Pod Insights Moonshots with Peter Diamandis EP #25 How to Build a Moonshot w/ Astro Teller About this episode In this episode, recorded during the 2022 Abundance360 summit, Astro Teller presents the wireframe for building and executing Moonshots and the power of turning crazy ideas into breakthroughs.
You will learn about:
09:57 | What’s a Moonshot?
13:32 | How to build a Moonshot Culture
15:53 | We can’t all be right.
22:47 | The “monkey first” strategy
Dr. Astro Teller's expertise lies in intelligent technology as the CEO of Alphabet's X, The Moonshot Factory. X is a company dedicated to bringing extraordinary, audacious ideas to reality through science and technology. He was previously the founding CEO of Cerebellum Capital.
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Resources
Visit X’s website.
Learn more about Abundance360.
Read the Tech Blog.
Learn more about Moonshots & Mindsets.
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This episode is brought to you by:
My executive summit, Abundance360
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Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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0:30 Speaker 01 Your idea is probably wrong. Whatever it is that you're currently really excited about, if it's a moonshot, it is probably wrong. It doesn't make any sense for you to be trying to do something radical and yet to believe that it is almost certain to work. That breaks the basic concept of radicalness.
0:53 Peter Diamandis? And a massive transformative purpose is what you're telling the world. It's like, this is who I am. This is what I'm gonna do. This is the dent I'm gonna make in the universe.
1:05 Peter Diamandis? It's a pleasure to share with you a conversation I had with the captain of Moonshot's Astro Teller. Astro Teller is the grandson of a Nobel laureate and the grandson of the gentleman who created the hydrogen bomb. He is brilliant in his own right. And he's the person who has started thousands of companies under the alphabet Moonshot factory. You know, if there's one person who can really tell you what a moonshot is, we're going 10 times bigger on the planet than anybody else's, it's Astro Teller. So, join me for a wide-ranging conversation and a how-to, a masterclass on creating a moonshot organization.
1:44 Speaker 01 Until just now, Steve Jervison had the record for the weirdest, creepiest introduction of me ever, and you just broke the record. Congratulations, that was really uncomfortable.
1:55 Peter Diamandis? I feel special about that. I'll try and do it next time.
2:00 Speaker 01 Speaking of uncomfortable...
2:04 Speaker 01 I'm gonna try to do what I can to make you a little uncomfortable today, including maybe convincing you that being uncomfortable is an important part of the process. But let's start with a thought experiment. Follow me here, we're gonna come back to this. But imagine an infinitely long room of slot machines. And every slot machine has many, possibly an infinite number of sub arms on it.
2:32 Speaker 01 And all you know going into this infinitely large room is that each slot machine is different. It has a frequency, it pays out one in K times. And so slot machine number seventeen might pay out one in a hundred times. Slot machine number two hundred and fifty might pay out one in a million times. But you don't know which is which, they all range in how often they pay off. And they all range in how much they pay off, and you don't know that either. One could pay off a dollar when it finally pays off, one could pay off a billion dollars.
3:02 Speaker 01 You do know that the little sub arms are in a tighter distribution around the payoff. So they'll all be somewhat different, but near the general payoff of that overall slot machine. That's all you get to know. You walk into the room. What are you gonna do? Are you just gonna pick slot number six and be like, "I got a good feeling about slot machine number six", and just sit there and pull it forever? Pull one arm on that machine forever? Maybe pull lots of arms on that machine forever?
3:34 Speaker 01 You could just go down the line forever, just pull one arm each time, just keep walking down that infinite hallway. You're trying to make a lot of money in this thought experiment over a very large period of time. Maybe many years, many decades even.
3:50 Speaker 01 Going down that hallway and only pulling each one once, you're not really gonna learn anything. That's kinda random. That's just gambling. If you stay with one machine and you just pull it forever, that's also just gambling. There's a right way to do this game. You would pick some of the machines and you would start pulling maybe the closest arm in each machine, or a random arm on each machine. And you would do it 10, 20, 100 times for each machine and you'd start gathering statistics. "Oh, it looks after 100 pulls like number 17 is better than number 6. I'm going to give up on number 6." I could be wrong. It's possible that number 6 will just pay off better over the long run.
