332. Rethinks: Learn Faster and Fail Smarter

0:03 Big ideas require us to think differently about failure, learning, and creativity. My name is Matt Abrahams and I teach strategic communication at Stanford Graduate School of Business. Welcome to this special Rethinks episode of Think Fast, Talk Smart, the podcast. My conversation with Astro Teller changed the way I think about what it takes to pursue ambitious ideas.

0:25 Astro shared so many insights about learning from failure, fostering creativity, and making big ideas understandable that I wanted to bring his advice back for all of you. And this time, we're sharing the extended version of our conversation. Enjoy. The best communication is architected for understanding.

0:45 My name is Matt Abrahams, and I teach Strategic Communication at Stanford Graduate School of Business. Welcome to Think Fast, Talk Smart, the podcast. Today, I am really excited to speak with Astro Teller. Astro is a computer scientist, entrepreneur, and inventor. He serves as captain of moonshots at X, Alphabet's Moonshot Factory, where he oversees audacious high-impact technology projects.

1:09 He has written two novels and the nonfiction book, Sacred Cows: The Truth About Divorce and Marriage, that he co-wrote with his wife. He's also a new podcaster, hosting the really fun and insightful The Moonshot Podcast. Welcome, Astro. I am super excited to be chatting with you. I've been excited ever since we arranged this.

1:29 Thank you for being here. Thanks for having me. Excellent. Shall we get started? Yeah, let's do it. To begin, I'd love for you to define for our audience what you mean by a moonshot. Sure. So we think of this as the blueprint for moonshots. And in order for us to have something that counts as a moonshot, it has to have three components.

1:47 One, there has to be a huge problem with the world that you can name and you want to solve. Number two, there has to be some kind of radical proposed solution that however unlikely it is you could make that thing, this is like a science fiction sounding product or service. We could agree ahead of time if you could make it, it would resolve that huge problem with the world.

2:08 And then three, there has to be some kind of breakthrough technology that gives us at least a glimmer of a hope that we could make that science fiction sounding product or service that would solve that huge problem with the world. Once you have those three things, we're not done. That means you have a moonshot story hypothesis.

2:27 You have a testable hypothesis. And from there, the question is, how quickly can we verify that you're wrong so we can move on to the next idea? Because anything that fits those three criteria that I just named, exciting as they are, it is exactly because it is so unlikely to work that we have to be constantly pursuing the reality that each one of them is likely to be wrong.

2:56 So the goal is actually to come up with these audacious ideas and strivings, and then to as quickly as possible negate them. Yeah, of course, we want any particular moonshot we come up with to turn out to be a once in a generation opportunity for the world. But since most of them aren't, wanting to win, wanting to get it to be right each time leads to sadness after sadness, and denial kicks in that slows up the efficiency of being the learning machine that we would aspire to be, verifying which of the many that we've started is in fact worth doubling down on.

3:35 You said several things there I want to dive deeper into. So you see this as learning, and it's a learning machine, as you said, which leads me to wonder, is there a particular type of mindset that you try to bring about in your organization that looks at it this way? Because many people don't think of projects this way.

3:52 They start a project, they want it to be successful, not let's start a project and figure out all the reasons why it won't be successful. Can you talk a little bit about that mindset? Sure. Let me give you one or two examples. I mean, the first is, if you were working at X, I would say, "Can we pre-agree before you've come up with something and then fallen in love with it, that if it's a 1 in 100 chance of working, it has a 99% chance of not working?" Which means that if you tie your sense of self-worth to getting a yes, you're just lying to yourself.

4:22 You think that you're the 1% and you're always gonna win, but this can't be Lake Wobegon, where we're all above average. So that's one way to help put some intellectual guardrails around what we're about to go do. Here's another way of doing it. Think of the last really hard thing that you and a team did.

4:39 I'd ask each of your listeners to think about that. Now imagine you lose all the hardware, all of the software, anything except what's in your and your team's heads. How long, once you've succeeded, would it take for you to go back and rebuild the solution, having already verified what it is? Most people say somewhere between 5 and 20% of the time that it took.

5:01 And for moonshots, it's much closer to 5% than 20%. Let's call it 10% on average. What are we gonna call that other 90% of the work? It's learning. Most of the work isn't the making of stuff. It's the learning what to make. And the more you're shooting over the horizon, which is what a moonshot is, the more of the journey is exploration, not the settling that happens afterwards.

