Every Day Learn Something, Every Day Build Something: 77 Patents Later

Sean Weisbrot: What made you so interested in investing in climate startups?

Tom Chi: So, uh, truthfully, I wasn't interested in being an investor at all because my overall career has been as an inventor technologist. I'm a named inventor on 77 patents. I've like all those things were actually built. I've probably patented maybe three or 4% of what I've actually built as opposed to just. Patenting a bunch of stuff to go protect a space with no intent to build, uh, intent to build it. Um, and given that that I've built a whole career around being the person that can actually just literally make the thing, or if I am projected, I'm like the leader of the team that's making the thing. And when you build your career with that sort of skillset, then going into investing where you just talk about making the thing as opposed to making the thing actually seems like a step down. So like in truth, like people with my background relatively rarely become investors. 'cause I, I will say that it is a little bit less, um, you don't get the satisfaction of the solve and the completion that, that I would normally get in a build process, right? Like I, I'm needing, there are important problems to solve, but, uh, I, I'm working with the founder to be able to complete them so I can't complete them in the ways that I would've if I were just running. A thing, but to answer your question directly, why would somebody of my background end up in this field? Then it is, um, what I think actually drives a lot of people, but is talked about less, which is tragedy, right? We, we like the inspiration stories because when, when you hear the inspiring thing, it's like, oh gosh, they got, they got so curious about this, and then they got a little bit obsessed with it and they built this amazing thing and honestly, it's a fantastic narrative and it really. Fits with the kind of positive vibe that we like to put out into the world when we, when we talk about things. But I will tell you that like some of the most deeply committed people, they got into it because of tragedy. And actually tragedy oftentimes has more staying power than inspiration. So for me in particular, then. I was, um, kind of at the height of my career as an inventor. I was one of the founding team members of Google X. I had hired an amazing team that was inventing at a pace, which is dramatically faster than, than, you know, the Google mothership had ever invented at. And we were working on self-driving cars and Google Glass and Project Loon and new approaches to ai, which became Google Brain and so on and so forth. It was about as technically compelling and exciting, a work that somebody with my background could ever do. But what happened during that same time period is I, um, you know, I was a, I was a technology exec, which meant that I've gotten my San Francisco home and I also had a vacation home and out in Hawaii. And my home in Hawaii was about two minute walk from a. Astoundingly beautiful coral reef, which I spent a lot of time on whenever I was in Hawaii. And while I was at Google XI actually watched that reef go from every color of the rainbow and life coming outta every pocket and corner to, um, gray and brown and no life in less than two months. And what I had witnessed was basically a mass bleaching and, and total reef collapse event. And, uh, look, I'm a, I'm a former scientist and I wanted to really understand what happened. I will tell you that the feeling of it was like tearing a hole in your heart because when you live next to a reef as opposed to just visited on vacation, it actually, at least to me, it became like an extended part of the neighborhood. Like I, I knew a bunch of organisms that lived on the reef, like I knew my neighbors. And watching that whole reef die was like watching all your friends and neighbors die or move away. And it just kind of tore this hole in my heart where I went and spoke with a bunch of coral scientists, marine biologists, to understand what was happening. And they told me that not only had my reef died that year, but a substantial proportion of all reefs on planet Earth had experienced, you know, some bleaching. And, and when I went and asked, you know, okay, um, how much time do we have left? Then if this type of thing is happening on the planet, then what, how much time do we have left? The consensus amongst two dozen coral scientists and marine biologists. 'cause I'm very thorough when I go after a thing. I didn't talk to one scientist. Um, then, you know, the consensus was that we were on track to basically extinct coral reefs as an ecosystem from planet Earth by the year 2055. And I was like that. That's insane. That means like the pain that I just felt the whole world is going to experience. But we're going to lose all the reefs, not just. A reef next to a neighborhood in Hawaii. And I, I asked them like, well, if that were to happen, is there any chance that corals like come back on planet Earth? Like, could they reeve? Like what happens if we extinct all these corals and these, these are biologists, marine biologists, you know, coral scientists. And they're like, it is possible. I mean, evolution can do a lot of things, but I think you got a budget like 20 million years. And I was like. What, what are we doing? We're making these decisions right now that are 20 million year decisions and I, and I have like, no, oh look, I have faith in humanity, but I don't have a a hundred percent certainty that we're gonna last a million years, much less 20. And this idea that like we're about to go do something that is going to wipe out the, you know, one of the richest ecosystems, well, you know, obviously the most biodiverse ecosystem. In the oceans for the rest of human history. It didn't sit right with me and I wanted to kind of figure out how to step up to prevent the same tragedy that I experienced. I wanted to see if we could make the big moves to, to try to avoid that tragedy for the totality of the world.

