The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Travis Kalanick no published score: only 6 usable exchanges on raw tape, and a fair score needs 8+ · coarse estimate ≈4.0/5 from 6 raw tape exchanges record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
6exchanges match
6on raw tape
1redirected or not addressed
Answered raw tape D 5 · C 5 · P 4 · Cm 3 4.45

Q What are you like? Not sleeping? Are you like?

A Well, I mean, the entire Uber thing was like a lack of sleep, you know, so it wasn't like this was a new lack of sleep thing. It was just, I mean, it was a new thing, but lack of sleep generally was a thing just because I had a global business that was really intense and, and very game theory oriented in the ways that I'm describing, which means it was always on and crazy weird things happen in cars at night. So, like, the first time I got woken up in the middle of the night because there was a, a drive-by shooting from an Uber. You know what I mean? Like, that's not good. The, the thing is, is that what happens in a city happens in an Uber.

AI assessment note: “the entire Uber thing was like a lack of sleep, you know”

Answered raw tape D 5 · C 4 · P 4 · Cm 4 4.30

Q Can you give us an example of what happened in China then?

A I mean, China was like amazing, but very difficult and in some ways impossible to predict. Let's go to China. Sounds like fun. It was a, it was a super awesome adventure because what happened was, is I was like, sounds cool. And I got, it was 2000, probably 2013 or early 13. Uber started in 2010. So it was still early crew. And I got a crew of folks, like super OG guys, and we stayed in an apartment in China for a week or two, a week and a half, two weeks, something like that, and met with everybody we could. It's actually when I first met Wan Shing, uh, at Meizuan, actually. Um, and he told me I was crazy. Don't do it. It's the worst idea ever.

AI assessment note: “we stayed in an apartment in China for a week or two... and met with everybody”

Answered raw tape D 4 · C 4 · P 4 · Cm 3 3.85

Q So when did they take the viewpoint? If they took the viewpoint that Uber is injecting instability into their city or area?

A They never did, but they, at some point, Felt like we were, we may win. And instead of really seeing super problems at the, we didn't, for the most part, we were treated fairly at the cities for the most part, not completely, but for the most part, but what happened was the, I, what I would call, what I'd say at the time is that the China war went global. So we were spending, let's say tens of millions of dollars a month fighting DD in all these cities. And the fight was like, uh, I needed to subsidize rides to gain market share. When I gain market share, there's network effect because if I'm bigger, then my system is more efficient. And if I'm more efficient than them, they have to subsidize more than I do. To compete with me. So how do I subsidize where, when, how to get that efficiency edge, that network effect efficiency edge so that I subsidize less than them. This is why, you know, like Lyft is smaller than Uber because we were better at this part of this, the thing, and people don't really know that's what it takes. It's, but like, how do you get efficiency edge? Efficiency edge starts when somebody even downloads the app and signs up. If it's easier to sign up on one versus another, you have an efficiency edge. If it's easier to call a vehicle and like get it to you without problems, you have an efficiency edge. Cause you'll have less support. You'll have less like peop…

AI assessment note: “They never did, but they, at some point, Felt like we were”

Partly raw tape D 3 · C 4 · P 3 · Cm 3 3.30

Q So can you give an example of like a problem you're creating when you start in China, how long it takes to come ashore and what happens when it does?

A Okay, so what you learn when you go and do what we did in China is you learn that when you go and take your business and go to China, you have to start over. So many people think that you can take your business and take it somewhere, which by the way, Uber kind of like trademarked that if there's such a thing, like We made that a thing where like cities, countries didn't matter. We created a system that was inevitable, but China was different because of how that country works. Everything's different. And that means you have to start from scratch, right? It's like a, something as simple as like, uh, the phones, uh, or let's say maps, GPS. There's a different GPS system in China than there is here. What does that mean? Well, it's like different. So if I want to understand how cars are moving through space, I have to change my GPS system so I can do that. So I understand. And that's like one of like a hundred things that are different in China, which means you have to start over. And so, yeah, you're starting a new business when you take it to China and you have to, you have to be in a very receptive, like, I am going to learn how to do things differently in this very different place and be excited and interested in how different it is. Whereas most entrepreneurs, let's say Western entrepreneurs that go to China, that is almost none succeed.

AI assessment note: “There's a different GPS system in China than there is here.”

Redirected raw tape D 2 · C 4 · P 3 · Cm 3 3.00

Q Do you still put an emphasis, I've heard you speak about this in the past, an emphasis of hiring and empowering young people? Is this business different than like when you were launching new cities in Uber, for example, where you gave a lot of responsibility to, you know, aggressive young people?

A Well, okay, again, so it, there's really interesting ways to do it. I, I, I sort of have this, this concept I call the line in sort of the, maybe the framework is finding the line. So there's a line. On one side is order, lots of structure, sorry, sorry, structure. Like as you, as you pull away further, further back into order, you have lots of rules, lots of structure, lots of process, and eventually lots of bureaucracy. And if you go too far back from that line, you're going slow and people are bummed. And if you go to the other side of the line, which is chaos, Lack of rules, lack of process, lack of structure. And as you go deeper and deeper and deeper into chaos, you also get to a place where you're going slow and people are bummed. So that line between order and chaos is innovation at speed and at scale. And the job of every leader is to find that line. And it's not in two dimensions. It's like an AD dimensions. Okay. And the best leaders are able to find that. And, you know, the, probably the most approachable way to describe this is the fewest number of rules while staying out of chaos is the, is the approachable way to describe this. But you go to back to like launch at Uber. You could think of it as like, okay, there's a bunch of 23 year olds launching cities. What happened was at the beginning, the first 20, 30 cities, I was deeply involved in whether that city was g…

AI assessment note: “I sort of have this, this concept I call the line”

Answered raw tape D 4 · C 3 · P 2 · Cm 2 2.90

Q Was there a specific reason you, you started with food, though?

A It just caught me. I mean, like, that is, like, I don't have a list. Well, first of all, of course I did Uber Eats, so, like, very familiar with this part of things, but nowhere close to the atoms that are necessary to do what I just described. You know, I like to say, like, I have lots of ideas all the time. I mean, I, I'm an idea factory, but other people have great ideas too, but like an idea comes to you or comes to you, if that makes sense. And I'd like to say, you know, you go out on a date with the idea, right? Was it a good date? Did it go well? Like how did you and the idea get along? And it's very much related to like, who are you is going to be a big part of which idea works for you.

AI assessment note: “It just caught me... of course I did Uber Eats, so, like, very familiar”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, about 40 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.