How Jeff Bezos Started Amazon | Lex Fridman Podcast Clips

Going back to sexy pictures on your Instagram, there's a video of you from the early days of Amazon giving a tour of your, quote, sort of offices. I think your dad is holding the camera. He is, yeah, I know, right, yes. This is with the giant orange extension cord, yeah. And you're like explaining the genius of the extension cord and how this is a desk and the CRT monitor and sort of that's where the, that's where all the magic happens. I forget what your dad said, but this is like the center of it all. So what was it like? What was going through your mind at that time? You left a good job in New York and took this leap. Were you excited? Were you scared? So excited and scared, anxious, you know, thought the odds of success were low. I told all of our early investors that I thought there was a 30% chance of success, by which I mean getting your money back, not like, not what actually happened, because that's the truth. Every startup company is unlikely to work. It's helpful to be in reality about that, but that doesn't mean you can't be optimistic. So you kind of have to have this duality in your head. Like on the one hand, you know what the baseline statistics say about startup companies, and the other hand, you have to ignore all of that and just be 100% sure it's going to work. And you're doing both things at the same time. You're holding that contradiction in your head. But it was so exciting. I love, you know, every from 1994 when the company was founded to 1995 when we opened our doors, all the way until today, I find Amazon so exciting. And that doesn't mean it's like full of pain, full of problems. You know, it's like, there's so many things that need to be resolved and worked and made better and etc. But on balance, it's so fun. It's such a privilege. It's been such a joy. I feel so grateful that I've been part of that journey. It's just been incredible. So in some sense, you don't want a single day of comfort. You've written about this many times. We'll talk about your writing, which I would highly recommend people read in just the letters to shareholders. So you wrote up explaining the idea of day one thinking. I think you first wrote about it in 97 letters to shareholders. Then you also, in a way, wrote about, sad to say, is your last letter to shareholders as CEO. And you said that day two is stasis, followed by irrelevance, followed by excruciating painful decline, followed by death. And that is why it's always day one. Can you explain this day one thing? This is a really powerful way to describe the beginning and the journey of Amazon. It's really a very simple and I think age old idea about renewal and rebirth. And like, every day is day one. Every day, you're deciding what you're going to do. And you are not trapped by what you were or who you were or any self-consistency. Self-consistency even can be a trap. And so day one thinking is kind of, we start fresh every day. And we get to make new decisions every day about invention, about customers, about how we're going to operate, even as deeply as what our principles are. We can go back to that. It turns out we don't change those very often, but we change them occasionally. And when we work on programs at Amazon, we often make a list of tenets. And the tenets are kind of, they're not principles, they're a little more tactical than principles, but it's kind of the main ideas that we want this program to embody, whatever those are. And one of the things that we do is we put, these are the tenets for this program, and then in parentheses, we always put, unless you know a better way. And that idea, unless you know a better way, is so important because you never want to get trapped by dogma. You never want to get trapped by history. It doesn't mean you discard history or ignore it. There's so much value in what has worked in the past, but you can't be blindly following what you've done. And that's the heart of day one, is you're always starting fresh. And to the question of how to fend off day two, you said, such a question can't have a simple answer, as you're saying. There will be many elements, multiple paths, and many traps. I don't know the whole answer, but I may know bits of it. Here's a starter pack of essentials. Maybe others come to mind. For day one, defense. Customer obsession, a skeptical view of proxies, the eager adoption of external trends, and high-velocity decision-making. So we talked about high-velocity decision-making. That's more difficult than it sounds. So maybe you can pick one that stands out to you, as you can comment on. Eager adoption of external trends, high-velocity decision-making, skeptical view of proxies. How do you fight off day two? Well, you know, I'll talk about, because I think it's the one that is maybe in some ways the hardest to understand, is the skeptical view of proxies. One of the things that happens in business, probably anything that you're, you know, you have an ongoing program and something is underway for a number of years, is you develop certain things that you're managing to, like, let's say, the typical case would be a metric. And that metric isn't the real underlying thing. And so, you know, maybe the metric is efficiency metric around customer contacts per unit sold, or something like, if you sell a million units, how many customer contacts do you get? Or how many returns do you get? And so on and so on. And so what happens is a little bit of a kind of inertia sets in, where somebody a long time ago invented that metric. And they invented that metric, they decided we need to watch for, you know, customer returns per unit sold as an important metric. But they had a reason why they chose that metric, the person who invented that metric and decided it was worth watching. And then fast forward five years, that metric is the proxy. The proxy for truth, I guess. The proxy for truth, the proxy for customer, let's say in this case, it's a proxy for customer happiness. And, but that metric is not actually customer happiness, it's a proxy for customer happiness. The person who invented the metric understood that connection. Five years later, a kind of inertia can set in and you forget the truth behind why you were watching that metric in the first place. And the