4:35 Speaker 01 It has a higher expected utility. But the statistics I'm building up are starting to make it look pretty clear that 17 is better than 6. And you might start, you add another one. "Okay, we were only on 200, now I'm going to add 201 to the list of slot machines I'm to be playing." There's a right way to do this if you're a computer scientist. This is an extension of a game called the K-arm bandit problem. You can go look it up if you want. But I'm going to come back to this thought experiment. The problem is that we're taught, starting when we're about 6, to exploit, not to explore. And innovation is a game of exploration.
5:18 Speaker 01 It is guided, thoughtful, purposeful exploration. But that is not what happens. A moonshot is an attempt to do radical innovation, and yet almost all efforts that look anything like a moonshot start with somebody walking up to a random machine. "I got a really good feeling about this. I've thought about it hard and I've convinced myself that slot machine number 17 is the one." And they just sit there and pull the arm over and over and over again. That was a moment of what felt like insight, I argue is not. I think we're all essentially no better than random. I'm sorry, Eric Schmidt from last night. I think we're, all of us, including me, including Eric Schmidt, including all of you,
6:02 Speaker 01 no better than random at predicting the future. I know you feel like the slot machine you're standing in front of is the right one. You've got great reasons for it. But everyone's got great reasons for their things, and I don't think that there's any evidence that any of us are any better than random at which slot machine we end up in front of.
6:23 Speaker 01 And everything you've been taught since you were six is to exploit. No one gets patted on the head for running an experiment in a really good way. You only get rewards since you were six years old for whether you got a win, whether you got an outcome that somebody can reward you for. It's the opposite of exploration. And it's the opposite of seeking to do radical innovation efficiently. If you stand in front of slot machine number seven and you pull it a lot, you could get lucky. That could be a great slot machine. I'm not saying that the slot machine you might be parked in front of is a bad slot machine. It's just gambling.
7:04 Speaker 01 So what I'm going to try to talk about today is the card counting version of innovation, not the gambling version.
7:13 Speaker 01 X is an experiment. We'll see how well it goes. I think it's going pretty well so far. But it is also a factory for running experiments. Our aspiration is to create really great things for the world that also have great value for Alphabet. That's our mission at X. And I believe that the best way to do that is to send people out not to build businesses, but to buy options on the future by very carefully, thoughtfully, methodically, running great experiments that answer the question, "How promising is this particular moonshot?" How promising, with respect to that thought experiment, is this particular slot machine I'm standing in front of?
7:56 Speaker 01 And if at some point the statistics start to make it look like that particular experiment, that particular proto-business, this option that might someday become a business at Alphabet, is looking less promising on a reward-risk ratio...
8:13 Speaker 01 Then the other things we could try, I know it could still work. I love it that you're excited about your teleporter project. But if the reward risk ratio isn't as good, if the evidence isn't mounting that it's possible, that it's going to have positive techno economics, let's stop. Let's go on to a different experiment, to a different slot machine in that thought experiment.
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10:26 Speaker 01 So a moonshot is a structured what-if.
10:30 Speaker 01 That has these three fundamental aspects to it. Number one, is there a huge problem in the world that you want to solve that you can describe clearly? If you don't have that, I would argue, it is a fundamentally academic exercise. So if you have a frictionless surface and you're very excited about frictionless surfaces, I applaud you for having created a frictionless surface, but it is not yet clear why we should spend time on frictionless surfaces. You have to describe the problem in the world you want to solve. Number two, there has to be a science fiction sounding product or service, however unlikely it is that you could make it, that your team could make it,
11:11 Speaker 01 that if you made it, would make that huge problem better or make that huge problem go away entirely. You might not be able to, but it has to be science fiction sounding, because if it's not, then everybody else is trying with you, and that means you are in a smartness competition, in a spending money competition with the rest of the world. You may want to get into that competition, but that's a competition I would like to avoid. And number three, there has to be some way to get started. If we're serious about experimentation and you say, "I'd like to make a time machine, sure sounds like a science fiction sounding thing to me, and here's all the problems in the world we could solve with a time machine."