Sean Weisbrot: Hey, business leaders and marketers. What if your brand could be featured right here? This ad spot could be yours. This channel is watched by a dedicated audience of ambitious founders, executives, and professionals who are actively looking for tools and services to help their business grow. If you wanna put your brand in front of this highly dedicated audience, that's difficult to reach. I'm currently looking for a few strategic partners for the channel. To learn more about sponsorship opportunities, click the link in the description. Let's go together. I went through your website after our first conversation, and I'm so used to venture capitalists saying, we back, great founders doing blah, very, uh, monotone. Nobody really says the thing that they, they are focused on and. When I saw your website, I was like, oh, this is not the way investors talk. This is the way that someone who's deeply concerned about something, talks about something, talks about a topic, and I've been deeply concerned about the environment for a very long time. And I am constantly harping on everybody I know to do better. Um, even though, you know, we could go on and on about how there's a number of companies that are probably the largest reasons for these problems, but also we have a responsibility because of our actions and the actions of those around us. And you are, what you're doing is the first time in my life where I felt compelled to. Think more about how I can be involved in climate tech, because anyone can build an ai. Anyone can build a B2B SaaS, but people that are out there trying to build something that's gonna change, you know, how the environment is in a positive way. They're trying to take out industries that are destroying the planet with better solutions and whatnot. It's, it's inspiring because there's so many people that are out there. That are saying but not doing. And something that was also really interesting to me, I don't have the exact statistics, but I came across something where some people were saying the best exits they've had or the most consistent exits they've had were from climate tech companies. That of all of the other companies that they've invested in or been involved in, climate focused ones changing the way things operate, are the, by far the best, uh, returns on their investment.

Tom Chi: A lot of people are chasing, you know, AI have been chasing enterprise SaaS, have been chasing all these sorts of things. And it means that for a lot of these things, it's like the, like the 10th version of the thing. Like it's the, it's the 10th option. So like if you're an enterprise SaaS and you make like new procurement software, you make new a TS tracking software, you new make new project management software, there's literally 10 other good options. And like when you introduce, you know, the 11th option to the marketplace, then we, we tend to call these sorts of decisions, discretionaries. 'cause Oh, I use my discretion and I try to pick the best option out of 11. Right. But in the, in the work that we do, here's the, the, the thing about physical production and physical industries, they're actually way less diverse than that. There aren't 11 options. Everybody that produces a particular good has basically. Zeroed in on the, the technical approach, the, the manufacturing approach that is currently the lowest unit economic. That's it. There's, there isn't like 5,000 different approaches to these things. There's not even 11. You, you typically have one or two approaches, which means if you beat that approach, you are the monopoly. It's not discretionary. If you actually have three times, you know, cheaper unit economics than the current cheapest approach, you are the new monopoly immediately. And this, you know, because honestly it's a little bit harder, uh, to go get these things done, you know, out of the gate than it is to just write another piece of software and. The people that are able to, you know, bring the right skills to bear, it is less hard for the people that have the right skills to bear. Like, for example, in, in our team, all three investment partners have a background in manufacturing and we have three other people on the team that just support the manufacturing de-risk for our companies. And I think if you have that, then physical businesses are not nearly as daunting. I think a lot of folks get into physical business. Oh, it's a hundred times harder. No, it's a hundred times harder for you 'cause you've never done this type of work before. But if you're a person that has set up lines before has done manufacturing in various types, it is another turnaround the block. And not to say that you can't have a cost overrun or that you can't get an estimate wrong, but it's not an alien thing to you. It's a thing that you've shipped multiple times in your career. And here's the n plus one. Iteration of you shipping another thing like it. So that said, if you are able to build the right team that's got the expertise to, for, you know, for which it's not as hard a discipline, then yeah, you end up, you know, you end up backing things and getting them over. The manufacturing de-risk that become the new defaults. And the new defaults basically are economically a monopoly.

