#212 Alfred Lin: How to Think (and Work) Like a World-Class Investor

0:00:03 One of the things that we talk about at Sequoia is you can’t just be better.
0:00:05 You have to be different too.
0:00:08 It’s whether you want to be conventional or contrarian, you have to be right.
0:00:13 If you’re right and conventional, it’s probably a less interesting solution.
0:00:19 But if you’re right and, um, and contrarian, you probably won’t be able to make
0:00:23 a lot more money because nobody’s fault, nobody’s going after that opportunity.
0:00:26 Um, I often find that it’s interesting.
0:00:29 There are people who just want to be contrarian, but if you’re contrarian
0:00:31 wrong, that’s not a great situation.
0:00:36 I try to put things in these two by two matrices of right and wrong
0:00:37 and conventional and contrarian.
0:00:46 Welcome to the Knowledge Project.
0:00:48 I’m your host, Shane Parrish.
0:00:52 In a world where knowledge is power, this podcast is your toolkit for mastering
0:00:54 the best what other people have already figured out.
0:00:58 Today’s episode will transform how you think about building and scaling,
0:01:00 transformative companies.
0:01:05 My guest is Alfred Lynn, one of Silicon Valley’s most successful operators
0:01:06 turned investors.
0:01:10 After meeting Tony Heich at Stanford over a pizza arbitrage scheme,
0:01:15 Alfred went on to help build and sell Link exchange to Microsoft, then
0:01:21 scaled Zappos from startup to its $1.2 billion acquisition by Amazon as
0:01:22 the COO and CFO.
0:01:25 Now he’s one of tech’s most influential people.
0:01:29 Like a lot of outliers, Lynn struggled in school, preferring to hack
0:01:31 solutions together than follow instructions.
0:01:32 Sound familiar?
0:01:36 That changed with one of his teachers who made him realize the importance
0:01:39 of enduring impact over short-term gains.
0:01:42 Whether you’re building a company, scaling operations are making complex,
0:01:44 strategic decisions.
0:01:47 Alfred breaks down the frameworks and mental models that have guided him
0:01:50 through multi-billion dollar outcomes.
0:01:53 We explore everything from his unique approach to company culture and
0:01:58 hiring that help make Zappos legendary to how he evaluates opportunities
0:02:02 at Sequoia to the crucible moments that shaped his decision making philosophy.
0:02:06 This conversation goes deep into specific practices around scaling,
0:02:10 competing with giants and navigating technological disruptions, while
0:02:14 revealing the deeper principles that have guided him through multiple
0:02:16 successful chapters in tech.
0:02:20 His insights on building and during impact over short-term gains are more
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0:03:50 You’ve had a remarkable journey from entrepreneur to investor.
0:03:53 And I want to know more about this story, but I want to start with some
0:03:59 of your early life experiences that changed you and impacted you in the future.
0:04:01 I guess I was born in Taiwan.
0:04:06 The two parents who were both commercial bankers.
0:04:12 In an early age, from what they tell me, I was always a little, I saw
0:04:15 the world a little differently and did things that are a little different.
0:04:18 The story that they like to tell about me being different was when
0:04:20 I was about two years old.
0:04:26 There was a new dresser that was delivered to our apartment in Taiwan.
0:04:30 And I figured out a way to get to the top by pulling out the first
0:04:33 drawer, crawling into it, then pulling out the second drawer,
0:04:37 pulling it, crawling into that and then getting all the way to the top.
0:04:40 And when I got up there, I thought I could fly, so I jumped off.
0:04:47 And so they left telling that story because they rushed me to the hospital
0:04:52 and they were very concerned whether there was any permanent damage
0:04:53 and things like that.
0:04:56 And my mom kept bringing me back to the hospital again and again.
0:04:59 And the doctor said, don’t worry, I think he’s fine.
0:05:00 I think he’s fine.
0:05:04 And eventually he said, well, is there going to be any problem with his development?
0:05:09 He’s like, well, he’s either going to be a genius or he’s going to be an idiot.
0:05:10 He’s one or the other.
0:05:15 I mean, so that’s that’s how my parents would describe me.
0:05:18 High variance and high beta.
0:05:21 And throughout school and throughout life, I was very much like that.
0:05:25 I like to hack things and not do the work until one day.
0:05:29 And this was in elementary school.
0:05:34 I just tried to not do the work and hacker my way through things and got
0:05:39 to spend it a few times, one of which was just coming up with a creative idea
0:05:42 of taking chairs from the second floor to the first floor.
0:05:45 I went down the slide instead of following the teacher’s directions.
0:05:46 I got suspended for that.
0:05:52 And so I didn’t never really like school that much because it was so rigid until
0:05:55 until I used to hack my way through things.
0:06:00 And one of the teachers that I had, Mrs. Einstein, had this way of teaching
0:06:01 where she would put up a problem.
0:06:07 She would then have us try to solve that problem or do the assignment and try
0:06:10 to understand why she put the the reading up there.
0:06:15 And I would always bet with her if I knew the answer or if I knew
0:06:18 the conclusion of the lesson, then I wouldn’t have to do the homework.
0:06:21 She let me get away with that once or twice.
0:06:25 And then she said to me once, you know, you’re you’re very smart.
0:06:27 I’ve seen a lot of people waste their talent.
0:06:32 So do you want to do you want to start first or do you want to finish first?
0:06:37 And I think I retorted back saying, well, I like to start first.
0:06:40 And finish first with the least amount of work possible.
0:06:46 And then she said to me, that’s a great answer for a sixth grader.
0:06:49 But what happens in life when there’s no finish line?
0:06:50 What are you going to do then?
0:06:53 And that sort of put me back.
0:06:58 And I didn’t quite understand it until maybe now that this is the whole
0:07:05 concept of having an infinite game and thinking through not some thing,
0:07:09 some finish line, some goal, but just think about what you want your
0:07:12 enduring impact to be and what you want to do and what you want to accomplish.
0:07:16 And when the world doesn’t give you a finish line, we all have the same
0:07:18 24 hours in a day.
0:07:20 What do you want to decide to accomplish in that 24 hours?
0:07:23 We have an unknown number of years on this planet.
0:07:25 What do you want to get accomplished?
0:07:28 That sort of shaped the way I sort of started thinking about the world.
0:07:32 Did it hit you then at the time or was it something you reflected on later?
0:07:39 I think it hit me then, but I didn’t think I, I don’t think I understood it then.
0:07:46 And so then that led to a number of explorations on what I did want to accomplish.
0:07:51 Why was it important to think about this concept of like infinite games?
0:07:54 How do you win an infinite game when there are no set rules?
0:07:58 You’re making the rules for yourself in an infinite game.
0:08:01 And the rules change.
0:08:02 You get to change some of the rules.
0:08:04 The world changes some of the rules.
0:08:07 How do you, how do you navigate that?
0:08:10 And then you quickly realize not that winning.
0:08:14 They’re in a finite game chest.
0:08:14 There’s a winner.
0:08:17 There’s a loser in an infinite game.
0:08:20 There are a lot of different people in the world.
0:08:27 They play the game differently and in some ways they’re all trying to get on
0:08:29 with the world and trying to do the best they can.
0:08:32 But some people are more successful than others.
0:08:37 And the reason they’re more successful, I think, is because they really know what
0:08:41 their, their values are and they really know what impact they want to have on the world.
0:08:43 What are your values?
0:08:50 Over the years, I, I thought through, and this has changed over time, but I think
0:08:56 the, the values for me are when you meant, when you want to accomplish something,
0:08:58 it’s about the inputs.
0:09:03 It’s about the process by which you go about getting the outputs.
0:09:06 I think it’s very, very important to have that.
0:09:14 And I value that clarity of input eventually leads to output and focus on the inputs.
0:09:20 I value consistent compounding and just getting every single, getting up every
0:09:25 single day and just making small improvements every single day and compounding that.
0:09:36 I value honesty and truth and just being very direct with people.
0:09:38 I don’t try to sugarcoat anything.
0:09:47 Um, I value, I value people for who they are.
0:09:54 My father, um, I learned this from my father where he’s, he told me once
0:09:58 because I was like, Oh, I’m just so much smarter than everybody else because
0:10:00 it’s a little cocky little kid.
0:10:05 And he said, well, actually you can learn anything from, you can learn many things
0:10:08 from every single person on this planet.
0:10:14 I think I was probably a six or seven at the time and he was, uh, he’d show me
0:10:20 all the different people that he learned from and that the collection of these
0:10:24 lessons from many, many different people is what you become.
0:10:27 And that was a pretty important lesson.
0:10:31 So I value people for who they are and trying to learn as much as I can from
0:10:32 each individual person.
0:10:36 I value family and friends.
0:10:38 Um, pretty important to me.
0:10:45 We talked a little bit about work life and work life balance from, from, as you said,
0:10:48 for many of us, it’s work life integration.
0:10:52 And if you don’t have some grounding with people who see you for you, who you
0:10:57 are, call out when you’re not, you’re not being a good person or you’re not doing
0:10:59 the things that you said you were going to do.
0:11:02 Um, what is there in life besides that?
0:11:07 How do you want somebody to call you out in those situations or how do you call
0:11:08 out other people?
0:11:15 The way I do it is try to be fact based and, um, just give examples specifically
0:11:20 of what has been working and what has not been working.
0:11:22 And that tends to work pretty well.
0:11:27 And there, there are times when we’re back at my wife will say, Hey,
0:11:28 this is not working for us.
0:11:31 So what do you want to do about it?
0:11:35 Uh, you can try to keep going the same way, same way down the certain path.
0:11:37 Well, we can try to change it.
0:11:39 If we don’t like something, we just change it.
0:11:44 And it’s just much easier to have those kinds of conversations.
0:11:50 Um, my son a few days ago was being, um, quite negative about his school.
0:11:56 And, you know, he’s starting, he’s 13, he’s going to be 14 this year.
0:12:00 He’s starting to be like me when I was younger and think that he’s smarter
0:12:02 than the whole rest of the world.
0:12:08 And said, Hey, Atticus, do you want to be, do you want to have a negative attitude
0:12:10 because you’ll spin into this negative spiral?
0:12:16 Um, and by the way, if you have a negative attitude, the world just looks worse.
0:12:20 When you have a positive attitude, the world just looks better.
0:12:25 And we played this, let’s use yes and for a bunch of things and let’s create
0:12:30 options and then you’re going through the no butt situation and it doesn’t work.
0:12:35 So let’s try to just change your attitude about some of these things.
0:12:39 And I thought that was quite an interesting conversation where just by simply
0:12:42 changing the framework, he became much more positive.
0:12:48 When you talk about inputs versus outputs, what inputs do you think about in life?
0:12:56 Well, I think the inputs I think about are, um, you know, that it depends on
0:13:00 what I’m trying to get accomplished, but if the inputs are just thinking about
0:13:03 hard work, how do I get up every day?
0:13:04 Do I want to stay healthy?
0:13:06 Do I get up every single day and work out?
0:13:10 I hear that you work out every single day because instead of trying to figure
0:13:13 out which days you’re going to work out, it’s always in negotiation with which
0:13:17 days and some days you don’t feel like, um, exercising.
0:13:19 You just work out every day.
0:13:20 I have the same philosophy.
0:13:24 You just get up every single day and do the things that are important.
0:13:28 Um, so the inputs I have is I get up every morning, I work out.
0:13:32 I look through, I read through my email and I try to think about what’s the
0:13:35 most important thing that I have to get right today.
0:13:40 What’s the most and, um, and think about first order issues.
0:13:43 What is the first order issue that I have to solve?
0:13:46 What is the first order issue of a company that needs to get fixed?
0:13:50 Um, what is the first, what is the thing that I need to do to influence an
0:13:54 outcome for, um, for a founder?
0:13:58 And, you know, that’s very, very clarifying.
0:14:03 Often we can create a very, very long to-do list and then you’ve got to pop up
0:14:06 the level and just look at the list of what’s the most important things I
0:14:07 have to get accomplished.
0:14:11 Because if you just list off to do is you probably will not be able to get to
0:14:14 all of them and the most important thing might be the last one you list.
0:14:18 And so you can’t just go down that list and do them one by one.
0:14:23 Often it’s by popping up a level where you sort of look at the whole list and
0:14:25 it’s like, okay, well, most of this is not important.
0:14:28 Is that what you mean by first order issue?
0:14:30 I think you mean something a little more nuanced.
0:14:33 Some people talk about the most important thing.
0:14:38 Um, and I think, I think about first order.
0:14:42 If I get this problem, I have a problem on my hands.
0:14:45 If I get to the first order issue and get to the root cause of that.
0:14:49 Usually that helps solve that problem.
0:14:52 And there are other issues that are not first order.
0:14:57 Um, and that concept is quite important.
0:15:03 We also sort of navigate that into other situations where, um,
0:15:05 where they are crucible.
0:15:13 So as an example, like you, you have, you have situations where the website’s
0:15:14 not working fast enough.
0:15:15 That’s apples.
0:15:17 We had a situation where the website’s not fast enough.
0:15:21 Is the first order issue that we have too many pictures?
0:15:22 Well, we want the pictures.
0:15:23 We have lots of photos.
0:15:27 We want to show those photos is the first order issue that we need to, um,
0:15:34 just trim the number of search results while customers want longer search results.
0:15:35 It’s like, no, it’s none of that.
0:15:38 We need to figure out how to make the website go faster.
0:15:42 And so we start cashing the, the search results.
0:15:43 We start cashing things.
0:15:48 And so you start developing the technologies that solve the speed issue.
0:15:51 But the first sort of issue is that we need to solve this with technology, not
0:15:54 with a bunch of either or solutions.
0:15:58 Um, that’s an example that I learned a long time ago.
0:16:04 Another situation is the distribution of the apples was not flowing well.
0:16:08 Um, and we couldn’t figure out which process was broken.
0:16:10 Was it the picking process?
0:16:13 Was the, was the ordering process broken?
0:16:14 What was broken about it?
0:16:21 And we went and just looked through the flow and the flow was broken.
0:16:27 And so, uh, there was too many handoffs, uh, across all of these
0:16:29 different discrete processes.
0:16:35 And so we had to sort of pop up a level and figure out what the flow of from when a
0:16:41 customer orders something, when it gets through the distribution center, how is
0:16:45 going to be picked, packed and packaged and shipped.
0:16:49 And when you look at that from a flow perspective, you start thinking about new
0:16:54 solutions that allow there to be much better flow throughout the distribution
0:16:59 center, then then to batch things for picking batch things for, um, packing
0:17:03 packed batch, batch things for, uh, for shipping.
0:17:05 So that’s what you mean by first order.
0:17:10 Uh, I want to get into more of your experience, not only at Zappos, but, uh,
0:17:14 being on the board of some of the companies that everybody has heard of, uh,
0:17:15 today or being involved.
0:17:18 But before we get there, I want to come back to the school for a second.
0:17:22 Are there any other experiences that you had during school with teachers that
0:17:23 might have impacted you?
0:17:29 You know, earlier on in junior high school, I was, um, I was suspended
0:17:33 from the computer lab because I built, uh, this was very old.
0:17:37 So they’re a radio shack, TRS 80s, so we call them trash 80s today.
0:17:44 Um, and there was the computer lab at, you know, you had to run time in our
0:17:47 computer lab to use the computer and it built this game.
0:17:53 And the central server at the time was literally a floppy drive where all of
0:17:56 us saved our programs there.
0:18:03 And one day, uh, a bunch of the students, uh, in the computer lab all found
0:18:05 the game that I programmed and then started playing with it.
0:18:09 The teacher and the principal just happened to walk in and saw that
0:18:10 we’re all playing this game.
