E160: How a SpaceX Rocket Engineer Became a Top Deep Tech VC

Jamie Gull is the GP/Founder of Wave Function Ventures, a deep tech seed fund, and an engineer turned investor who previously worked at SpaceX during its early, intense years of scaling. In this episode, Jamie and I discuss the high-responsibility culture at SpaceX, how it shaped Jamie’s approach to company building and investing, and what makes a deep tech founder stand out. We also explore why fast iteration matters more than perfect planning, how techno-economics drive investment decisions, and why deep tech’s reputation for being overly capital-intensive is becoming outdated. Jamie shares firsthand stories from his time working under Elon Musk, his angel investments in companies like Boom Supersonic and K2 Space, and the founding principles behind Wave Function Ventures. If you're interested in the future of deep tech investing, how to identify category-defining founders, or how hardware startups can scale efficiently, this is a must-listen.

• 0:00Speaker 00

  While at SpaceX, you had several one-on-one meetings with Elon. These have been popularized by Marc Andreessen recently. Tell me about these one-on-one meetings and what did you take from lunch?

• 0:09Speaker 01

  Generally, they were checking in on a system that I was designing to make sure things were on task. And was there any problems that were happening that he needed to come in and help fix? And that's kind of what he's best known for. You know, he still retains that chief engineer title. I don't know if it's official, but that's his role. Help solve the problem, dive in, fix it. Oh, we're fixing this today or this week and I'm going to sit here until it's done, which is extremely effective.

• 0:42Speaker 00

  Today, I'm thrilled to welcome Jamie Gull, founding partner of Way Function Ventures, a seed fund investment for deep tech and hard science. Jamie began his career as an engineer at SpaceX in 2010, when the company was still in its early days. Today, we'll dive into Jamie's firsthand experience with SpaceX's responsible engineer culture. We'll also share insights from one-on-ones with Elon Musk, lessons learned from building rockets, and how those principles shaped Jamie's investment approach as a venture capitalist.

• 1:22Speaker 00

  Jamie, welcome to the How I Invest podcast.

• 1:24Speaker 01

  Thanks for having me.

• 1:25Speaker 00

  Jamie, you were an engineer at SpaceX in 2010, 15 years ago. What was it like working at SpaceX at this time?

• 1:31Speaker 01

  Yeah, in 2010, when I started, things were moving super fast. Falcon 9 had launched a handful of times, but we were basically redesigning the rocket in between launches, based on what we learned. All the engineers would sit down after a launch, crunch the data, and immediately go back to work to redesign it for the next time to make it work better, fix any problems. And I cut my teeth right before that at Scale Composites doing aircraft design. They're very well-known for rapid prototyping and putting a lot of responsibility on young engineers. But when I went to SpaceX a couple of years later, it was like that, but it was on steroids. The responsibility level and the Excellence level was a large jump up and it reflected it in the culture and the pace of what we were working on.

• 2:15Speaker 00

  SpaceX pioneered this concept of a responsible engineer. What is a responsible engineer and how did that apply to how you went about your day to day tasks?

• 2:25Speaker 01

  So a responsible engineer is the person who's responsible for the design, but more importantly, the delivery of a successful system on the rocket. And what that means in practice is that if, if they come to you and say, I want you to design this system. Traditionally in aerospace, you would sit down, you'd do the, the requirements, the CAD. And then you would maybe throw it over to an analyst who would tell you, it's not strong enough here. Fix it. Then you throw it over to a pre-production team who would build it and you can pass it off. At SpaceX, you're responsible all the way through production until the moment the launch button hit is hit.

• 3:06Speaker 01

  And so if something goes wrong with the analysis or the pre-production or the testing or the actual production, you're the person that has to go fix that. So in practice, what that could look like was a vendor promises you they're going to get you a part in eight weeks with some specs. They call you four weeks in and say, hey, this is going to take 12 weeks. You take that to say the VP of Vehicle Engineering and say, oh, this is going to get delayed, which is going to delay the rocket. The answer is more not okay, we got to change our schedule. It's why aren't you on a plane to that vendor right now? Why are you talking to me? Go fix this. So you would have to fly out, sit down with the vendor and pull the schedule back in and get it done right. Like, so the responsibility doesn't end when you release a drawing and then throw it over the fence.