11:55 Speaker 01 My question would be, okay, what's the hypothesis we can test and get a first glimmer of whether your idea is real or not now? Like in the next six months, not the next 20 years. Time machine's a weird side effect. I'm maybe as long as you solve it, you could come back and just tell me it's working now, yesterday, I guess. But for the teleporter, let's say. So you have to have these three things in order for it to be a moonshot, at least at X. So we've had about 2,000 what-ifs at X over the last 12 years.
12:32 Speaker 01 And believe me, there were tears for all of the ones that we closed down. Sometimes the tears were small, sometimes they were pretty big. And I'm being serious about this. It hurts to turn off an experiment that you have become passionate about. And we need to work on things with great passion, or we won't be clever and creative about them. But we also have to stop and be dispassionate and assess the results of those things in order to say, is this one really that special? Or should we stop it in favor of better experiments? So what if cars could drive themselves? Became Waymo, which is now an other bet at Alphabet. What if we could reinvent the way goods are delivered?
13:16 Speaker 01 Became, first a project at X as Waymo did, now an other bet called Wing, which is also at Alphabet. Here's some examples of ones you may not have heard of. These are still at X. Tapestry is our moonshot for trying to reinvent how the electric grid works. Mineral is a moonshot that we have in computational agriculture. How could we take care of plants on a per-plant basis instead of on a per-acre basis? And title is our moonshot in ocean health. Those are just examples. They happen. Those ones happen to be going well right now. But for every one of those, there are literally 100 that sounded that great beforehand that were like, ugh, no, that one's not gonna work.
14:00 Speaker 01 Move it on. So how to build a moonshot culture? Here's my first tip. And I want to be clear as I give you these tips. There is no rulebook. I cannot give you, and to their great frustration, I cannot give the people who work at X a set of charts and rules to follow. You will make a moonshot. You will be a great Xer if you do these things. Check, check, check. It doesn't work like that. Doing moonshots requires enough creativity. It is as much art as it is science. It is as much about the playful side of us as it is about the critical side of us. And unfortunately, that means that these tips that I'm gonna give you,
14:45 Speaker 01 I think that they're important, but they're rules of thumb. The first one is, aim for 10x, not 10%. You've probably talked about that a bunch here. The two most ba— there are a lot of reasons why to do this. There are a lot of fixed costs in starting up something, for example, and you can't overwhelm them if you're shooting for something small. But the two— there are lots of things that are like that, that are more pedestrian. But the two most important ones. Number one, you set people's hearts on fire when you get them excited about really changing the world, about shooting for something huge instead of something small. And that passion converts into a lot of incremental energy, creativity, stick-to-it-ness, that can turn out to be the things
15:30 Speaker 01 that help you discover what would cause this thing to work. And the second one, maybe even more important, is if I ask you to make your car work and go a little bit farther on a gallon of gasoline, you'll say, "Okay." And you'll go to the car, as it's currently working, and see if you can tinker with it to make it a little bit more efficient. But if I ask you to make your car go 10 times as far on a gallon of gasoline, you know you have to start over. It won't work for you to tinker at the edges with the current design. And so 10x thinking is a fundamental reminder, often unconscious to the teams. You must start over. This is not a smartness game we're playing.
16:14 Speaker 01 This is a creativity game that we're playing. And that requirement of 10x instead of 10% is a reminder to them to do that. Now here's the bad news. Don't worry, it's gonna get a little bit better. Your idea is probably wrong. Whatever it is that you're currently really excited about, if it's a moonshot, it is probably wrong. It doesn't make any sense for you to be trying to do something radical and yet to believe that it is almost certain to work. That breaks the basic concept of radicalness. You can't all be right. I can't be right more than 1% of the time. I don't think Larry, or Sergey, or Eric Schmidt,
16:59 Speaker 01 or anyone can be right more than about 1% of the time if you're trying to do things that are really radical.