Sean Weisbrot: So what exactly are the things that get you excited? Like you had mentioned, uh, uh, several times, cheaper cost of production, something like that. What, what exactly do you look at?

Tom Chi: Uh, I'll tell you exactly how we do it. So basically, purpose of our firm is to help humanity become a net positive to nature, which sounds very lofty. So how do you go and concretize that nature to us has. Four physical sub components, air, water, soil, biodiversity. And now that we have the sub components, we can stack rank the industries that are currently doing the most damage. So for example, for water pollution, over 90% of global water pollution by volume comes from just four industries. So, agriculture, textiles, paper, and pulp. Oil and gas. Oil and gas will say they're not on the list, but they have enough. Spills and accidents that I consider that to be the normal action of the industry. 'cause when you're doing spills and accidents every year, that is just what your industry does. Even if you say, oh, that's not officially how our industry works. Anyway. So between those four, if all you did was change how those four industries related to water, you could address 90% on the global water pollution. If you, you know, if you care about the last 10%, well that's a thousand more industries. So if you have limited capital and limited time to be able to go and invest in such a way to be able to have the biggest positive impact on the planet, then you should focus on the industries that are at the top of the stack rank. It also has the benefit of the industries at the top of the stack rank are some of the largest industries in the world. You don't have this kind of like niche tam problem where, oh, I care about the environment and now I'm on some little niche. You know, sub wrench. No, we're going after the big metal, the stuff that basically creates our modern world. Now, what we're looking for when we're trying to go upgrade that is we, we look at our investments through this lens that we call the triad. The triad is a disruptive deep tech, which helps to usher in radically better unit economics, paired with radically better environmental economics. And what does radically better mean? For us radically better. If you're trying to go displace primary manufacturing production of goods and services that are driving a lot of the damage to air, water, soil biodiversity, then a good rule of thumb is whatever the margin is for that industry, you're gonna wanna find the deep tech that is gonna crash the primary cost of production by more than three x that margin. And that is basically the range that basically drives, um, incredibly um. Incredibly robust and active upgrading of the industry as opposed to kind of like, oh, let me pilot and let me sample and let me kinda like muck around for three, four years and then maybe I'll do like a little co like a like a little co facility with you. And then maybe on year eight, no, like you want landslide sort of adoption. And I think what people have not been thinking about in this space before. Because look, a lot of people that do this type investing, they do it because they think that they're doing the most moral thing. So they're like, yo, I'm gonna do this because I really care about things and I'm gonna make these amazing products that people are gonna pay more for this. The idea of a green premium, I'm gonna tell you, green premiums will never change. The industrial defaults. The the B2B players that are basically doing the industrial defaults could care less, that you might be able to sell a luxury green good to, to two to 3% of the audience Who cares? Right. They care about lowering the lowest cost, not raising the highest cost. So green premiums step out. We don't touch it. But amongst the people that care about the environment, there's also a big camp that is excited about getting to parody. They basically say, well, what if the, what if there's a clean, green way to do this industry that had the same cost structure as the dirty damaging industry we have today? And honestly, that sounds pretty promising. But if you try to go do that in practice, you're gonna find that you are. Devilled by what, what in our firm we call CapEx inertia. And what that basically sounds like is if you went to a factory owner and you said, oh, I have this clean green solution. And it like produces equally, you know, a good of equal quality and you have the same opex, but you know, it reduces your emissions by 90%, it gets rid of half of your water pollution. The particulates are gone. So your, your staff is not going to wear, need to wear masks when they're at these two stations. Right. Sounds like a great pitch. If you gave that pitch to a actual factory owner, then they would reply with something like this. They would say, okay, let me get this straight. You have this new invention, I gotta, you know, and you want me to adopt it. And if I adopt the invention, I get to go from my current CapEx. So let's say it's a hundred per unit CapEx. I get to go from that to your, the new CapEx, which is a hundred per unit CapEx. So what you're telling me is I get to go from a hundred per unit CapEx to a hundred per unit CapEx, and all you ask of me is that I, uh, that I dump $250 million of productive CapEx and the conversation's over, right? And this is why parody doesn't really do what people think it does. Like parody could only really compete on a greenfield build, where the people are confident enough in the new approach that they would be fine getting the same opex on a greenfield build. But when you go and look at the industries that are doing the most damaged nature, they already have huge install bases. It's mostly brownfield, and it means that largely it is brownfield upgrades. It is not greenfield builds, which means that you actually need to beat the unit economics profoundly. And if you beat the unit economics by three x more than margin. The math flips around. It flips around to if I don't upgrade within three years, if I don't upgrade within five years, I'm losing crazy money. But with the parody math, then if you do upgrade, you are losing crazy money.