5:28 So if you agree conceptually, intellectually, that we're on a learning journey, then scary as it is to be wrong, we need to focus on the moments where we learn something. And when do you learn something? You learn something when you have a model about the world, and then in some way you get some data that tells you you're wrong.

5:48 You learn nothing when you're right. At best, you deepen grooves in your brain. If you're wrong, whatever else we wanna call it, that feels bad. That's a failure of a kind. If you hate failure, you will emotionally avoid that moment, which means you're emotionally avoiding learning. If we just agreed we're gonna spend 90 plus percent of our time learning, then we need to de-stigmatize failure so we can have our learning loops be as tight as possible.

6:15 So a moonshot mindset is really about seeing learning as the goal. How do you inculcate and support that, and how do you produce anything if, for many companies, productivity is what's the goal? So how do you produce the amazing things that you've done and help people see learning as the goal, not productivity?

6:34 It's very hard to prevent people from chasing progress. Even at X, there's a decent amount of it, even though I'm constantly going around trying to stamp it out and redirect people towards learning. So it's not hard for the end result of a lot of learning to turn into something very valuable that looks ultimately like great progress.

6:55 During the journey, the thing that is hardest to fight is you feel, especially once you've done some learning and you've found something that works, it's so hard for you as an X-er not to feel like, "I found it. I'm right. Now just let me build it, and then I'll give it to the world and we're gonna be great."

7:13 And I just have to say, we, the leadership at X, have to say over and over again, "I know it feels like you've found it, and you know more about the teleporter, if that's what you're working on, than I do. But I'm telling you from induction, having watched this hundreds of times now, you're not correct yet.

7:30 You have a lot to learn, and what you think is the answer isn't the answer. It's not that I don't want you to be right. It's just my experience tells me you have a lot more to learn, so I need you to stay in learning mode, keep your humility and your curiosity really high for another two or three years." It's helping people to do that that's really hard.

7:50 I find it really interesting that humility and curiosity are what keep the flames going for learning. How do you capture the learning across the different teams? We had Amy Edmondson on, and she talks a lot about the right kind of failure and learning from the failure and the processes you can put in place.

8:07 What are some of the best practices you've implemented so if somebody learns something, that learning is cascaded so others can benefit from that learning? There's a bunch of different ways. The truth is, some of it is just institutional knowledge, and that's sort of a background radiation that's very real at X. There are lots of things that we capture.

8:25 We actually have a document called headwinds and tailwinds to remind us of some of these learnings. These kinds of things tend to be tailwinds. In our experience, these kinds of things tend to be headwinds. That doesn't mean you can't ignore one of them if you want to or if you think it's worth it, but these are good reminders from the past that we've learned.

8:46 We have maybe 20% of the people who work at X aren't on one of the projects. They're in these central teams. So this is like finance, legal, public policy, some business development, a lot of sort of hardware prototyping. And what happens is they go over here and they help the teleporter team, and then they go over here and they help the time machine team.

9:08 And so they act as a kind of vector, transplanting interesting ideas and learnings from one team to another. So even if those teams don't talk to each other very much, because they share these central teams, the central teams can move good ideas back and forth. So you actually have a structural element where there are people spoke and hub, and the, those folks in the hub bring those learnings across.

9:31 I find that really helpful for other people to think about in their organizations how they might do that. Yeah. It is hub and spoke from a help perspective, but it is not as the concept or the visualization of hub and spoke might imply, a highly top-down process. Discovery is mostly a bottoms-up process.

9:51 It's very hard to dictate, so you have to create some structure and guardrails, but then let people be pretty free range within those guardrails, or they won't ultimately find things that are unexpected. So you have to have just enough boundary setting to keep things moving forward, but not so much that people can't be creative.

10:11 And we've seen that a lot. We've talked a lot about improvisation and how that mindset helps. In, in improv, they have some rules, and that's what allows for that creativity. Right. Let me give you an example. Obviously, we have to have a performance management system. It'd be weird if we didn't. The temptation across the whole world, so including at the Moonshot Factory, is to have our performance management system be one that rewards people for outcomes.

10:35 You rang the bell, you got the million dollars or the big deal you signed. Good for you, bonus, promotion, whatever that is. That is the death of radical innovation, because if I'm asking you to do things that have a one in 100 chance of success, and then you get rewarded on the basis of a yes, of a success, you will very quickly learn to pretend you're doing radical innovation, but find ways to get the safety of like, "Okay, maybe it's not as radical, maybe it's not as innovative, but I'll dress it up so it looks like that, and I'm pretty sure I can make this work even if it's not that exciting.

