dynamic was, and some of the emotions involved in that.
00:02:09 Aziz: Yeah, sure. I mean, I first entered the VC industry in 2008, 2009, which was prime time for someone to learn. Maybe not the best time in terms of market dynamics, but holy moly, did I get to learn a lot. I was looking at some old NVCA yearbooks, and that was the low point in terms of number of active venture capital funds in the US. There was a trough. If you think of like ‘99, 2000, 2001, you're like way ascendant. And then you had the long decline as funds hit end of life. And so it was a super interesting moment because we were very much a cottage industry at that point. There was only a few hundred venture capital funds on Earth. The average size of a venture capital fund was about 3 people and an associate.
00:03:00 Aziz: That was typical VC back then. So you're talking about an entire industry that was maybe 2,000 people. And holy moly, has the world changed since then. I think the last time we tried to make an estimate over at NVCA, I think we said the industry had grown by 16X between that low point and then when we hit a high point around 2021 in terms of number of operating funds deploying capital. But it really gave me this weird and amazing and awesome backstage pass to see how everything operated because I'm entering into this industry when everyone is running out. And so I'm like, Hi, I'm a new venture capitalist. What can we do? And people are like, Oh, come meet my full partnership and let me tell you everything that we're up to. And so it was a fantastic time to be entering into the industry.
00:03:49 Aziz: I made my first investments in 2009, 2010. As you mentioned, I was the first non-partner at Mercury Fund. And so I tried to rectify that as fast as I could. And the way I did it was I just acted like a non-partner as soon as I showed up because there was no other modality to treat anyone. From that standpoint, it's like when people ask me my opinion, I just tell them my opinion. And then when they didn’t asked me for my opinion, I still told them my opinion. From that standpoint, I just didn't know any other way to behave.
00:04:22 Aziz: In the early days at Mercury, we were still figuring out what we were good at. And so to a certain degree, we spent a lot of time thinking about different business models in wildly different verticals. So if you look at that first 2005 vintage fund, you see a wide variety of different investment types that we were looking at before we focused more in certain areas of specialization. And that was just us just trying to hone our craft and figure out where lessons were learned and applying them as fast as possible.
00:04:53 Aziz: I describe my job here as an investor as, man, our job is to make every mistake exactly one time and then to distribute that knowledge as fast as possible. So it's like I get to absorb all the scar tissue across the portfolio so that you don't have to as an entrepreneur. And so it was very much like share learnings as fast as possible, get them distributed across the portfolio as fast as possible, so that we could all figure out how to play this unfair game together.
00:05:21 Aziz: And I describe it as an unfair game because if you look at the math, startups are not supposed to be successful. We try to take our unfair advantages in terms of our experiences, our technology, our markets, and our customers, we try to figure out how to play this game so that we can all win. And so, man, if we don't use that knowledge across the portfolio, we're not doing it right. So I always looked at my role… it didn't matter when I was an intern or an associate or a partner or a general partner at the firm. It's always been the same game, which has been take the lessons and communicate them across to as many people as possible as fast as possible. That always is the job. Now, portfolio construction, stuff like that, that all comes as you progress in the evolution of the fund. But the core job has always stayed the same.
00:06:09 David: Yeah, I think that's great. Ari and I refer to that as runtime and pattern recognition. Old guys have a little more pattern recognition and runtime than some of the newbies in the industry. And that super helps you frame your context for how you make decisions, why or why you don't invest, and how you drive those things forward and how you can add value as an investor, which is always one of the biggest questions. Like, oh, why should I let you invest? And well, because we've made all the mistakes, we know what not to do. And we can kind of help you avoid those mistakes yourself.
00:06:39 David: So you guys had some real runtime, obviously, as a fund. And obviously, you answered at an interesting time. Markets went crazy. I think we've seen kind of a little pullback now on them. I'd be curious to see what the NVCA data says now about the number of investors in the market. But here's the real question. So the real question is, what was the runtime and the data that you guys used? Or what was the key inflection point?
00:07:01 David: Because Ari and I like to focus on inflection points. What was the key inflection point that got Mercury to, I want to say this right, kind of renew your focus on deep tech? Because I know you guys have a real big background in enterprise SaaS, a lot of interesting industries, you know, not Silicon Valley based. You'd like to be early investors. So like, what were those key inflection points that got you as a firm to kind of renew your focus on the deep tech industry?
00:07:24 Aziz: Yeah, I mean, so deep tech, frontier tech, you know, however you want to describe it, we're talking about taking big swings at very large TAMs with new paradigms. That's the game. And to a certain degree, I feel like that's always been something we as venture capitalists have done. But the verticals that they're applied to, based off the technologies in the markets, that's always a fluid situation. And so when you think about where to apply those learnings, and where to apply your investment capital, you have to kind of play the game that's on the field in front of you.
00:07:56 Aziz: And so when I think about the game that's in front of us right now, I mean, we're just in this magical moment right now, where you have, and I apologize for using maybe some disparaging language here, but you've got some really interesting incumbents out there that have pretty brittle business models that are particularly challenged to dealing with new technology and new innovation. Man, you know, you talk about incumbents, take like the defense industry right now, where you have like these very large stayed and set in the way incumbents that are super focused on making quarterly profit numbers. And that just takes away the ability for them to invest in that new technology.
00:08:40 Aziz: And so with these brittle business models, going against what is the most dynamically changing technology landscape ever, with all kinds of advancements all across the board, it's like the magic time to disrupt these incumbents that frankly looked pretty untouchable a decade ago. And so it's just a super exciting time to go after. In certain degrees, it's like we're elephant hunting right now. I don't know if that's politically correct to say, maybe a big game hunting. Is that better?