Sean Weisbrot: How can founders. Get their head out of the box so that they can come up with these solutions. Because, for example, I just came across a startup that I wanna talk to you about a little bit later, that they're, they found a way to get costs lowered by 40%, and that's not the three x that you're looking for, but I think they, they're trying really hard.

Tom Chi: So let me go to the foundations of where the, the winds come from. And, uh, we didn't talk about this, but you know, I have, my formal training is in physics and electrical engineering with a specialization of robotics and signal processing, but I, I actually was a working physicist for six years. I was an astrophysicist and published research and did peer reviews, all those sort of things. So I do know how to do the fancy equations in physics, but like what I explain to people about our investment work is. It's amazing investing in physical businesses because when you invest in physical businesses, literally everything has to follow the laws of physics. So it actually gives you all these additional diligence tools that you would not have. If you're looking at software. If you're looking at software, software is a little bit like clay. If a person can imagine it and they're a good enough coder, you just need to believe that they could code it. Will it actually be coded at the level that it can achieve all the things that they said a lot of times, no. Could, you know, even if they code it right, does it always get picked up in the marketplace? No. A lot of times, no. So there's a lot of have to believe that, that you do in software that you don't need to do in hardware. In hardware, the physics, if you get way better unit economics, it is typically because you have way better physics and you can actually check the physics at the beginning. So even though I'm a, I'm an actual physicist and I know how to do fancy equations, I like to go and. Simplify physics for, for folks that didn't study it formally by saying it's really nothing more than the study of matter and energy moving through time and space. So there's only four things to track, and if you're trying to understand whether a new piece of technology has the ability to go displace the incumbent industry, you actually just go head to head on those four attributes. How did matter change between the old system and new? How did you know energy use change between old and new? How did time change? How did space change? And if you don't have a big win on at least one of those four attributes, you can already pass on the deal because it means that they're using similar physics to what is uh, the incumbents have been using. And if you use similar physics, you're going to end up with similar unit economics and it's gonna take you 10 years to catch up to the unit economics of the existing industry, which means it's kind of a dud as investments go. So to answer your question really directly, for this team that has got the 40% win, I would actually sit down and say, well, are you at the theoretical maximum of your physics win? Right? So for example, if you know half of the cost of the, of the system was the feed stock cost, the atoms that went into it, but you're able to go reduce the amount of atoms really substantially because of the, you know, the way that you're handling matter. You just need way less of it to be able to go build the thing. Then I can already say that like just based on your physics, you have the potential for savings that is this large, right? Because you were able to get rid of 80% of the feed stock on 50% of that cost structure. So that's where the 40% wind comes from. Now, if that's where the wind came from, and they had actually all fully realize that, then the 40% that they're at is actually the theoretical maximum and they can't go further, but. If some of the wind was coming from matter and some of the wind was coming from energy. 'cause let's say the other half of the cost structure of this hypothetical business was energy cost, right? Well, if you could reduce that by half, then you could say, well, there's another 25% that I can get on top of that 40%. Does that all make sense?