• 3:52Speaker 01

  You go out to the production floor and you damn well better be out there a couple of times a day to make sure your stuff is being built properly and there's no problems. And if there is a problem, you can literally pull out a red pen, redlining, fix the drawing, tell them how to do it differently. And that is a release drawing at that stage of the company. It's changed a little bit now, but that again is going back to you being the responsible engineer. You're making the call live and, and it just flows down from there. So it's a very high level of responsibility and essentially a zero excuse environment. You don't get to make an excuse that some other team. Didn't do it fast enough or dropped the ball. It comes down to you.

• 4:37Speaker 01

  And if it's not delivered on time on the rocket and it's a successful launch, it's your fault.

• 4:41Speaker 00

  It's essentially getting every single engineer in the company, the same level of responsibility that startup CEO might have. And you put this on every single person within the organization.

• 4:51Speaker 01

  That's a great analogy. Like you don't get to make an excuse and you don't get to say, hey, that team changed some requirement. Like you have to sit down and hash it out live with the other responsible engineer and come to an agreement that's best for the company and the program.

• 5:07Speaker 00

  What are the downsides of this responsible engineer framework? And why don't more companies do that?

• 5:12Speaker 01

  The biggest reason people don't do that is that a lot of people can't perform to that level. And so if you don't have the systems and checks in place, it falls apart. Like all of a sudden, something doesn't get done, falls through the cracks and nobody catches it because there's not enough safety nets in place. And so you have to have the entire company bought into that culture and idea. And you have to have everybody who can perform in that level. And that's really hard to do. Let's be honest, like a lot of people can't perform at that level in a high pressure environment. And so if you don't have that, you gotta have different systems in place.

• 5:52Speaker 00

  When we last chatted, you mentioned that there was three different types of people at SpaceX. What are these three different types of people?

• 5:59Speaker 01

  Yeah, it's kind of a broad generalization that I've come up with. And it kind of goes back to the responsible engineer ethos and culture. And I've kind of bucketed three people, people into three buckets, which is those who are there for three months to a year. And they have to depart because they're let go or because they decided they can't keep up either pace wise or responsibility wise and leave on their own accord. Then there's folks kind of like myself. I loved it there. I was there five and a half years. So put in a serious stint, but wanted to do other things with my life and try other things. And then there's folks who've kind of been there 10 or 15 years. And when you ask them, do you want to do something else?

• 6:45Speaker 01

  They're like, what else could I possibly work on that's cooler than this? Why would I leave?

• 6:50Speaker 00

  There's no way to out frame the mission of going to Mars. For some people, that is the ultimate mission for humanity.

• 6:57Speaker 01

  And there are other very important missions out there that in my eyes are just as important, but it's hard to beat that straight up like more than, you know, in order magnitude, more interesting or harder. It's not possible.

• 7:10Speaker 00

  You're in this very intense culture at SpaceX of the responsible engineer of everything having to be done, everything being mission critical. Looking back, that was now 15 years ago and you stayed till 2015, roughly 10 years ago. How did that evolve you as a person? And do you bring anything from that period into what you're doing today?

• 7:31Speaker 01

  Oh yeah, absolutely. The upside is once you're in that environment, that's what your expectations are for yourself and people around you. And it means you can perform at a really high level, get other people to perform at a really high level and do really big, interesting things. And like, that's the upside. The downside is the exact same thing. Once you're exposed to that and that's your expectation, it's really hard to reproduce.

• 7:56Speaker 01

  Or you go to another company and it's not at that level. And you get to maybe sit back, which is nice, take things a little bit slower, not be as stressed out, but it also gets super frustrating when somebody will come to you. I hear this all the time from former colleagues. Like, oh yeah, I had to buy something today. It was $300. I had to get six signatures. It took two weeks. And at SpaceX, you would have had it that afternoon. You make your own decision on something that costs that little. And then, you know, your colleagues making excuses, like I was talking about with the responsible engineer framework of like, oh, that's somebody else's problem. And that's really frustrating to hear when you're not used to that.

• 8:38Speaker 01

  But you do have a more relaxed environment and in some ways that can make people happy.

• 8:42Speaker 00

  While at SpaceX, you had several one-on-one meetings with Elon. These have been popularized by Marc Andreessen recently. Tell me about these one-on-one meetings and what did you take from them?

• 8:52Speaker 01

  My personal experience was maybe less interesting from a Marc Andreessen or public sphere.