00:09:09 Ari: I don't know. I don't think you can do that anymore either, but like, let's not touch that one. Yeah. Hold on. I want to back up a little bit cause – Like there's two big questions I have for you here. One is, you know, Mercury has spent a lot of time in enterprise and SaaS and you're doing more in deep tech again. So you know, it's easy in the industry to say, oh, this VC is a tourist or they're like hanging out in some hot new industry. And David and I have certainly heard our share of stories in the last, even like 90 days of XYZ fund is now like interested in deep tech, like, which is great.
00:09:45 Ari: But let's like unpack it a little bit. First of all, where is Mercury's interest? Why is this a renewed area of focus for you? And then what the hell was going on in SaaS and enterprise over the last like 18 months? And the AI thing that sort of got you guys as a partnership to go, Hey, wait a second, we want to be deploying more capital into going for these giant bets in these other sectors that are very different than where you were playing before. Like what is going on here?
00:10:14 Aziz: Yeah. So, the first thing I'll say is that if you look at the backgrounds of all the partners at Mercury Fund, what you'll find is that our vertical focuses are pretty darn similar to where they've always been. Like, if you look at my partner, Adrian Fortino, he's always been an industrials guy. He's Mr. Michigan, went to that school twice, has always, you know, you know, has done like, you know, two and a half startups in the industrial space. I was talking to him the other day and I was like, Oh man, like, you know, these big swings you're making land, like, you know, industrial tech.
00:10:49 Aziz: And he's like, Aziz. Whoa, I've started more companies in industrial tech that you can like, you know, list out. I'm like, okay, fair. And so, you know, it's like when you look at like what he's doing there, I mean, you know, when I think about how I started my career, a funny story about me is, is, you know, before I could drive a car, I used to ride a bicycle to the first startup I worked for. It was called Access Multimedia Technology. And we were pioneering OCR engines, if you're familiar with those things. Object character recognition engines, which at the time was considered a really big swing.
00:11:22 Aziz: We were trying to figure out how to take like, you know, printed letters on paper, and turn them into some, you know, digital characters that we could actually like utilize and do stuff with. Now, because the technology stack was so immature, it was frontier tech at the time. But you know, that's always been kind of like baked into the DNA of kind of like how these things work. And so when I think about like the market dynamics that make us say, hey, like, what's going on right now, I would say that incumbents across all industries have never been more susceptible to new entrants.
00:11:57 Aziz: And so if you look at like the last decade, our industry had a fantastic run, basically using a tried and true, almost cookie cutter approach to kind of launching SaaS startups to kind of gobble up incremental market share in a pre-existing technology stack. And that was because the cloud computing technology stack was one of those amazing wealth creating devices that we had to take advantage of. It was right there for the taking. And so you had to do it.
00:12:29 Aziz: But in a world in which those technology stacks are now being fundamentally disrupted by new technology, the name of the game is not use those pre-existing infrastructure stacks to kind of build end user facing use cases. That's not the game anymore. The game is use like, you know, start from a fresh sheet of paper now and build net new companies to go after the available space. And the available space right now, it's all about… you know, my partner Adrian talks about first order versus second order type problems. And the first order problems that I think about are, hey, do we have the technology to solve the problem? And two, are there people willing to pay for people to solve the problem? Okay, great.
00:13:18 Aziz: If you solve those two questions, it's just a question of execution now. And so let's take on these massive incumbents that frankly, you know, we didn't… you know, folks didn't have the risk appetite to take on over the last decade. And let's go straight after them and kind of disrupt the game. And that to me is what frontier technology investing is all about. It's taking bigger swings against bigger incumbents.
00:13:39 Ari: It's all… I think what you said earlier is really important. Like it's always been that way when we were building internet 1.0, that was frontier tech at the time. Right? And is there something that's going on with enterprise or SaaS or cloud business models where from a venture perspective, you just don't believe, or still do believe that the returns are there or the ability to truly differentiate and create billion dollar companies is changing? I mean, I think what you said earlier is important. Like so many of these ideas were just incremental variations on a theme, like the incrementally better version of something.
00:14:17 David: It's easy to do. Everyone can do it. And they're trying to do it a little bit better. Right? And I think that's kind of building on what Ari's saying. I think that's one of the keys to deep tech now, as opposed to kind of the software revolution is that most of the challenge in deep tech now, it's actually a combination of software and hardware. Right? It used to either be a hardware company or a software company. And now it's a combination that you have to nail both. So, you know, like it's not as easy as it was where you can just spin up a new software version and kind of take on, like – so I'm sorry. I’m ranting. I think that's the question.
00:14:48 Aziz: No, but I mean, another way to look at the problem is every aspect of that legacy business model that you're describing is under threat right now. First of all, it's very hard to find a moat. And what I mean by finding a moat is in a world in which thanks to a lot of the tooling that we built up over the last decade, building a software application is almost trivial now. So, take that to the extreme. Anyone can build any software for free. Okay. Man, that's super hard to build a moat around.
00:15:17 Aziz: Number two, customer discovery has completely gotten turned on its head. I don't know if you've been looking at like Google search traffic, but one hits, which is where someone just types in something, gets an answer through Gemini and then never clicks on a link has exploded. Okay. So customer discovery is broken. So now all your CAC costs are all kind of, you know, shot to hell. So, then what are you left with? I guess, like maybe like a unique channel strategy?
00:15:41 Ari: Distribution, right? So that's the story now is that if building is free distribution is everything. But if you can't control distribution because Gemini is controlling the search results, then you end up with like a Monday.com situation. Right?