11:11 And so I'm gonna focus on this thing because I know I'm only gonna get rewarded when I get a yes." All humans will do that. And so the performance management system we have directs people back towards the habits, not towards the outcomes. What are the kinds of things like humility and curiosity that tend to have wild success as a long-term side effect?

11:38 And then you have to trust, and this is a big, scary trust fall, that those outcomes will happen when you focus on the habits. And you have good evidence that will happen. It's harder from a management point of view to measure those kind of things versus did you ring the bell or not? That's a very binary, easy thing to do.

11:54 So you have to have more flexibility and openness as managers, I guess, as well. Yeah, and this is a struggle to this day at X. It is so much harder to train managers to hold people accountable to habits rather than to outcomes, that they routinely will try to find ways to hack the system so that they can reward people for outcomes, or they'll gripe about their performance management system.

12:18 I get it. And that's an example where we're trying to create some guardrails, let them use some creativity within those guardrails, but also make sure that they're pointed, in this case, towards the habits rather than the outcomes. I really like this idea of rewarding people for habits, not for outcomes.

12:36 I really wanna dive deeper into this notion of failing fast and looking how to kill projects. Can you share a little bit about that? And you do some kind of celebration, the Dia de los Muertos, that I'd love to hear a bit about as well. Sure. We have a lot of traditions. That's one that we, we haven't done in a few years, but we did it for 7 or 8 years, the Day of the Dead celebration.

12:57 In order to help people feel good, or at least not avoid failures at X, we have to help them destigmatize it. In order to destigmatize it, you can get at that in a bunch of different ways. But some of it is, it is sad to have something that you worked on for a long time need to stop. And we set up a remembrance party.

13:21 So the Day of the Dead is a very long-standing tradition for remembering people who've gone from our lives. And so by doing that and sort of respecting that aspect of the tradition, but adding to it the sadness we have about people who've just left X, they're not dead, they've just left X. We're remembering projects that were really touching to us.

13:44 We wish they could have made it, but for a variety of reasons they didn't. It allows us the catharsis and the grieving, after which we can move on from it a lot more productively than if we're holding on to that sadness, and often then projecting anger at whoever made us stop doing that. What I find really interesting in what you said is you're really taking care not just of the act, but also the emotion that people feel about it.

14:08 So you worked hard on this thing, and maybe it didn't go where you wanted it But you have an emotion and an attachment to that, and you're allowing people to recognize it and express it in a way to hopefully move on. Even in a widget factory, humans aren't robots, and it doesn't go super well trying to treat them like robots.

14:24 But the more you want people to show up in ways that are creative, that get the most out of themselves, where they bring the most interesting parts of themselves to work and combine them in an important unexpected alchemy that turns into something like self-driving cars over time, the more you have to recognize the things that hold them back are mostly here in their hearts and down here in their guts.

14:50 Their heads are fine. The number of people in any organization who need to leave because they're incompetent is very low. The number of people who don't work out for other reasons, most of those reasons are style reasons, their egos are too large or too brittle or whatever that is. That's all about their hearts and their guts.

15:11 It's not about their heads. Absolutely. I want to take a step back. We haven't actually heard from you an example or two of what you guys have created. Can you share one moonshot that was successful so we can have an appreciation of the different types of things you work on? Let me give a few examples.

15:27 Google Brain, which is one of the places that caused the explosion of industrialized machine learning that is now the sort of hot topic in the world, that came from X. That's an example. Uh, the self-driving cars, now called Waymo, those came from X. Uh, Wing, the drones for package delivery, which are actually doing almost as well as Waymo, and people haven't caught on that it's going to be as big a deal, that came from X. And I will give some more examples, but let me use Waymo as an example.

15:59 So this is now 15 years ago. Huge problem with the world. More than a million people a year die in car accidents in the world because of human error. More than a trillion dollars is wasted between sitting in traffic and all of the costs of the accidents, even leaving death aside. Between a million lives and a trillion dollars, that's a problem worth fixing.

16:22Radical proposed solution what if, just like we got to the place with elevators

16:28 where we realized you didn't have to have a human driving the elevator, you could just trust the elevator to drive itself, we can get behind the idea that if they could drive themselves, we could get to the place where these metal boxes, like an elevator, take the passengers where they need to go, and you just push a button and say, "Here's where I want to go," and it takes you there much safer.