Sean Weisbrot: Yeah. And so is this something that you go through with any company that you invest in?

Tom Chi: It's the literal first set of questions in the technical review. And it's actually honestly very easy for technical people to answer questions about matter energy, time, and space. 'cause I'll go in there and it's like, Hey, how did energy change between the old process and the new process? And they're like, well, in the old process, the reaction requires, you know, 550 joules of input in order to go drive. And in the new process then it only takes 143 joules in order to go, you know, have the reaction take place. And I'm like, okay. So like, honestly, technical people can answer these questions incredibly crisply and the, and this is in comparison to when technical people make like business performas and. And you know, these extensive decks, I know that a bunch of that stuff's bullshit, right? Like people draw like the, you know, the ascent to like the hockey stick curve on all these things. It's like, that's not gonna happen. I know we're doing the dance. You need to say it'll happen. I use it to go see how you do business modeling. And that's really all that's happening on this slide. But when it comes to the physical stuff, technical people are very close to the metal. They can typically tell you exactly how much matter has been reduced, how much energy has been reduced. How much time or space has been reduced in the new solution? It's lit. Literally the thing they built.

Sean Weisbrot: It's really interesting 'cause yeah, just going back to other conversations with investors, like they, especially on the software side, you don't have those conversations usually. It's always just, you know, how many customers do you have? How much are they paying? How, what's your churn look like? And, and some investors don't even ask those questions.

Tom Chi: Software, like I said, is like clay. And actually this is why I think the conventional wisdom is wrong, right? A bunch of people recently, because we basically had two and a half decades of almost entirely software focused venture. And it means that the people that created Silicon Valley, they've all aged out, but it's called Silicon Valley. It's not called lines of Code Valley, it's called Silicon Valley, because original venture capital was all hardware. So the idea that suddenly, oh, there's no way to make money in venture capital when you do hardware, what are you guys talking about? It was literally invented, the entire discipline was invented on hardware. The fact that we'd spent a generation just looking at software, well, that's our fault, right? And because we spent a generation on it, then we convinced a bunch of folks like, well, if you really wanna be a serious investor, you really gotta understand software. Look, I actually understand pretty software. Uh, I understand software pretty well. I was a software engineer. Did that for several years. I like ran two multi-billion dollar software businesses. Like I, I do know what that side of the coin looks like. But even with all of that background, then I will tell you that I love the additional diligence constraints that physical businesses allow, that you cannot apply to software. 'cause I can get so much clarity on this investment, even when it's three people and then we're just talking about. Time, energy matter and space on their approach versus the old, right? Like with software, when it's three people, it's like, oh, well, you know, we haven't built that much yet. And um, you know, if you just believe then and put in some money then, and you believe in our pedigree is that we can build this type of software, then maybe it'll turn out well for you. And the reason that those investors asked for the metrics that you just mentioned is those are the first times that you can dive, you know, depart from just pure faith and belief. And actually get a number like, oh, what was your monthly, you know, recurring revenue. Oh. Like, you know, tell me about like, which features the customers are using. That's the first, like actual feedback that you can get on software with the, with, you know, physical businesses. I can pre-assess all the things just on matter, energy, time, and space, even before they've done 90% of the work.

Sean Weisbrot: So even though you're able to do that. What's the point in which you like to invest in them?