00:15:55 David: But I think the real advantage is, and obviously, you know, Ari and I believe this together, right. And so it's because it's so easy and the moat is virtually non-existent anymore so when the startup costs for company are zero and the moat is virtually non-existent, right? What are the new moats that deep tech are really representing? And Ari and I think about this a lot. Is the moat your deep technical insight into a very specific technology or application that can truly change the industry much more than an incremental way that no one can just read up on and be as good as you are? And is that really where the new opportunities are in deep tech? Like that's certainly, if we look at our past several investments, right?
00:16:37 David: They've been in founders and companies that have such a deep background in the space that they're building in. Like this wasn't just some person with a problem, an idea, right. These were founders that have been thinking about these challenges that they've been working on for years, either a doctorate or scientific level and spinning up truly novel solutions that their background really is the moat.
00:17:00 Aziz: Yeah. I mean, we at Mercury, we talk a lot about a founder's right to win and the right to win comes from the fact that they're not tourists in this industry as you know, you know, to borrow a phrase. These are folks that have spent a good chunk of their lives building up the expertise to have that unique insight to win. We talk a lot about folks who understand the ins and outs of an industry with amazing fluency that gives them a unique market insight.
00:17:30 Aziz: So technology advantage, market insight into what will actually turn this market. And then it's our job as investors to make sure that we've got [inaudible] wins on our side. And if you can kind of put that constellation together of unique advantages and unfair advantages to win, then I think you've got an investment to pursue here. But you got to get all three of those lined up.
00:17:56 Ari: I think maybe there's a fourth. I'm curious for your take on it, which is how important is clear commercial traction or market pull when you're evaluating a company, especially in deep tech.
00:18:06 Aziz: Yeah. I mean, it's super case by case. I am personally a person who, because of when I entered into this market, I am uniquely traumatized by the clean tech boom of 2008, 2009, 2010. And so like, you know, let me just speak for Aziz for a second here. But I lived in a world in which we saw potential for technology and I saw large noises about potential market demand. And we as an industry… I mean, at one point it was the biggest vertical that VCs were investing in. And then, you know, our reward for that over the subsequent years was we watched one by one by one, a lot of these deals just kind of go belly up.
00:18:53 Aziz: And so in trying to deconstruct those lessons learned from that window of time, I've been a lot harder in terms of what the true market looks like for some of this stuff. Because if you look at what we were able to accomplish during that initial clean tech boom, we did a lot of the things that we set out to do. Like, if you look at like the cost of solar on a kilowatt basis, we really drove those prices down. If you look at like, you know, like, the total demand for electricity, that definitely went sky high. So a lot of like the elements kind of like, you know, held true, but the story for some reason, like didn't come together.
00:19:27 Aziz: Now you can point out like potential external competition. You can point at like injections of capital from state actors and a bunch of other stuff. But at least I've been a lot harder in terms of making sure that I can think about the entire investment process from a capital need point of view, because you need to make sure that your company is funded throughout its journey. But then also making sure that there are hard dollars available to the startup as it kind of goes down that path so that we can actually get like customer traction.
00:19:57 Aziz: Now, does that mean that we've got like a hard rule here saying like, Oh God, like we won't invest in anything unless you have pulled in like $10 billion of NREs from external customers? Now, I just don't think you can be prescriptive like that here, but you have to be truly honest with yourself about what that capital flow looks like, or else we might run into making those same mistakes again.
00:20:17 Ari: Interesting. All right. So I have a follow on question then. So one of the things you said, which is it's case by case basis when it comes to traction, right? And then when we're dealing with deep tech and nuanced technologies, where there's a convergence of software, hardware, deep IP, and a lot of tribal knowledge required about the industry, as you said, the founder has to have the right to win. You put all of that together, trying to get a partnership to understand in a deal review meeting, why this is the company we have to invest in right now… it can often be near impossible because the amount of nuance and detail that goes into the diligence process. How do you overcome that? And, like, what is the process of Mercury did to… as you guys dive into these deep tech companies?
00:21:00 Aziz: I mean, you got to trust your deal champions here. So a little inside lingo within the venture capital spaces is the person who kind of finds an opportunity and champions that opportunity you refer to as a deal champion. We also at Mercury, we try as much as possible to pair up on deals. In fact, for a while, I still have to double check with my partners, but for a while, we had an official designation of someone as a skeptic to kind of like push back internally, you know, just saying like, Hey, like, you know, is this assumption really true? Is this really true? Like, like that sort of a thing.
00:21:32 Aziz: But you're totally right. I mean, you can spend a month immersing yourself in a vertical and understanding the ins and outs of a piece of technology. And your reward for that is you're barely fluent with your founder. And then to expect to pull up the rest of a partnership up with you is, you know, man, that's super hard to pull off. And frankly, you know, you'd grind the operation of a firm to a halt if you required everyone to intricately understand the ins and outs of every deal. Like, that's not how you run a partnership.
00:22:02 Aziz: The way you run a partnership is you get together periodically to make sure that you're all looking for like similar types of proof points. So we do regular offsites in which we talk about like our core assumptions. We're very transparent and vulnerable with each other about like, Hey, for this to win, this needs to work, but this falls apart if this doesn't happen. And you have to be very transparent about what those things look like. And then, you know, and then you trust each other to kind of make like really smart decisions here. And when we think someone is, you know, making one too many assumptions, we tell them pretty, you know, candidly. And when we think someone is making the right type of risk, we say, let's go.
00:22:43 Aziz: The other thing is, is we are proudly a non-consensus fund, if that makes sense. Man, if every one of us thinks a deal is going to win, that means that it's so obvious that it's not the contrarian play anymore. It's so obvious that everyone's going to chase that. So, those are almost like… that's almost a sign that maybe you're playing in the wrong space. So the last thing I'll say on this is as a partnership, we're really proud of ourselves that like… just because one person has a strong opinion saying this isn't going to work, doesn't mean that we're not going to do the deal. If anything, it makes us more confident about the deal because it means that it's less of a… it's more of a contrarian pick, which is where you find like a lot of your biggest winners.