0:18:15 And, um, I was told that computer lab is valuable time and you should
0:18:18 be doing something much more productive than, than producing a game.
0:18:22 So I, I was no longer allowed to work in the computer lab.
0:18:25 And the computer lab teacher was Mrs.
0:18:31 Petosa and she, she also ran the math team and she said, well, you’re, I’m
0:18:33 sorry, the principal wants you out of the computer lab, but you should
0:18:34 join the math team.
0:18:36 And I joined the math team there.
0:18:39 And, um, one of the things I was really good at was math.
0:18:43 And she told me that if you want to be a leader and you want the team to
0:18:47 win, it’s not good enough for me to just solve the problems.
0:18:50 We figure out how to get the rest of the team to perform.
0:18:54 And so I started teaching the rest of the math team.
0:18:58 Some of the reasons why I was able to solve some of these problems more
0:18:59 quickly than there were.
0:19:03 They’re very talented, but I had figured out tricks that they had not figured
0:19:06 out and they taught me tricks that I had not figured out.
0:19:09 So we got better and better by riffing each off each other.
0:19:13 And so I’d learned the value of teamwork by just being thrown into
0:19:15 a situation like that.
0:19:19 You started a company before you joined Zappos.
0:19:20 What was that?
0:19:21 I started a bunch of things.
0:19:23 I started a lemonade stand when I was younger.
0:19:26 I, those were not interesting.
0:19:29 I started a long-long service in junior high school.
0:19:32 Um, I did it myself and realized it was not fun.
0:19:34 It was too hot in New York city.
0:19:39 So I, I got the contracts and then asked some of my friends from school if
0:19:43 they would do, help me do the work at a few odd jobs here and there.
0:19:50 And it was just never as fulfilling as working at a company that from the ground
0:19:55 up when Tony Shay left, um, Oracle to start this company.
0:19:59 That was originally called internet marketing solutions because they’re
0:20:00 building websites.
0:20:02 Uh, he asked me to join that company.
0:20:06 I said, no, then they found out that they couldn’t get any of, anybody to
0:20:07 go visit these websites.
0:20:09 So he connected all of them.
0:20:12 Um, and that became link exchange.
0:20:15 And I joined that company soon after Sequoia invested in that company.
0:20:18 And it was a banner advertising exchange.
0:20:23 That was one of the largest banner advertising exchanges in 1998, 1999.
0:20:26 We saw that to Microsoft for 265 million dollars.
0:20:29 And, um, that was quite the experience.
0:20:33 Did you know at the time we were sort of in a bubble or how did you
0:20:35 think about it back in the late nineties?
0:20:39 I mean, we had a business, we had 15 million dollars in revenue.
0:20:43 You can kind of tell that we’re in a bubble when someone would be willing
0:20:47 to buy a company that at 15 million dollars in revenue for 265 million dollars.
0:20:52 Um, but also, you know, it was the third largest acquisition at the time.
0:20:58 So I think when you’re in it, you don’t realize you’re in a bubble, but popping
0:21:00 up, like the numbers don’t make sense.
0:21:01 Yeah.
0:21:07 So that’s why I think it’s valuable to have people who are slightly outside
0:21:10 of where you work to keep you accountable.
0:21:12 It’s like, Hey, how’s this, how does this work?
0:21:18 Just by simply asking questions, you get into a situation where like, wait, I
0:21:19 can’t explain that question.
0:21:21 I can’t answer that question six only thing.
0:21:22 I can’t explain it.
0:21:27 Maybe that person’s question has more insight than I would have expected.
0:21:30 What are some of the lessons you learned from link exchange?
0:21:36 Boy, that was so many, um, there are many, many lessons because it was
0:21:40 the first time we’re doing anything, um, that was at scale.
0:21:50 And you hear this all the time that, um, that you should hire, you should hire
0:21:54 slowly and make sure you really, really understand who you’re hiring for.
0:21:59 And you, you know, often when someone’s not working out, you should, it’s
0:22:00 probably time to let them go.
0:22:02 And we always gave people too long.
0:22:08 And, and I think the company’s velocity, uh, didn’t, couldn’t go any faster
0:22:10 because we didn’t hire as well as we could have.
0:22:12 We didn’t let people go when they weren’t working out.
0:22:15 And those are very, very important things to get right.
0:22:19 I often sort of think about the velocity of a company velocity.
0:22:21 And I measured that in two ways.
0:22:25 This, you know, use the word velocity, velocity as opposed to speed
0:22:30 because speed is just how fast you’re going, but velocity, velocity also
0:22:33 has direction and think the combination of two is quite important.
0:22:37 But the whole speed of a company generally doesn’t get any faster
0:22:41 unless you’re pushing and the best companies, they keep pushing.
0:22:46 And otherwise you’re just going to go slower and slower and slower.
0:22:51 You know, I think building a real business is really important.
0:22:57 Um, many of the companies that were founded in 1999, 1998, 1999, 2000,
0:22:59 they were not real businesses.
0:23:01 They had lots of eyeballs.
0:23:02 They had lots of users.
0:23:06 Um, but that’s not really enough.
0:23:11 And at Sequoia, we often talk about the fact that we own shares in a company.
0:23:13 We don’t own shares in the founder.
0:23:15 We don’t own shares in the product.
0:23:18 We don’t own shares in their market strategy.
0:23:22 We own shares in the company and that company needs to have a business one day.
0:23:27 My partner, Pat Grady, loves to say that free cash flow equals freedom
0:23:32 because eventually a real business generates real free cash flow.
0:23:38 And the freedom being that the freedom that allows you to not have to raise money
0:23:43 and the freedom to allow you to invest in new areas, the freedom to continue
0:23:48 to grow because you can invest in growth and invest in new novel technologies
0:23:54 and new product lines, the freedom to, um, not worry about the quarterly, uh,
0:23:57 sort of pace of having to do more and more sales.
0:24:01 You just, you, you generate free cash flow and it just generates a lot of freedom.
0:24:06 Let’s go back to the push-pull theme for, you know, you said companies don’t
0:24:09 generally increase velocity without force.
0:24:14 How do you think about the difference between adding force or removing obstacles?
0:24:19 That’s a very, that’s very, very insightful of you.
0:24:26 I think many times applying force, um, is what, what leaders try to do,
0:24:30 which is just to apply a forcing function and make you make a choice.
0:24:36 And often I think removing obstacles are just as important as, as applying
0:24:39 the pressure to keep going on and on and on.
0:24:45 But often, you know, when you apply force, you realize where the
0:24:50 obstacles are because you, you butt against that obstacle.
0:24:53 And then you realize, okay, I keep butting against this.
0:24:55 Maybe I have to figure out a way around it.
0:25:02 Um, and I, you know, my job as a board member is to help you identify
0:25:06 obstacles and help you remove it, but sometimes you just need to be pushed against it.
0:25:10 Is there an example that comes to mind when you say that where you push and it
0:25:12 helped you identify an obstacle?
0:25:16 Maybe in the early days of Airbnb, I think people forget it was much
0:25:20 more of a listing service and it was less of a marketplace.
0:25:24 And if you sort of take the definition of a marketplace, you have to complete
0:25:29 the transaction and you just not only have to complete the transaction, you
0:25:31 have to remove as much friction as possible.
0:25:38 And so Airbnb in the early days had a calendar, held the money, paid
0:25:42 out the money, but there was this big friction, big, big friction.
0:25:48 And it was because there was not enough trust between the host and the guest.
0:25:55 And so the early days of the removing of that friction was to get, um, connected
0:25:57 through Facebook Connect.
0:26:01 So you can check someone out and check out their Facebook, um, pages
0:26:05 and who they are and to see if this is an authentic person.
0:26:10 But even that, checking that out took 24, 48, 72 hours.
0:26:12 That’s just too long.
0:26:18 And you just kept pushing, this is not going to work long term, um, because
0:26:24 there’s only so many people that can book travel and wait 24 to 72 hours
0:26:26 before they know that they can go there.
0:26:33 And, and so it started out, many great companies start out as a fringe sort
0:26:37 of activity and you have to figure out how to make it more mainstream.
0:26:42 Often that is about removing obstacles or removing friction, but you
0:26:45 butt against this and you’re like, what’s the solution here?
0:26:47 And you keep playing, playing for us.
0:26:50 This is, this is going to limit our growth if we don’t solve those.
0:26:55 And eventually, um, Brian and the team and the product team figured
0:26:56 out that we needed instant book.
0:27:00 We needed to figure out how to instantly book people.
0:27:05 Well, you have a whole set of hosts now that are used to not accepting
0:27:08 guests just because they booked them.
0:27:10 So how are you going to remove that obstacle?
0:27:11 Well, you start with new hosts.
0:27:16 It’s like, let me show you that Airbnb can be trusted.
0:27:20 We’re going to, as new hosts, we’re going to send you some customers and you
0:27:22 should just book them automatically.
0:27:27 And eventually more and more of the, of the hosts realized that instant
0:27:28 book is just the way to go.
0:27:34 And, um, that’s an example where you just have to be pushed against that for a
0:27:36 bit of time to find the solution.
0:27:38 Was DoorDash sort of fringe too?
0:27:41 And when mainstream, did they start in like the suburbs or something?
0:27:44 DoorDash started more fringe than even the suburbs.
0:27:47 It started on a, on, on a college campus.
0:27:54 And the reason, uh, we, we passed on the seed round at Sequoia was we’re
0:27:59 concerned that the frit, this is like just something that college students
0:28:01 did with their parents’ money.
0:28:08 Um, and then they started out, um, focusing on Stanford and then Palo Alto.
0:28:09 And they went to other suburbs.
0:28:15 And it turned out that it, that was a very smart thing to do because everybody
0:28:16 was going after the cities.
0:28:20 And one of the things that we talk about at Sequoia is you can’t just be better.
0:28:22 You have to be different too.
0:28:26 And if it’s easy to say and hard to implement because everybody, and when
0:28:32 everybody is chasing after, uh, the cities, because conventional wisdom tells
0:28:36 you that that’s the right thing to do, uh, it’s very, very hard to do
0:28:39 something slightly, to do something slightly different.
0:28:46 Um, but if you just hear, uh, Tony and the team talk about their business, you
0:28:50 realize that they had way more than just, Oh, I’m going and doing something
0:28:51 contrarian.
0:28:55 They actually had real reasons why the suburbs were actually a better place
0:28:59 to start the value for someone who lives in the suburbs.
0:29:02 I have to drive 20 minutes to go get their food as higher than someone that
0:29:07 they can go from their, um, apartment, go downstairs and walk a few blocks
0:29:08 and get the food and bring it back home.
0:29:12 So that was like pretty interesting.
0:29:16 The other one was, well, is there enough density, uh, around the
0:29:16 suburbs?
0:29:20 And it turns out, yes, there’s, there is density.
0:29:21 You just might not think about it.
0:29:27 And they had examples where that’s in Palo Alto, there was University
0:29:32 Avenue and there was California’s, um, street and both of those places.
0:29:35 There, that’s where all the restaurants were.
0:29:40 And so there’s density in where you can go to those, those restaurants
0:29:42 and you can radiate out from there.
0:29:47 So it was not as random as any, any restaurant can be anywhere
0:29:48 and any home can be anywhere.
0:29:54 Um, and it turned out when you go look and look at the data, small towns
0:29:57 all have this, there’s the reason why small towns, there’s a main street
0:29:58 where everything happens.
0:30:04 And so then you start realizing that the density problem is not as, not
0:30:05 as complicated as you might think.
0:30:09 And they won because they were able to take the profits of the
0:30:11 suburbs to go into the cities.
0:30:16 I often think about that as, um, you know, there are people who, uh,
0:30:20 think of the world and they just follow conventional wisdom.
0:30:22 And then there are people who want to be contrarian.
0:30:26 Well, in either case, whether you want to be a conventional or contrarian,
0:30:27 you have to be right.
0:30:32 If you’re right and conventional, there’s probably, it’s probably
0:30:33 a less interesting solution.
0:30:39 But if you’re right and, um, and contrarian, you probably won’t be
0:30:42 able to make a lot more money because nobody’s following, nobody’s
0:30:44 going after that opportunity.
0:30:47 Um, I often find that it’s interesting.
0:30:49 There are people who just want to be contrarian, but if you’re
0:30:52 contrarian wrong, that’s not a great situation.
0:30:56 I try to put things in these two by two matrices of, uh, right and wrong
0:31:00 and, and convention, conventional and, uh, contrarian.
0:31:04 You know, the term I use for that is advantageous divergence.
0:31:06 Advantageous divergence.
0:31:07 Tell me more about that.
0:31:07 Well, that’s it.
0:31:09 It’s exactly what you just said, right?
0:31:10 It’s not enough to be contrarian.
0:31:11 You have to be right.
0:31:15 And so you have to diverge from the crowd, but you also have to be correct.
0:31:15 Yeah.
0:31:18 So it sounded like it’s kind of the Walmart strategy, right?
0:31:22 Where it’s like, we’re going to go in this area with hat, which has less competition.
0:31:25 We’re going to get really good at what we do.
0:31:28 And then we’re going to use the money or profits or, and we’re going to funnel
0:31:30 into maybe the more desirable area.
0:31:35 Like when Walmart started competing with Sears, they didn’t go into cities and
0:31:40 came out, you know, they went into the suburbs where nobody was, or the contrast,
0:31:46 I think between their ability and what they were competing against was much higher.
0:31:47 Yeah.
0:31:51 And, and, and I think that that is, uh, that’s what all startups should focus on.
0:31:55 You don’t want to compete with someone bigger than you head on because they
0:31:57 have more money and they have more people.
0:32:02 They have more history, wherever they have more, uh, abilities.
0:32:06 You just want to compete with them where they’re not competing.
0:32:07 Double click on that for me.
0:32:12 Well, your example about Walmart, where the example about DoorDash focused on,
0:32:18 um, the suburbs, there’s a example about DoorDash where you want to win McDonald’s
0:32:21 or do you want to win the top 100 merchants?
0:32:23 And it’s not just about one or two.
0:32:29 Yes, McDonald’s is one of the largest merchants, but winning a whole suite of
0:32:30 them is actually more valuable.
0:32:39 Um, Google, but long tail keywords were valuable than, you know, the head.
0:32:43 And most of advertising was broadcast advertising.
0:32:48 You start from the top and this is a bunch of like long tail keywords.
0:32:55 And they think a lot of great companies, um, whether it’s intentional or not, um,
0:32:58 try to do things very differently than what exists today.
0:33:03 Apple, they weren’t the first to many things.
0:33:07 They were, you know, they didn’t make the first, uh, personal computer.
0:33:12 They just made the user, their focus was always about the user experience.
0:33:18 Whether it was the computer, the phone, the watch, everything they do is about
0:33:19 having a great user experience.
0:33:22 That was not the conventional thing that people thought about.
0:33:26 It was about, you know, in the early days of the PC, it was about processing
0:33:29 speed and which processor was the fastest, et cetera, et cetera.
0:33:32 Uh, when the phone came out, it was about the keyboard.
0:33:34 We don’t use the keyboard anymore.
0:33:37 The Apple thing is fascinating.
0:33:38 So is the Blackberry thing.
0:33:40 Cause they really hung on to that keyboard thing.
0:33:43 But I remember when they came out with their new, I forget what the device was called.
0:33:45 It was like their apple killer.
0:33:49 And I used it as a demo and I couldn’t figure out how to get on the internet.
0:33:50 And I was like, they’re done.
0:33:52 The user experience is so important.
0:33:55 It took a demo to like figure out how to use the internet.
