Lenny's Podcast: Product | Career | Growth
00:32:05 · Lenny Rachitsky, Caitlin Kalinowski
[00:32:05] S1: What's an example of that, just to make it more concrete for us? [00:32:09] S0: A great example is the Quest 2. So we reduced the Quest 2 price quite a lot, and what we had to do is understand, what are we trying to do? We're trying to democratize VR, we're trying to get VR to more people. And the only way we could do that is reduce the price. And so what it required is a redesign of the entire product, essentially, for cost, which then, I think, led to the highest-selling VR headset of all time. And it's not easy, because you had to, in our case, remove cameras, remove components, change materials, change manufacturing processes. But when you have alignment that you want to get this to more people and the way to do that is to reduce the cost, then that kind of drives everything else. And it was still a very high-quality product with great, I think, low return rates, and it was a very strong product. Maybe even stronger than if we hadn't done that, funny enough, but it hit our price point. [00:33:07] S1: Okay. Coming back to just the question of, say a company's like, "Okay, we need to build some hardware. We're going to build our own glasses. We're going to build a little phone device and secretive thing," whatever OpenAI is up to. What other tips do you have? I know it's impossible to like, "Here's all you need to know," but just what else should people be thinking?
00:33:24 · Caitlin Kalinowski
[00:33:24] S0: Having your goals defined early and sticking to them is important. Hardware's not as adaptable to lots of changes throughout its development as anything digital. And so if you set out to say, "Okay, we want to make something that's $300," and then halfway through you say, "Oh, it actually has to be $150," you've almost burned a lot of that early time. So you kind of need to have a sense of having pre-thought out what you want, and having those, I like to call them KPIs, but essentially goals written down, and try to change them as little as possible. So that is very tough. In fact, that may be the toughest thing. Because if you do that properly, and you have the right prioritization of those things, you know whether you can ship or not. You know whether you're done. And in hardware, one of the challenges is, we talked about compiling four or five times. Every time you build and you iterate your design, that's another three months or four months or five months or whatever it might be. And so you're trying to time the feature set, with the quality, with the timing. And in hardware, timing is important, because if you come out with your product a few weeks before your competitor, you might get all the PR, you might get all the interest. It's pretty brutal. And so each of those days that you ship before your competitor is worth a lot of money. It might be worth $10 million to you. I'm making this up. I don't know. So you have to balance that with how many times you iterate. And if you know what your goals are upfront and you hit them, then you know you can ship. And often engineers, and I'm guilty of this too, especially on the hardware side, never feel like they're done. So this is a pretty nuanced thing. So that's one thing. The second thing is we tend to design the things that we know how to design first, and actually the right approach is to design the hardest parts first. One example will be, and there's no IP here, so I'm obviously not going to share any IP or anything internal, but at one point we had to route cables through a hinge in a device, in a laptop we were making. And because it wasn't clear that those cables would fit, that's where the architect started. And he looked at the diameter, and how to split the cables out, and made sure that they would fit before finalizing the hinge design.
00:35:40 · Caitlin Kalinowski
A lot of people would start at the part they knew, like, "Oh, we're going to use this display, so I'm going to put this in CAD, and I'm going to do all this other stuff." But the architects who are the best actually look at where are the pinch points, where is this going to fail? And they start to do the detailed design there first. And then a couple other points is, the part that your customer touches or interacts with the most needs way more iteration than everything else. So easy on a computer, you touch the trackpad the most, and then maybe the keyboard next. So those things have to be really good. They have to feel good, they have to respond properly, they have to be highly reliable, and then maybe the other pieces further out don't take quite as much iteration. So you have to boost your iteration on the things that people touch the most or interact with the most. So those are kind of some principles that I wrote about, but these are just things that you learn trying to build quickly. And the last piece that's really critical if you're making hardware for folks out there who are trying to make hardware is, you can't wait around, ever. There's never enough time. So if you know that you need to do something, what I learned from folks like Shelly Goldberg at Apple now, who I think is a VP now, and Kate Bergeron when I was there at Apple is, you need to do it right now. Anything you know you need to do, you need to do right now, because in two days there's going to be a surprise coming around the corner that you need that time to fix. And so this sense of stacking the things that you know you need to do and just getting them out of the way, even if you technically have more time, is this kind of ruthless efficiency that I learned with them.
00:37:24 · Lenny Rachitsky, Caitlin Kalinowski
[00:37:24] S1: Amazing. Okay. Let me just summarize your advice here. So one is be very clear on goals, I want to come back to this. Two is do the hardest part first, the riskiest piece, essentially, to physically build. Three is focus on the pieces that people will use most, say the trackpad, keyboard. I want to talk about that. And four is just like, do it now. Even if you think you have more time, you never know what's around the corner, and it's better- [00:37:51] S0: You just don't. It's not even that you don't know what's around the corner. If you're working in hardware, you actually don't have more time. [00:37:57] S1: Okay. On the goals, what are kind of like buckets of goals? So cost is when you shared like, "We need this under $300." What are some other buckets of types of goals people should be thinking about?
00:38:06 · Caitlin Kalinowski
[00:38:06] S0: So in VR display resolution or arc minutes, like how many pixels per degree do you want is actually one of the key metrics. So you need to understand what your key metrics are. And why is that key? Well, that's your visual field. So you think about Retina displays on MacBooks. They figured out the KPI of what the human eye could see, probably overshot it a little bit, and built that. And then do you really need to keep as much engineering pressure up on the resolution of a display after that? Maybe not. So VR's not there yet, not even close. Not in mass-produced VR, we don't have Retina displays yet. So that is one aspect of pushing that up is one example. I think on a computer, obviously you're talking about clock speed, you're talking about how many parallel processes you can run, you're talking about weight, you're talking about price, and you're talking about features. So when we did the MacBook Air, it became very clear, because we were machining it, that there are certain features, like ambient light sensor, that we just ... didn't make sense anymore. And so being willing to just jettison them for what we were going for, which was weight and size. So if you have those overarching goals, you can actually make decisions, engineering decisions pretty quickly. And this is actually something that I think Elon, I've heard, does very well, is define the value of a gram of weight versus the cost, or he does, I've heard, engineering ratios, essentially and he's able to put numbers on what those ratios should be, which I think is really smart.
00:39:47 · Lenny Rachitsky, Caitlin Kalinowski
[00:39:47] S1: Interesting. So it's a very easy trade-off. "Okay, here's the formula telling us weight is less important in this case." [00:39:54] S0: Yeah. And if you can do that, then the decisions fall out pretty easily. [00:39:58] S1: Speaking of the Air and weight, I remember, I feel like there's a very classic moment in Steve Jobs lore where he comes out and has this manila envelope, and has the MacBook Air inside it, and then takes it out and everyone's like, "No way." Were you part of that? Was that something that people wanted to do from the beginning? [00:40:15] S0: I think, if my memory serves, the very, very, very first MacBook Air was a pretty low volume device that was machined, but kind of had more of a proof of what could be done. And that was the manila envelope one, I think, where the side door opened out to give you the port, and it had this shape underneath. And then the next rev of that was the MacBook Air that we know, essentially which is wedge shaped, which is different. And so the wedge shape is the one that I worked on, and the one that went and hit more volume. But that manila envelope one was the one that proved you can CNC a computer. And so they each have really important roles in the roadmap. [00:41:01] S1: Coming back to your point about focusing on things that people use the most, famously, Apple screwed up this keyboard. There was this butterfly keyboard situation for a long time. You're like, your eyes are closed [inaudible 00:41:16]. What happened? What happened, Caitlin?