00:23:23 David: Got it. So I imagine there's a lot of group hugs going on. [crosstalk]
00:23:30 Aziz: It's like, you know, the sign of a good relationship is bite marks all over your tongue.
00:23:38 David: I don't think I've ever heard that one. [inaudible] So you guys have added a few partners recently, right? Like you guys have been growing as a fund. What's the process like bringing them up to speed on how you guys really work from our culture, how you think about deals and you know, and most importantly, like how are you getting them to think ahead of you guys? Because the assumption is like you want them to really drive the next wave of investments. So what are you doing from a cultural perspective when you bring them on as new partners to get them to think?
00:24:13 Aziz: I mean, I feel like this is a pretty tried and true playbook, but what I've learned is like, Hey, like, you know, in a pretty dynamic industry, what I think is tried and true may not be tried and true. But you know, it's like I do things the way I always learned how to do them, which is you get folks to shadow you on boards. You basically have like an open door meeting policy. So, you know, everyone comes to the investment team meetings and kind of hears us kind of go back and forth.
00:24:38 Aziz: We try to get a lot of reps through. For every investment we make, there are several investments we don't… we're pretty transparent about like how that process works. And we use a lot of Google Docs with a lot of commenting on them as they kind of progress down the pipe. What's it called? I don't have one handy next to my desk. That's kind of a shame. We actually have flow charts that we have all around the office that kind of talk about our investment process and everyone kind of like talks about them on a pretty regular basis. Very regular meetings, lots and lots of collisions.
00:25:06 Aziz: You know, I think some people think we're a little insane, but like we're very much in the office collision type partnership here. So we're always spending physical time with each other and we're always kind of bouncing ideas off each other while grabbing coffee and like sitting in physical rooms with each other. We've tried to embrace technology as much as possible at the same time. We have Zoom rooms all over our office. We try to use like as many of these presence tools as possible to make sure that we have more of those spontaneous types of collisions.
00:25:34 Aziz: But it's all about building reps with each other around a common process in which you try to build up trust over time. And as you kind of go down that path, what you quickly discover is that old fossils like me stop being the source of like the new ideas and they end up becoming the source of new ideas. And that's actually kind of a good thing. You want them to be doing more investments than you, especially because I'm like old and senile at this point. You know, it's like if I have an option to kind of sleep in my own bed, I kind of try to do that. But you know, I'm still clocking in my 100,000 miles a year though. So I'm still not doing the job completely right. But yeah.
00:26:14 David: We see all the pictures.
00:26:18 Aziz: I'm very famous for Instagram selfies on airplanes.
00:26:22 Ari: Do you have a preferred seat? Like do you always try to get the same spot?
00:26:25 Aziz: Man, you know, so I actually have a plaque here from the folks over at United after I crossed a million miles. So they pretty much let me sit wherever I want now. But usually I'm taking a windows. If it's a window versus aisle, I always kind of take window. I actually think that it's a foolish thing to get a meal on a plane. So I never eat on the plane. I'm always on my laptop because that's like my best downtime. The crappy internet I actually think is a feature, not a bug on those things.
00:26:50 Aziz: If there's something that I'm really a fan of, I got a SIM put in my laptop. So it's always online now. So like, so you know, it's like when you fly enough, they let you preboard and like, man, that's 30 minutes of prime email time. And I got time for anyone to, you know, put up a hotspot or anything. So I use the SIM on there. And now, if you're a T-Mobile customer, T-Mobile resells Earthlink. So they have the T-satellite service. So you're always online now. It's pretty great. So I'm a huge fan of that.
00:27:14 Ari: Here's a question for you. So based on what you just described about your partnership and trusting the deal lead, when it comes to you as the lead investor or the one championing a deal, especially in deep tech… like one of the things I've struggled with is, is I can have conviction about the market or the opportunity or, you know, like in our vernacular, Massive, we know this thing is going to be inevitable. It's this market's going to happen. Someone's going to win in that category in some way. But how do you build conviction sometimes with these early stage deep tech companies where like there's infinite vectors of risk?
00:27:50 Ari: There's so many vectors of risk, even if the founder knows what they're doing. What are some of the things you've gone through around this as you look at these companies to get to the place where you're like, I believe this is the company that's going to win in this category when they're still in the lab and they haven't actually proven that they can make the thing work in production yet?
00:28:09 Aziz: So, if I could just amend the setup to the question just by a hair, it's not just that you have to believe that they could win. You got to believe that they can win now. And there's a nuance there, but I want to make sure that we put some timescale on this. And this is because, again, you know, maybe this is the trauma that I'm experiencing from having lived through 2009, 2010, 2011. It's not just about like having that vision for the future, but it's the immediacy of that vision.
00:28:37 Aziz: And so, when you force yourself into the constraint of thinking about the immediacy of a vision, suddenly, you don't have like five years to wait for a market to figure itself out. Because you throw that five years of waiting on top of the scale up of a technology, coupled with like figuring out like a lot of market dynamic – I mean, suddenly, you're in like 10, 15 year territory. And so, for a world that's kind of bound by like certain time-based return profiles, that just doesn't work. It's not very compatible with institutional funds. So, you have to kind of always have in the back of your head the time constraint factor here. And that forces you to think about stuff that's closer to kind of getting there. The immediacy forces you to kind of shortcut your way through a lot of those different types of risk factors.