0:33:56 Once you figured it out, it was great.
0:33:59 But I was like, oh man, this is so not intuitive.
0:34:03 You know, let’s go back to hiring and firing a little bit.
0:34:09 Was there any moments sort of at Zappos or earlier with link exchange where you
0:34:12 thought you had the wrong fit, but it turned around?
0:34:17 That’s a great way of asking that question.
0:34:23 I, I would say probably not in the early days of link exchange, we hired and back
0:34:29 to like conventional and, you know, we hired the conventional right person.
0:34:31 We were looking for a marketing person.
0:34:35 We’re looking for a marketing person that marketed to small, medium sized businesses.
0:34:36 They understood the internet.
0:34:41 They fit all the specs that you would have in a job description.
0:34:46 But they didn’t fit the way we operated.
0:34:49 They didn’t fit the way we value what we value.
0:34:56 And, you know, it’s easy to sort of limit that down to like they’re just a professional
0:34:59 marketer and they’re mercenary, non-emissionary.
0:35:01 That’s how Tony was told the story.
0:35:06 But at the end of the day, they didn’t value what we were trying to build.
0:35:09 They didn’t have the same values that we had.
0:35:14 And which is why when Zappos started, Tony spent a lot of time defining the values.
0:35:18 This is Tony Shea of link exchange and Zappos, the values of the company.
0:35:22 And it’s something that I talked to founders about.
0:35:27 If you don’t have the same mission, you don’t have the same values,
0:35:32 you don’t have the same operating understanding of the company.
0:35:34 It’s very, very hard to work together.
0:35:40 And then, you know, you’re asking someone to change when they fundamentally don’t
0:35:44 fit to the company and how the company works.
0:35:47 That is generally the issue.
0:35:58 Then the other issue on the flip side, on the functional side, when your
0:36:03 company is growing really, really fast and you see someone who is growing, but
0:36:07 they’re not growing as fast as the company, every single day, the delta
0:36:12 between how far the company is moving or how fast the company is moving versus
0:36:17 how fast or how far the person is moving, the delta gets bigger and bigger and
0:36:19 bigger, so it gets very hard to turn around.
0:36:24 And so we have this concept that a lot of people have at Sequoia.
0:36:27 We hire for slope, not intercept.
0:36:33 So experience obviously matters, but if you just hire for the experience and
0:36:37 their slope is not fast, that’s going to become a problem at some point.
0:36:42 And so we really, really ask founders to think about what is the person’s
0:36:48 potential, what is their slope and we much rather bet on someone with high,
0:36:56 high slope and low intercept because in startups, in companies that are new,
0:37:02 the experience is helpful, but you’re doing something different and new and
0:37:03 you need to reinvent.
0:37:10 Bring a playbook over from somewhere else is helpful up to a degree, but usually
0:37:13 many of the problems that you need to solve are just different.
0:37:17 And that’s why you hear a lot of founders talk about first principles,
0:37:25 thinking and don’t reason by analogy, et cetera, because you do have to solve
0:37:28 the problem a different way.
0:37:32 What’s the difference between slope and potential?
0:37:38 It’s just, well, slope is pretty much the same thing, slope and potential.
0:37:45 But having a high rate of learning, high rate of being able to move fast.
0:37:50 And so if someone has a lot of potential, they’re over here, their potential is
0:37:52 up here, that slope when you draw that line is pretty high.
0:37:55 How do you gauge somebody’s potential?
0:37:57 It’s like, you might be able to do this job and you might be able to grow
0:38:01 into it, but coming into it, they’re not going to check the boxes.
0:38:02 They’re going to look different.
0:38:06 The future does not look like the past, but you have nothing else to go on,
0:38:10 but the past and you can see whether someone moved really, really quickly
0:38:14 in the previous situation where they promoted three times in the same year
0:38:17 at a different company that was moving very, very quickly.
0:38:18 Do they have a sense of urgency?
0:38:20 You can test for some of these things.
0:38:22 You can ask about these things.
0:38:25 But yeah, you don’t know whether they have the potential to grow
0:38:30 into the next stage of the company until you put them in that position.
0:38:35 Often, I think the challenge is the company is moving so fast and you’re
0:38:39 hiring someone that has done the job before and you know that they can do
0:38:42 the job for the next year or two and that’s maybe good enough.
0:38:45 If you hire someone, you have to let them go on three months.
0:38:46 That was an asire.
0:38:50 There’s almost no reason why that person was not going to be able
0:38:52 to do the job for three months.
0:38:54 They either were not a cultural fit.
0:38:55 They didn’t have the right skills.
0:38:59 If they stick around for a year or two, it’s usually because they’ve done
0:39:02 the job before and they’re picking up a bunch of low-hanging fruit.
0:39:07 But I look at Tony at Doorash.
0:39:11 Many of the people who work for him have worked for him for a long period of time.
0:39:13 He likes to grow people from within.
0:39:15 He obviously hires from outside as well.
0:39:19 But many of the people who’ve been around the company have been around for a long time.
0:39:28 Amazon, many of the senior VPs that were around Bezos had been around
0:39:30 the company for a long, long time.
0:39:36 Now that Jassy’s there now as CEO, he’s trying to develop people also
0:39:38 for a long period of time.
0:39:43 If you look at great companies, they’re very, very good at developing talent
0:39:45 both from within and hiring from outside.
0:39:48 Is it a red flag if the turnover is too high then?
0:39:51 Is it like a sign that people don’t know how to hire, right?
0:39:55 I think it’s a red flag and you look at it and you don’t want to.
0:40:01 So the issue with metrics is people start managing to the metrics.
0:40:05 And so if you start telling them, hey, your turnover is really high,
0:40:08 they start managing to the turnover number.
0:40:10 And that’s another thing.
0:40:13 You have to manage the turnover of regrettable.
0:40:15 What is a regrettable turnover?
0:40:19 Why are you not able to retain your best people?
0:40:26 And if you have unregratable turnover, then why did you hire these people
0:40:27 in the first place?
0:40:30 And so if you break the problem down that way, you can’t find or read
0:40:32 some what the issue is with the turnover.
0:40:38 I really like thinking about it in terms of regrettable versus unregratable turnover.
0:40:42 A lot of people when they’re hiring, they sort of, we need this job.
0:40:45 I want to know somebody who’s done it at the next level because that’s where
0:40:46 we’re growing to.
0:40:48 So they’re trying to anticipate where they’re growing.
0:40:52 And one of the problems that I hear commonly is that people run into, well,
0:40:56 that person might have done the 100 million to 300 million growth,
0:40:59 but they had a different team than we have.
0:41:01 They have a different system, different resources.
0:41:04 How do you think about that when it comes to hiring?
0:41:07 My observation is that when you try to hire someone that is
0:41:12 from a company that is one chapter or two chapters ahead, they tend to work out better.
0:41:16 And then part of that is because they’re only one or two chapters ahead of you.
0:41:20 If you try to hire someone who you’re over here and you’re trying to hire
0:41:24 someone that’s 10 chapters ahead, that usually is a problem because you don’t
0:41:28 know whether they understand the problem a few chapters before.
0:41:29 It’s been too far away.
0:41:35 On this, on your particular point about the system, I do think that if you hire
0:41:41 people who are 10 chapters ahead and they have a whole system in place, even though
0:41:46 they took it from 100 to 300 in a product division inside of a large, large company,
0:41:50 they probably had a lot of guardrails that allowed them to not make a bunch of
0:41:55 mistakes. And so you have to dissect whether that operating system works
0:41:57 the same way as your operating system.
0:41:59 Most startups don’t have an operating system.
0:42:05 So the thing that you have to sort of assess is how well can this person
0:42:11 operate when it’s just more nebulous, it’s just less clear.
0:42:14 Are they going to put the operating system in place?
0:42:20 I’ve been to this story behind Zappos from sort of the initial idea in the early
0:42:25 days, just high level five minute version to the exit with Amazon.
0:42:31 Maybe from the start, Zappos was, this is this weird idea, I can’t even
0:42:38 believe we funded it because this was originally founded by Nick Swimmer.
0:42:42 He had called and left a message on our answering machine.
0:42:47 This is how old and back we were going in 1999.
0:42:52 And Tony and I were running a seed fund, a venture fund, an incubator
0:42:53 called Ventra Frogs.
0:42:57 And Nick said, hey, I have this crazy idea.
0:43:04 I’m a webmaster at Auto by Tel, which is an auto website.
0:43:05 I’m the webmaster there.
0:43:10 I think it’d be great to just start something for shoes because I went to
0:43:12 one store I couldn’t find the right size.
0:43:14 Once another store couldn’t find the right color.
0:43:18 Once another store, they didn’t even have the style that I’m looking at.
0:43:24 And he had already searched the web and found a whole bunch of websites where
0:43:27 people were basically trying to sell specific shoes on the internet.
0:43:29 And we thought it was the craziest idea.
0:43:34 And we almost, I think one of us had our finger on the delete button to that
0:43:40 voicemail and then he said that you might think this is crazy.
0:43:47 But mail order is already 5% of sales in the US for shoes.
0:43:50 I’m like, OK, 5% still small.
0:43:54 But the shoe industry is 40 billion, 5% is 2 billion.
0:44:01 And it just wasn’t rocket science to understand that the internet
0:44:03 was going to be bigger than mail order.
0:44:06 And so we took a meeting with the sides of making investments.
0:44:10 And we funded the company $500,000 at a time.
0:44:13 When we were venture frogs.
0:44:18 I had to then leave to go work at a company called Tell Me Networks.
0:44:23 And Tony joined Zappos relatively early on as an advisor and then became
0:44:25 co-CEO and eventually CEO.
0:44:29 But the most important thing back then was because it’s an e-commerce company.
0:44:32 And we were going from 1999 to 2000.
0:44:34 It was growing from 2000 to 2001.
0:44:37 I was like, uh-oh, we have a situation.
0:44:43 And the day after 9/11, the company had zero on sales, zero.
0:44:46 You went from whatever it was, which was small to zero.
0:44:51 And that was the first crucible moment using the term because Sequoia
0:44:54 uses terms crucible and what we’re going to do about that.
0:45:00 So it shook the company and we basically went back to basics and
0:45:02 we wanted to build a company that was profitable.
0:45:07 And so we ran, so Tony ran the company at break even and continued to grow
0:45:12 the company for a long period of time until Sequoia came in in 2004, 2005
0:45:14 to make the first investment.
0:45:20 Most of, and so most of the company was financed from a small seed round.
0:45:25 Tony invested $10 million of his own money, but most of it was financed
0:45:29 through being very creative, figuring out how to get merchants that we,
0:45:34 we ordered from to give us credit and to increase the credit line.
0:45:38 We had a, eventually got a, a line of credit from Wells Fargo.
0:45:42 But the company burned very little cash.
0:45:47 And for a company that went from zero, when we sold the company, you know,
0:45:52 had $1.6 billion in sales, uh, that really didn’t have a lot
0:45:56 of equity financing, uh, was pretty incredible.
0:45:59 When you hear about companies raising hundreds of millions of dollars
0:46:06 to get to $1.6 billion in GMV or, um, or in sales.
0:46:10 And here’s a company that basically raised $10 million.
0:46:15 And it probably was under capitalized, but it really did highlight
0:46:21 that you can build a company by having cat be profitable on the first order,
0:46:25 by being focused on customer service and not focus on marketing.
0:46:28 Talk to me a little bit more about that because you didn’t have
0:46:30 a huge budget for marketing.
0:46:34 You had to get, you know, within the first month, you basically
0:46:36 had to pay back yourself for marketing.
0:46:39 How, how do you think about that?
0:46:42 Not only back then, and then what’s different now in a world
0:46:46 where there’s a lot more money and, and maybe all the players
0:46:48 aren’t rational about how they’re spending money to grow.
0:46:52 Back then, we thought that that was a, you know, we probably thought
0:46:56 it was a curse that we couldn’t raise more money because you probably
0:47:00 would rather run the business a little bit looser so we can grow
0:47:02 a little faster, et cetera.
0:47:07 But being tight led us to find solutions that was again, non-obvious
0:47:09 or divergence to use your term.
0:47:14 Um, and the divergent idea we had was if we can only spend money
0:47:18 that was profitable on the first order, we needed other ways to grow.
0:47:23 And the focus was to become, um, much better at customer service.
0:47:29 We noticed that it was much easier to keep a customer and ordering,
0:47:33 getting that customer to order more than it was to acquire a new customer.
0:47:38 And then we just went down the line of what we can do for the customer.
0:47:42 We, we, we tried to make the website load as quickly as possible.
0:47:45 We tried to pick back and ship within four hours.
0:47:48 The solution to pick back and ship in four hours was to solve
0:47:53 a operations flow issue and not batch the, the operations, which I don’t
0:47:57 think anybody else figured out in a commerce back then, besides Amazon.
0:48:05 Um, we, we decided to work very, very closely with UPS in particular,
0:48:10 and then FedEx and USPS to figure out how to get, um, the shipping
0:48:12 raise as low as possible.
0:48:16 We started shipping so that it was, you know, five to seven days,
0:48:20 um, ground shipping to eventually overnight shipping so that
0:48:22 the customer got it the next day.
0:48:25 We figured out logistics, uh, reverse logistics.
0:48:28 So we’re bringing the shoe to your home.
0:48:33 Um, we heard lots of reasons why people didn’t, uh, want to order shoes
0:48:34 on the internet.
0:48:39 We knew that before, before we invested and we knew that we needed to
0:48:44 bring the, the, the store to your home, have you tried on and then return
0:48:47 to things that you did not, uh, that didn’t work for you.
0:48:48 You did not want it anymore.
0:48:53 And by doing all those things, um, we provided much better customer service.
0:49:01 When we, on any given day, the, the orders that we had, 80% of it was
0:49:07 from repeat customers and we grew the business, some with marketing, but the
0:49:12 majority would, by providing great customer service, having high repeat rates,
0:49:19 having high LTV and having customers basically tell everybody else how great
0:49:23 that business was, how well they were treated, et cetera, et cetera.
0:49:27 I read somewhere, and this was counterintuitive when I, I came across it.
0:49:31 So correct me if I’m wrong, that your best customers returned the most shoes.
0:49:31 Yeah.
0:49:37 That was a very contentious discussion because every, every year, the return
0:49:40 rate would go slightly higher and it was slightly higher.
0:49:41 Well, we kept crying.
0:49:46 So one way to look at it is, well, it’s not really hurting us.
0:49:51 And then the other way is, well, the return rates are high and the most
0:49:58 expensive process in the distribution center was, was managing the returns.
0:50:00 You had the return shipping.
0:50:02 You had to open up the boxes.
0:50:07 You had to look at the product and figure out whether it, it’s ready to go back
0:50:11 on the shelf, it’s damaged, I need to fix it, or it can no longer be sold again.
0:50:15 Because if you put something that cannot be sold away again on the website,
0:50:19 on the website and make it available and that gets ordered, it’s freaking
0:50:20 going to come back and be returned again.
0:50:26 We then did this analysis, and this is the type of analysis I really enjoy doing.
0:50:29 It’s like, let’s take our best customers and let’s take our worst customers
0:50:31 and look at their return rates.
0:50:35 And it turned out that our best customers at the highest LTVs return the most.
0:50:38 And like that, that is crazy.
0:50:39 How is that possible?
0:50:45 Well, it turns out because they were, they understood how to use Zappos.
0:50:47 They just ordered more.
0:50:52 Yes, they returned more, but they kept more too, because they would be willing
0:50:55 to try things if you never returned anything.
0:50:59 That means the only thing you buy are the things that you’re super comfortable with.