16:54 And there's all kinds of benefits, including maybe particularly the lives that are being saved, because those metal boxes can now take themselves there much, much safer than a human driving the car. So that's the radical proposed solution. And then there was a set of, at the time, new technologies, how to coordinate LiDAR, radar, and cameras around a vehicle.

17:20 There'd been some evidence before we started on what is now called Waymo from the DARPA Grand Challenges, the first of which in 2006 was won by Stanford here. That car was called Stanley. And DARPA, just so people understand, is something that the US federal government, it's a funding source for creative ideas that can be used for defense and other things.

17:44 Exactly. And so there was this worldwide, or at least countrywide, grand challenge that was announced about cars that could drive themselves. And while even in the second time it was run, there were three groups that completed the 150 miles. They were out in a desert. It was 1/1000th of the difficulty of what Waymo currently has to do, but it was enough evidence that maybe, just maybe, it was time.

18:08 I love that example, and many people listening perhaps have not seen a Waymo or been in one. I have, and where I live is where a lot of them were tested, so I'm a little more used to it. It is freaky to be in the back of a car that has no driver, but it is absolutely cool as well. And I assume that you are seeing some of the goals realized, like more safe arrival, fewer accidents, et cetera.

18:31 Yeah, the evidence we have is that the Waymo cars are at least an order of magnitude safer than human drivers in similar situations. And of course, every time a Waymo car learns anything, all of the cars get that learning, so it's a one-way ratchet of safety. I have been in San Francisco, where you literally see a fleet of them driving people around, and it's very cool.

18:57 I want to come to something that you just did. You just told us not just about Waymo, but you told us a story. How important is storytelling in defining and realizing moonshots? I think storytelling is phenomenally important, but I watch people at the Moonshot Factory get a little bit confused about this.

19:17 At least when I say storytelling, I don't primarily mean marketing or just getting someone excited. I mean, if you worked at X and you're proposing that we start a moonshot for teleportation, let's say, I need from you an architecture of understanding. Where are we trying to go? What makes us think we might be able to get from where we are to there?

19:40 And how should we interpret things along the way? What's that set of lily pads that you can envision? You'll be wrong. I'm fine with the fact that you're wrong, but if you can't paint that picture so that we have a hypothesis to test, it's very hard to get behind the idea that the upside of getting there will be worth the risks if you can't even paint an idealized picture of how we would get there in a controlled way where the costs aren't out of control, where nobody gets hurt, et cetera.

20:11 The idea of an architecture of understanding is what a story provides, and the outcome of the story for you that's important is a hypothesis that can be tested, and that's a really unique way, I think, of looking at storytelling. You are very good at telling stories. I'm wondering, do you reflect often on how to tell stories better?

20:29 I noted in the Waymo story one tool you seem to use is analogies. You talked about self-driving car being like an elevator, and that makes it very accessible. I might not have been in a self-driving car, but I've certainly been in an elevator. Talk to me about your own internal process for the stories you tell.

20:45 What do you think about? I think I understand the world mostly through mechanisms and call it the gross high-level systems thinking. That's just how I understand the world, which makes it easy for me to find two things that feel related because they have similar mechanisms, like I just did in this example between Waymo and elevators.

21:07 Now, I can sometimes get caught. Let me tell you an example where I was wrong. I mean, I wasn't intellectually wrong, but I was wrong as a storyteller. For quite a long time, I used as an analogy to help people understand about what we're trying to do at X. And I would say, "We are not the gamblers of innovation. We are working really hard to be the card counters of innovation."

21:30 If we go back to that conversation we just had about habits versus outcomes, whether you win or not, let the statistics take care of that. I want you to focus on playing the odds, those are the habits, correctly. So you can see the analogy with card counting. Only I've discovered more recently that a lot of people would nod along with me when I said card counting and used that as an analogy to what we're trying to do to systematize radical innovation at the Moonshot Factory, only to discover more recently, most people don't really understand card counting.

22:03 Am I right that that's a good analogy? Maybe. But as a storyteller, I'm failing if I'm using analogy that doesn't really connect with people because they don't understand the mechanism of, of card counting. So whatever tools you use to tell a good story, you have to make sure that they're doing their job.

22:20 And that required you to do a fair amount of reflection because most people just tell a story and move on to the next story rather than reflecting, is it really working? So that reflective piece is important and not surprising because a lot of what it sounds like you do is reflect and learn. Can we dive deeper into creativity?