00:29:26 Ari: Yeah. I think that's really true. And you know, that brings up like a lot of my own scar tissue too. Like I've been investing in deep tech and frontier tech for ages. And one of the things that happens in some of these sectors is they start to capture the imagination and they get a little buzzy. And then the first wave of companies, they all think that they're at these early inflection points because they think they've got the right signals coming to them.
00:29:53 Ari: But the truth is that what often happens is that the industry or different verticals have curiosity about how to apply new technologies to their business. And so, there's all these sort of essentially false flags and actually head fake situations where the company thinks what they're getting is market pull. And the CEO will stand up and say, we're raising the Series B. We totally have product market fit. I need to raise a giant round. And then you find out that all of these companies were really just kicking tires and had curiosity. And that there were some internal mandated, a large corporate to play around with some new technology to learn. And the bottom falls out on the revenue growth. And everyone that thought they were going to do a pilot and turn that into an enterprise license, they never get past the pilot.
00:30:37 Ari: And a lot of the venture community backs up this wave because everyone's chasing this next sector. And the next thing you know, you've got an overfunded sector that's under-delivering on commercial revenue. And now all these companies are over their skis. This has been why we have so much wreckage in hard science and deep tech industries that can't really get to commercial product market fit. And so, we've just seen it over and over again. What do you think about that? And how do you navigate it?
00:31:06 Aziz: There are a lot of facts that you're conveying there that are hard to argue with. The trial problem is always going to be a problem that we run into in any net new technology. You can't get to recurring revenue without having some kind of a trial and pilot phase, especially for a net new technology. That's always there. But there has to be a forcing function to make sure that you stick with the product. And man, it's like part of the industry keeps on running into these problems is because, man, it's just so hard to tell the difference between what's going to work and what's not going to work on a recurring basis. And making sure that those market dynamics that made everyone eager to trial, we'll make sure that they stick with it.
00:31:52 Aziz: There's a fun cartoon that I reposted this morning about that. I think Dave, you actually gave it a laugh symbol. But it was like every CEO in America is like, I need to use AI. What are we using it for? We're not sure yet. I don't know. But we got to use it now. But it's those types of ambiguous crowd, wisdom of crowd type moments that, frankly, are the false positives that you think about a lot. If everyone's chasing the thing, but they can't tell you why they're chasing the thing, they can't put actual economic rewards around why they're chasing the thing, and there's no real advantage to chasing the thing, then why are they chasing the thing? It's a lot less clear and it's pretty hard to get to a real proof point there.
00:32:40 Ari: I feel like the place I always come back to with this is that you've got to look at real market signals or you got to go interview the CFO at a company and understand what their top five problems are. And if you're not solving one of the CFO's top five problems, you're probably a nice to have.
00:33:01 Aziz: Let me just double click on that. I'm from a place called Houston, Texas. If you don't know Houston, Texas, it is the energy capital of Earth. And if you know anything about the oil and gas and the energy industry, man, the mother of all capital intensive industries. These are folks who spend a billion dollars getting an offshore oil rig up and running. And every now and then, I hear about some nifty little software solution for the space. And the pushback that we always have on stuff like that is we're like, man, the problem with the energy industry in particular is the ratio of capital intensity versus the reward for using a net new technology. And if there's too much of an imbalance there, you're never going to get the customer's attention.
00:33:49 Aziz: And so in a multi-trillion dollar industry, saving a billion dollars just isn't on anyone's radar. What's on everyone's radar is securing cheap acreage at the right time using the right upstream techniques. And in that world, maybe tightening up your supply chain by like 2% never was going to move the needle. And it was never going to be considered the thing that anyone wanted to focus on.
00:34:12 Aziz: Applying that lesson to a lot of these other industries really jives with what you're saying there, Ari, which is effectively, hey, if this isn't enough to get the CFO's top 5 priorities, you're never going to cut through the noise of getting them to actually switch to the net new technology. It's just never going to get there. And so the sense of urgency is so critical. Because the act of a customer switching to a new technology is disruptive. It takes work. And so you have to… It has to be top of mind or it's never going to happen.
0:34:49 Aziz: And this is maybe a big difference between what we were seeing with some of the more incremental software businesses versus some of these more important frontier technology businesses. Those things work hand in glove. It was like a slightly better answer that had no switching costs associated with it. And it gave you that incremental improvement. Great. God bless. We did a lot of that in the 2010s. And folks made money doing that. But for these bigger swings, for these bigger changes, you have to be top of mind in terms of the problem that you're solving, or no one's going to put up with the switching costs of moving over to the new paradigm.
00:35:26 Ari: How much do you look at these... Let's use the tailwinds or headwinds analogy, right? How much are you looking at market, regulatory, technical, or even press headline and zeitgeist? How important is that to you? Or do you look at these first principles issues of… Energy is a great one. AI data centers need way more energy than we can produce. We're way behind on the energy production curve. It actually doesn't matter whether we drill or burn atoms or collect solar rays. We need all of it. But then there's all this regulatory stuff. So how do you stack rank those signals as you think about investing in these kinds of companies?
00:36:09 Aziz: Yeah. By the way, fun aside, I'm from Texas. What regulations? We got this thing down here called ERCOT. We have our own power grid down here. But look, when I think about these types of very obvious, call them demand-driven signals, and how do you try to solve against them? Man, I still ask myself the same basic questions I've been asking myself for 20 years, which is, what is my unique market insight? What is my unfair advantage to win? When I think about unfair advantages, if it's a technology-based one, it's like, how long is it going to take someone to figure this out once I figure it out?
00:36:49 Aziz: These sound like super glib, super simplistic approaches to it. But I feel like those are still the right answers. The regulatory risk one is a weird one. And look, I've been a side software investor since as long as I... I mean, a side healthcare investor since as long as I've been an investor. And when I think about and talk about regulatory morass like no other, imagine investing in healthcare, especially around insurance and reimbursement policies and God knows what else.
