Lenny's Podcast: Product | Career | Growth
00:00:57 · Lenny Rachitsky, Tony Fadell
[00:00:57] S1: You often come back to the value of storytelling for product builders. [00:01:00] S0: Too many times when we're technology-led, we talk about the what. We don't talk about the why. The why is with storytelling. When I watched Steve, he was honing the story of the iPhone every day. And so when you saw him come on stage, it was just because he had done it a hundred thousand times. [00:01:19] S1: Today, my guest is Tony Fadell. Tony doesn't know this, but ever since I started this podcast, he's been near the top of my wishlist of people that I've dreamed to have on this podcast. And that's because Tony is the epitome of what most people listening to this podcast want to become. He co-created some of the most innovative and beautiful and popular products in history. The iPod, the iPhone, the Nest Thermostat. He's also famous for being part of the legendary team at General Magic. He's co-authored over 300 patents. He also wrote one of the most important and valuable and inspiring books for builders called Build. Tony is currently an active investor and advisor to deep-tech startups with his team at the Build Collective. He was recently named the Inaugural Designer in Residence at the MIT Morning Academy of Design. There's so much gold in this episode. [00:02:31] S0: Thanks for having me. I appreciate it.
00:02:31 · Tony Fadell, Lenny Rachitsky
[00:02:31] S0: Thanks for having me. I appreciate it. [00:02:33] S1: I have a bazillion questions I want to ask you. I feel like I could feel four hours of conversation with all the things that I want to get out of your head. I want to start with the BlackBerry. I was just watching the Blackberry movie recently, and it's kind of this journey of the BlackBerry founders and their story. And then at the end, they're like, "Oh, and this iPhone thing launched." And they're like, "No, this is dumb. It's like no keyboard. This is not serious. Can't do anything with it." I've always wondered, just being on the other side of this, being within Apple building the iPhone, how much did you guys actually doubt that, "Okay, maybe they have something, maybe we need to add a keyboard."
00:03:08 · Tony Fadell
[00:03:08] S0: It was the most heated conversation and it dragged out the longest. There was one way of looking at the BlackBerry, which was that is the market we want to go after or we want to win. And then there's the other side, the flip side of that argument, which is only 1% or 2% of mobile phone users at the time had a BlackBerry, knew what a BlackBerry was. So what about the other 98% of the people? What would they want? What would they need? Why are we going to go after winning this very loyal and incredibly passionate user base and try to pull them away from something? And so there was this basically head-to-head competition between a display keyboard or virtual keyboard and a physical keyboard. I had been doing virtual keyboards for a while since General Magic in the '90s, and I knew what handwriting was and keyboards were like on these touchscreens and... but I was only doing it on a... and I was writing software and calibrating them and trying to make them work with a single-touch display, resistive or what have you. And so I knew what the limitations were of those kinds of things. So I was like, "Hmm, this is really going to be difficult." And we had... Multitouch just was on a big ping-pong table. It hadn't been scaled down, so it wasn't like something in a consumptive form where you could really do user test with it. And so we set out a set of tests like, "Okay, how fast can I type this text? How fast can I do this on a hardware keyboard? And then how can we do this on the virtual one with multitouch?" And it was a hardware-software integration challenge of how we could get this to work. So we were going back and forth and back and forth, "Oh, that doesn't quite work in the software. Oh, we need to change this in the hardware." And so this was over a set of months would, "Okay, the hardware keyboards here," and depends on how... how much you've been using it, but there's this margin error, and we could really understand it. This, over time, was started way down here, and it started to get it, and it got a little faster and a little faster and a little faster. And how many errors, not just how fast, but how many errors, and how do you correct the errors, and all of those things. And at the end of the day, I was able to convince myself it wasn't going to be a hardware issue, and I was convinced at some point that we were good enough.
