Lenny's Podcast: Product | Career | Growth
00:45:30 · Caitlin Kalinowski, Lenny Rachitsky
[00:45:30] S0: Yeah, we are in trouble as an industry. And I'm not an expert on this, but I think that AI has to do with why. And I also think that the supply chain is constrained. I have been advising startups and companies to pre-buy memory, and to have enough memory in stock, if they can afford it, to ride out price spikes. Like anything in this category, let's see, this happened in COVID too. So we had so many supply chain disruptions, and getting enough memory was one of the challenges. So we had to pre-buy as well. I won't say who, but the company I was working with had to pre-buy memory as well. And so this is part of what I wanted to talk to you about today, is these supply chain disruptions. And if a key component that goes into a lot of tech, like memory or silicon, is constrained, there's not much you can do. You either pay, or you have already pre-bought enough that you can ride things out. And so those are the only real options. Obviously there's a risk to pre-buying, and the price might go down. And so the challenge is, I think, there's a latency with supply chain in something like memory, where it can't adapt fast enough, often, to demand, or there's a new category of product, or, in this case, maybe data centers, that are just eating up so much and are actually not as cost-sensitive as somebody in consumer electronics like Matic might be. And so they'll just pay for these higher costs. This is tricky and something we have to deal with all the time. [00:47:09] S1: How much have prices gone up? How bad is this problem, and where do you think it'll go?
00:47:09 · Lenny Rachitsky, Caitlin Kalinowski
[00:47:09] S1: How much have prices gone up? How bad is this problem, and where do you think it'll go? [00:47:14] S0: Actually, this is a great question, Lenny. I don't know what's going to happen. I think prices are going to double, probably. I don't know on what timeline. If I knew what timeline the prices were going to double on, I'd be trading, which I'm not very good at. I'd really be, I'd be doing a different job if I could predict these things, but certainly we're going to have a supply chain shock. [00:47:34] S1: And it's already gone up a lot. If you're saying it'll double, but it's already gone up. I don't know. I saw numbers like 6x and some like that. [00:47:39] S0: Oh, really? I didn't realize it was that bad. [00:47:41] S1: That's a number I saw, let's not quote that. And you're saying, yeah, from what I hear, it's AI-driven, just like you need ... And when you talk about memory, it's like DRAM and things. What is memory, when we talk about memory? What's going on there?
00:47:41 · Lenny Rachitsky, Caitlin Kalinowski
[00:47:41] S1: That's a number I saw, let's not quote that. And you're saying, yeah, from what I hear, it's AI-driven, just like you need ... And when you talk about memory, it's like DRAM and things. What is memory, when we talk about memory? What's going on there? [00:47:55] S0: Processing. So the way to think about it is processing memory. You think about memory on your hard drive or your solid state drive, where you're keeping files that you're not using, essentially, in many cases or that you're dealing with maybe documents or pictures that you have. Maybe that's in cold storage on a server, maybe that's using a hard drive somewhere. This is usually things that you don't need really, really fast access on. But if you're running a program, some of that program is actually going to be run in RAM. And so there's different kinds, obviously, for servers. There's different kinds of server racks. Some server racks are actually focused on this type of memory, and some server racks are focused more on what we consider like a cold storage or a slower ... Now, this isn't my area of expertise, but certainly most of the products that I built, maybe all of them have had RAM, and we've had to figure out how to ... For me, mostly it's a packaging issue. Where do you put it? Does it need to be accessible? Which RAM do you pick? How fast does it need to be, and what is the cost? Is usually our trade-offs. [00:49:10] S1: And what is the bottleneck with more RAM? Is it just the companies that make memory are just not able to produce at this rate, because there's so much demand?
00:49:10 · Lenny Rachitsky, Caitlin Kalinowski
[00:49:10] S1: And what is the bottleneck with more RAM? Is it just the companies that make memory are just not able to produce at this rate, because there's so much demand? [00:49:17] S0: That's right. That's exactly what's happened. [00:49:19] S1: So this is a really good specific example of just how hard it is to build hardware. All it takes is one piece to be not available, and your whole thing's screwed. [00:49:29] S0: Yeah, you can't build anything if you have one component missing. [00:49:32] S1: So let's say Matic is an example. How many components are there that they all have to assemble and not have one not available?
00:49:32 · Lenny Rachitsky, Caitlin Kalinowski
[00:49:32] S1: So let's say Matic is an example. How many components are there that they all have to assemble and not have one not available? [00:49:38] S0: I'm doing the math in my head. They probably have between 50 and 150 parts. It's possible that they have more. I haven't seen their CAD, so I don't know what it's like inside their device, but they do have a lot of things going on. They have the wheels of the device that are obviously moving around. Then they have a vacuum, but they also have a mop, and obviously they have a vacuum bag. They have the reservoir that- They have a vacuum bag. They have the reservoir that the liquid has to go in for the mop. They have a system which I think is SLAM-based, which can see your room and make a map of it and identify which surface is which, and that, I believe, stays on the device, so it doesn't go up to the cloud, which is also what we did in VR as well, which I think is a good privacy practice. And then, they, of course, have wireless modules that connect up so you can communicate with your device. They're going to have a SoC silicon, they're going to have RAM, they're going to have PCBs. If you take everything off of those things like all the little caps off the PCBs and everything, then you're in the thousands of parts easily. So it depends on how you count, but this is not a simple device. [00:50:48] S1: And all it takes is one piece to not be available.
00:50:48 · Lenny Rachitsky, Caitlin Kalinowski
[00:50:48] S1: And all it takes is one piece to not be available. [00:50:51] S0: Yeah. So imagine you're a vendor that sells you a component that's a die-cast component, goes out of business. You can get another die-cast component in three months maybe and at quantity in five months or something like that at high quantity. This is recoverable. If your silicon goes out, if you can't buy your silicon, you can't buy your chip. Now, you have to redesign your board, and you have to find something else that might work. This is a catastrophic redesign. If you can't get the RAM you wanted and the form factory you wanted, this is what I call a... Essentially, it's a catastrophic redesign. You now have to redesign the entire guts of your product and then secure supply chain for these new things, build it again on the production line, test it again, do all the reliability testing. It is non-trivial, and so this is why we care. So there's a hierarchy of components. Often in consumer electronics, we start with silicon and the display, which are the longest lead time things usually in my world. In robots, actuators are pretty tricky to get, even just for prototyping. Sometimes it takes a month or two to buy an actuator. [00:52:01] S1: This is why Elon famously just starts building it all himself.