Tom Chi: Yeah, absolutely. So there is a specific point that we wanna be in the, in, uh, getting into the business and if you're familiar with the government TRL levels, um, which are basically about technology readiness, um, then I basically have a version of that for venture, which is a bit simplified because why add extra things for a model if it's not relevant to you? The particular application space you're, you're applying it to. Uh, but for, for me, you know, in venture there's kind of six readiness levels which are of interest. There is early lab bench, mid lab bench, late lab bench, early commercialization, mid commercialization, late commercialization. We're doing all of our investments as a early stage venture, uh, firm in late lab bench, early commercialization. Because what we want to do practically is not take on science risks. We wanna take on engineering risk and manufacturing risks because, you know, science risks and, and engineering risks are quite different. Like science risk is, I don't even know if this thing could be invented and I have no like, sense of exactly how much time it would take me to invent it, but I have a hunch that it could work. And okay. I mean, there are some investors that want to take on that type of risk, enormous risk profile. A lot of those things never work. Or if they do work, then they take substantially longer than the 10 year fund life to be able to get into any sort of interesting commercial outcome. Um, and that's why we don't really touch that. But engineering risk is quite different. Engineering risk is, you know, the thing can be engineered. It is just a question of whether you can put the right team in place to go do it in the time that you hope to go do it. That's a very manageable risk compared to the unknown time risk of scientific discovery. Now, how do you tell the difference between early, mid, and late lab bench? Early lab bench basically sounds like first time in the world a thing was discovered or achieved and you know, and because it's literally the first time. Then we haven't gone through the entire process of multiple labs have also gotten the, the effect. And given that we've been able to do peer review validation, that the effect exists. And we've already seen a bunch of points in history where, you know, people jumped at the chance to go do early lab bench and a lot of money flowed. So like back in the early nineties there was a belief that, you know, with a single research team that they had discovered cold fusion. And it turned out that it was not the case, but a bunch of investors were ready to be like, how do I put all my money into cold fusion? And then like about three years ago, we had a similar sort of early lab bench thing where a bunch of folks said, Hey, we made room con room temperature soup protectors. It's gonna change the whole world. And a bunch of investors like, how do I throw money at it? And it's like, guys, it literally has not been validated by one other team. And for both of those, when they actually tried it, it wasn't a thing like, it, it, it never even existed. Look by by comparison. I actually still consider the, the nif rean, uh, the NIF result National Ignition Facility at, uh, Los Alamos, which is the first in the world to get Q greater than one for fusion. I actually still consider that to, well, that is a verified result. Like we can tell that that actually happened, but I still consider that to be incredibly early. That's like somewhere between early and mid. Now what is Mid Lab bench? Mid Lab bench basically is multiple teams around the world have been able to replicate your result and verify that it definitely is a true result given that it's a true result. A bunch of people are contemplating. Well, you know, this might have important implications for industries. Oh, this might have a great application if we were to put it in this spot in the world. But at Mid Lab bench, you know, the result is real and they, people are speculating the industries that it could, that it could. Um. You know, drive fantastic innovation on, but nobody's like built a prototype to go show that, you know, um, that like it does the actual effect that it needs to do for that industry. And then late lab bench is the point where somebody has built that first prototype and you can just measure the inputs and outputs and actually see. That the, that the effect that you're trying to drive into industry. Oh, the reduction in thermal energy input, the, the higher efficiency on so and so, work cycle, blah, blah, blah, actually exists. And if that exists, then we're, we're ready to invest. Right. We don't care that there's a lot of engineering risk after that. We don't care that there's a lot of manufacturing risk after that. So we're still quite early, but we're past the science risk.

Sean Weisbrot: What's the most important thing you've learned in your career so far?

Tom Chi: Oh my career or in investing?

Sean Weisbrot: What, either way, what, whichever is you find is more, uh, important for you.

Tom Chi: Sure. I mean it like in my entire life, I think the most important thing that I've learned is that people are obsessed with states and status and nouns. Where it's like, oh, I have this title now, or I, you know, or you know, I am now a billionaire or whatever. Right. And really the most interesting thing is metabolisms. The thing is the verb that you are right. The verb that you live in the li in your life is you know the crux of what your life is. The achievements are just things that get integrated because you do the verb long enough. So for me, the verb of my most of my life has been incredibly simple, which is every day learn something, every day, build something. That's it. Given that I've like used that to go learn so many things and build so many things in so many spaces and become better at building every single day, and that is the metabolism that's created my entire career. But I think that like people get way more focused on like, oh, you got this outcome. You were a founding member of, you know, of Google X. Oh, you worked on the self-driving car. You shipped this product that 2 billion people use, and that's great. I'm fine with it. Like that. Those are also factual, but on the flip side of it, it's like, Hmm. Is that how that happened though? No. The, the, the how was the metabolism and the metabolism was incredibly simple. It was every day, learn something, every day, build something.

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