• 9:00Speaker 01

  Approach. Generally, they were checking in on the system that I was designing to make sure things were on task. There weren't any decisions that had to be made to change course. And was there any problems that were happening that he needed to come in and help fix? And that's kind of what he's best known for. You know, he still retains that chief engineer title. I don't know if it's official, but that's his role. And so he, from a high level, looks at things, but then also dives, deep dives into all the subsystems once in a while, checks on things and makes decisions. And when there are problems, generally schedule wise, but also performance wise, he'll go sit down with the responsible engineer

• 9:42Speaker 01

  that's at very bottom of the engineering org and help solve the problem live. Dive in, fix it. We're fixing this today or this week, and I'm going to sit here until it's done, which is extremely effective. It also can be nerve wracking if you're in that seat from the RE side.

• 10:02Speaker 00

  Is there some higher level strategy there to show that he's in the pit with the responsible engineer? Or is it just that he sees this as unlocking the most important bottleneck?

• 10:12Speaker 01

  It's both, for sure. Like, it's, I mean, a CEO's biggest job is outside of being the chief storyteller is unblocking bottlenecks. And so when you dive in like that, everybody knows that you have the resources there, the backing, but it's also a spotlight on the problem. And you don't get to hide anything, right? Like, you'd have to fix it now. The boss is in the seat with you.

• 10:38Speaker 00

  So let's fast forward to today. You run a seed fund called Wave Function Ventures, a $10 million fund focused on deep tech. Tell me about your fund and tell me about what you look for when it comes to founders.

• 10:50Speaker 01

  Wave Function is a deep tech VC fund that I started last summer. My definition of deep tech for this fund is hardware, hard problems. I'm not looking at biotech. And I'm not doing software for hardware. So I'm focused on actual atoms. I do that due to my background and expertise, but also my strong belief that that's what makes a large difference, a positive difference in this world, is the actual physical structures. Like, we're in a post software change everything world now, outside of AI. So that's what I'm focused on. I bring to the table a pretty interesting background as a fairly hardcore engineer. And then I was a two-time deep tech founder myself.

• 11:35Speaker 01

  And I started a space deployables company and then an electric vertical takeoff and landing aircraft company, went through Y accommodator, raised money. I got eight government contracts with the air force. And then we got acquired by a company in LA called Amp Air in 2023. So I've been through that wringer on the founder's side, been through that wringer on the engineer's side. So I can bring a pretty unique lens to the investing landscape, both through assessing companies, but then also once I make an investment, actually helping them.

• 12:08Speaker 00

  You have a pretty strong view on business founders solving technical problems or MBA going after technical problems. Why is it such an issue for an MBA to go after a technical problem, assuming that they could partner with the right chief technical officer?

• 12:24Speaker 01

  I don't love seeing like an MBA run a deep tech company without some, a very high bar and some other things being in place, not even, not just a technical co-founder. And one of the reasons there is in deep tech, it's, you know, if you look at software, you're like, okay, I'm solving this problem for a customer that I can understand really well. And somebody can build that software, like I know they can do it. It's just a matter of how fast, how efficiently, and how good will the software be? In deep tech, there's a bigger question of can it be built? Can it work? And can you do it with the right economic impact for your customers? And not understanding that deeply from a technical perspective makes it much harder

• 13:08Speaker 01

  to navigate the business side, the pitching side of a company as a CEO. So it's, you've really got to have that understanding because especially in the early days, you know, you're changing things on the fly, you're talking to customers. If you don't understand that from a deep technical perspective, how can you talk to a customer and say, here's what I can actually deliver for you now that I've heard what your pain points and needs are? If you're an MBA, you gotta go back to your CTO and say, here's what they need. Then they have to do a bunch of research and then you gotta go back and forth. So it just rapidly slows you down as you go through the IDMA's and you're finding product market fit. So it's a, it's a tough sell for me to have a non-technical CEO.

• 13:51Speaker 00

  You can't disintermediate the selling from the technical consultation. It becomes something that one person needs to be handling and one person leading the company.

• 14:01Speaker 01

  At later stages, I think it's totally reasonable to decouple that. But at early stages, it's a huge hindrance. It can be done, but it's gonna slow you down. It's gonna cost more and early-stage startups, it's all about speed of execution. And so you're basically handicapping yourself.

• 14:19Speaker 00

  Talk to me about techno-economics. What are techno-economics and how does that inform your decision-making process?