0:51:01 You know the size, you know the style.
0:51:07 So we were trying to help people open up the aperture, try new things.
0:51:12 So we did this analysis on the extremes and compared them and realized
0:51:14 our best customers have the highest return rate.
0:51:18 So then you say, well, the board doesn’t like the fact that we have
0:51:22 such expensive return policy and it’s costing us a bunch of money.
0:51:28 So then the solution is not to reduce the return policy and make it less liberal.
0:51:31 You want to keep the return policy as liberal as you can,
0:51:34 but make the cost of processing as low as possible.
0:51:39 And so the first order issue there is exactly going back to first order issue.
0:51:41 The first order issue is not the return rate.
0:51:47 The first issue is making the return process as cheap and efficient as possible.
0:51:49 It’s so counterintuitive, right?
0:51:51 When you think about it, because you’re actually like, no, we’re OK
0:51:54 with people returning shoes as long as they’re buying more.
0:51:58 And then they’re trying to monitor at home, which is exactly what we want.
0:51:59 And sending back what doesn’t work.
0:52:02 You know, I think we changed the whole industry.
0:52:05 And it originally was just a competitive response.
0:52:08 We had a liberal return policy in 30 days.
0:52:10 Other people copy 30 days.
0:52:13 Then it was 90 days out of the people copy 90 days.
0:52:17 And then we made it 365 days and not everybody can copy that.
0:52:21 Some did. But by doing that, it would put a stake in the ground
0:52:26 that we want people to try the Zappos experience and have a great experience.
0:52:31 Why do you think it works for shoes, but doesn’t seem to get as much traction
0:52:33 when it comes to clothing?
0:52:35 No, I think it got a lot of traction for clothing.
0:52:39 It was an understood problem by the time we got into clothing
0:52:42 that you wanted wanted to have for high returns.
0:52:44 You’re going to have high returns.
0:52:47 And therefore you need better processing for clothing.
0:52:51 I think for clothing, for shoes
0:52:55 and for a variety of soft goods, return rates are high
0:52:57 because you need to try it on and try it out.
0:53:03 I’d also point out that shoes, the difference in sizing really does matter.
0:53:08 I mean, you wear a smaller or medium, both could probably fit.
0:53:11 And you may look more buff when you wear a small
0:53:16 and you lose fitting when it’s a medium or whatever size you want to use.
0:53:20 But for shoes, the difference between seven and seven and a half
0:53:23 or 12 and 12 and a half is big difference.
0:53:26 And did you guys do things?
0:53:28 And I was nowhere as opposed to customers, so sorry.
0:53:32 But like, did you do things where it’s like, hey, last time you you’re ordering
0:53:36 in 10.5 or 11, last time you ordered a 10.
0:53:40 We’re just letting you know as an effort to like reduce returns.
0:53:42 Like maybe you hit the wrong button.
0:53:43 We let people know those things.
0:53:47 We also let them know that this brand, you’re used to buying this brand.
0:53:52 Like A6, running shoes and Nike fits a little looser.
0:53:56 So you might want to up the size with this measure of like,
0:54:01 does this fit true to size or does it fit a little looser or a little tighter?
0:54:04 You guys also had like an incredibly unique culture.
0:54:07 What went into the thinking behind them?
0:54:11 The culture of Zappos was very special.
0:54:16 And it was something that we wanted to preserve, partly because
0:54:21 Tony Shea had this experience at Link Exchange, where we didn’t define
0:54:22 the values of the company.
0:54:27 We started hiring people that were conventionally right for the positions
0:54:28 in the job.
0:54:32 And one day he woke up and realized the company that he had founded
0:54:36 and built was no longer the company he wanted to work at.
0:54:39 And he wanted to make sure that the company
0:54:44 that had this special culture that was Zappos kept the culture.
0:54:48 In the early days, it was not very well defined.
0:54:50 What is the culture of Zappos?
0:54:54 Well, you know, that that was
0:54:57 more nebulous in the early days.
0:55:01 And then the company grew and people asked, well, what is the culture?
0:55:03 We don’t have it written down.
0:55:04 How do you know someone’s a culture fit?
0:55:06 Well, does Tony like them?
0:55:07 Does Fred like them?
0:55:09 Does Alfred like them after the interview?
0:55:13 And I don’t like the term the word like.
0:55:16 Like could mean so many different things.
0:55:18 It was just not well defined.
0:55:21 And at some point, Tony decided to just ask the company,
0:55:23 what do you think the values of Zappos are?
0:55:26 What are your personal values?
0:55:28 And what do you not like about Zappos?
0:55:31 And just parsing through that.
0:55:33 We got a lot of responses.
0:55:36 And in his book, Delivering Happiness, he talks about the fact
0:55:39 that we started with 38 different values that, you know,
0:55:43 these are all Zappos values and combined them, shrunk them.
0:55:46 And we ended up with 10 core values.
0:55:50 The problem with 10 is that they’re probably a handful of people
0:55:52 that remember all 10.
0:55:55 Most people remember the first one or two or three of them.
0:55:59 And the first one was to deliver well through service.
0:56:04 It was the, in some sense, the most important core value.
0:56:08 But we meant it in a way not just to deliver well through service
0:56:14 to customers, but also to employees, to our partners,
0:56:16 our business partners and to investors.
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0:56:37 You had a different management system as well.
0:56:40 Talk to me about, was it holistic management?
0:56:41 Holocracy.
0:56:42 Holocracy.
0:56:43 Holocracy, yeah.
0:56:49 So the management philosophy was different,
0:56:51 partly because we wanted to hire people
0:56:56 that could just self-run and self-sustained.
0:56:59 And so there was an element of allowing people
0:57:04 to do what they loved the most and pair them with other people
0:57:08 who love other things and make it sort of homegrown.
0:57:11 I think Tony’s perception of his job
0:57:17 was that his idea of creating a operating system
0:57:21 for the company was to basically build a greenhouse.
0:57:25 It was his analogy and he’s going to try to help
0:57:31 every single person grow as tall and as strong as possible.
0:57:35 And so he very much focused on allowing people
0:57:38 to focus on their strengths and hire other people
0:57:41 for their weaknesses to supplement them.
0:57:43 Is there an ideal growth rate, do you think?
0:57:45 Like, can you grow too fast?
0:57:46 The answer depends.
0:57:51 I think the easy, if you’re growing so fast
0:57:55 and the customer experience starts to degrade,
0:57:57 you’re hurting yourself.
0:58:01 And so yes, you can grow so fast that it’s just a complete mess.
0:58:05 You’re losing customers because you’re not servicing them correctly.
0:58:09 And at Zappos, we were very mindful that whatever customer experience
0:58:12 that we delivered, it was the best customer experience
0:58:15 that we can deliver at that growth rate.
0:58:21 And I think if you ask Tony Hsu at DoorDash or Brian Chesky at Airbnb,
0:58:23 they would probably say the same thing.
0:58:27 It’s like, we want to grow as fast as possible with the constraint
0:58:31 that we want to make sure that there’s a great customer experience.
0:58:33 And maintain the internal culture.
0:58:39 Yeah, and maintaining the internal culture is one way of thinking about it.
0:58:43 And you may have to grow the culture over time.
0:58:45 You have a company, it’s growing.
0:58:48 Do you think the culture that was on day one is going to be the culture
0:58:53 that’s going to work five years, 10 years in?
0:58:54 It’s not a static thing.
0:58:55 It’s not a static thing.
0:58:58 Cultures should not be static.
0:59:01 Every year, you do a strategic plan and a financial plan.
0:59:04 You figure out what your next year’s revenue is going to be.
0:59:07 You’re hiring a plan, you’re marketing a plan.
0:59:09 You have all these plans.
0:59:12 You should also have a plan for culture on how to grow that.
0:59:14 I think the best companies think about that.
0:59:17 Like, how does our company change?
0:59:18 How do we grow up?
0:59:24 How do we become one year older and better and faster at the same time?
0:59:28 How when you’re having so much success scaling,
0:59:32 like going from a million dollars in sales to a billion,
0:59:36 do you not sort of get complacent?
0:59:37 I think that–
0:59:39 Because you were dominating the market at the point in time.
0:59:43 You were the leader clearly in that space.
0:59:44 You’re talking about Zappos?
0:59:46 Yeah, well, in general, either.
0:59:49 In general, I think in for every company,
0:59:54 if you read Jim Collins’ book, Why the Mighty Fall,
0:59:58 it’s the first sign is the hubris of much success.
1:00:04 And at Sequoia, we’re just never complacent.
1:00:07 But you only really work not to be complacent.
1:00:09 We actively work not to be complacent.
1:00:11 At almost every single company, it’s
1:00:14 to make sure that you’re not complacent.
1:00:17 Successful companies just think that way.
1:00:22 At Sequoia, we talk about you’re only as good as your next investment.
1:00:30 At Sequoia, as Zappos, we talked a lot about how easy
1:00:34 it is to ruin a good reputation.
1:00:38 The next order, if that’s not good for a customer,
1:00:43 you’ve built all this effort to build a good reputation
1:00:49 with a customer and one bad order on an important order,
1:00:52 like their wedding day, and you ruin that reputation.
1:00:54 And so I think a lot of companies
1:00:58 have different ways of thinking about that.
1:01:00 And Brian Chesky thinks about what’s the next thing?
1:01:03 What’s the transformation that we’re going to create?
1:01:05 What is the next thing for the customer experience
1:01:07 that’s going to be great?
1:01:11 Tony Shoo thinks about the next product
1:01:15 to power the local economies.
1:01:19 What’s the next set of people that we’re going to help?
1:01:27 And I think if you go back in the history of any business,
1:01:32 you notice that customers are just enormously impatient.
1:01:35 They’re enormously unsatisfied.
1:01:40 Everything that is new and novel becomes standard.
1:01:43 And based on this line about how customers are just
1:01:46 always, always dissatisfied.
1:01:48 I want to kind of go deeper on that.
1:01:50 It’s almost like there’s a natural entropy
1:01:54 to create more sediment inside an organization.
1:01:56 Toby, Luke, and our interview use the word sediment,
1:01:59 like you start building up the bureaucracy.
1:02:02 And entropy being like that’s the natural result
1:02:03 of growth and scale.
1:02:05 And then you actually have to apply a lot of energy
1:02:08 to make sure that it doesn’t happen.
1:02:12 What are the early signs that you see that–
1:02:14 of sediment?
1:02:18 Well, there are a lot of examples of this.
1:02:26 When you– the reason I always take a snapshot of when I go
1:02:27 into a company for the first time,
1:02:30 just see how fast they’re moving.
1:02:35 And then I tell them, today is a great day.
1:02:39 Hopefully, you will move faster than today.
1:02:41 And I hold that as a bar.
1:02:43 And if you don’t have that mentality,
1:02:46 it will start to slow down.
1:02:48 And so what’s the sediment?
1:02:50 Like the process becomes–
1:02:54 instead of making fast, good, fast decisions,
1:02:59 the thing that people value is having a good process that
1:03:02 slows you down to make sure you have the right decision.
1:03:07 You have to make high-velocity decisions at scale.
1:03:08 And I look for that.
1:03:12 Like, are we able to make high-quality, fast decisions
1:03:13 as quickly as possible?
1:03:18 Or do you let the process determine the decision?
1:03:21 How do you judge a decision’s quality?
1:03:25 You can, necessarily, at the moment in time.
1:03:28 You can think about things at the moment in time
1:03:31 as how reasoned, how deep have you
1:03:33 thought about the problem, how much research have you done.
1:03:38 And you can sort of at least say, well, you researched the problem.
1:03:40 You understood it deeply.
1:03:42 And you picked a course.
1:03:43 And hopefully, that’s the right decision.
1:03:47 And in hindsight, you can always look back
1:03:49 and look at whether those decisions are right or wrong.
1:03:53 And I don’t think enough companies look at that enough.
1:03:55 And instead of projecting next year’s revenue
1:03:59 and next year’s strategic plan, part of the strategic plan
1:04:01 should be about looking backwards.
1:04:03 What decisions did you get right?
1:04:05 What decisions did you get wrong?
1:04:07 Why do we need to course-craft?
1:04:09 You guys also had an element of–
1:04:12 I think it was even specific back before it became popular.
1:04:16 But getting 1% better talked to me a little bit about that
1:04:19 and what it meant, practically speaking.
1:04:24 There are two things at Zappos that I push very hard
1:04:25 and popularize.
1:04:29 One was the power of and, because I
1:04:34 found too many people trying to figure out ways to do either or.
1:04:39 And it wasn’t like, OK, we’re going
1:04:43 to ship product more quickly, but the website’s
1:04:45 going to be slower.
1:04:48 Those are– you got to do both.
1:04:54 And if you think about the little things that we do at Zappos,
1:04:58 it was about just compounding 1% every single day.
1:05:05 And I used to write on the whiteboard 1 plus 1% to the 365.
1:05:09 Because if you take a dollar and compound it 1% every single day,
1:05:15 you get this ridiculous result, which is you get $37, $38.
1:05:22 And so when I hear about making a leap forward,
1:05:26 1 to 38 is a big leap.
1:05:29 And it’s on a scale of figuring out what’s a 10x idea.
1:05:31 It’s even bigger than a 10x idea.
1:05:36 I hear founders talk all the time about I only want 10x ideas
1:05:38 because those are the things that move the needle.
1:05:43 And it turns out just simply compounding 1% every single day
1:05:46 moves the needle even more than a 10x idea.
1:05:49 Where do people tend to go astray, right?
1:05:51 So you have a great core product.
1:05:53 And I’m just imagining you start building up a team.
1:05:55 You start getting out of your focus.
1:05:58 Like, where do companies go wrong?
1:06:03 A number of places, if you just look at great companies,
1:06:07 they compound at a very high rate for a long period of time
1:06:09 in their core business.
1:06:11 Google for a long period of time was search.
1:06:14 Amazon for a long period of time was e-commerce.
1:06:19 And I think there’s a difference between Act 2
1:06:20 and category expansion.
1:06:24 So in Amazon, they went from books to music to electronics
1:06:28 to a whole bunch of– they just went category by category.
1:06:30 But it was the same rule, like core business,
1:06:35 which is getting product to the distribution center,
1:06:37 pick pack and ship the products that you want
1:06:40 and shipping it to you.
1:06:40 And it could be books.
1:06:41 It could be music.
1:06:42 It could be electronics.
1:06:43 It could be shoes.
1:06:46 It could be tools.
1:06:47 It could be a hammer.
1:06:49 But that’s one core business.
1:06:52 And I think founders start their company
1:06:55 because they have novel and compelling insights
1:06:58 into the world, and specifically for their company.
1:07:01 And they like the new shiny penny.
1:07:03 I’m not saying that you shouldn’t focus on the new shiny penny
1:07:05 that is adjacent to your business.
1:07:08 I’m just saying that you shouldn’t focus on the new shiny
1:07:12 penny that is way out, away from your business.
1:07:15 Eventually, all companies needed Act 2.
1:07:18 AWS was an Act 2.
1:07:22 That was very different than the e-commerce business.
1:07:28 But even the way that Amazon thought about their web services
1:07:31 business is like, well, we’re very good at building
1:07:34 distribution centers.
1:07:36 Originally, the distribution center that we built
1:07:38 was for physical things.
1:07:41 And here, we’re building a distribution center
1:07:44 for electronic things, for bits.
1:07:48 Like, even the way to think about it was quite interesting.
1:07:51 They didn’t think this was a high margin business.
1:07:53 They thought of it as like, OK, this will be a low margin
1:07:54 business, too.
