a16z Podcast: Innovating in Bets

with @annieduke, @pmarca, and @smc90 Every organization, whether small or big, early or late stage -- and every individual, whether for themselves or others -- makes countless decisions every day, under conditions of uncertainty. The question is, ar...

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Hi, everyone. Welcome to the A6NC Podcast. I'm Sonal. And today, Mark and I are doing another one of our book author episodes. We're interviewing Annie Duke, who's a professional poker player and World Series champ, and is the author of Thinking in Bets, which is just out in paperback today. The subtitle of the book is Making Smarter Decisions When You Don't Have All the Facts, which actually applies to startups and companies of all sizes and ages, quite frankly. I mean, basically, any business or new product line operating under conditions of great uncertainty, which I'd argue is my definition of a startup and innovation. So that will be the frame for this episode. Annie's also working on her next book right now and founded HowIDecide.org, which brings together various stakeholders to create a national education movement

• 0:43Speaker 00

  around decision education, empowering students to also be better decision makers. So anyway, Mark and I interview her about all sorts of things in and beyond her book, Going from Investing to Business to Life. But Annie begins with a thought experiment, even though neither of us really know that much about football. So what I'd love to do is kind of throw a thought experiment at you guys so that we can have a discussion about this. So I know you guys don't know a lot about football, but this one's pretty easy. You're going to be able to feel this one, which is do this thought experiment. Pete Carroll calls for Marshawn Lynch to actually run the ball.

• 1:16Sonal?

  So we're betting on someone who we know is really good.

• 1:18Speaker 00

  Well, they're all really good, but we're betting on the play that everybody's expecting.

• 1:21Marc Andreessen?

  Yeah, the default is the assumed rational thing to do.

• 1:24Speaker 00

  This is the assumed rational thing to do, right? So he has Russell Wilson handed off to Marshawn Lynch. Marshawn Lynch goes to barrel through the line. He fails. Now they call the timeout. So now they stop the clock. They get another play now, and they hand the ball off to Marshawn Lynch. What everybody expects. Marshawn Lynch, again, attempts to get through that line, and he fails. End of game, Patriots win. My question to you is, are the headlines the next day, the worst call in Super Bowl history? Is Chris Collinsworth saying, "I can't believe the call. I can't believe the call." Or is he saying something more like, "That's why the Patriots are so good. Their line is so great. That's the Patriots line that we've come to see this whole season."

• 2:10Speaker 00

  We'll seal Belichick's place in history. It would have all been about the Patriots. So let's sort of divide things into like, we can either say the outcomes are due to skill or luck. And luck in this particular case is going to be anything that has nothing to do with Pete Carroll. And we can agree that the Patriots line doesn't have anything to do with Pete Carroll. Belichick doesn't have anything to do with Pete Carroll. Tom Brady doesn't have anything to do with Pete Carroll as they're sealing their fifth Super Bowl victory. So what we can see is there's two different routes to failure here. One route to failure, you get resulting. And basically what resulting is, is that retrospectively, once you have the outcome of a decision, once there's a result, it's really, really hard to work backwards from

• 2:53Speaker 00

  that single outcome to try to figure out what the decision quality is. This is just very hard for us to do. They say, oh, my gosh, the outcome was so bad. This, this is clearly, I'm going to put that right into the skill bucket. This is because of Pete Carroll's own doing. But in the other case, they're like, oh, you know, there's uncertainty. What could you do? Weird, right? Yeah. Okay. So you can kind of take that and you can say, aha, now we can sort of understand some things. Like, for example, people have complained for a very long time that in the NFL, they have been very, very slow to adopt what the analytics say that you should be adopting. Right? And even though now we've got some movement on like fourth down calls and when you're going for two point conversions and things like that, they're still nowhere close to where they're supposed to be.

• 3:38Marc Andreessen?

  So they don't, so they don't make the plays corresponding to the statistical probabilities?

• 3:41Speaker 00

  No, in fact, the analytics show that if you're on your own one yard line and it's fourth down, you should go for it, no matter what. The reason for that is if you kick it, you're only going to be able to kick to midfield. So the other team is basically almost guaranteed three points anyway. So you're supposed to just try to get the, try to get the yards. Like, when have you ever seen a team on their own one yard line on fourth down be like, yeah, let's go for it? That does not happen. Okay. So we know that they've been like super slow to do what the analytics say is, is correct. And you, and so you sit here and you go, well, why is that? And that thought experiment really tells you why. Because we're all human beings. We all understand that there are certain times when we don't allow uncertainty to bubble up to the surface is the explanation.

• 4:24Speaker 00

  And there are certain times when we do. And it seems to be that we do when we have this kind of consensus around the decision. There's other ways we get there. And so, okay, if I'm a human decision maker, I'm going to choose the path where I don't get yelled at.

• 4:39Sonal?

  Yeah, exactly.