• 14:25Speaker 01

  Techno-economics is just meshing of the economics on the business side and the, the technical design and build. I'll give you an example. I've looked at another, a number of companies and say hydrogen generation space. That is a product you have to deliver to a customer at a certain price point, certain volume. And you've got all these assumptions through your tech stack of how you can actually produce hydrogen. So you can do that analysis and then do a rough sensitivity analysis at the early stage. It says, what happens if this input doubles in cost to a geopolitical concerns? What does that do to how much I can sell it to my customer for?

• 15:09Speaker 01

  Or what does that do to my margins? And in deep tech, they're just so deeply entwined compared to software where your, your techno-economics is basically, how many engineers do I need to build this? And how much does it cost to sell to a customer? You're not really dealing with the fact that your software itself is gonna change in price due to some external factor.

• 15:31Speaker 00

  So even though something could be technically feasible, it becomes infeasible because of the economics and that nobody's gonna buy it if you were to create it.

• 15:38Speaker 01

  Exactly. And if you get that wrong by a large factor upfront, what you could find is that you've built something successfully. You've delivered, but you can't sell it. And you, you know, you can back yourself into a corner where it's not possible to get that price down to a point where it makes sense for people.

• 15:57Speaker 00

  Think on this framework on how you figure out whether a hard tech company is investable. Thank you for listening. To join our community and to make sure you do not miss any future episodes, please click the follow button above to subscribe.

• 16:09Speaker 01

  I mean, there's a bunch of things I look at, some of which are very similar to all venture capital, the top one being founders, founders, founders.

• 16:20Speaker 01

  This, you know, can go back to my requirement or near requirement, I should say, about the CEO being a technical founder and also their ability to execute at an excellent level in the build process, which looks like a responsible engineer from SpaceX. You have to iterate quickly. And if you're coming from a background of like slow waterfall design processes, where you are choosing your requirements incredibly carefully upfront, and then doing this very careful design and build to this perfect end product, you're going to find out that your assumptions were wrong in some way via your customers

• 17:02Speaker 01

  or your, or your technical assumptions. And now you're stuck and you've wasted all this time. So the ability to execute crazy fast on the engineering side, but also do it on the fly and adjust as you go is incredibly important on the founder side.

• 17:19Speaker 01

  One of my superpowers is because of my engineering and founder background, it's relatively easy for me to assess, is this tech possible? Does it make sense? Or is it pie in the sky? And kind of skip through that process incredibly quickly and dive into the, the tech economics and the founders at a deeper level, rather than having to spend a bunch of time researching the technology to see if it's feasible.

• 17:46Speaker 01

  So those are the kind of the the top things I look for. There is a somewhat of a myth out there around deep tech that it's much more capital intensive than software and you can't get good returns. And that's the myth is getting busted. It doesn't mean that it's not more capital intensive and time intensive upfront. It is. It's hardware. It takes longer and it's more expensive to develop. But where the myth is getting busted is once you're in market, you can scale differently. So you can scale with things like project financing or government contracts that you're getting paid for and not by continuing to have the venture capital cannon fired over and over as you eat through capital. And we've seen

• 18:28Speaker 01

  software, the early days, it didn't require a lot to get into market. And then, once you were there, you could scale rapidly. Now, it's such a crowded space. And we've seen this so much right now in AI, is it becomes a race. It's easy to replicate. So it becomes a race. And how much money can you throw at the problem to scale your team and scale your customers? There's some interesting charts floating around the Twitter sphere right now about comparing valuations and amount of capital required for some very well known companies. And when you put them side by side, a lot of the deep tech stuff is about the same as the software for capital required and valuation of the company. So that that myth is being busted. And the reason is, the second half or second two thirds

• 19:12Speaker 01

  of company growth in deep tech can be more can look more like an industrial process where you scale with project financing, you scale with government help, and you're bringing in tons of revenue from your customers. And you've built this large moat because the hardware is hard to develop, because there's a somewhat limited customer set, and you've you've locked them in. It's much harder for somebody to chase you once you're there. And so you don't have to keep throwing dollars at that problem. You can scale more again.

• 19:41Speaker 00

  Somebody might counter argue that by saying, well, that's only in the software companies that have scaled really big, or the rideshare companies that have raised billions and billions of dollars. But venture capital fundamentally is about those companies. What happens if you succeed and all the returns actually go to those power law outcomes to those huge winners? So the real question is, if you're going to be successful in this company, will it take more or less money? And if it takes the same amount of money to go public, that's really what investors should be looking at versus what does it take the average company or the median performing company to get to scale?