17:06 Speaker 01 That's tough. But I think it's true. There's some good news, though. You can be efficient about how you filter your ideas. Just because you can't be better than random at coming up with one of which slot machine we should try next. You can be very thoughtful about how you take the statistics on all of those slot machines, on all of the moonshots that you could try. Or if you have an organization that has the ability to try many moonshots. You can be organized and thoughtful about running experiments and keeping statistics and making wise, hard, dispassionate choices about which things to stop and which things to keep going on. That you can do.
17:50 Speaker 01 That you can be much better than random about because most of the world is doing it randomly. That's the opportunity. It's depressing. I understand how fun it is to feel like the teleporter's gonna work. Every entrepreneur is taught that if you just jack up your excitement about your thing through the roof, that somehow that will solve your problems. But no amount of excitement makes it any more likely that the teleporter is the right solution. It's tough. Now. If you don't have... This is why I've set up a moonshot factory because I have been an entrepreneur. I have run a hedge fund. I understand both sides.
18:35 Speaker 01 And I'm telling you that the environment is inefficient on both sides. It can work. I just don't think it's efficient. That's why we set up a moonshot factory. But if you are in a situation where your cards have already been dealt, you are into the teleporter project, and believe me, I get it. You want to walk up to that machine and start pulling and seeing whether that's a great payoff, your teleporter project, or whatever that slot machine is for you. But it probably costs a hundred thousand dollars every time you pull the arm in your startup. So you have to go convince someone to give you like ten million dollars. You can pull that arm enough times to figure out whether it's gonna work. So you have to tell them, "Hey, I'm no better than Random. You should give me ten million dollars." No one's gonna give you ten million dollars if you say that.
19:20 Speaker 01 So you don't tell them that you're no better than Random. You say, "This is the one, and I know, and here's my, all my slides about why it's better than everything else." And then they give you ten million dollars. But now you're really in for it. You just took ten million dollars of their money. You better stand in front of that machine and just keep pulling the arm. Even if it's not looking really good, you're just like, "It's gonna be there. It's gonna be there. Trust me." And you just keep pulling the arm.
19:44 Speaker 01 But it turtles all the way down in the following sense. Even if you're committed to your teleporter, and it could be right. I'm not saying it can't be right. I just don't think it's efficient way to pick which slot machine to stand in front of. You can still do what I'm describing within your effort. For what products you make, for what features you add, for what customers you prioritize. You can run experiments. And you will find that what I'm talking about is just as uncomfortable to really do this. Not pretend to do it, but to be dedicated to experimentation as the way to solve your problems.
20:24 Speaker 01 Even at X, like seriously, in the last couple of months, we did a survey across all of X. And there were a good number of people who said, "I don't have time to run experiments. I'm too busy doing my job."
20:38 Speaker 01 I guarantee you, I've been ranting like this to them on a weekly basis for 12 years. Experimentation is your job. There is no other job. That is how we solve our problems. Milestones aren't something we shoot for. They are hitting milestones as an accidental side effect of running great experiments in really thoughtful ways and being this passionate about the outcomes. Being a lifelong learner.
21:08 Speaker 01 Which takes us here, tip number two. The whole, what I'm explaining is, pick smart experiments to one. Ones that have high expected utility, like the slot machines. It doesn't matter what the frequency is or what the payoff is. It matters whether the expected utility of pulling that arm is better than any of the other arms you can find. That's what you're looking for. That's a smart experiment. So you can design one of those in the real world. What is that experiment you're going to run to tell you whether the teleporter might be a great idea or a bad idea? And I don't care whether it's a great idea or a bad idea. I am not paying you to make the teleporter work.