22:37 You've given us some ideas, focus on habits, failure is essential. Are there other things you have found really help spark and not just spark creativity, but foster it and keep it growing? One of the things that people struggle with is the reality that creativity's wellspring is almost entirely humor.

23:00 Being serious and being creative are nearly impossible to do at the same time. Creativity is a willingness to scramble your understanding in some maybe random or not random way And that means there's a looseness that has to happen. The idea of seriousness is a tightening up. It is an organizational imperative.

23:27 That's what the idea of serious is. So you hear from people, "Are you playing or are you working?" Because we think fundamentally that work is serious and that the alternate when we're having fun, that's not work. But creativity, as I just described, only happens in the play state. And so constantly trying to inculcate a sense of wonder, silliness, experimentation without concern for looking silly, for example, looking dumb, is absolutely required in order to be really creative.

24:06 And yet people resist that push for playfulness. So I find that's one of the things that we have to keep coming back to at X is I'm not asking for silliness because I disrespect the journey that we're on. I'm demanding silliness and playfulness because the journey we're on is so serious in its goal and can only be seriously pursued through a non-serious attitude.

24:36 What are some things that you specifically do to bring silliness and playfulness into work? Well, as we were talking before we started, I live on my rollerblades at work. One, it's just fun for me, frankly. Two, I get around a little bit faster. I probably save eight or nine minutes a day. It's a fairly big building.

24:54 But three, it sends a signal to people not to take me too seriously, not to take themselves too seriously, not to take the work too seriously. And when they see me doing that, I don't need them to wear rollerblades, but unconsciously it's one of 100 signals that we send each other at the Moonshot Factory to keep ourselves from tightening up into the rigidity of seriousness.

25:20 When you interview people to come on and be part of the X team, give me an example of an interview question you would ask that helps you get insight into if this person will fit into the culture and perhaps help prepare them for what the culture would be like. I mean, one of the main interview questions I ask, but it's not a trick, so you can't prep for it really, is if you come to work at X and you don't really understand what we're trying to do, 'cause you just think it's cool from the outside, like watching someone jump out of an airplane, but when I have you at the door of the airplane and I'm asking you to jump, it might not seem like your jam anymore.

25:58 And I reserve the right, we reserve the right, to torture you if you're at X and you're not actually down for the thing we're trying to do, for those habits. So this is not an interview. You and I should be failing fast together. If we can possibly discover that you're not right, that's definitely in my best interest, but it's also in your best interest.

26:18 And I know some part of you wants to believe that you guys, your job here is to trick me into hiring. But look at me, I am serious. I will torture you if you do that. You will not be happy on the other side of this. You and I want the same thing in this moment. So let's spend the next 45 minutes trying to fail fast here, verifying why you won't be happy at X.

26:43 Wow, that's like an experiential interview on steroids, where it's, you wanna have that experience of failing, and you wanna be comfortable that that person is okay with it. Number one, if somebody isn't comfortable doing that with me, then they're probably not gonna fit at X. But if they are comfortable doing that with me, then I'm getting what I want, which is for us to have a real conversation about why it might not work out.

27:04 I can only imagine people come away feeling that experience was special and unique, and you probably end up bringing someone on who works out. Your success rate is much higher, likely. It is quite high. It's certainly not 100%. I would also say that our success rate is as good as it is partly because we're very flexible.

27:22 If I was hiring you to come on, I would say, "I do not have a perfectly shaped job for you here." You might suspect what it is, but let's be honest, if you're coming in, I'm gonna be running naked and so are you, and we're gonna basically invent your job on your way in and probably for the first year or two you're with us.

27:41 And if that's not your jam, please don't come, because all of X is like that. It's just gonna drive you crazy. But if you're up for that, we have a better chance of winning because I don't have to be right ahead of time about exactly what your superpowers are. We can design a job around your superpowers.

27:57 It sounds like that's a perfect example of what you talked about earlier about setting some boundaries, but not being rigid. Allow that flexibility. So you've added podcast host to your list of titles and accomplishments. What do you think about the hosting gig, and what motivated you to start the show?

28:13 I listen and I love it. I've learned a lot. It's really cool for me to be in person with you after having listened to you in my headset. What brought it about? First, if people are interested, they can just look up Moonshot Factory, Moonshot Podcast. We were turning 15 years old, and at least one of the things was we're trying to get a little bit less secret, and we wanted to start exposing some of how we work and what we've done, what we've learned, partly because we want to empower other people to take their own moonshots.