• 20:17Speaker 01

  That's exactly right. It's still a power law driven business. So, you know, if I can dump $20 million into a software company and they can sell for 500, that's awesome for the founders. Venture capitalists aren't chasing that. They, they need those 50, 100 or 1000x returns to, to have their fund perform. And so it's about the big winners, just the same in deep tech.

• 20:41Speaker 00

  And given that it's deep tech versus traditional software, are you still looking for the same level of power law outcomes? And do you still have the same economics as an investor? Or do they differ slightly?

• 20:52Speaker 01

  Definitely still looking for the power law outcomes, almost, almost exactly in the same way as more traditional venture capital. You know, outcome wise, I think in deep tech, you might be able to expect a few more smaller winners instead of failures, because if they can get to market, they can make some good money and be a decent company versus maybe your consumer where you just never found consumer product fit. And it's, it's going to go to zero. I think in deep tech, you'll, you'll see more like small, middle outcomes as opposed to going to zero. But again, because you're power law driven, those don't really matter. You still need the big winners.

• 21:36Speaker 00

  And in deep tech, you typically have the issue of technical risk, not market risk.

• 21:42Speaker 01

  Yeah, the stuff that I'm focused on, that is the case with the caveat. So I don't want to back something where it's unclear if you can, if you are able to build it, that there's no market for it. There's obviously market risk in the sense that you're not totally sure the customers will choose you. Or, you know, that somebody else might not come along and eat your lunch. But it's clear to me when I'm investing that like there is demand for for that product. The technical risk is there, except for I would I would caveat that with, I'm not looking for science technical risk. I'm not looking for can this be done or not? I don't want that risk.

• 22:26Speaker 01

  I want it. Can the team execute well enough with this idea? That kind of technical risk from an engineering risk perspective. So there's definitely cases where they can't execute well enough and they can't build what they're promising, but it's not, is it even possible? And it's going to take three years to find out and you get a binary yes or no after three years, which you could compare to more like biotech is is commonly in that realm, where you can have a early stage that they after three years, they figure out in the lab like, oh, this doesn't actually work. So I'm not looking for that type of technical risk at all.

• 23:02Speaker 00

  How do you gauge whether something's a scientific risk or an engineering or execution risk before something's actually developed?

• 23:10Speaker 01

  The stuff I focus on is right idea at the right time, bringing the right things together. And I love to give the example of K2 Space, which is one of my angel portfolio companies. K2 Space is building large satellites for a Falcon nine and Starship world, where launch costs have come down. They're competing against what used to be a half billion dollar communications bus that took five to 10 years to develop and build. With a much cheaper thing where they can throw, throw mass at the problem or throw non-exquisite engineering at the problem because it's so cheap to launch. So there's technical risks in the sense of can they engineer that? But there's, it's all known processes. Satellites have been flown for a long time.

• 23:54Speaker 01

  They're putting components together in a new way with a larger satellite. But they're not just like inventing something from scratch. And so the timing there is key, because if they had done that pre Falcon nine, it would have been a nonstarter. If they'd done that pre Falcon nine reusability, probably wouldn't have been viable. Once Falcon nine's launching multiple times per week and costs have come down a bit, also to make sense, and they know when Starship comes online, costs come down even more and they can throw even more mass at the problem. So that's a right time. You know, bring together the right things without a lot of science risk involved and a killer team that executes like crazy. So that's, that's kind of a canonical example of what I want.

• 24:39Speaker 00

  So there that company is taking advantage of the second order effects of something that is highly likely to happen. Just a lot of people might not be thinking about what that kind of world looks like and who will be the natural buyers of the product. Other, another company you invested in, in the seed round was Boom Supersonic. We had the CEO Blake Scholl, episode 153, who talked us through the story of meeting Richard Branson, raising hundreds of millions of dollars and getting to launch. What did you see in Blake Scholl when you invested over a decade ago?