1:07:56 And we like low margin businesses.
1:07:59 And that was Bezos’ famous quote, right?
1:08:02 Your margin is my opportunity.
1:08:03 I like the idea of Act 2.
1:08:06 For a lot of companies, Act 2 is the founder steps down.
1:08:09 Professional management sort of comes in.
1:08:10 Talk to me the difference between,
1:08:12 as you see it, a founder-led company
1:08:15 and a professionally-led company.
1:08:17 And I use the word professionally loosely,
1:08:18 because founders are professionals.
1:08:21 But I just want people to get the distinction in their head.
1:08:24 Well, there’s a lot being said about the difference
1:08:26 between founder mode and manager mode.
1:08:29 And I would go back to the question,
1:08:31 is shouldn’t it be and?
1:08:33 Shouldn’t you want– don’t you want to be both?
1:08:35 I have a concept of fire and ice.
1:08:39 The best company is at both this huge fire.
1:08:41 They have this entrepreneurial spirit.
1:08:44 And they run hot because the idea is
1:08:46 so compelling and interesting.
1:08:49 But they also have this icy side.
1:08:50 It’s just cold facts.
1:08:51 It’s management.
1:08:54 It’s about getting to the details.
1:08:56 And the best companies have both.
1:09:01 And it pains me to see that you have to choose one or the other.
1:09:04 Because the best companies do have–
1:09:08 they figure out how to make sure that both are
1:09:09 in the company.
1:09:11 What are the different strengths, I guess,
1:09:12 then maybe that’s a better way to think
1:09:16 of this question between founder mode and management mode.
1:09:18 What are the weaknesses and strengths of each?
1:09:20 How do they work symbiotically together?
1:09:26 I would say that there are many different modes of a founder
1:09:29 or a manager.
1:09:32 The beginning days, you’re a creator.
1:09:34 You’re finding zero to one.
1:09:37 You’re creating something that the world has not seen before.
1:09:40 And the mode there is to be a creator.
1:09:41 And instead of calling it a founder,
1:09:44 you’re creating something that the world has never seen.
1:09:47 Once you create that, sometimes it
1:09:51 gets into operator mode.
1:09:53 And many founders are finding operating
1:09:56 and making their creation better.
1:09:58 It’s about understanding the inputs and outputs.
1:10:03 How do I make the system better?
1:10:05 I create something I need to go to market with it.
1:10:11 How do I systematically make the go-to-market happen?
1:10:15 And you’re trying to just operate the thing in a way
1:10:19 that sort of scales the business.
1:10:23 And if many founders are very, very good at the scale,
1:10:25 then you get to a mode where you need to manage.
1:10:28 You’re trying to figure out resources, resource allocation.
1:10:32 And it’s like, should I invest a dollar in the core business
1:10:36 or should I invest that dollar in a new project?
1:10:38 And sort of having a framework on how to make management
1:10:40 decisions like that.
1:10:44 That’s what a lot of companies at scale,
1:10:46 but the CEO needs to figure out.
1:10:48 And then there’s just a level of leadership
1:10:52 around how do you lead the organization
1:10:56 and think about it from an organizational standpoint.
1:11:01 So some of that is manager mode and some of that is founder mode.
1:11:04 But let’s just break it down to what it is
1:11:09 and not talk about one contrast over the other.
1:11:10 I want to go back to something you said earlier
1:11:13 about crucible moments.
1:11:15 What are they and how do you identify them?
1:11:21 Crucible moments is the term we use at Sequoia
1:11:25 for things that are basically very important type one
1:11:27 decisions.
1:11:34 And I’ve had to deal as an operator before Sequoia,
1:11:36 we didn’t call them crucible moments,
1:11:39 but I’ve gone through a fair share of crucible moments.
1:11:45 Link exchange, do we want to sell the company in Microsoft?
1:11:52 Had tell me networks were burning $60 million a quarter.
1:11:54 How do we get through that?
1:11:58 And how do we pivot the company from a consumer business
1:12:00 that wasn’t working into an enterprise business?
1:12:04 These are decisions that change the trajectory of a company.
1:12:12 At Zappos, it was what do we do after 9/11 when sales went to zero?
1:12:14 What do we do during the financial crisis
1:12:16 when credit became very, very difficult
1:12:20 and we were borrowing $60 million.
1:12:22 We had $60 million that we did nothing wrong,
1:12:27 but the banks didn’t have the liquidity anymore.
1:12:28 They’re calling the loan.
1:12:31 And how do you go through these things?
1:12:34 At Airbnb, there have been a number of crucible moments
1:12:36 as well, one of which started very early on.
1:12:38 Brian Chesky talks about a lot, which
1:12:44 was the PR crisis with a guest trashing a host.
1:12:47 And that led to host guarantees.
1:12:48 But there were many of those.
1:12:51 There was a fight to win Europe.
1:12:55 And a competitor called Windu that copied the Airbnb
1:12:57 website pixel by pixel.
1:13:02 Or Jordan Ash’s decision to go after suburbs
1:13:04 and not the cities.
1:13:05 They didn’t give forgo the cities,
1:13:07 but we’re going to start with suburbs first.
1:13:11 Jordan Ash’s decision to focus on merchants and selection
1:13:13 over speed.
1:13:17 And you can have a situation where
1:13:21 you can increase speed delivery by just having a smaller
1:13:26 radius, which then if I only showed you the restaurants that
1:13:29 are close to your home, you’ll get them faster.
1:13:31 But it doesn’t give you the breadth of selection
1:13:33 that you may want.
1:13:36 And these decisions changed the trajectory of the company
1:13:41 and their choices that many of the times,
1:13:42 they’re one-way doors.
1:13:44 Once you make that decision, you can’t go back.
1:13:49 And I think they’re very, very important to get right.
1:13:52 And so at Sequoia, we have a podcast about it,
1:13:54 partly because we want to highlight
1:13:58 how the founders and the management teams puzzle
1:14:01 through these decisions.
1:14:04 And then other characteristics about crucible moments
1:14:08 is every one of them doesn’t look like the other.
1:14:11 So you’re presented with a new problem.
1:14:14 And you’re trying to figure that out for first principles,
1:14:16 how to solve that problem.
1:14:18 That’s the second or third time you’ve
1:14:19 brought up first principles thinking.
1:14:20 What does that mean?
1:14:23 For me, it means start from a blank sheet of paper
1:14:25 and you have a bunch of frameworks
1:14:28 that you have that help you sort of triangulate the answer.
1:14:29 Throw those out.
1:14:33 Maybe you need a new framework for this particular situation.
1:14:35 You’re the king of dental models.
1:14:37 To me, they’re frameworks.
1:14:40 We love them because it instantly
1:14:42 helps us think about the world and narrow down the options.
1:14:46 In some situations, you want to generate more options
1:14:49 and more ideas.
1:14:51 And in those particular situations,
1:14:52 you’re on narrow, you’re thinking.
1:14:53 You want to broaden your thinking.
1:14:58 If we’re on a board together and we get a problem imagined
1:15:00 and it comes up, and how do you think through that
1:15:02 in first principles thinking?
1:15:05 How would you do that in that setting?
1:15:09 I’ll give you an example from Airbnb.
1:15:12 And when the pandemic hit, you can
1:15:14 decide to do a variety of things.
1:15:18 And there’s all these pressures.
1:15:23 There’s the investors who want you to raise enough capital
1:15:28 so that you can go through and weather the storm.
1:15:30 There are employees that want to know
1:15:31 that they’re going to be employed.
1:15:37 There are hosts that want to know that even though guests
1:15:41 can’t travel, that they have a non-refundable cancellation
1:15:42 policy, they’re going to get the money.
1:15:47 You have guests who want to figure out
1:15:50 how to get their money back because they’re not traveling.
1:15:53 You have a business that went from a business that
1:16:00 was growing 20%, 30%, 40% a year to a business that declines
1:16:03 and you lose 80% of your revenue.
1:16:05 There’s all these pressures.
1:16:07 It’s a complete mess.
1:16:09 And the solution that you had yesterday
1:16:12 doesn’t work for today.
1:16:14 Because Airbnb, before the pandemic,
1:16:17 was a lot of cross-border travel.
1:16:21 And today, after the pandemic, there is no cross-border travel.
1:16:23 How do you think about this problem?
1:16:25 Where do you start?
1:16:26 It’s a mess.
1:16:29 Everybody is yelling at you from all these different angles.
1:16:31 And Brian, just one of the most important things
1:16:34 is to stay calm and look at the problem that we have at hand
1:16:38 and figure out what the most important problems to solve
1:16:40 for a second and third.
1:16:43 And he had principles that he had outlined.
1:16:46 We used to have these emergency board meetings.
1:16:48 And it was just always discussing what’s
1:16:50 the emergency this week, this week, this week.
1:16:54 And then he leveled up and decided to say, hey,
1:16:58 we need principles to decide what we’re going to do.
1:17:06 And he decided that we have a once-in-a-generation pandemic,
1:17:09 one in 100 years.
1:17:11 That’s outside the building.
1:17:13 There’s nothing that he can do to fix the pandemic.
1:17:17 But what he can do is to make sure
1:17:21 that Airbnb survives for the next generation.
1:17:23 And he had principles by which he
1:17:27 wanted to make sure that when we get out of this,
1:17:31 we’re seen as someone who created Airbnb
1:17:34 for the next generation and not something
1:17:37 that wasn’t going to survive this generation.
1:17:39 Then he went to work.
1:17:45 And he had these great plans of we’re
1:17:49 going to reduce our burn by doing all the things in this order.
1:17:50 We’re going to cut marketing.
1:17:52 Nobody’s traveling anyway.
1:17:53 Easy decision.
1:17:56 We’re going to cut contractors.
1:17:59 We don’t have enough work for the easy decision.
1:18:01 We’re going to have to raise money.
1:18:03 And we’re going to do it in a way that
1:18:06 doesn’t burden previous investors.
1:18:08 So we’re not going to raise money at a low valuation.
1:18:10 We’re going to raise debt.
1:18:12 Why do we need to raise the money?
1:18:15 To survive this crazy situation where
1:18:19 both the guests and the hosts want their money back.
1:18:23 We have $3 billion of capital on the balance sheet of Airbnb.
1:18:28 But we have $3 billion or $4 billion of customer deposits.
1:18:31 We can give all of that to one side,
1:18:33 and one side will be pissed at us.
1:18:36 Give it also a host, the guests will be pissed.
1:18:38 If we give it to the guests, the hosts will be pissed.
1:18:44 And we won’t have a business when we emerge from the pandemic.
1:18:46 So he goes out and raises $4 billion.
1:18:50 $2 billion of debt, so $2 plus our $3 is $5.
1:18:53 We can cover both sides and then take both sides.
1:18:56 OK, we can pay both sides.
1:19:01 Instead of paying it out, why don’t you just calm down.
1:19:02 You’ll get this money.
1:19:04 You know you can get this money.
1:19:07 And let’s see how the system works itself out.
1:19:12 And so he had to sort of project confidence and imagine
1:19:13 your way out of this thing.
1:19:17 And you imagine a solution which is, OK, well, we’re
1:19:18 in New York right now.
1:19:20 Not a lot of people want to stay in their apartments
1:19:21 in New York.
1:19:22 They’re traveling upstate.
1:19:24 In San Francisco, where I was, not a lot of people
1:19:25 wanted to be in San Francisco.
1:19:27 They went to Napa.
1:19:31 And so slowly but surely, it didn’t happen in March.
1:19:32 It didn’t happen in April.
1:19:36 But in May, we found resilience in the business model
1:19:40 where people started to travel again, just in their own
1:19:42 backyards, in their own country.
1:19:47 And that allowed the company to come out of that.
1:19:51 And the thing that he did last was to lay off employees.
1:19:53 He knew that the employees were going
1:19:57 to have a harder time finding another job during that time,
1:19:58 during the pandemic.
1:20:01 And so you just had these principles
1:20:03 of how he’s going to go solve this problem.
1:20:08 Nobody would have told him to do that in that order.
1:20:10 That’s an incredible example, thank you.
1:20:13 And then on the flip side, this is the craziest thing.
1:20:17 So because Airbnb was the poster child
1:20:20 of the number one IPO possibility for 2020.
1:20:24 And they had seen their revenue go down 80%.
1:20:28 And then they came out of that and then went on
1:20:32 to be the number one IPO of that year in December.
1:20:36 And DoorDash, I had the opposite experience
1:20:40 of DoorDash, which was, boy, they were also
1:20:42 going trying to go public that year.
1:20:45 But instead of being beaten down by the pandemic,
1:20:48 they really accelerated during the pandemic.
1:20:53 And also there, Tony Hsu had a lot of principles
1:20:56 behind what he wanted to get accomplished.
1:20:59 And it was like anything else during the beginning
1:21:02 of the pandemic, it was very, very scary.
1:21:05 Because around the world, there are some places
1:21:09 that were completely shut down, including restaurants.
1:21:12 And if you shut restaurants down because of his experience,
1:21:14 having worked in a restaurant with his mom,
1:21:18 by his mom’s side, washing dishes with his mom,
1:21:20 he knew that restaurants wouldn’t survive.
1:21:22 They had less than 30 days of cash.
1:21:26 And that’s less than 30 days of cash when they actually
1:21:28 are running at full speed.
1:21:32 So now they have less cash.
1:21:38 The restaurant is shut down for a period of time.
1:21:40 People didn’t know whether they can order food
1:21:41 and it would be OK.
1:21:44 As soon as we figured out that the restaurant shouldn’t be
1:21:46 shut down and the restaurants can
1:21:49 remain open for delivery and take out,
1:21:53 he went to full force and making sure
1:21:58 that the business could help merchants bridge the gap.
1:22:02 This is not something that other companies couldn’t have done.
1:22:07 But one of the things I really respect about Tony and the team
1:22:11 is they decided these merchants are going to be hurting
1:22:12 and we need to help them.
1:22:17 And so they proactively went out and uploaded menus
1:22:21 from different merchants on to DoorDash and said,
1:22:23 hey, I know you guys are hurting.
1:22:25 The only thing you can do is delivery.
1:22:26 We’re here to help you.
1:22:29 We’ve uploaded the menu, your menu.
1:22:31 We found your menu, whether it’s on the internet
1:22:33 or we’ve got a copy of your menu, we uploaded it.
1:22:34 It’s ready to go.
1:22:37 Just let us know if we can turn it on for you.
1:22:41 And that allowed DoorDash to grow very, very quickly
1:22:42 during the pandemic.
1:22:48 I thought that DoorDash was a well-run company in 2019.
1:22:52 And it was a process by which they grew very fast.
1:22:55 They probably grew too quickly.
1:22:58 Their unit economics wasn’t great.
1:23:02 They had a few hard fund raising rounds for the C&D.
1:23:04 They fixed the unit economics.
1:23:07 So in 2019, it was a walled oiled machine.
1:23:11 And I saw this walled oiled machine pushed to another level
1:23:15 in 2020 during the pandemic when they really
1:23:21 did help restaurants when they were in a world of hurt.
1:23:25 So the pandemic is a crucible moment for every business.
1:23:27 It was a crucible moment for every business.
1:23:33 What differentiated the founders in Sequoia
1:23:36 from the ones who took advantage of that opportunity
1:23:40 and came out of it stronger and the ones who didn’t?
1:23:45 I think we were–
1:23:48 I hate to say this as a baby tripe,
1:23:51 but going through the pandemic, we all came out stronger.
1:23:52 It was a shared experience.
1:23:56 Sometimes when you go through crucible moments and crises,
1:23:58 you don’t have the shared experience.
