01:25:38 · Scott Nolan
[01:25:38] S0: I mean, the the classic Tesla example is LiDAR versus no LiDAR. And I think for a long time, the the thinking was, hey. A LiDAR is only a few thousand dollars. Maybe it's tens of thousands, but why don't we just put it on the car, make life easy on ourselves? And then years later, you realize, hey, it's not a perception problem. We can perceive the environment with cameras. It's a controls problem. It's a logic problem. So that's probably the most salient example, where even I, circa 2010, would have said, why not use LiDARs? They're here. We have them. Yes, they're expensive, but the costs will go down. And then it's like, okay, but how much will the cost really go down? Why don't we just think through this ten years out? And it's going to be cameras. At SpaceX, I think that thing might have been going to Falcon nine sooner than people would have expected. When I was there, at some points, we were working on both, Falcon one and Falcon nine. And Falcon one was still in the process of having its first successful flight, and yet we were working on Falcon Nine. And that was Okay from a resourcing standpoint because many of us we'd worked on the Merlin engine. Merlin engine was working. It was working pretty well. And we knew it would be used on Falcon nine, that product could be reused. But there was a lot more rocket to develop. And I think at one point, Falcon nine was Falcon five. And then it was realized, hey, for this thing to really cover the market and to give us the performance we need, it needs to be Falcon nine. And so, yeah, I would say there were probably people in the company who were surprised by that, like, oh, wow, we were doing Falcon five. Now we're already doing Falcon nine. Is this the right choice? And and, obviously, it was. So I think it can be things as simple as that of when do you launch your next product line, when do you when do you take on another challenge, when do you work on something that's, like, much sooner than you would have thought while you're still trying to get the first thing successful, but clearly proven correct, clearly Falcon one was serving what turned out to be a very small market for a very long time, and that market didn't emerge very quickly. And the correct thing was to jump straight to the larger satellite market. And and I think there were other examples of this too.
01:27:54 · Scott Nolan
Even on the tech side, really, that switch from ablative rocket nozzle to regen, you were just adding a whole block in the schedule for that... For its development versus hoping to just get there, and then that's turned out to be absolutely correct versus the unreliability that would have come through the ablative engine. And there were other decisions like that, too, like, hey, instead of this type of nozzle for the vacuum engine, we could use this other more exotic but really exciting other one. And the decision was, no, don't worry about that. We just need to get this working, and don't worry about that potentially higher performance thing. This one is known to be reliable. We can buy it. It's cheap enough, and it's going to get us to where we need to go. So let's do that. And there was just many, many practical decisions like that along the way. I would say many more practical decisions that were obvious when you looked at what the long term mission was versus really, really deep tech breakthroughs. And I think seeing SpaceX succeed over the years, it's been evident that it's just make a lot of decisions that are in line with the core metric that you're going after. And if you stay focused on that, you can do pretty well. Even to that point, on day one of joining SpaceX, we had an employee handbook. And remember the first page of the employee handbook, I think in big, bold letters, said, This is not a science experiment. This is an engineering problem. And so to that question of what unconventional choices were made that turned out to be right, I think they either followed two categories. One was those choices were pragmatic and very focused on cost and schedule. Or category two, those choices were they really looked at the big picture. And let's not optimize for a dead end that's going to come two years from now, like in the case of LiDAR. Let's think a decade out. What are the trends? What things can we really bet on that we know are going to be true? And, yeah, how do we just optimize for that?
01:29:52 · Ty Morse
[01:29:52] S1: While you're mainly focused on Founders Fund, what was the biggest thing that you kind of evolved in your own way of company building and your your thinking on company building during that, like, huge ten plus year stint?
01:30:03 · Scott Nolan
[01:30:03] S0: Yeah. When I started at Founders Fund, this was 2011. There were a lot of... At the time, Founders Fund was really focused on two things. One, back founders unconditionally. And two, what things can we invest in that are great that otherwise won't receive funding? So where can we make a big impact, both on the team side and then market or sector side or technology side? And so there was this belief that technology was what could fuel the next wave of growth in The US, and it was systematically underfunded and that we should be trying to help that succeed through capital. When I started in 2011, the way that that showed up was you would there were lot of very early stage engineering driven companies. Hard tech, like engineering driven companies were not nearly as popular as they are today. The focus was really things like software and consumer. And so early on, for the first few years, I was much more focused on, I'd say, early stage, smaller checks, seed stage checks into engineering driven companies, which did remain my focus over the twelve plus years. But over time, realize more and more, some of these companies work at a much larger scale than you ever think that they will. And the correct thing is actually to focus on the very small handful of companies that are going to be the most successful, that are going to be the most important, and where you really feel the most conviction in the team, and just work with those companies. And yes, that means you're not getting to invest in a seed stage company at necessarily a really attractive valuation. Maybe you're accepting, hey, I'm not investing in a company that's $10,000,000 pre. I'm investing in a company that's a billion valuation, but what are the odds that this goes 100x? I think these things are sometimes scale invariant, where the probability of going from 10 employees to 100 employees to 1,000 employees, you might be more likely to go from 100 to 1,000 than from 10 to 100. And so looked at in a different way, the conclusion I have is that sometimes it's easier to build a really hard company than it is to build an easy company. At the end of the day, it gets back to what really important problem are you solving that's not getting solved.
01:32:27 · Scott Nolan, Ty Morse
And I think if you are focused on that, if your mission as a company is doing something that's really critical, potentially really challenging, which is why it hasn't been done to date, you can just attract the best people. You can usually get the resources that you need to go do this if you're executing well. And in total, it actually becomes a lot easier than trying to start a small business or something that is much more competed over. And so I think one way that people understand this is start companies in areas without much competition, avoid competition, etcetera. I think the more meaningful way to think about that is don't focus on problems that are already getting solved or adjacent to problems currently being solved that you know are going to be tackled by someone else. Focus on the problems that are big and that are just not getting solved. Dedicate yourself to them. If you do that, it will be very challenging, but it may actually turn out to be easier than starting the next small business or the next small software company. [01:33:35] S1: Yeah. It's funny because you can kind of attract different types of talent. Like, the very best talent... And from what I've seen and experienced, the very best talent wants to work on the hardest problems even if it, like, basically gives them less money or these other things. Like, the enjoyment of working on something that's important and valuable is is more attractive to them. [01:33:54] S0: Yeah. Maybe the problem is twice as hard, but you get 10 times better people. And so, net, it's somehow easier.