• 25:11Speaker 01

  The way I met Blake was pretty funny. That was, I want to say in 2014. It was before he'd gone to Y Combinator, before he built out a team. He started asking friends and telling them about this idea and then who do I talk to? And so I was actually the first person in aerospace Blake talked to. He asked a buddy, said, hey, I played hockey with this guy at Stanford. He's at SpaceX now. You should talk to him. Blake flew his aircraft down to Hawthorne and we, we met there. And his kind of question was like, from a technical perspective, is this a dumb idea? It's like, no, actually, I think you've kind of hit the nail on the head of this has all been done, but things have progressed technically. So you can do it better. You can

• 25:55Speaker 01

  do it cheaper. And his insight around going around the right market and not focusing on business jets or massive passenger jets like the Concorde, massive in the number of passengers, I think is the right way to go about it. And so just kind of like, I think this is a good idea. And so as soon as he formed it up, I asked him to put some money in and then helped him with his first non-founder hire with a friend of mine. So that's how I met Blake and got involved. And

• 26:24Speaker 01

  Watching him in those early days as this kind of goes against my grain of non-technical founder. You know, he was a software guy before, so I was skeptical, but I watched him knock down barriers of getting people on board or getting into Y C. And this, I don't know if he told the whole story about Branson right before demo day, but like it's crazy. Like somebody who can run through those walls that early as a non-technical founder just gave me a lot of confidence. Like if anybody's going to do this, it's Blake, so I want to back him. And so been a supporter throughout and very excited. They just flew supersonic very recently and got to go watch that flight myself.

• 27:07Speaker 01

  And Blake and I remain close. He was an advisor to my prior company and he's advisor to my fund now, so we're still heavily in touch.

• 27:16Speaker 00

  Blake's one of these geniuses in asking questions. You must have been on the, on the receiving end of a question he used to ask back in the day, which was, who is the best engineer that you know, regardless of whether you think I could recruit him or her? In your case, he actually wasn't able to recruit you and you still invested, but it's one of his great questions. The other question they asked Richard Branson is when we do accomplish this, the first flight, do you want a Virgin logo on it? So these powerful questions really helped shape the trajectory of that company.

• 27:48Speaker 01

  Yeah, and Blake's question around hiring, like who's the best person you know, whether or not I could get them, obviously led to him getting some of them. So it's a great question. And then all, and it lets people not filter other folks out, right? Like you might be like, oh, you should be so and so, but there's no way they're going to leave wherever they are. And then that and his, his investor updates and format and cadence. Both that question and his updates have become basically standard wide combinator advice. So he kind of pioneered those and now a lot of people think of that as like, here's how you do an investor update. Y C teaches you this, but like Blake was kind of the OG around both those things.

• 28:31Speaker 01

  It's been disseminated down to a lot of. founders through Y C.

• 28:35Speaker 00

  When it comes to weighing the probability of a success of a deep tech founder, how much do you weigh the actual founder and the founder's conviction versus the problem that they're going after or the market?

• 28:46Speaker 01

  Yeah, so I think the problem, the market, the techno economics are boxes that have to be checked, but they're not enough. They're requirement, but they won't tip me over. So the founder thing weighs incredibly heavy in that process. So it's almost like you can use those other things to eliminate companies from consideration, but not to make the investment.

• 29:11Speaker 00

  They're table stakes. As human beings, I think we systematically undervalue the compounding benefit of fast, fast iterations. Give me an example of the most extreme outcome where you saw somebody start with a problem, maybe in completely wrong area and how they were able to iterate into success.

• 29:28Speaker 01

  Iteration remains critically important in deep tech startups. You do not want to see a founding team, and I mentioned this earlier, set up these like perfect requirements. Here's exactly what they want from us. Here's exactly, I'm going to build it. I'm going to do this very carefully. You want to see them build something and, and start testing it, both with customers, but also internally as fast as possible. And it's a little bit different from a startup perspective, but when I was designing like the F thermal shield on F9, for example, so it enabled the reentry and landing of F9 for the first time.

• 30:07Speaker 01

  Nobody had done that. So knowing what material or what shape or how to interface with the engines was a completely open problem. And I think I ripped through five to 10 designs and materials that took about a week each in the early days. We threw them all away. This was all on computer, but then we started, you know, prototyping parts. And I saw this play out over and over where you could design like a key joint in a system that has to take all the load. And rather than do everything carefully, like you just build a prototype of the joint and break it and see what happened.

• 30:49Speaker 01

  That's your like key, your key linchpin to that system. Prototype it and break it and see what happens and then go from there. Don't, you know, spend a long time doing incredibly careful analysis. So, you know, we used to do some analysis that was both incredibly sophisticated, but also very rough around the edges and then just go test it and correlated to the analysis and move rather than spending, you know, months trying to get your analysis perfect. So that's what I want to see in founders too, is the best is when they come in, even early stage idea, and they've like built something in their garage and tested it in some way and adjusted course. Like, that's a very good sign that they're going to do this in the right way.