1:24:04 But to answer your question more succinctly,
1:24:11 I think there are people who knew that the crisis was
1:24:12 an opportunity.
1:24:16 And then there are those who just thought of it as a crisis.
1:24:21 And I think it was Andy Grove that says that good companies
1:24:23 are– get better.
1:24:25 They’re defined by a crisis.
1:24:29 Whereas there are a lot of companies
1:24:31 that are destroyed by a crisis.
1:24:37 And many great companies were defined
1:24:40 and they changed the way they did things in a way that you–
1:24:43 they found solutions that you would not have imagined
1:24:46 when the crisis didn’t happen.
1:24:50 And I think the founders that are–
1:24:53 they realize they’re in a crucible moment.
1:24:56 They realize they need to do something differently.
1:24:59 They stay calm.
1:25:00 They stop.
1:25:01 They look around.
1:25:04 And they figure out– they look around 360 degrees
1:25:07 and say, that’s the direction I’m going.
1:25:10 Even though the whole world is revolving around them
1:25:12 and it’s a complete whirlwind.
1:25:16 And they imagine why they should go into that direction.
1:25:20 And in most cases, they had to find a different solution,
1:25:24 a different product, a different way of operating,
1:25:27 and then scale that into that direction.
1:25:32 Those are the ones that come out really, really successful.
1:25:37 In Airbnb’s case, they had to change cross-border travel
1:25:38 to local travel.
1:25:40 They changed to long-term stays.
1:25:44 They changed to having experiences.
1:25:49 In DoorDash’s case, they simply had to sort of do things
1:25:51 that they’ve never done before.
1:25:52 There wasn’t a new–
1:25:54 it wasn’t a product change.
1:25:56 But they had to imagine a different solution.
1:25:59 But they’re not going to wait until merchants call them
1:26:02 and say, negotiate a deal.
1:26:05 They said, look, we’ve uploaded your menus
1:26:08 onto the website, into our app.
1:26:09 These are our standard terms.
1:26:12 Do you want to go or not?
1:26:14 That wasn’t a product that they had designed
1:26:15 before the pandemic.
1:26:19 Often, you need to find a completely different solution to–
1:26:22 I mean, they seem so simple after the fact.
1:26:24 But at that moment, it is completely
1:26:27 unclear that that was the right decision.
1:26:29 But that’s why you need to stay calm.
1:26:32 That’s why you need to look around.
1:26:34 You need to stop, look around, and find the right direction
1:26:37 that you want to go in, and then accelerate.
1:26:41 I think that’s really an interesting approach, right?
1:26:44 Where you sort of stop, you don’t panic,
1:26:47 you evaluate what’s going on as rationally as you can
1:26:51 in the moment, despite everybody wanting things from you
1:26:53 and all this pressure that you probably have from investors,
1:26:56 but you also put on yourself to take care of your employees,
1:26:59 to take care of your customers, to take care of your family,
1:27:01 and everybody’s worried to put the same thing.
1:27:03 So you’re operating in a very amplified environment
1:27:06 to begin with.
1:27:08 And the best founders are doing this day to day.
1:27:11 But here, the time frames are much, much shorter
1:27:12 and much, much more compressed.
1:27:16 And people’s voices are much louder.
1:27:22 Just recently, Tony said that it’s about many good decisions
1:27:23 about sequencing.
1:27:27 We all know what we need to do, but sequencing it, right,
1:27:30 is actually what matters.
1:27:33 And the sequence of how you do something often
1:27:37 determines whether you’re remembered or not remembered.
1:27:41 In the example that we talked about for Airbnb,
1:27:46 there’s a sequence of what is the values that I have
1:27:51 for the company, and let’s go through the sequence that most
1:27:52 matches the values.
1:27:58 So Brian wanted to take care of the employees the most.
1:28:01 And so the layoff was the last thing that he did.
1:28:04 He tried to do everything else before the layoff.
1:28:09 In Tony’s case, the sequence was to make sure–
1:28:11 because he had a heart for merchants–
1:28:14 the sequence was to take care of the merchants.
1:28:21 So it’s just when you have these well-understood values,
1:28:24 it makes the sequencing a lot easier.
1:28:25 And often, people forget.
1:28:28 They write down their values for a good reason.
1:28:31 Because when you don’t have a playbook anymore,
1:28:36 all you have left is the essence of what the company is,
1:28:37 which is the values of the company.
1:28:39 Often, that’s the essence of the founder,
1:28:42 the values of that founder, and how they want to operate.
1:28:45 But you forget that because it’s noisy.
1:28:49 Lots of people, lots of different parties
1:28:52 wanting your time and your attention.
1:28:57 Work from home has become a somewhat contentious topic.
1:29:00 But I really want to hear your thoughts on the pros and cons
1:29:02 and how you see it.
1:29:08 Pros and cons.
1:29:12 I think it’s very, very hard to build an early-stage company
1:29:13 remote.
1:29:16 And the reason I say that is, unless you’ve
1:29:20 worked with each other before, I view there
1:29:24 to be a well of trust that is created when you work together.
1:29:29 And the reason why people who have worked together
1:29:33 for a long period of time can anticipate each other’s
1:29:35 movements and what they’re going to do next
1:29:37 is because they’ve been around each other for a long time.
1:29:42 And as you know, most of our communication is not verbal.
1:29:46 There’s body language and how you said, how you react.
1:29:48 There’s a lot of communications that we
1:29:53 miss through work from home.
1:29:56 And you just can’t read it as well on the screen
1:29:57 versus in person.
1:29:59 Because there’s only your–
1:30:01 on screen and in Zoom, you only have your head.
1:30:05 There’s the rest of your body that you don’t see.
1:30:10 And so I think it’s quite important for early-stage teams
1:30:12 to work together.
1:30:13 I mean, they don’t have an office.
1:30:16 They find the coffee shop to work together at.
1:30:17 Why do you do that?
1:30:18 You can all work from home.
1:30:20 But why do you get together, a coffee shop to work together?
1:30:22 It’s noisy.
1:30:24 There are a lot of people around.
1:30:26 There’s a reason why you want to do some of these things.
1:30:29 And I think, does it mean that every single day I’m
1:30:31 more productive in the office?
1:30:33 No, there are days when I’m writing a memo.
1:30:36 It’s probably better if I sit in the office
1:30:40 or I’m at home and just cranking.
1:30:42 It’s also very hard to build culture
1:30:46 if you’re all separate and apart from each other.
1:30:47 There’s no ritual.
1:30:49 Culture is the values.
1:30:51 But how do you express those values?
1:30:54 They’re your behaviors.
1:30:55 They’re the rituals.
1:30:58 They’re the narratives that we tell each other.
1:31:03 And those things are just a lot harder to do over Zoom.
1:31:08 So I think all companies should go back to being
1:31:11 in the office a certain number of days a week.
1:31:13 It doesn’t have to be five.
1:31:16 I think that we can’t put the genie back in the bottle
1:31:18 on remote work.
1:31:21 But at the same time, we thought the world
1:31:24 was going to be different when we were all online.
1:31:28 And it turns out we actually enjoy seeing each other in person.
1:31:30 We enjoy having dinner together.
1:31:33 I don’t enjoy having dinner over Zoom with someone.
1:31:37 I enjoy it when we’re breaking bread right next to each other.
1:31:42 Do you believe that you can please both sides?
1:31:44 And that’s sort of the hybrid model
1:31:46 where people are going to work at the office
1:31:47 two or three days a week.
1:31:50 And then you can work from home two or three days a week.
1:31:52 Do you believe in that being effective?
1:31:55 Or do you believe you have to pick a predominant one
1:31:57 and focus?
1:31:59 Like, because you’re operational back-end,
1:32:00 your company culture, your cadence,
1:32:02 they’re all going to be determined by what you pick.
1:32:04 And if you pick in the middle, you’re
1:32:06 probably making trade-offs on both sides
1:32:08 and not getting maybe the advantages
1:32:11 because you don’t want to make trade-offs.
1:32:16 I think it’s best if you take a stance, take a side.
1:32:19 Hybrid– I would cripple with the fact
1:32:21 that hybrid doesn’t work at all.
1:32:23 I think you can be in person.
1:32:24 You can be remote.
1:32:25 You can be hybrid.
1:32:27 You just need the systems around it
1:32:32 to make up for the fact that you’re
1:32:34 going to operate in this way.
1:32:37 Every multinational corporation,
1:32:38 when they have multiple locations,
1:32:41 was doing some form of hybrid.
1:32:43 You have some people who are in this office.
1:32:44 Some people in this office, they’re
1:32:50 connected through telecommunications.
1:32:52 And some people are on the road.
1:32:56 Any company that gets a certain scale,
1:32:58 the salespeople in the field, they’re not actually
1:32:59 at headquarters.
1:33:03 And you are having in all hands those people call in.
1:33:06 But when you have an important all hands,
1:33:07 you call everybody in.
1:33:08 You have an important offsite.
1:33:11 You call everybody in.
1:33:13 And there are just certain things
1:33:14 that should be done in person.
1:33:17 There’s certain things that are OK to do over Zoom,
1:33:21 over telecommunications, over email.
1:33:25 I think that there is a different medium
1:33:29 to do different jobs, depending on the objective is.
1:33:32 And you should understand what the drawbacks
1:33:35 and the advantages of each one.
1:33:39 At Sequoia, we take a lot of first meetings over Zoom.
1:33:43 And during the pandemic, when we were only
1:33:46 doing meetings over Zoom, you just
1:33:50 never got the right texture for the company, the cadence
1:33:52 of how the company operated.
1:33:55 And yeah, we might still take first meetings over Zoom,
1:33:59 but we’re going to meet the team at some point in person.
1:34:02 And did you analyze your investing during that period
1:34:06 where you’re meeting more over Zoom versus more in person
1:34:08 when it comes as approaching the investment decision?
1:34:11 Yeah, we can make those assessments.
1:34:14 But the hard part is the environment is also different.
1:34:17 So 2021 valuations were nutty.
1:34:20 Was it the issue of making those investment decisions
1:34:21 over Zoom?
1:34:24 Or was it the environments that drove valuations higher?
1:34:26 So therefore, the returns are going
1:34:29 to be more difficult, more challenged when–
1:34:30 valuations are higher.
1:34:33 Why do you play when the valuations are higher?
1:34:38 When sort of like the game is loaded against you in a way?
1:34:39 Why choose to keep playing?
1:34:42 Why not back away and then come back when
1:34:43 the odds are in your favor?
1:34:47 Well, historically, valuations have gone up.
1:34:51 But if they keep going up, then how does that work?
1:34:55 I think our LPs pay us to make money
1:34:57 during good times and bad times.
1:34:59 And here’s the thing that is most interesting
1:35:01 to me.
1:35:05 You can decide to shut down, but then you
1:35:09 won’t get the texture of those companies being developed.
1:35:13 And sometimes, you got to keep meeting companies, right?
1:35:14 So you don’t shut things down.
1:35:20 You can decide to invest fewer dollars when things are hot.
1:35:23 And you could decide to invest more dollars
1:35:25 when things are cold.
1:35:28 But the market is also smart.
1:35:30 So when things are hot, it’s usually
1:35:33 because something new is happening.
1:35:34 And things are cold.
1:35:38 Maybe it’s just not a good time to invest, too.
1:35:42 If you could identify when it’s irrationally exuberant,
1:35:45 yes, you’d decide not to invest in the irrationally
1:35:47 exuberant situations.
1:35:50 But in 1999, which was one of the–
1:35:53 if you go back in history and look
1:35:57 at megatrends in investing, you know,
1:35:59 I’m 52 years old right now.
1:36:02 When I was in junior high school,
1:36:04 one of the things I did as a business
1:36:11 was to build PCs, clone PCs, because the IBM PCXTAT,
1:36:14 they were really expensive.
1:36:20 And so that was one megatrend, which is the PC revolution.
1:36:23 Then there was the internet revolution.
1:36:25 And then more recently, the cloud revolution,
1:36:28 the mobile revolution, right now we’re
1:36:29 in the AI revolution.
1:36:32 And the internet revolution, when I first
1:36:35 started working professionally after college,
1:36:36 was the Ed Lake exchange.
1:36:40 And then we started investing in 1999.
1:36:42 That’s when venture frogs started.
1:36:44 And if you decided not to invest in that time,
1:36:47 you would have missed out on Google, Salesforce, PayPal,
1:36:50 Zappos, OpenTable.
1:36:51 There are a lot of great companies
1:36:53 that were still founded during that time.
1:36:57 And paying market prices for those investments
1:37:00 would have been just fine.
1:37:00 And you can–
1:37:02 Would have been better than just fine.
1:37:05 Would have been better than just fine.
1:37:07 But you could wait until 2001.
1:37:09 And maybe you could invest in lower valuations.
1:37:13 But often, in the public markets,
1:37:16 you can wait because those companies
1:37:20 are available when the multiples are low.
1:37:23 And private companies, just because the valuations have
1:37:26 come down, doesn’t mean the company that you want to invest
1:37:28 in is looking to raise around.
1:37:33 Maybe in 1999, you wanted to invest in Google.
1:37:35 In 2001, they happened to be public.
1:37:37 You could invest in Google.
1:37:39 But if they were private, maybe you wouldn’t be able to.
1:37:39 Yeah.
1:37:43 John Bragg said this thing in my recent interview with him
1:37:46 that I had never fully appreciated, I don’t think,
1:37:49 which was he had a reputation for overpaying
1:37:51 for all of the land he was acquiring.
1:37:53 And I said, why do you do that?
1:37:55 He’s like, well, if we’re easy to deal with,
1:37:56 people want to deal with us.
1:37:59 And he’s like, these assets only go for sale once.
1:38:02 And he’s like, so maybe it takes 12 years instead of 10
1:38:03 to get our payback.
1:38:05 But it doesn’t really matter because there’s no opportunity
1:38:08 10 years from now to buy it again.
1:38:11 Yeah, I think that’s an example for us.
1:38:15 It’s the same as true in investing in private companies.
1:38:18 It’s still much better to pick the right company.
1:38:23 And slightly overpay than to invest in something
1:38:25 that is cheap.
1:38:29 You brought up AI as the next revolution.
1:38:30 Where are we going with AI?
1:38:31 Where do you see that?
1:38:34 And obviously, the longer we go out on the horizon,
1:38:35 the harder it is to predict.
1:38:37 So maybe let’s start with, what do you
1:38:41 see as the next 12 months in AI?
1:38:43 And where do you think we–
1:38:47 how do you envision 12 months to five years?
1:38:50 It’s funny because I think in the history of technology
1:38:54 changes, and then Bill Gates said this, it’s easy.
1:38:58 We almost always overestimate what
1:39:00 things are going to happen in a year.
1:39:03 And we underestimate what’s happened in 10 years.
1:39:06 Yes, it’s harder to imagine 10 years out.
1:39:10 But in the business I’m in at Sequoia,
1:39:14 we are paid to make investments and to hold on long term.
1:39:18 And we do have to sort of imagine 10 years out.
1:39:21 In the next year, these foundation models
1:39:26 are getting so good that you can see certain things being
1:39:29 automated that we used to do that we’re not
1:39:30 going to do as much.
1:39:33 But I think the next step after that
1:39:35 is if you think about–
1:39:37 lots of people talk about customer service
1:39:41 and how we can automate some of the customer service emails
1:39:43 or calls and things like that.
1:39:45 OK, let’s say we do that.
1:39:46 What’s next?
1:39:49 Well, then you should reimagine the customer experience.
1:39:52 And so AI will help us automate some of these things,
1:39:55 and there’s the massive cost savings.