21:52 Speaker 01 I am paying you to answer the question, is this thing, the teleporter, have a chance of being one of those very small number of things that could really change the world? And the answer no is just as good as the answer yes. That is the honesty at the end of an experiment. If you don't believe that the answer no is just as good as the answer yes, you fundamentally aren't running an experiment. That's the whole point of an experiment is you don't care what the outcome is. So we need people to become lifelong learners. And the number one reason that we aren't lifelong learners is because you don't learn from confirmation bias. We spend all of our time trying to get everyone to tell us we're right about everything. We seek out reasons
22:37 Speaker 01 to find out that we're right about everything. And you don't learn anything from that. You learn when you're wrong. Failure is the only meaningful mechanism for improvement on whatever it is that you're doing. And yet, it's the thing we avoid. It's the ultimate no-no. So if you want your team to be obsessed with learning, which I believe is the only way to be obsessed with winning, then they need to find failure, the answer, nope, there was nothing under that rock when they turned it over, to be something they can say with active pride.
23:14 Speaker 01 So how do you do that?
23:17 Speaker 01 So here's one of the things that we try to use at X, which is monkey first. I've said this kind of as a joke about four or five years ago at a Wall Street Journal Live Conference, but it sort of stuck at X. Someone was saying, because I always say, "Work on the hardest parts of the problem first." And some of the interviewer said, "What do you mean, Astro?" And I said, "Look, if you were trying to train a monkey to stand on the top of a 10-foot pedestal and recite Shakespeare, what should you do first? Train the monkey or build the pedestal? You should train the monkey first, because if you get the monkey working and the poor little monkey's standing down here, we can definitely get it a pedestal for it.
23:59 Speaker 01 If you build the pedestal, you have made zero progress at derisking the situation. But go look in your organization. It is littered with people frantically building pedestals and asking you for a bonus and a promotion because of the gorgeous pedestals they've just built for you. Because you reward them accidentally, I know you don't do it on purpose, for the pedestals that they built. It feels kind of like progress was made, but they haven't been running at the risk. And the risk is the only interesting thing. If you're obsessed with finding out as fast as possible whether you're on the right path, if you have decided, "We gotta go down this path no matter what until, you know, there's
24:43 Speaker 01 like fiery hell at the end of it," I guess building a pedestal puts off bad news for a while, so that sort of makes sense. Here's another one. If you hire world-class people, which we certainly try to do at X, I hope you all do, the smarter they are, the more talented they are, the more they have learned, "I'm really good. I do things right the first time because I can think it through and figure out what the right answer is." But the definition of a moonshot is that it resists people thinking through the solution. You are not smarter than everybody else. Whatever it is you're working on, the answer has to be counterintuitive, or it's not a moonshot.
25:25 Speaker 01 If it's not counterintuitive, other people who are at least as well-funded as you, who are at least as smart as you, would already be doing it. So when you have a group of people who are trying to help you, their attitude, "I know what to do because I'm very smart," isn't just a mediocre idea, is an actively destructive idea. So you have to build into your culture an excitement around version 0 dot crap.
25:53 Speaker 01 We want to get into the tightest learning loops possible, which means I want you to go make the worst possible experiment, the crappiest, barely held together with duct tape experiment you can think of. Run it as fast as you can, thoughtfully, but in a scrappy way, that just barely gets us data of some value and meaning. And we will use that data in a tight loop to go do it again. Because if you spend one extra day past that point on this, you're kidding yourself. You think you know what the right answer is. We're not going down that path. This is part of training individuals and also teams to be lifelong learners. So this is tip number three.
26:38 Speaker 01 No one of us has all of the good ideas. No one of us could possibly by ourselves do what a great team could do. And a great team made up of 20 Astros is arguably worse than one Astro, because now we have to coordinate with each other and we still only got one Astro's worth of ideas on the team. What you want is people who think as differently as possible.