• 31:30Speaker 01

  Some of these things that I'm investing in are too big, too complex to do that at scale. But immediately what you'll see is the same process applied to subsystems. So what, what can we build small now and test and start testing our major assumptions as fast as possible? Again, rather than spending a year doing, you know, fantastic design work.

• 31:52Speaker 00

  I've heard the story of Idea Lab when they would do rapid prototyping. So if they were to create an iPad, he would be walking around with a block of wood and pressing buttons on a block of, block of wood before they even created the mainframe for the product. It's very difficult to actually overdo rapid, rapid prototyping.

• 32:10Speaker 01

  Yeah, I totally agree. I, that's a good example and that's hardware. It's, it's different than the hardware and the stuff that I'm looking at, but yeah, it would have been really easy to sit there and, you know, design a really nice iPad on your computer and then get it sent off to a manufacturing facility to come back with working buttons and screens and then realize that you put the button in the wrong place or whatever. And like, why did you just spend months doing that when you could have just gone down to the shop and shaved it out of a block of wood in a couple of hours? So, you know, at the stuff that I'm looking at, you can't do it as easily. But how can you apply that mindset to do that as much as possible is incredibly important.

• 32:49Speaker 00

  When you look at your portfolio, you look at the biggest winners, the power law outcomes. Are these cultures that embraced idiosyncratic attributes, like doing something very odd? Or were these best in class engineers hacking away in an existing paradigm?

• 33:05Speaker 01

  It's more the latter. There's some.

• 33:09Speaker 01

  Idiosyncrasies that usually show up in organizational design or the way the culture goes, but I think the key thing comes more down to the rapid iteration and engineering excellence as being the key drivers there.

• 33:24Speaker 00

  You have to know the rules before you break them.

• 33:27Speaker 01

  And Elon's famous for, you know, reducing and eliminating requirements as much as possible or questioning them. And that's also key. And you see that again in like a lot of big aerospace where they sit down with a bunch of committees and create all those requirements and something that will be designed and built for the next five years based on those requirements. And they never actually had the engineers on either team sit down and talk to each other and say, hey, is this a dumb requirement? Like, do you actually need this? Do I have to make this design to go operate at 100 degrees Celsius? Or can you give me back 20 degrees or 40

• 34:08Speaker 01

  degrees? And have the other team say, you know what? Yeah, we can give you that. Like, it's only going to cost us a pound here and it's going to save you 20. Let's do that. That doesn't happen in other organizations. Like, you all get the system that you design the requirements around on day one, and that's that. And nobody's ever questioned it ever.

• 34:28Speaker 00

  It's almost this redesigning within a corporation you have to do in order to account for the evolutionary need to be consistent. So everybody's been doing this process. You have to opt out of that process versus opt out of the process of using first principles.

• 34:42Speaker 01

  Exactly. And it goes right back to the classic innovator's dilemma, which is like, you know, how many people ask Blake, why isn't Boeing do this?

• 34:51Speaker 00

  Still?

• 34:53Speaker 01

  Yeah, still. One of the answers, you know, is that, like, they don't have the culture in place that's able to do it.

• 35:01Speaker 01

  And the same thing happened with SpaceX. Like, everybody laughed at us for a long time as being cowboys. What they didn't see is that every week, the design and the team was getting so much better that if you extrapolate that curve out, they were going to get their lunch eaten. By the time they figured that out, it was too late. It's almost impossible to revamp an organization to embrace that that's large. And so that's why startups have an advantage when they come in and disrupt it. So they get to build that culture and from day one.

• 35:30Speaker 00

  I think Zuckerberg realized this, which is why he was so focused on M and A and finding the company that had, you know, just grown very fast, that might still have a small user base, like in Instagram when it was starting out. He was so paranoid about this because he understood that even though at the top of the organization, he embraced innovators, he talked to everybody about it. There was no way that he could really evolve the ossified nature of Facebook, that he was doomed to being disrupted if he didn't buy the next disruptor.

• 36:00Speaker 01

  And he was very good at extrapolating those curves out. You're like, why would you mess with Instagram? It's like tiny user base and nobody cares. And he looks at the curve and he's like, well, in five years, this is bad. Well, let's just, let's just take it down now and bring it in house. Like, he was very good at doing that very early.

• 36:18Speaker 00

  As somebody that worked in the earlier days of SpaceX and was around Elon, what would you say his one biggest superpower, especially one that most people wouldn't recognize?