world shifts a little. And now that proxy isn't as valuable as it used to be, or it's missing something. And you have to be on alert for that. You have to know, okay, this is, I don't really care about this metric. I care about customer happiness. And this metric is worth putting energy into and following and improving and scrutinizing only in so much as it actually affects customer happiness. And so you've got to constantly be on guard. And it's very, very common. This is a nuanced problem. It's very common, especially in large companies that they are managing to metrics that they don't really understand. They don't really know why they exist. And the world may have shifted out from under them a little. And the metrics are no longer as relevant as they were when somebody 10 years earlier invented the metric. That is a nuance, but that's a big problem, right? There's something so compelling to have a nice metric to try to optimize. Yes. And by the way, you do need metrics. You know, you can't ignore them. You want them, but you just have to be constantly on guard. This is, you know, a way to slip into day two thinking would be to manage your business to metrics that you don't really understand. And you're not really sure why they were invented in the first place. And you're not sure they're still as relevant as they used to be. What does it take to be the guy or gal who brings up the point that this proxy might be outdated? I guess, what does it take to have a culture that enables that in the meeting? Because that's a very uncomfortable thing to bring up at a meeting. We all showed up here, it's a Friday. This is such, you have just asked a million-dollar question, so this is, if I generalize what you're asking, you're talking in general about truth-telling. Yeah. And we humans are not really truth-seeking animals. We are social animals. Yeah, we are. And, you know, take you back in time 10,000 years and you're in a small village, if you go along to get along, you can survive. You can procreate. If you're the village truth-teller, you might get clubbed to death in the middle of the night. Truths are often, they don't want to be heard because important truths can be uncomfortable, they can be awkward, they can be exhausting. Impolite. Yes, challenging, they can make people defensive even if that's not the intent. But any high-performing organization, whether it's a sports team, a business, you know, a political organization, an activist group, I don't care what it is, any high-performing organization has to have mechanisms and a culture that supports truth-telling. One of the things you have to do is you have to talk about that. You have to talk about the fact that it takes energy to do that. You have to talk to people, you have to remind people it's okay that it's uncomfortable. You have to literally tell people it's not what we're designed to do as humans. It's not really, it's kind of a side effect, you know, we can do that, but it's not how we survive. We mostly survive by being social animals and being cordial and cooperative, and that's really important. And so, there's a, you know, science is all about truth-telling. It's actually a very formal mechanism for trying to tell the truth. And even in science, you find that it's hard to tell the truth, right? Even, you know, you're supposed to have hypothesis and test it and find data and reject the hypothesis and so on. It's not easy. But even in science, there's like the senior scientists and the junior scientists, and then there's a hierarchy of humans where somehow seniority matters in the scientific process, which it should not. And that's true inside companies too. And so, you want to set up your culture so that the most junior person can overrule the most senior person if they have data. And that really is about trying to, you know, there are little things you can do. So, for example, in every meeting that I attend, I always speak last. And I know from experience that, you know, if I speak first, even very strong-willed, highly intelligent, high-judgment participants in that meeting will wonder, well, if Jeff thinks that, I came in this meeting thinking one thing, but maybe I'm not right. And so, you can do little things like, if you're the most senior person in the go last. But everybody else go first. In fact, ideally, let's try to have the most junior person go first, and the second, and try to go in order of seniority so that you can hear everyone's opinion in a kind of unfiltered way. Because we really do, we actually literally change our opinions. If somebody who you really respect says something, it makes you change your mind a little. So, you're saying implicitly or explicitly give permission for people to have a strong opinion that, as long as it's backed by data. Yes, and sometimes it can even, by the way, a lot of our most powerful truths turn out to be hunches, they turn out to be based on anecdotes, they're intuition-based, and sometimes you don't even have strong data. But you may know the person well enough to trust their judgment, you may feel yourself leaning in, it may resonate with a set of anecdotes you have, and then you may be able to say, you know, something about that feels right. Let's go collect some data on that. Let's try to see if we can actually know whether it's right. But for now, let's not disregard it because it feels right. You can also fight inherent bias. There's an optimism bias. Like, if there are two interpretations of a new set of data, and one of them is happy, and one of them is unhappy, it's a little dangerous to jump to the conclusion that the happy interpretation is right. You may want to sort of compensate for that human bias of looking for, you know, trying to find the silver lining and say, look, that might be good, but I'm going to go with it's bad for now until we're sure. So, speaking of happiness bias, data collection, and anecdotes, you have to, how's that for a transition? You have to tell me the story of the call you made, the customer service call you made to demonstrate a point about wait times. Pete Yeah, this is very early in the history of Amazon. And we were going over a weekly business review and a set of documents, and I have a saying, which is, when the data and the anecdotes disagree, the anecdotes are usually