28:44 And giving them that learning opportunity hopefully gives them a boost. Rather than me just blah blah blah-ing about moonshot taking, what we've done is we've sliced it up into about 50-minute episodes, 10 of them in the first season, where we've given people who've come through the Moonshot Factory a chance to tell their stories, what they've learned.

29:06 So you get to hear in the first person what it was like to be taking those moonshots. And these are some people who are now luminaries in their field, Sebastian Thrun or Andrew Ng or Jeff Dean and others. And how did we get to something like Google Brain? How did we get to something like Waymo, the self-driving cars?

29:25 And when you hear from them the mistakes they made or those initial things that gave them the faith to start, that, that seed crystal that they thought was worth building on, I hope it then helps other people not only understand us and the moonshots we take, but inspire them to go do some of their own.

29:44 It's very inspirational, and it's really cool to hear in their own words what they've done. And there are learnings that come. I have listened and thought differently about ways I team with people and the ways that I think about the decisions I need to make. So I'm excited that you're doing it, and I'm excited to listen to season two.

30:02 Before we end, I ask all my guests three questions. One I create just for you, and then the other two are similar. Are you up for that? Sure. I'd be very curious, what's a current moonshot you're working on that has you really excited? We started this about eight years ago. This is very typical of the moonshots we take.

30:17 They seem crazy when we start them, and then at least occasionally, much later, they turn out to be in the right place at the right time, is a moonshot for the electric grid. It turns out that everyone would like to make software that helps the electric grid get better, including us, and you can't. You can't until somebody has a circuit diagram for the grid itself.

30:42 If you don't have a digital twin for the grid, where every wire is, where every inverter is, where every transformer is, no software on top of that will help you manage what you have or plan for the future or optimize it in real time. And so what our team, Tapestry, did over the last seven years was build out the tools for taking in a wide variety of data, including the very noisy and imperfect data that grid operators have about their own grid, 'cause they don't have a map of their own grid.

31:15 And then using lots of different sources, Street View cars, drone data, satellite data, lots of different inputs, we can then use induction and deduction to do the detective work and back out the exact grid that a particular grid operator has. And then we can help them manage the grid they have, plan for the future of their grid, and optimize their grid in real time.

31:41 So it's as if you've decoded the genome for the grid, and now we can do some work with it. That sounds very useful and hopefully very beneficial. Question number two, who is a communicator that you admire and why? I enjoy giving public talks, and so oration has always been very interesting to me. And I have watched a wide variety of public speakers, not because I'm going to be any one of them, but to understand how each of their patterns functions.

32:11 You know, Martin Luther King Jr., great speaker. His preacher style, there are things you can learn from that. James Baldwin, amazing speaker. Not a preacher. Somewhat professorial, but with a calm angriness because of the specifics of the life that he led. Barack Obama, very professorial. My grandfather, Edward Teller, actually was another great public speaker, and I learn a lot from watching each of these people.

32:40 Yeah, they each bring a really interesting approach that you can then synthesize. And by the way, your TED Talk is one that everybody should listen to because you deliver it very well and it's very exciting to learn from. Final question, what are the first three ingredients that go into a successful communication recipe?

32:57 I personally don't love the start with a personal story. I would encourage people to get real, as in honest, get specific, and you can be human. So when we tell a story, like in our podcast, we use visuals from the field, from the actual people who are doing it. We explain what we were trying to do and how where we actually ended up wasn't that, getting real.

33:28 We show people how we harvest value even from being wrong, and can have fun in the process of learning. And when you get a cycle of those three things, while that doesn't feel like Mary Jane in Idaho, start of the sort of New York Times article, it is deeply human. You can feel what it feels like for these people to go through it.

33:50 It's exciting, it's meaningful, you can see yourself in it, it's memorable because of those things. So that's how we try to do it. Be real, be specific, be human, and all of that allows you to connect through emotion. And I appreciate that recipe. And I appreciate this conversation, Astro. This was fantastic.

34:07 You've talked about architecting to understanding, and you certainly did that for us, and I hope all of us can build these habits and reward ourselves for these habits and not just outcomes. Thank you for your time. Thank you. That was a lot of fun. Thank you for joining us for another episode of Think Fast, Talk Smart, the podcast.

34:24 It was great learning from Astro. Among the many ideas he shared, the one that stands out most to me is that being wrong isn't something we should avoid. It's often where the most important learnings happen, and embracing it can help us move forward faster. To learn more about creativity and innovation, please listen to episode 70 and 120 with Jeremy Utley and Tina Seelig.