00:37:19 Aziz: But I always think about like, hey, I still lean back on my old MBA training of looking at Porter's 5 Forces. And I'm like, hey, whoever had the thrust around the initial sets of regulations here, are we on their team or are we on a different team? And I try to figure out whether or not we're fighting on the force of where the market is headed versus not. And man, like in my life, as long as you're on the same side as the market, you tend to be pretty okay in terms of where the demand ends up being. Sorry, that's a super rambly ranty answer.
00:37:53 David: Let's take the ramble and the rant and let's turn it maybe in a little different direction. You kind of touched on these points, but let's focus a little differently. Let's talk about it from the founder perspective for a second. You're an investor. You've seen a lot of founders building a lot of interesting companies. Obviously, we already talked about the fact that this new deep tech wave is a little different than the software wave that we lived through 10 years ago.
00:38:14 David: And so when you're talking to founders, you're looking at early stage investments. What are the key things that you are really focusing on from their perspective? Because a lot of these founders of deep tech, they're very scientific, they're very data driven, but not a lot of them have built businesses before for a lot of different reasons. And so how are you counseling them or what are the things you're thinking through from a key pattern recognition perspective, key inflection points? How are you talking or thinking about, can they actually turn this into a real business from an early stage perspective?
00:38:48 Aziz: Man, I got to tell you, we've looked hard at this problem. And I'm not giving you a law. I'm not giving you a rule. But second-time founders are so good. Folks who have dealt with dealing with trying to get customers to buy a product for money and have lived to tell the tale, there's something different about a second-time founder versus a first-time founder. It's such a beautiful thing.
00:39:18 Aziz: And so man, it's super hard to bet against the second-time founder because they've been through that valley, because they've been through that process. There's something super special about that. Now, sometimes you can fake it. And what I mean by fake it is, I have a founder that I'm on the board of right now. And his father was a repeat entrepreneur in the restaurant space. And so he watched… Basically, from age 12, he was working in his dad's restaurants and had to deal with that. That gave him a lot of founder DNA. And so that helps.
00:39:51 Aziz: But man, there's something special about having struggled through customer acquisition and having to honor a P&L. Super hard to replicate, super hard to teach. Some schools do a really good job of putting this into their students through accelerator programs and stuff. I advise down here in Houston. Rice has this thing called OWL Labs. And I was like, man, if there's only one takeaway, I want them to learn that this is really hard. And I want them to go through the reps of watching it not work. It's like... So when I'm looking for things in a founder, it's like that… I sound like a broken record. But unique market insight that comes from deep technical expertise. But man, if I could… If there is an entrepreneurial DNA to have there, man, that makes this so much easier.
00:40:35 David: Yeah. I talk about this a lot. Too many people start startups because they're sexy and they just want to start something cool. But when you look in their eyes, you understand the people that know how hard this is actually going to be. And that's not something that people understand initially. You and I, we've done a lot of talks at Techstars and for early stage companies. And one of my favorite situations in that early stage conversation is when you're talking to a first time founder and cool company. And they're making good progress. And then you just get to see you on the room and they look at you and they're like… And you see those eyes and they're like, when's it going to get easier? And you have to slowly explain and say, it never gets easier, only faster.
00:41:19 Ari: The problems only get bigger, right? The problems only get bigger.
00:41:22 Aziz: Have I already told you the hot dog story?
00:41:24 David: Which story?
00:41:26 Aziz: The hot dog story. So I went to high school. I went to high school in Houston with this guy named Yasir Salem. Very easy to Google Yasir. We're very dear friends. So Yasser is a competitive eater. And he invites me. He used to be at that final table at Coney Island every year for that hot dog eating contest. And he's super proud of himself. He's like showing off. And he's like, he's like, Aziz. Because I'm at the final table, I can walk into any Nathan's hot dog chain and I can get free hot dogs. And I was like, okay, so I just want to make sure I got this straight. Your reward for eating all these hot dogs is more hot dogs.
00:42:07 Aziz: And so this is like a shorthand I use with my entrepreneurs now. Because I'm like, you know, running a startup is just a hot dog eating contest. Your reward for solving this problem is more problems. Your reward for scaling to this point is you have to scale to this bigger point. It just never ends. You're just going to keep on escalating up the chain.
00:42:26 David: One of the things I used to do, you need like this is, you know, when you look at a founder, you're like, bring it on. Like they want the bigger problems. And it's those people that think it's just going to get easier once they get off the ground. And especially in deep tech, when like the challenges are so big, the valleys are big, the capital needs are so big, right? The time to market, even though it seems small, like it's still like the barriers there. If you're a defense tech, it's understanding how to navigate the government. Your energy is like, it's…
00:42:54 Ari: One of the patterns we see in deep tech over and over again is relatively senior person at giant company gets fed up with giant company, leaves and start something in the sector that they know. So they check your first box for deep technical expertise, domain expertise, a right to be in that market. What they don't know is all of the other things. They just know that they want to go do their own thing because they're fed up with the way that the big guys were doing.
00:43:19 Ari: So it's funny. One of my quick, like my fastest, like no button filters when I was doing a lot of Techstars screening for founders, which oftentimes were first-time founders was the very simple question. Why do you want to start this company? And whenever I heard the answer of, well, this is a big market and I wanted to do a startup. It’s a no.
00:43:46 Aziz: You know, my quickest no’s are folks that have always been at a Fortune 100 company. It is so different trying to work in the context of an existing machine versus building your own machine. It's just so different. You know, in a former life, I launched a new division of a public company versus… what's it called? I was the executive chairman at a startup that was just a true startup. And the problems you run into are just so different.