right. And it doesn't mean you just slavishly go follow the anecdotes then, it means you go examine the data. And it's usually not that the data is being miscollected, it's usually that you're not measuring the right thing. And so, you know, if you have a bunch of customers complaining about something, and at the same time, you know, your metrics look like why they shouldn't be complaining, you should doubt the metrics. And an early example of this was we had metrics that showed that our customers were waiting, I think, less than, I don't know, 60 seconds when they called a 1-800 number to get, you know, phone customer service, the wait time was supposed to be less than 60 seconds. But we had a lot of complaints that it was longer than that. And anecdotally, it seemed longer than that, like, you know, I would call customer service myself. And so, one day, we're in a meeting, we're going through the WBR and the weekly business review, and we get to this metric in the DAC, and the guy who leads customer service is defending the metric, and I said, okay, let's call. And I picked up the phone, and I dialed the 1-800 number and called customer service, and we just waited in silence. What did it turn out to be? Oh, it was really long, more than 10 minutes, I think. Oh, wow. I mean, it was many minutes. And so, you know, it dramatically made the point that something was wrong with the data collection. We weren't measuring the right thing. And that, you know, set off a whole chain of events where we started measuring it right. And that's an example, by the way, of truth-telling, is like, that's an uncomfortable thing to do. But you have to seek truth, even when it's uncomfortable, and you have to get people's attention, and they have to buy into it, and they have to get energized around really fixing things. So that speaks to the obsession with the customer experience. So one of the defining aspects of your approach to Amazon is just being obsessed with making customers happy. I think companies sometimes say that, but Amazon is really obsessed with that. I think there's something really profound to that, which is seeing the world through the eyes of the customer, like the customer experience, the human being that's using the product, that's enjoying the product. They're like, what they're like, the subtle little things that make up their experience. Like, how do you optimize those? This is another really good and kind of deep question, because there are big things that are really important to manage. And then there are small things internally to Amazon, we call them paper cuts. So we're always working on the big things. And most of the energy goes into the big things, as it should. And you can identify the big things, and I would encourage anybody, if anybody listening to this is an entrepreneur, has a small business, whatever, think about the things that are not going to change over 10 years, and those are probably the big things. So I know in our retail business at Amazon, 10 years from now, customers are still going to want low prices. I know they're still going to want fast delivery, and I just know they're still going to want big selection. So it's impossible to imagine a scenario where 10 years from now, I say, where a customer says, I love Amazon, I just wish the prices were a little higher. Or I love Amazon, I just wish you delivered a little more slowly. So when you identify the big things, you can tell they're worth putting energy into because they're stable in time. Okay. But you're asking about something a little different, which is in every customer experience, there are those big things, and by the way, it's astonishingly hard to focus even on just the big things. So even though they're obvious, they're really hard to focus on. But in addition to that, there are all these little tiny customer experience deficiencies, and we call those paper cuts. And we make long lists of them, and then we have dedicated teams that go fix paper cuts. Because the teams working on the big issues never get to the paper cuts. They never work their way down the list to get to, they're working on big things as they should, and as you want them to. And so you need special teams who are charged with fixing paper cuts. Where would you put on the paper cut spectrum, the buy now with one click button, which is I think pretty genius. So to me, my interaction with things I love on the internet, there's things I do a lot, I may be representing regular human, I would love for those things to be frictionless. For example, booking airline tickets. Just saying. Buying a thing with one click, making that experience frictionless, intuitive, all aspects of that. That just fundamentally makes my life better. Not just in terms of efficiency, in terms of some kind of cognitive load and inner peace and happiness. First of all, buying stuff is a pleasant experience. Having enough money to buy a thing and then buying it is a pleasant experience. And having pain around that is somehow you're ruining a beautiful experience. And I guess all I'm saying as a person who loves good ideas, is that a paper cut a solution to a paper cut? Yes. So that particular thing is probably a solution to a number of paper cuts. So if you go back and look at our order pipeline and how people shopped on Amazon before we invented one-click shopping, there was more friction, there was a whole series of paper cuts. And that invention eliminated a bunch of paper cuts. And I think you're absolutely right, by the way, that when you come up with something like one-click shopping, again, this is like so ingrained in people now. I'm impressed that you even notice it. I mean, most people... Every time I click the button, I just... Most people never notice. Surge of happiness. There is, in the perfect invention, for the perfect moment, in the perfect context, there is real beauty. It is actual beauty, and it feels good, it's emotional, it's emotional for the inventor, it's emotional for the team that builds it, it's emotional for the customer, it's a big deal. And you can feel those things. But to keep coming up with that idea, with those kinds of ideas, I guess, is the day-one thinking effort. Yeah, and you need a big group of people who feel that kind of satisfaction with creating that kind of beauty.