• 36:29Speaker 01

  Superpower is organizational design and culture. He's very good at his first principles thinking. It's how he came up with the idea of SpaceX in the first place. You know, he's a good chief engineer, although I've seen him make decisions in that regard that a lot of us thought were really bad decisions and like kind of ended up being right about that. But so his superpower is that he builds, builds the org that can out execute everybody through that culture. And once he figured that out, you know, he's replicated it, what, five or six times now? That's crazy. Like, so it's not that he's... Sitting down and doing this amazing engineering and he's like a brilliant physicist and engineer.

• 37:12Speaker 01

  And that's a lot of people think it's that it's this ability to like build the org and replicate that and unleash a team and then build them into a mission that motivates them to work that hard and take on that much responsibility. So picking the right ideas.

• 37:28Speaker 00

  Tell me more about his superpower around organizational design.

• 37:32Speaker 01

  Yeah, so it really harks back to the responsible engineer culture, but other things that are interesting is like a pretty flat organization. The ability to move up and down the org rapidly with decisions is built in. I'll give you an example back to requirements. I'm a responsible engineer. I look at a requirement. I'm butting up against another team. I want them to, you know, give me some space here so that my system can be better. And I can make an assumption that it will barely affect them, but they come back and they disagree with me. And this happens all the time. So in a lot of words, what happens is like you might, you basically like give it to your boss and like your hands off at that point. SpaceX, the culture is you email

• 38:18Speaker 01

  your managers, both managers, here's the problems as we see them. You sit down, you hash it out. Then the managers can hash it out. If they can't come to a mutual agreement, that just gets run straight up the tree. And this happens like basically on a day by day basis. And sometimes it just goes straight to Elon. And that you're encouraged to do that and you're still on that email chain as a responsible engineer. You're like ending up, you're part of that decision process. And if people can't agree on something that's mutually beneficial to the company, you run it straight up to Elon if you have to. And he can be the final arbiter or maybe the VP of Vehicle Engineering can make the decision. And so like, that's pretty rare. And you generally just kind of pass that decision off to somebody with.

• 39:04Speaker 01

  You know, more decision-making power and then they come back to you and say, this is what we decided. So that's like a good example of keeping it relatively flat, but the ability to go up rapidly.

• 39:13Speaker 00

  So you go up to your two higher-ups, they can't decide. So it's a stalemate. So it goes up to another two people. Essentially, the top people are only focused on decisions that are non-obvious, non-consensus.

• 39:25Speaker 01

  The question is like, if you're at a stalemate, it's always like, why have you escalated it yet? And you just, you can just write up. And I've tried to talk to friends who would be like, at other companies, you're like, I'm having this big problem. Like, have you escalated it yet? And you're like, you can't do that here.

• 39:39Speaker 00

  We're both investors in a company, Varda, started by Delian from Founder's Fund. Tell me about Varda. What was your thesis when you invested? And tell me about the company today.

• 39:48Speaker 01

  Varda is an interesting one for me. I met Bruy, the CEO, when the company was an idea. I helped him with his first pitch deck. And then wasn't really deploying. So I didn't, didn't invest, didn't ask to invest. But I've stayed in touch. And then, you know, a round or two later, I was like, I know I'm a small check, but can I get in now? Because like, I love what you guys, like, how fast you're moving, executing. And the capability that you're bringing online. So it's definitely exciting. I mean, that's an excellent team. And there's a lot of former SpaceXers there. It's the same culture. It's hard charging, high responsibility.

• 40:31Speaker 00

  Function Ventures. What would you like DODNIS to know about you, about Wave Function Ventures, or anything else you'd like to share?

• 40:38Speaker 01

  My favorite time to get involved is before the pitch deck is even polished, before the idea is polished. Because I've been through that process. I've helped other founders through that process. It lets me help the founder shape the story and kind of dig into the company as a potential investor in a different way, rather than just seeing, you know, what is then a polished pitch deck. So like, I'd love to talk to founders when it's just an idea, and help them through that. And then I can decide from there if it's, it's an investment or not.

• 41:09Speaker 00

  They may love what you're building. Thanks for jumping on the podcast. Look forward to sitting down soon.

• 41:13Speaker 01

  Thanks for having me, David.

• 41:14Speaker 00

  Thanks for listening to my conversation with Jamie. If you enjoyed this episode, please share with a friend. This helps us grow and also provides the best feedback when we review the episode's analytics. Thank you for your support.