27:06 Speaker 01 On all possible fronts, you want people who are honest and vulnerable and creative with each other, but are bringing to the party, huh, I hadn't thought about it that way. That's what everyone in the team should be saying when anyone else opens their mouth on the team, almost constantly. Because that's what's going to cause you to look in unexpected, uncomfortable places for the solution. And I guarantee you, if you're working on a moonshot, the moonshot solution is not sitting there obvious out in the open. And it's going to take somebody whose expertise you're not quite sure why you have on the team until afterwards, and you're like, oh my God, thank God we have a puppeteer on the team. Thank God we have a concert pianist on the team. Thank God we have a marine biologist on the team. Thank God we have somebody
27:51 Speaker 01 who lived in Ghana for the first two thirds of their life. Whatever that is, they're bringing things to your team that the rest of your team wouldn't have thought of. And that's the magic of making a team that's more than just the smartness of the individuals.
28:07 Speaker 01 Part of what I think causes something really great to happen in making moonshots is it's not just that we fail and we move on, but we've learned things in the process. The people we keep, they recirculate through the factory, but what they bring with them is the memories of all of the things that we've tried and that compost, as we call it, of all of our failures and why it didn't work and the little bits, we're like, oh shoot, this is an awesome moonshot and we're gonna have to kill it because right in the middle, like the, the engine is driven on unobtanium and nobody can find any unobtanium, I guess we're throwing that moonshot away. But then if we find some unobtanium later, we hope that someone's like, wait, you remember
28:52 Speaker 01 that thing that we did before that was like awesome, except that we didn't have any unobtanium? Why don't we go get that out of the freezer?
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30:36 Speaker 01 So, I'm just gonna use two examples here very briefly, but this is true of most of our things. For the three pictures I showed for you before, our moonshot for the electric grid, our moonshot for agriculture, and our moonshot for ocean health. When we look back, we can trace very directly, there's probably more than this, very directly, a whole bunch of things that didn't work out. Things where we tried to grow seaweed in the oceans, whatever that was, vertical farming, each of which didn't make it for a variety of reasons. But, those ideas, the opportunities, and some of the people, by staying at X and recirculating, eventually turned into something that looks incredibly promising. So, moonshot composting,
31:20 Speaker 01 finding value from what didn't work, which is related to the idea of celebrating failures, is part of our superpower. Here's one of my favorite examples. Loon, which just closed down after nine years, one of the most painful close downs that we've had. I was very excited about it for a long time. It was the right thing to do to close it down. One of the problems they were trying to figure out was how to send, it was basically beaming 4 and 5G down to the ground so people could talk to handsets all over the world, even if there was no telco infrastructure nearby. But the balloons had to talk to each other and had to talk to the ground. And there was a period during which we weren't sure whether a collimated RF, kind of like a laser but made from radio frequencies, or made from light, was the right way to have these balloons
32:05 Speaker 01 talk to each other at very high frequency. There was this wonderful moment where we actually had the balloons up and running, talking to each other with lasers, and we were bouncing the movie Real Genius back and forth between two balloons that were like 100 kilometers apart between these two lasers. Loon was closed down, but, in the process, Tara... Which is another moonshot that we have for bringing connectivity to the world. Harvested those lasers from the balloons. And they're now doing terrestrial lasers. Where if you take something the size of a traffic light, strap it to a pole, up to 20 kilometers away, you can get fiber speeds with less than 1% of the cost of trenching fiber between those two places.
32:48 Speaker 01 It has to be line of sight, but there are a lot of places that are up to 20 kilometers away that have line of sight with each other on poles and towers, etc. This is being rolled out in India and Africa right now, and I'm super excited about this. And it is partly thanks to Loon, where we stopped what wasn't working, but saved the parts that were great compost for the next opportunity.
33:11 Speaker 01 So, I've said these three things as tips for you to think about. But before you get too excited about the tips, I want to tell you the truth. The tips are the easy part. I mean those tips, I think they're real. But here's the thing. Telling your employees what to do doesn't work very well. I assume every single person in this room understands what I'm talking about, if you've ever had an employee. They don't do what you say. They do what your organization is set up to tell them secretly, implicitly, is what you actually want. It is the thousand signals that you send to them about what you really want that is what they line up behind.