00:44:21 Aziz: I mean, you know, because, because your primary success factor for launching a new division in an existing company is basically being really good at bureaucracy. It's like, how do you get money out of this budget? How do you get this manager to sign off? How do you get this facilities rec fulfilled? Like, how do you do this? How do you do that? Versus like in startup land, it's just like, do a now and like, and like what is a one-week project in the first example is like, you have 30 minutes to do this now in the second example. And there's no… it's just totally different.
00:45:01 David: It’s totally different.
00:45:03 Ari: I learned my lesson the hard way. [crosstalk] You only learn the lesson once. I ended up learning it twice at the same time because I made the mistake twice at the same time. So I had two pieces of data, right? I was literally on the board and had led the seed round for a company where the executive came from large enterprise, like SAP. Right. And then I had backed somebody else in a different category, similar deal. And I was getting the same lessons coming at me twice at the same era. And I was like, okay, well, got it.
00:45:33 David: My car alert, that whole conversation is in all the companies that I started, I always paid MBAs less. Because it took them so much time to unlearn what they were told, what was going to actually happen versus what actually goes on. And you know, once they actually get it, they can be amazing, but the unlearning curve cost me time in [inaudible] because they were taught, this is how things work. And if you're going to go to a Fortune 500 or a Fortune 100, yeah, absolutely. But if you're going to go to a startup, a whole different world.
00:46:02 Aziz: So, let me ask y'all a question because I'm super curious on this one. What do you think about consultants becoming founders?
00:46:10 David: So as a consultant that became a multi-time founder, I will tell you, kind of thinking back to our initial conversation, it depends on the person. It's all about the person, right? Like if they're in the consulting business because they think they're smarter and they just deserve to get paid more and they don't want to actually do the work and they want to come in and tell you, this is what you have to do. Just, you know, lower cost, increased revenue. That's all they have to do. Right.
00:46:37 Aziz: I started my career as a consultant. I started at Ernst and Young way back when. I was talking to someone who is at EY Consulting right now. And they're on their fourth iteration now of having a consulting practice now because they keep on spinning it off, selling it off to somebody. But man, I tell you, it's like unlearning the mentality of charging yourself by the hour is so hard. Yeah. It is so hard.
00:47:02 David: The outcomes are not [inaudible]. When you're building a startup, it's about objectives. Where can I get the company? That's the value prop. It's not how much time I put into it. No one cares how much time you put into it.
00:47:17 Ari: It's totally the person and how they're wired. Like you end up consulting for experience, but you get this broad, you know, this broad set of instructions. And the CEO of my first company in the nineties was an ex-consultant, but he saw five steps ahead of everyone else and was able to go execute against it.
00:47:34 Aziz: Yeah. I mean, I tell you, you know, it's super interesting. It's like, there are certain types of fields that people come out of and become entrepreneurs. And I feel like each one of those fields has a unique insight that comes with it, but also comes with a super obvious blind spot to everyone but themselves. So like, I've noticed this with consultants and I say this as a former consultant myself, this is the hours put in versus value blind spot because you're trained as a consultant to do something, get something called a utilization rate. And that's the goal is to put in effort.
00:48:09 Aziz: With lawyers, what I've noticed is an over-focus on whether or not you can do something from a legal or from a contractual point of view versus whether you should do something. That's super hard log jam to kind of get past in their heads. With doctors, because there's a structural shortage of physicians in this country, they have no concept of customer acquisition cost is what I've run into.
00:48:34 Aziz: Because again, America has a structural shortage of physicians and that's because we gave them an antitrust exemption. But because of the constant shortage, no doctor knows how to actually acquire a customer. They just say, I'm a doctor and people start showing up. And so they never can think through the CAC problem correctly. But every field has its own unique, weird challenge associated with it as they try to go down this true entrepreneurial journey.
00:48:59 Ari: Interesting.
00:49:00 David: So we want to start close wrapping. So I'm going to ask some interesting kind of fire forward questions now. So based on that, different industries have different perspectives, right? They play, they bring different value props and blind sides to each, to the startup world. Let's kind of flip that a little today. As Mercury, as venture investors, especially as you renew your focus on deep tech, right? So what are you seeing or thinking about as some of the next emerging trends in deep tech that are going to drive massive markets?
00:49:30 Aziz: Yeah. I mean, so look, I live in Houston, Texas, as I've reminded you, I think five times today. There's a lot of space here.
00:49:37 David: That little state in the Northeast, right?
00:49:39 Aziz: Yeah. Yeah. Yeah. Tiny little state no one's heard of called Texas, but you know, so space is always something that's always top of mind here. Aerospace is always super top of mind here. So, you know, it's kind of like, you can't go to an evening spot here in Houston and not talk about like aerospace space. And so, man, like, you know, like I went to Clear Lake High School, which is where all the astronauts kids go. And so, you know, it's like… I'm confused why we don't have cities on the moon right now. But it seems like something imminent always all the time.
00:50:11 Aziz: You know, that's part of the reason why we've invested in like low earth orbit satellites. That's part of the reason why we invest in aerospace companies. But because for us, you know, it seems like one of those obvious things. And man, there's a lot of dollars now kind of getting allocated to the space. And we think there's some imminency there.
00:50:26 Aziz: We see the same thing around like, you know, next generation industrial type applications. You know, Dave, you and I were co-investors on the quantum side of the equation here. I think that's super interesting. You know, the running joke is quantum has been five years away for the last 20 years. But there are so many redundant paths to finding something kind of happen there, whether it's on the locational side, whether it's on the quantum computing side, whether it's on the networking side. But there are lots and lots of paths to success there.
