The Swyx Mixtape

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How I Approach First Principles Thinking via Logic and Epistemology

Transcript

So what's your source of belief in situations like this when the engineering problem is so difficult, there's a lot of experts, many of whom you admire, who have failed in the past. Yes. And a lot of people, you know, a lot of experts, maybe journalists, all the kinds of, you know, the public in general have a lot of doubt about whether it's possible and you yourself know that even if it's a, non-normal set, not empty set of success, it's still unlikely or very difficult. Like where do you go to both personally, intellectually as an engineer, as a team, like for source of strength needed to sort of persevere through this and to keep going with the project, take it to completion. 

I suppose the strength. Hmm. I just really not how I think about things. I mean, for me, it's simply this, this is something that is important to get done, and we, we should just keep doing it or die trying, and I, I don't need, I source of strength. So 

Quitting is not even like, I'm 

Just not, it's not in my nature. Okay. And I, I don't care about optimism or pessimism, fuck that. We're going to get it done. Gotta to get it done. 

Can you then zoom back in to specific problems with Starship or any engineering problems you work on? Can you try to introspect your particular biologic when you're in that network, your thinking process, and describe how you think through problems, the different engineering and design problems. Is there like a systematic process you've spoken about first principles thinking kind of, 

Well, you know, like saying like, like physics is low and everything else was a recommendation. I'm like, I've met a lot of people that can break the law, but I, I have never met anyone who could break physics. So, so first for any kind of technology problem, you have to sort of just make sure you're not violating physics. And, you know, first principles analysis, I think, is something that can be applied to really any walk of life, any anything really? It's just, it's, it's really just saying, you know, let's, let's boil something down to the most fundamental principles. 

The things that we are most confident are true at a foundational level, and that sits your at your sets, your axiomatic base, and then you reason up from there. And then you cross check your conclusion against the, the axiomatic truth. So, you know, some basics in physics would be like, oh, you Vida and conservation of energy or momentum or something like that, you know, then you're slugging to work. So that's yeah. So that's just to establish it. Is it, is it, is it possible? And then another good physics tool is thinking about things in the limit. If you, if you take a particular thing and you scale it to a very large number or to very small number, how does, how does things change 

Like temporary, like in number of things, you manufacturer, something like that. And then in time, 

Yeah. Like, let's say, take example of like, like manufacturing, which I think is just a very underrated problem. And, and like I said, it's, it's much harder to take a, an advanced technology product and bring it into volume manufacturing than it is to design it in the first place. My more's magnitude. So, so let's say, you're trying to figure out is like, why is this, this part or product expensive? Is it because of something fundamentally foolish that we're doing? Or is it because our volume is too low? And so then you say, okay, well, what if our volume was a million units a year? 

Is it still expensive? That's what I'm invaluable thinking about things to the limit. If it's too expensive at a million units a year, then volume is not the reason why your thing is expensive. There's something fundamental about design. 

And then you then can focus on the reducing complexity or something like that. 

We could change the design to change the chains apart to be something that is not fundamentally expensive, but like, that's a common thing in rocketry. Cause the, the unit volume is relatively low. And so a common excuse would be well, it's expensive because our unit volume is low. And if we were in like automotive or something like that, or consumer electronics, then our costs would be lower on like unlike. Okay. So let's say now you're making a million units a year. Is it still expensive? The answer is yes. Then economies of scale are not the issue. 

Do you throw into manufacturing? Do you throw like supply chain, you talked about resources and materials and stuff like that. Do you throw that into the calculation of trying to reason from first principles? Like how are we going to make the supply chain work here? Yeah, yeah. And then the cost of materials, things like that, or is that too? 

Exactly. So like another, like a good example, I, of thinking about things in the limit is if you take any, you know, any, any product, a machine or whatever, like take a rocket or whatever, and say, if you've got, if you look at the raw raw materials in the rocket, so you're going to have like an aluminum steel titanium in canal, especially specialty alloys, copper. And you say, what are the, what's the weight of the constituent elements of each of these elements and what is their own material value? 

And that sets the asymptotic limit for how low the cost of the vehicle can be, unless you change the materials. So, and then when you do that, call it like maybe the magic one number or something like that. So that would be like, if you had the, you know, like just a pile of these raw materials here, and you could wave a magic wand and rearrange the atoms into the final shape, that would be the lowest possible cost that you could make this thing for, unless you change the materials. So then, and that is always, almost always a very low number. So then the what's actually causing these to be expensive is how you put the atoms into the desired shape. 

Yeah. Actually, if you don't mind me taking a tiny tangent, had a, I often talked to Jim Keller, who's somebody that work with use. 

Yeah. Jim was a great work at Tesla. 

So I suppose he carries the flame of the same kind of thinking that you're, you're talking about now. And I, I guess I see the same thing at Tesla and, and space X folks who work there, they kind of learn this way of thinking and it kinda becomes obvious almost. But anyway, I had argument, not argument. He educated me about how cheap it might be to manufacture a Tesla bought. We just, we had an argument. What is, how can you reduce the cost of scale of producing a robot? Because, so I got an, a chance to interact quite a bit, obviously in, in the academic circles with human robots and then my Boston dynamics and stuff like that. 

And then they're very expensive to build. And then Jim kind of schooled me on saying like, okay, like this kind of first principles thinking of how can we get the cost of manufacture down, I suppose you do that. You have done that kind of thing. If a Tesla bought in for all kinds of all kinds of complex systems that are traditionally seen as complex, and you say, okay, how can we simplify everything now? 

Yeah. I mean, I think if you, if you are really good at manufacturing, you can basically make at high volume, you can basically make anything for a cost that asymptotically approaches is the raw material value of the constituents. Plus any intellectual property that you need to license anything. Right. But it's, it's hard. It's not like that's a very hard thing to do, but it is possible for anything. Anything in volume can be made of, like I said, for a cost that asymptotically approaches this raw material constituents plus intellectual property license rights. So what will often happen in trying to design a product is people will sought with the tools and parts and methods that they are familiar with and then, and try to create a product using their existing tools and methods. 

The other way to think about it is actually imagine the, try to imagine the platonic ideal of the perfect product or technology, whatever it might be. And so what is this, what is the perfect arrangement of atoms that would be the, the best possible product. And now that are trying to figure out how to get the items in that shape. 

I mean, it's, it sounds, and it's almost like Rick and Morty absurd until you start to really think about it. And you really should think about it in this way, because everything else has kind of, if you think you, you might fall victim to the momentum of the way things were done in the past, unless you think in this way, 

Well, just as a function of inertia, people will want to use the same tools and methods that they are familiar with. They just that's what they'll do by default. Yeah. And then that, that will lead to an outcome of things that can be made with those tools and methods, but is unlikely to be the platonic ideal of the perfect product. So then, so that's why it's good to think of things in both directions. Like what can we build with the tools that we have, but then, but, but also what is the, what is the perfect, the theoretical perfect product look like? And, and that, that theoretical poet part is going to be a moving target, because as you learn more the definition of, or for that perfect product, what will change because you don't actually know what the perfect product is, but you can successfully approximate a more perfect product. 

So thinking about it like that, and then saying, okay, now what tools, methods, materials, whatever do we need to create in order to get the atoms in that shape? Fitbit for people rarely think about it that way, but it's a powerful tool.