33:55 Speaker 01 And what I'm describing, it's very simple, but it's unbelievably hard to get people to do this because it's so counterintuitive. They will only do it if you send them those thousand signals. So here's an example or two for you. In our front lobby, when you come in, we have a bunch of glass cases with some stuff that we've built. This is the first one. That looks bad. But that's the point. We celebrate learning. We celebrate experimentation. This is one of the first payloads that Loon had. We don't care to make it cool or to celebrate the outcome. We are celebrating the process.
34:36 Speaker 01 When we hire someone, we don't ask exers after you interview somebody, "Tell me about their IQ. How many people have they managed? How many people have they fired? How much money did they make for their last business? Don't care, don't care, don't care, don't care." These are literal questions that we ask exers to rate these people on when we're considering hiring them.
35:03 Speaker 01 I want you to think about what are the things you actually ask your interviewers to rate the people who are coming in? Because is it things like creativity and humility, a growth mindset? This isn't a complete list, but these are important ones that we ask them to rate it on. This is what we think drives people being great at taking moonshots. And when it comes time to promotion, we bring this list back out again. If you show up to promotion and you write a long, like, "I did this, and I did this, and I got all these great outcomes," not interested. You have to celebrate the process, not the outcomes, or no one will run an experiment. Why would you run an experiment
35:48 Speaker 01 that has a 1% chance of succeeding if you believe that you're going to get promoted only if you get a yes to the experiment you run? No rational person would do that at a business. So we make sure that when it comes time to promotion, people understand at X, it's about the journey of learning and experimentation that they will be judged on, not the outcomes that they got.
36:12 Speaker 01 There's another one. You have to wire into your culture the things that are important to you. So for example, Google has what they call "Google We", and it's like Halloween every year. And we don't do that. We celebrate the Day of the Dead, Dia de los Muertos. Our cultural alchemist, whose name is Gina Rudan, has helped us use the Day of the Dead celebration as a way to think about the people who've gone in our lives, but also to grieve all the projects that we've let go. And it tells people at X, "We're serious about your emotions. We understand that it's painful. Let's go through the grieving so that we can move on," which is an important part of the process.
36:57 Speaker 01 So, I wish I could leave you with what's your moonshot. I hope you have one, I hope you're working on it, and I certainly wish you well. But this is what I'm actually gonna leave you with before I transition to questions. How ready are you to savagely attack the thing that you're working on? To find out whether it holds up to those attacks? How badly do you really wanna know if your thing has an Achilles heel? If you don't, I understand. But you're probably gonna find out later, even if you don't find out now.
37:39 Speaker 01 I would encourage you to get excited about finding out if there's an Achilles heel. Find out now. And you want your employees to be just as determined, just as excited to find that Achilles heel? And they won't if they don't run experiments, and they won't if they don't believe that you will reward them for running the experiments that are the highest risk and then being honest about the results. So, I hope you can find it within you to savagely attack your darlings, the things that you're working on that are most precious to you, not because it causes success in the short run, but because it's the most efficient way to make moonshots in the long run. I hope that you go out there and make good trouble every day,
38:22 Speaker 01 and I hope that every step on your journey is uncomfortably exciting.
38:26 Peter Diamandis? Everyone, this is Peter again. Before you take off, I want to take a moment to just invite you to subscribe to my weekly tech blog. Today, over 200,000 people received this email twice per week. In the tech blog, I share with you my insights on converging exponential technologies, what's going on in AI, how longevity is transforming, adding decades to our life. In the tech blog, I often look at the 20 meta trends that are gonna transform the decade ahead and share the conversations I've had with incredible tech thought leaders on how they're transforming industries. If that sounds cool to you and you wanna try it, join me. Go to dmads.com/blog, enter your email, and let's start this weekly conversation.
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