1:39:59 But AI should also allow us to reinvent the customer experience.
1:40:02 And that’s why we’re very excited about a company like Sierra.
1:40:05 They’re not just going to help you automate customer service
1:40:06 tickets.
1:40:08 They’re going to help you reimagine what customer service looks
1:40:09 like.
1:40:13 Just similarly to what happened in the internet,
1:40:15 you could– in the internet happened,
1:40:18 we could book things–
1:40:21 we could book travel on the internet.
1:40:23 We didn’t have to call it a travel agent.
1:40:24 It changed the experience.
1:40:25 We could search.
1:40:26 That changed the experience.
1:40:28 It broadened.
1:40:31 I had to imagine where I wanted to go and call someone
1:40:33 to get me a techie or to get–
1:40:34 now I can search.
1:40:37 So my imagination could be broadened.
1:40:43 And that just changed my experience of travel.
1:40:47 And the airlines didn’t allow you to change tickets
1:40:51 once you bought them, because that was in some back-end system.
1:40:53 They didn’t want to open up that system.
1:40:57 Now we can change flights on the website.
1:40:58 Well, the same will be true with AI.
1:41:01 Like, start with automation, start with new experiences,
1:41:04 and the experience will completely change over time.
1:41:06 And it always takes a little longer.
1:41:09 I mean, I remember we talked about autonomous vehicles
1:41:12 probably 10 years ago, and today we
1:41:16 have autonomous vehicles working in a few cities with Waymo.
1:41:20 People imagine that that would be solved very, very quickly.
1:41:22 But where are we going?
1:41:25 I think we’re going in a world where
1:41:28 many of the problems that we have in the past
1:41:30 will get solved through automation.
1:41:32 Many of the things that–
1:41:35 many new problems will get solved through AI,
1:41:38 because they’re going to be as good as we are
1:41:41 and doing analysis and doing– being creative and things
1:41:41 like that.
1:41:46 And so I think it will be a very, very productive mega shrub.
1:41:50 One way to explore this topic is to ask you what you’re
1:41:52 looking to avoid with AI investments.
1:41:55 And I’m thinking maybe something that comes to my mind
1:41:58 is like it’s a wrapper over chat GPT or something.
1:42:00 What are you trying to avoid when it comes
1:42:02 to making AI investments?
1:42:05 So the wrapper is a good example of something.
1:42:09 It just is just a different user interface
1:42:11 on top of a foundation model.
1:42:16 But I think we’re trying to make sure that something persists.
1:42:17 And what if it persists?
1:42:19 It has its unique distribution.
1:42:22 It’s embedded into your workflow.
1:42:25 It has true ROI for a long period of time.
1:42:29 And it changes the experience.
1:42:32 Other things I’d say we try to avoid
1:42:39 is things that are roadkill along the way of a company
1:42:43 like OpenAI or Google or Amazon or Meta.
1:42:47 So small refinements into what the model doesn’t do well today.
1:42:50 That’s just going to be roadkill along the way.
1:42:57 And then I think we’re trying to avoid things that are–
1:43:01 that sound good, but they’re not good businesses.
1:43:03 Back to 1999, there were a lot of things
1:43:07 that had lots of usage that not had the revenue.
1:43:09 And so right now, there’s a different example
1:43:12 where there’s a lot of test revenue.
1:43:15 But the churn is very high because people don’t stick.
1:43:18 So there are a lot of things where
1:43:20 you see very, very fast adoption,
1:43:23 but the churn rate is very, very poor.
1:43:25 So we’re trying to avoid those kind of companies.
1:43:27 Do you think Google and Microsoft,
1:43:31 like how do you think you compete with them
1:43:33 on a foundational model basis?
1:43:36 Like, A, they can scale into enterprise overnight.
1:43:39 B, they can spend $100 billion on GPEs.
1:43:41 How do you think about that?
1:43:42 Are we going to end up in a world
1:43:45 where there’s only a few foundational models
1:43:47 and we’re all going to plug into them?
1:43:49 To be honest, I don’t know.
1:43:54 But I’ll tell you this, in the history of technology
1:43:56 investing that I’ve been involved with,
1:43:59 if you’re afraid of the incumbents,
1:44:01 you should just punch out.
1:44:05 But in 1999, you could have been afraid for Microsoft
1:44:08 because they have lots of money and lots of servers.
1:44:10 And yet they didn’t win search.
1:44:12 Someone else won’t search.
1:44:17 Microsoft won the browser war for a hot socket.
1:44:21 It was Netscape against Internet Explorer.
1:44:24 I don’t know many people who use Internet Explorer today.
1:44:26 Most people I know use Chrome.
1:44:31 So this is not a static situation.
1:44:34 I think you just have to sort of have an open mind on why
1:44:36 you will win.
1:44:40 And often, the reason why large companies don’t win
1:44:43 is because they have their own internal issues
1:44:44 that slow them down.
1:44:46 So Microsoft, during the internet,
1:44:51 it was the antitrust situation.
1:44:52 And that slowed them down.
1:44:58 They could no longer bundle IE into the operating system.
1:45:01 And so they had to break all those things apart.
1:45:04 Google has its own regulatory challenges,
1:45:05 and so does Microsoft.
1:45:08 So I don’t presume that they’re all just going to win
1:45:09 because they have a lot more money
1:45:14 and they have more capital and they have a lot more people.
1:45:16 And besides, if you thought that,
1:45:18 then I would be out of a job.
1:45:21 So how important do you see what Facebook’s doing,
1:45:24 then, where they’re spending $50 to $100 billion,
1:45:26 but they’re making it open source?
1:45:29 I think open source is a very, very important aspect
1:45:31 of what has happened in technology.
1:45:36 And you have these religious fights between closed and open,
1:45:39 and you have religious fights between Apple and Microsoft
1:45:41 or Apple and IBM.
1:45:46 Let’s go back to ant.
1:45:49 The world is built on ant.
1:45:52 And open source, in the internet days,
1:45:54 there are lots of things that were built on open source.
1:45:57 And some of it was closed source and some is open source.
1:46:03 And I think the same will be true with AI.
1:46:04 There are going to be things where you just
1:46:08 want to host it on a closed source model
1:46:10 because you know it has the breath of functionality.
1:46:13 And there are things where you can only make it work
1:46:17 if you use your specific data, train it very specifically
1:46:22 for you, and you’re going to use open source models for that.
1:46:28 And just like Google built a great business that
1:46:34 is pretty close source on open source software like Lytx,
1:46:37 I think the world of AI is going to be ant as well.
1:46:39 There’ll be closed source and there’ll be open source.
1:46:44 I want you to imagine you’re in charge of, let’s say, Canada
1:46:47 and the US and maybe the UK.
1:46:51 And I tell you that we are optimizing
1:46:54 to be the best in the world at AI.
1:46:56 What are the policies that you think about?
1:46:58 How do you approach this problem?
1:47:03 And how do you encourage us to be the world leaders?
1:47:10 I’m maybe overly optimistic about human nature.
1:47:18 And so I believe that you want to have as little regulation
1:47:21 as possible in the early days, let people experiment,
1:47:22 let people try things.
1:47:25 And is it all going to be good?
1:47:26 No.
1:47:29 But if we had over-regulated the internet,
1:47:31 it would not have grown to the scale that it is today.
1:47:33 And do we have problems on the internet?
1:47:35 Absolutely.
1:47:38 And so I believe in sort of having regulation that
1:47:43 is more open than not and then slowly close off things
1:47:47 that you know is not good or the behavior is not good.
1:47:49 Regulators often worry about the fact
1:47:52 that if you wait too long, you won’t be able to regulate it.
1:47:55 I don’t know if I believe that.
1:48:01 And then on the flip side is it’s always been–
1:48:04 I don’t know of a time that has ever
1:48:06 worked to fight against technology
1:48:09 and to over-regulate technology.
1:48:11 You could have over-regulated the fact that the Scribes were
1:48:14 going to no longer have jobs because we came with the printing
1:48:18 class and go all the way back in time like that or figuring out
1:48:23 how to have a plow so that you need fewer people to sow seeds
1:48:27 because the plow could do the work of three or four people
1:48:28 all the way up to a tractor.
1:48:32 How have we done trying to regulate or over-regulate
1:48:37 or control things that sort of make human beings much more
1:48:37 productive?
1:48:39 That’s what we’re talking about with technology
1:48:41 and that’s what we’re talking about with AI.
1:48:49 And then if you want to start applying regulation,
1:48:52 there’s maybe a slightly different framework
1:48:55 that I would use, which is you want–
1:48:58 as an example, with the combustion engine,
1:49:00 nobody regulated the engine.
1:49:04 We regulated what engines can go on the streets,
1:49:06 what can go into a plane.
1:49:09 You regulated how it was applied.
1:49:15 But in a lab, and people were sort of doing research
1:49:18 and trying to make the combustion engine even more powerful,
1:49:20 being more fuel efficient.
1:49:22 You don’t regulate that.
1:49:26 You regulate it when it gets in the hands of a consumer.
1:49:29 So that was like removing barriers almost.
1:49:31 But what about amplifying?
1:49:32 What about the push?
1:49:34 How do we encourage more?
1:49:38 How would you embrace this as a country?
1:49:41 The market is pretty good at pushing.
1:49:45 When they see opportunity, more and more capital goes into it.
1:49:48 More people go into school to–
1:49:52 in almost every single technology revolution
1:49:55 I’ve been part of, there are too few people
1:49:58 who understand that technology.
1:50:04 So when it was the PC industry, there are some people
1:50:05 who understand Ray friends.
1:50:07 Very few people understand PCs.
1:50:08 More and more people–
1:50:10 more and more investment went into PCs.
1:50:11 More and more people bought PCs.
1:50:13 More people started using PCs.
1:50:16 More people started building applications for PCs.
1:50:19 And so over time, there was just a lot more people
1:50:21 and a lot more investment in it.
1:50:23 People went to school to sort of write software specifically
1:50:26 for the PC as opposed to the mainframe.
1:50:27 That happened the internet.
1:50:30 Most people didn’t know how to build a website.
1:50:34 More and more people learned how to program in HTML and Python
1:50:40 and wrote and Linux and how to use Linux to build today.
1:50:43 And that happened with Cloud and mobile.
1:50:45 So today, we have probably too few people
1:50:48 who really, really understand the technology
1:50:50 and its application.
1:50:52 But you have so many people go into today
1:50:57 because they see the future is going to be powered by AI.
1:50:58 And so wait a year or two.
1:51:01 I bet you there’s plenty of push today.
1:51:06 That’s why the valuations are high for AI companies.
1:51:07 And wait a year or two.
1:51:10 There’s going to be a lot of things that are going to be built.
1:51:15 And in fact, the hot take is that many things will be overbuilt.
1:51:21 So maybe we’re building too many GPUs for a year or two years out.
1:51:24 Maybe there are too many data centers that have GPUs a year
1:51:25 or two years out.
1:51:27 And maybe those things will get cheap.
1:51:30 And when they get cheap, we’ll find new applications
1:51:31 when it gets really, really cheap.
1:51:33 That would be sort of the history of market.
1:51:35 Actually, it’s interesting that you brought up
1:51:36 don’t fight technology.
1:51:39 There’s a saying in investing, don’t fight the Fed.
1:51:42 It’s sort of the same sort of–
1:51:45 If Fed is way more powerful in many respects–
1:51:46 Then technology?
1:51:48 No.
1:51:53 Well, I think the Fed can constrain or can loosen money
1:51:56 supply in a very dramatic way.
1:52:00 So it applies throughout the whole economy,
1:52:03 as opposed to just about technology.
1:52:05 And historically, businesses have cycles.
1:52:08 We tend to overbuild when we’re optimistic.
1:52:09 And then you go through that phase,
1:52:13 you just talked about, out of the large technology companies
1:52:17 today, who do you think is best positioned?
1:52:18 That’s hard.
1:52:22 Well, if you want to use don’t fight the tape,
1:52:26 when I started in my technology career,
1:52:28 Microsoft was the largest technology company.
1:52:32 And today, they’re the largest company.
1:52:35 And so they seem to have figured out,
1:52:38 through their ups and downs, how to stay relevant
1:52:39 and stay on top.
1:52:46 I think Google’s having some challenges
1:52:50 with their own regulatory issues.
1:52:55 And Apple don’t ever count Apple out.
1:52:59 Because back to, they weren’t the first to come up with the PC.
1:53:03 They weren’t first to come up with the mobile phone.
1:53:05 There’s so many other mobile phones.
1:53:06 They just wait until they can create
1:53:08 a great customer experience.
1:53:11 And then when they do, they pounce.
1:53:16 They weren’t the first to come up with an MP3 player.
1:53:16 More phone.
1:53:17 More phone.
1:53:19 How do you think of NVIDIA?
1:53:32 I think NVIDIA is a very great company for a variety of reasons.
1:53:38 One of which is, it went from a graphics processing company
1:53:44 to being the way we power all of AI.
1:53:48 And they fought for so long about this idea
1:53:53 of parallel processing, where the CPU worked a certain way.
1:53:55 The GPU worked a different way.
1:53:58 And the GPU is now shown to be more powerful.
1:54:03 After we sort of got to the edge of Moore’s law,
1:54:05 the GPU is winning out.
1:54:09 Because they can process things much more efficiently.
1:54:13 But they worry about, they’ve only had one leader
1:54:14 in their whole cycle.
1:54:17 I worry about what happens when Jensen decides
1:54:23 not to be at the head of NVIDIA.
1:54:25 Yeah, that is the question, I guess, right?
1:54:27 I think that’s the question a lot of people have.
1:54:30 Jensen’s a remarkable sort of CEO.
1:54:32 Jensen’s a remarkable CEO.
1:54:35 And he does things very differently than anybody else.
1:54:36 We had him speak at our base camp,
1:54:39 which is our annual retreat for our founders.
1:54:42 And he just came out with so many great stories
1:54:44 about NVIDIA, about his personal life,
1:54:47 but also about his management style that is so different.
1:54:49 I remember being there, and that was awesome.
1:54:52 Yeah.
1:54:54 Sometimes you’ve said in the past
1:54:56 that sometimes the path to greater efficiency
1:54:58 is doing things sequentially.
1:55:00 And sometimes it’s doing them in parallel.
1:55:01 Can you explain that?
1:55:05 I think most people are trained to do things in serial.
1:55:07 They take a problem, they break it down into pieces,
1:55:09 and they do one piece at a time.
1:55:12 So step number one, solve the problem number one,
1:55:13 solve problem number two.
1:55:17 Because we need the solutions of problem number one
1:55:19 to feed into problem number two.
1:55:22 And they eventually go down the path.
1:55:26 And a lot of– if you’re an individual contributor,
1:55:29 you just write code, you just keep writing the code,
1:55:31 and you finish the code, and you submit it.
1:55:33 But if you’re managing a team, you
1:55:37 need to break down this piece of software into components
1:55:39 so that you can give it to your team members.
1:55:43 You now have all 10 of them working on it.
1:55:47 As opposed to you write it yourself,
1:55:51 and even if you’re a really good software writer,
1:55:54 you literally have to be a 10x engineer on top
1:55:55 of your 10x engineer.
1:55:57 So you have to be a 100x engineer to do it
1:56:02 in the same time frame that 10x engineers can do it.
1:56:04 And sometimes it’s just more efficient
1:56:08 to just break the problem down so that you can put them
1:56:10 in parallel and then stick them all together.
1:56:14 How do you think about companies and time span,
1:56:18 and specifically maybe with an angle towards positioning
1:56:22 yourself to rapidly adopt to whatever the future brings,
1:56:25 versus trying to predict the future and running ahead of it?