00:05:40 · Tony Fadell, Lenny Rachitsky
Were we as good as a hardware keyboard? No. But were we good enough? Yes. And then other people came to that conclusion, but at the same time, there were other people who were adamant that the hardware keyboard has to be there, and they were unrelenting. And so it came down to... So this was a classic, like I say in Build, data versus opinion-based decision. And if you think about it, you had data that said there was pros and cons on both sides. And what happened was the data was not clear that we should choose one over the other. And Steve said, "We are going this way." Enough other people kind of said, "Yeah, that seems like that's the right thing to do. We're going to get close enough to get there." And then other people were like, " No, my opinion is this." And guess who wins at the end of the day? Steve Jobs' opinion does. [00:06:34] S1: Steve Jobs.
00:06:34 · Tony Fadell
[00:06:34] S0: And he was like, "If you're not going to get on board, get out of this room, and you can go work on another project, but you're not going to work on this one." When you're doing a 1.0 of anything, when you're doing... if you're doing anything that matters, and it's a 1.0, and it's a new category, or it's a new device the world hasn't seen before, you have very few analogs that you can use to make data-driven decisions. And so if most of your decisions are going to be opinion-based decisions for a 1.0, you have to have one or two or a very, very small set of people who are charged with making the opinion-based decisions and can actually get you from point A to... from a white paper or a white... bank sheet of white paper or whiteboard to an actual 1.0 spec. Because if you try to do data-driven decisions all the way along, you're either not doing a differentiated product because you're taking data from another thing, or you're just getting just bullshit data, right. So you're going to have to figure out how to get opinion-based decisions to happen, and that means you have to have, for lack of a better word, taste makers. This is what we are doing. We are the person or the team who is going to make those opinion-based decisions. Of course, some people aren't going to like it, and it's going to be like, "I'm sorry, this is a benevolent dictatorship. This is what's going to happen, and this is the vision." And we don't know what we don't know until we ship it and we get opinions from the users. Now it's very different when you do this in a B2B context versus a B2C context. And so the hardest environment to work with it when you have these opinion-based distinctions is in a B2C context because you have to see these decisions in the full light and you don't... a consumer does. They have to see it from the marketing, from how they discover it in the marketing, the key feature sets, the ability to use the product, all of these different things for them to actually come up with an opinion of what they like, and what they don't like and being able to critique it. And if you don't... And if you're doing a 1.0 and the world hasn't seen, you're not going to get that from consumers ever.
00:09:38 · Tony Fadell
You have to ship it, and you have to build the entire kind of ecosystem so those consumers see it in the fullness, so that when they do the evaluation, and they spend their own money, then you're getting real feedback. When it comes to consumer... atoms-based products with services or not, whatever it is, you have to build the entire thing and visualize the entire thing to be able to make those opinion-based decisions. And so you need a small team who's looking at the marketing angles, the engineering angles, the sales angles, all those different things to go, "Okay, that's the way we're going." And there's only so many ways you can do it because the rest of the team doesn't see this either. And so you have to be very articulate about how... what that opinion-based decision is made for, why, how it might affect market, how you do it, and make sure the team understands it. Now, if the team is just fully against it, well then maybe it has to be unkind, but hopefully if you've done a good job and you really have an informed gut and you can articulate that, you can get everybody moving in the same direction even if it is... And it's going to be risky. You're right. You got to know that you got to take risk because most people in those other functions, they don't want to take any risks. And so there's someone who's got to be the target, right. And today, in many contexts, people go and hire consultants, right. They go and hire, "Okay, we're going to do a user study, or we're going to do all this." And they don't have the user studies and have the full context like I was just describing. They don't go buy the product, and they don't what have you and then they get data, and that's because the leader or whoever's in there, board maybe, it's like, "We need data to make sure this 1.0 is going to be a success." And I saw this so many times at all these major corporations, so they're just kind of covering their with bullshit data and not really doing the hard work of saying, "I'm going to make this decision and we are going to select this, and yes, I might be wrong or we as the opinion based decision makers are wrong and we will correct it later and we'll take the heat for that." So that's the... a great product manager or a great person who's leading this thing has to understand that that's what they have to do if they're really doing something innovative.