00:50:56 Aziz: Robotics is super interesting right now. I think that something that folks kind of overlook is that AI changed the equation on how to train robots on net new use cases. I don't know if you saw the same optimist demos that I saw, but the ability to like have like, you know, basically throw a camera in front of a human doing a problem and then having a robot replicate like the same motion within like five minutes is super game changing. You can do some super interesting things.
00:51:24 Aziz: We have portfolio companies that operate in the logistics space that do stuff around like distribution centers and supply centers. And robotics are just kind of changing that real time. But there are so many of these like hardware/software/new technology use cases that are just there available for the taking in which the incumbents are so old and are so bad at what they do that it's really, really a fun time right now.
00:51:53 Ari: This is the convergence that David and I keep talking about, right? Like the robotics unlock is really coming from computer vision and AI.
00:52:04 Aziz: Yeah. Robotics to me feels a lot like what smartphones felt like, like, you know, in like 2010, 2011. Man, there was this restaurant app in 2011, 2010, sorry, that just kind of blew my mind. It was like, you know, because for the first time you had like this mobile computing device that was like in your pocket and it was able to take advantage of like the social media reviews that were all crowdsourced.
00:52:32 Aziz: And like the funny thing was, the way it would work is when you wanted to eat, you would shake it and it would make like a little cash register sound. And then it would tell you like the nearest restaurant that had like a reservation available. And it just blew all of our minds. We're like, you can do that now? But that was a combination of like five technologies stacked on each other that kind of gave you like this friction-free experience. And you're seeing that now with robotics, which makes it so much fun. Man, it's just a fun time to be here when all of the things stack on top of each other.
00:53:01 Ari: All right. So on the flip side of all of that goodness and hype and excitement, what do you think is the most like overcooked thing going on in deep tech right now?
00:53:11 Aziz: Man, I tell you.
00:53:12 Ari: And you can't say AI, that doesn't count.
00:53:16 Aziz: Man, I love AI. I don't know about you.
00:53:20 Ari: We all love AI too, but aside from AI, what is the most overhyped, overcooked thing that you think is not going to materialize as a market?
00:53:28 Aziz: Man, every 18 months, someone tells me they finally figured out cold fusion. It's like the perennial Charlie Brown in the football. They keep on telling us they figured it out, and then it keeps on not happening. I think the latest one was one that came out of South Korea a few months ago. They even published papers on it in peer-reviewed journals, and it still ended up not being quite right. So cold fusion is like a pretty perennial one that we keep on missing out on. So that's a real one. I don't know.
00:53:58 Ari: So you don't think Commonwealth will get operational?
00:54:00 Aziz: Man, look, there are... You know, by the way, the first rule of VC is you never make fun of a startup, because holy moly, you'll look like really, really dumb really, really fast in this industry. There are really, really smart people chasing stuff that know stuff that you don't. So man, I'm not going to make fun of anyone in particular. But talking in generalities, that one seems kind of far away. Talking in generalities, I don't know.
00:54:28 Ari: All right. So related to that, is there a one that got away, an anti-portfolio company where you thought you made the right call and you regret it deeply?
00:54:39 Aziz: So this is a true story. I tell this in a lot of public forums. But the first pitch I've ever listened to as a venture capitalist was when I was in Chicago, going to Northwestern. And another Northwestern student pitched the firm I was interning at that I will not name on his idea called The Point. And so he comes in, he pitches this thing called The Point. And as he walks out of the room, everyone at this firm is just making mercilessly fun of this idea.
00:55:13 Aziz: The Point was this idea. It was actually built on the shoulders of another crowd-sourced business in Chicago called Threadless, in which you would get people to vote on ideas. The Point ends up becoming Groupon. So that was the very first pitch I ever heard. And we obviously did not do that deal. And I know the people who did that deal. And they're very, very happy that they did that. That was the very first pitch I ever heard.
00:55:38 David: That's a great story. I think we all kind of have stories like that. We could keep going forever on this topic, but we do need to wrap. So, Aziz, I just want to interrupt you. I want to say, when people ask me about you, I describe them as, aside from being an amazing investor and an [inaudible] personal good friend, I describe you as being like Tigger without the ego problem. And you have 100% lived up to that today. And we are deeply, deeply grateful for your time with us today and being a guest on Massive Signals. And I hope I see you very soon.
00:56:08 Aziz: Yeah. I mean, I'll tell you, it's like... The thing I love about this industry is that you only get to survive in this industry for any prolonged period of time if you end up just being... It's very hard to be successful in this industry if you're just a jerk. Because...
00:56:25 David: But they're out there. But they're out there.
00:56:28 Aziz: I mean, look, look, look. We are not an industry of saints by any stretch. But it's like the longevity of friendships like yours and mine, Dave, are the reason why I love this job. And they're the reason why I love these relationships. I love running into you on the beaches of Aruba. I love… Yeah. I love riding Shinkansen with you for milestone birthdays. I love harassing sushi chefs at the counters at hard-to-get-into restaurants. These long-standing relationships that really make this industry work for me. And thank you for being a huge part of it.
00:57:06 David: By the way, I'm honored to be a part of it. And thank you so much for today. And I hope I see you soon.
00:57:13 Aziz: Good to see you guys.
00:57:14 Ari: Thanks for being on. See you soon.
00:57:15 Aziz: Thank you.
00:57:17 David: Thanks for tuning in to Massive Signals. If you enjoyed today's conversation, be sure to follow us on Spotify, Apple, or YouTube. And share the episode with someone who cares about the future of deep tech. And subscribe to our substack at massive.vc to stay in the loop on all of our current investments, thinking, as well as upcoming events like our quarterly deep tech table dinners, and the second annual Deep Tech Summit May of 2026. Find it all at massive.vc. Until next time, keep listening for the signals that are shaping our future world.