1:56:29 I think the consensus would tell you
1:56:32 that it’s very, very hard to predict the future.
1:56:38 And your ability to predict the future is uneven,
1:56:42 because in the world that you know,
1:56:46 you may be able to be very good at predicting the future.
1:56:49 But the world is not stationary, and the world changes.
1:56:52 And in this new world, trying to predict the future
1:56:55 when you don’t have many facts or many patterns
1:56:58 that you can go against, it’s much better
1:57:02 to have a machine that goes one to pounce
1:57:05 than to try to predict what’s going to happen.
1:57:07 Go deeper on that a machine.
1:57:09 Well, your company is in some sense a machine,
1:57:11 and so you’re trying to figure out
1:57:15 when you should pounce on an opportunity.
1:57:17 You’re building, you’re building, you’re building,
1:57:23 and you decide, I’m going to take this path now,
1:57:25 and you’re going to make your company
1:57:28 and go in this direction, because you
1:57:33 see the opportunity in this path.
1:57:36 Maybe make the example more concrete.
1:57:38 Perhaps, as an example, DoorDash
1:57:43 started with food delivery, but specifically restaurant
1:57:46 delivery, and they waited until they figured out
1:57:50 an advantage that they can have in grocery.
1:57:54 But the mechanism by which to deliver restaurant food
1:57:58 and grocery food were pretty much the same.
1:58:01 And figuring out when to enter the grocery market
1:58:05 had a lot to do whether the company was ready,
1:58:08 the customers were ready, the market was ready,
1:58:10 the groceries were ready.
1:58:16 And you can predict that customers want this
1:58:18 before they want it, or you can just
1:58:22 wait until you see lots of customers bang on the door,
1:58:28 writing into DoorDash, hey, can you also get my groceries?
1:58:29 And so it’s a matter of what, do you
1:58:32 want to be pushing the customer to do what you want,
1:58:37 or do you want the customer to pull you in the direction
1:58:39 that they want to go?
1:58:40 Is the biggest risk there that you
1:58:43 try to tackle two problems at once?
1:58:46 I’m assuming they knew they wanted to get into groceries.
1:58:48 So part of the risk at the start is
1:58:50 if we’re focusing on restaurants and groceries,
1:58:53 all the time we’re spending on one of those two things,
1:58:54 and not all of it, but a lot of it’s
1:58:56 coming at the expense of the other.
1:58:59 Or do you see that as no, it’s not?
1:59:01 It’s a very sharp insight that you have.
1:59:05 I think the one thing that you’ll find
1:59:10 is that there are lots of examples that I could use
1:59:12 to support your conclusion there.
1:59:16 Because before DoorDash happened,
1:59:20 there were plenty of other service solutions.
1:59:24 And most notably, there was Grubhub.
1:59:27 That was just the website.
1:59:30 And then they passed the order to the restaurants
1:59:32 and the restaurant delivered.
1:59:36 And Tony’s observation was that’s
1:59:39 not deep enough of a solution.
1:59:41 And so why was it not deep enough?
1:59:43 Well, there are a lot of restaurants out there
1:59:46 that don’t have their own delivery staff.
1:59:48 And why don’t we just–
1:59:50 You’re creating problems for them in a way.
1:59:51 Exactly.
1:59:56 And so the only restaurants that would be on Grubhub’s website
2:00:00 were all the companies that already had delivery
2:00:01 staff available.
2:00:04 So what DoorDash did was to expand the market.
2:00:05 And by expanding the market, they
2:00:08 were very focused on that problem.
2:00:13 Because really, you’ll take the orders, I cook it,
2:00:14 and you’ll deliver it for me.
2:00:15 I’ve never heard this before.
2:00:19 So you’re just educating the market for a period of time.
2:00:21 Because you’re just focused on that problem.
2:00:26 As opposed to besides Grubhub, which didn’t do that,
2:00:28 there was Postmates.
2:00:32 Originally, Postmates wasn’t just in restaurant delivery.
2:00:33 They were doing anything.
2:00:36 They would pick up from anywhere.
2:00:38 And they would deliver it to anywhere.
2:00:40 And they would even pick up something
2:00:44 from, I don’t know, Bloomingdale’s or from Walmart.
2:00:48 But in that example, there’s just too many different things
2:00:50 that you could do.
2:00:51 And it wasn’t focused.
2:00:54 And even more broadly than not, there
2:00:56 was TaskRabbit where you can run errands.
2:00:59 Well, one of the errands you can have them run,
2:01:02 someone who’s on TaskRabbit is to go pick up food
2:01:03 from any restaurant.
2:01:09 So simplicity of the solution is the reason why I think
2:01:12 you want to start with a very focused problem.
2:01:17 It’s much easier to tell people, this is what Dornash does.
2:01:19 And then over time, you expand that.
2:01:21 You expand the remit because you’ve
2:01:25 earned the trust of the customer to allow you
2:01:26 to do more things.
2:01:29 One of the problems when you were saying that is like,
2:01:32 how did Dornash find drivers in those early days?
2:01:33 Yeah, it was hard.
2:01:40 Because the one thing that if you believe
2:01:44 that it was more profitable to transport humans
2:01:48 than deliver food, then you would come to the conclusion
2:01:53 that Uber and Lyft would get all the drivers.
2:01:54 And Dornash would not get any other drivers.
2:01:57 And it turned out that, well, A, there
2:02:01 are some people who prefer to deliver food or a package
2:02:02 over delivering people.
2:02:04 They didn’t want to have to have social interactions.
2:02:08 And then there are some people with perfectly fine cars.
2:02:12 But they’re not perfectly fine cars to transport humans.
2:02:17 And so early on, we thought it was going to be a problem.
2:02:21 But it was less of a problem than we had originally imagined.
2:02:25 One of the problems that I anticipate or maybe
2:02:27 from the outside looking at and I can be completely wrong
2:02:29 is when you sign up a grocery store customer,
2:02:31 they want to work with you in a particular way.
2:02:34 But it might not be a standardized way.
2:02:36 And then you might say yes, because you
2:02:37 want to sign up that customer.
2:02:39 Maybe it’s like Albertsons or something.
2:02:41 But then you go to the next largest grocery store chain
2:02:43 and they want to work with you in a different way.
2:02:46 How do you think through the standardization, which
2:02:49 is like, no, we work in this way versus creating
2:02:50 all of these one-offs?
2:02:52 And I see a lot of startups do this
2:02:54 where they want to sign a customer.
2:02:57 So they’ll violate their standard procedures.
2:02:59 And they’ll create these one-off contracts
2:03:01 and technical solutions.
2:03:03 And then they’re trying to get revenue
2:03:04 so that they can still exist.
2:03:07 How do you think about that trade-off?
2:03:08 It’s a very–
2:03:09 I think it’s a–
2:03:18 I use the accordion example often, which is you pull the accordion
2:03:20 too far, and then you have to push it back in.
2:03:26 And at some level, if you are super rigid,
2:03:28 you’re not going to win your first few customers.
2:03:32 So at the very beginning, the accordion is completely folded.
2:03:34 And you do pull the accordion.
2:03:37 And you allow things that you may not have allowed.
2:03:41 You may not want to allow in that very early days.
2:03:42 And it gets super far stretched.
2:03:45 And you’re like, shoot, I need to standardize a bunch of things.
2:03:47 And then first, you’re not going to go back
2:03:51 on these customers or merchants.
2:03:55 So you’re going to go into the next inning
2:03:57 with a lot more standardization.
2:04:03 Or you break up your 100 customers into three personas
2:04:07 or four personas and try to have four different standardizations.
2:04:10 But trying to be overly standardized at the beginning
2:04:14 is generally not a great idea.
2:04:18 And the opposite of that is have a standardized product
2:04:23 and then allow customization on the edges.
2:04:25 And I think a lot of software companies
2:04:28 try to do that when build a platform.
2:04:30 The platform is not changing.
2:04:31 You’re buying the platform.
2:04:34 But on the edges, we lock for customization.
2:04:36 And you allow– you do it at the beginning.
2:04:39 You find other developers who are
2:04:42 willing to do the professional services on the side
2:04:45 and go from there.
2:04:48 It’s almost like you earn the right to do standardization
2:04:49 when you’re trying to be the back end,
2:04:51 where you have to accommodate at the start
2:04:52 and widen the accordion.
2:04:55 And then as you get scale and network effects
2:04:59 and more and more benefits to the merchant or partner
2:05:03 that you’re partnering with, you can more standardize.
2:05:03 Is that true?
2:05:04 That is true.
2:05:08 And I also just think it’s very–
2:05:09 there’s a lot of hubris in thinking
2:05:11 that you can standardize at the beginning when you don’t even
2:05:14 know whether that’s the right solution for everyone
2:05:16 to standardize on.
2:05:18 And so bring some customers.
2:05:21 They’ll tell you your standardization doesn’t work for–
2:05:23 not only just because it doesn’t work for them.
2:05:27 It may be that it doesn’t work for many people,
2:05:28 and at least learn from that.
2:05:31 What’s the difference between working backwards
2:05:32 and working forwards?
2:05:35 So working backwards is this idea
2:05:40 that Amazon popularized, which was
2:05:44 you start with the vision of the world that you want to imagine.
2:05:49 And you think about, if everything goes right,
2:05:51 what is the world that we live in,
2:05:54 and what does this product become that you’re trying to build?
2:05:58 And at Sequoia, we’ll call that the pre-period.
2:06:01 And if everything goes right with this company,
2:06:03 what does it become?
2:06:07 And then you work backwards from there.
2:06:11 One year before that, what does it look like?
2:06:15 Two years before that, what does it work look like?
2:06:17 And Amazon popularized by working backwards,
2:06:22 meaning that go from the future all the way to today.
2:06:25 And I love that concept, in a sense.
2:06:27 But I’ve also seen lots of founders
2:06:30 struggle to take it from the future, which
2:06:31 they have this great vision of the world,
2:06:35 and really map it all the way back to today.
2:06:38 They map it somewhere five years out, 10 years out,
2:06:40 but they can’t map it today.
2:06:43 And I also tell founders, OK, that’s
2:06:45 the future that you’re aiming for.
2:06:47 Here are the realities of today.
2:06:50 What does it look like one year ahead, two years ahead,
2:06:51 three years ahead?
2:06:53 That’s working forwards.
2:07:00 And if the two don’t match, you’re not on the same trajectory.
2:07:03 And so I believe in having founders work both backwards
2:07:04 and forwards.
2:07:07 Often when you work backwards and you think
2:07:10 you have a great plan, and then you miss executes,
2:07:13 and you don’t know that you’re not executing,
2:07:15 it’s because you haven’t worked forwards
2:07:18 on what the year one, two, and three look like
2:07:21 to be on that trajectory.
2:07:24 What are the two or three mental models
2:07:26 you keep coming back to most when you’re making a decision?
2:07:34 I’ve been asking you that question.
2:07:35 This is your interview.
2:07:37 Nobody’s here to listen to me.
2:07:40 I want to know what your three mental models that you use.
2:07:42 I think the one that I learned from Amazon
2:07:45 is whether this is a type one or type two decision.
2:07:48 And if it’s a type one decision, I’ve
2:07:51 learned from Brian Chesky to run out the clock
2:07:54 because he can’t go back as a type two decision.
2:07:59 And you just move forward, make a call,
2:08:02 and of course, correct along the way.
2:08:06 Type one being irreversible, and type two, yeah.
2:08:08 So if it’s irreversible, run out the clock,
2:08:10 meaning get all the information, make sure
2:08:14 that that’s a high confidence decision.
2:08:17 Type two, if you can always change it,
2:08:20 make a fast decision, and keep iterating.
2:08:21 That’s one model.
2:08:29 The other mental model I think about is working backwards,
2:08:30 working forwards.
2:08:34 That’s also top down versus bottom up.
2:08:36 It’s a similar sort of idea.
2:08:38 Some problems are better solved thinking top down.
2:08:45 Some problems are more easily solved just working bottoms up.
2:08:51 Another one generally is to break up hard problems
2:08:53 into smaller and smaller, bite-sized problems
2:08:56 and solve each of those individually.
2:08:58 And just the way I live my life, this
2:08:59 is not a mental model.
2:09:02 It’s a lot about consistent compounding.
2:09:08 And just every single day doing the little things
2:09:12 that sort of improve myself or oneself or the company
2:09:13 that I’m working with.
2:09:16 Talk to me how you think through the breaking problems
2:09:21 thing, because you mentioned bringing it
2:09:22 into smaller problems, solving those,
2:09:24 and then you get the solution.
2:09:28 How do you think of that versus the individual–
2:09:32 like the optimal solution for that particular sub-problem
2:09:37 might not lead to the optimal solution for the bigger problem?
2:09:42 Yeah, so I think there is local optimization and global
2:09:44 optimization you’re talking about.
2:09:45 That’s a much better way to work it.
2:09:48 If you want to solve a global optimization problem,
2:09:49 you need to pop up.
2:09:52 And if you’re trying to solve a local optimization problem,
2:09:54 you want to go down.
2:10:00 And so I think the problem first and foremost
2:10:02 has to be at the right altitude.
2:10:05 And then you can break the problem down from there.
2:10:08 Is there an example that comes to mind for your thinking?
2:10:11 If you’re trying to climb a mountain,
2:10:18 and the top-down problem is what’s the path?
2:10:20 So even before you climb the mountain,
2:10:24 you’re going to plot the path before you get onto the mountain.
2:10:26 But once you’re on the mountain, then you have a path.
2:10:30 You’re just going one step in front of the other on that path.
2:10:33 And if you find that the path is not right,
2:10:36 hopefully you’ve had some backup paths and backup plans
2:10:39 that you can go one foot in front of the other.
2:10:40 Path A doesn’t work.
2:10:41 Well, path B might be a little better,
2:10:47 because I plotted the alternative plot to path B.
2:10:52 So that’s an example of planning top-down on your path
2:10:55 and your alternatives and doing a bunch of scenario analysis.
2:10:58 And then when you’re executing on a day-to-day period,
2:11:02 you just literally just go execute.
2:11:04 And I don’t see that any differently than a company.
2:11:06 You have a plan for the year.
2:11:09 You have some scenario planning around it.
2:11:12 And so the more scenario plans that you have,
2:11:15 the more easily you can course correct.
2:11:18 You know you’re supposed to be on path A.
2:11:21 You decide that you’re still going on path A.
2:11:22 You’re slightly off.
2:11:24 Let’s go back on path A.
2:11:26 Path A turns out not to be the right thing.
2:11:28 We’re going to pick path B because that’s
2:11:29 the second alternative.
2:11:32 We’re going to go right one foot in front of the other,
2:11:35 plotting against path B.
2:11:38 We always end these interviews with the same question, which
2:11:41 is, what is success for you?
2:11:43 I know that this question was coming.
2:11:52 And to me, the success is just the process
2:11:54 and having a good process.
2:11:59 Because if you have a process that is consistent
2:12:04 to who you are and your values, and you live that every single
2:12:06 day, and you get up every day and follow
2:12:09 through on that process, you’re already successful.
2:12:13 When lots of people talk about success is not
2:12:15 the destination, it’s the journey,
2:12:18 I think it’s just the process before the journey.
2:12:21 Which direction are you going to go?
2:12:23 Why did you decide to go in that direction?
2:12:25 How fast do you want to go in that direction?
2:12:28 Before you can go on that journey,
2:12:29 hopefully you’ve planned things out
2:12:33 and you have had a process to sort of plan that out.
2:12:35 And if you did that right, you know
2:12:38 you’re going to be successful.
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