• 4:40Speaker 00

  So basically, we can kind of walk back and we can say, are we allowing the uncertainty to bubble to the surface? And this is going to be the first step to kind of understanding what really slows innovation down, what really slows adoption of what we might know is good decision making because we have conflicting interests, right? Making the best decision for the long run or making the best decision to keep us out of a room where we're getting judged.

• 5:03Marc Andreessen?

  Yelled at, yelled at, or possibly fired. So can I, let me propose the framework that I used to think about this and see if you agree with it. So it'd be a two by two, a two by two grid and it's consensus versus non-consensus and it's right versus wrong. And the way we think about it, at least in our business, is basically consensus right is fine, consensus, non-consensus right is fine. In fact, generally, you get called a genius. Consensus wrong is fine because you just, you know, it's just the same mistake everybody else made.

• 5:31Sonal?

  You all agree, right?

• 5:32Marc Andreessen?

  Non-consensus wrong is really bad.

• 5:34Speaker 00

  Horrible.

• 5:35Marc Andreessen?

  It's radioactively bad.

• 5:36Speaker 00

  Right.

• 5:36Marc Andreessen?

  And so, and then, and then as a consequence of that, and maybe this gets to the innovation stuff that you'll be talking about, but as a consequence of that, there are only two scripts for talking about people operating in the non-consensus directions. One script is they're a genius because it went right. And the other is they're a complete moron because it went wrong. Is that, does that map?

• 5:55Speaker 00

  That's, that's exactly, that's exactly right. And I think that the problem here is that what does right and wrong mean? In your two by two, wrong and right is really just did it turn out well or not?

• 6:05Marc Andreessen?

  Yeah, outcomes.

• 6:05Speaker 00

  And this is where we really get into this problem because now what people are doing is they're trying to swat the outcomes away. And they understand, just as you said, that on that consensus wrong, you will have like a cloak of invisibility over you, like you don't have to deal with it.

• 6:21Sonal?

  Right.

• 6:21Speaker 00

  So let's think about Other things besides consensus. So consensus is one way to do that, especially when you have like complicated cost benefit analyses going into it. I don't think that people, when they're getting in a car, are actually doing any kind of calculation about what the cost benefit analysis is to their own productivity versus the danger of something very bad happening to them. Like, what is the society? Someone's done this calculation. We've all kind of done this together. And so therefore, like, getting in a car is totally fine. I'm gonna do that.

• 6:53Marc Andreessen?

  And nobody second guesses anybody. If somebody dies in a car crash, you don't say, "Wow, what a moron for getting in a car."

• 6:57Speaker 00

  No. Another way that we can get there is through transparency. So if the decision is pretty transparent, another way to get there is a status quo. So like, a good status quo example that I like to give, because everybody can understand it, is you have to get to a plane, and you're with your significant other in the car, and you go the usual route.

• 7:18Sonal?

  This is the common sight of fights for every couple.

• 7:19Speaker 00

  So you go your usual route. Like, you go the, literally, this is the route that you've always gone, and there's some sort of accident, there's bad traffic, you miss the plane, and you're mostly probably comforting each other in the car. It's like, what could we do? You know? But then, you get in the car, and you announce to your significant other, "I've got a great shortcut. So let's take this shortcut to the airport." And there's the same accident, whatever, horrible traffic, you miss the flight. And that's like that status quo versus non-status quo decision.

• 7:48Sonal?

  Right. You're going against what's familiar and comfortable.

• 7:50Speaker 00

  Exactly. If we go back to the car example, when you look at what the reaction is to a pedestrian dying because of an autonomous vehicle versus because of a human, we're very, very harsh with algorithms. For example, if you, if you get in a car accident, and you happen to hit a pedestrian, I can say something like, you know, "Well, Mark didn't intend to do that." Because I think that I understand, your mind is not such a black box to me. So I feel like I have some insight into what your decision might be. And so more allowing some of the uncertainty to bubble up there. But if, if this black box algorithm makes the decision, now all of a sudden, I'm like, get these cars off the road.

• 8:30Sonal?

  Never mind that the human mind is a black box itself, ultimately, right?

• 8:32Speaker 00

  Of course. But we, we have some Sort of illusion that I understand sort of what's going on in there, just like I have an illusion that I understand what's going on in my own brain. And you can actually see this in some of the language around crashes on Wall Street, too. When you have a crash that comes from human beings selling, people say things like, the market went down today. When it's algorithms, they say it's a flash crash. So now they're sort of pointing out like, this is clearly in the skilled category. It's the algorithm's fault. We should really have a discussion about algorithmic trading and whether this should be allowed. When obviously, the mechanism for the market going down is the same either way. So now, if we understand that, so exactly your matrix. Now we can say, well, okay, human beings understand what's going to get them in the room.

• 9:12Speaker 00

  And pretty much anybody who's, you know, living and breathing in the top levels of business at this point is going to tell you, process, process, process. I don't care about your outcomes, process, process, process. But then the only time I ever have like an all hands on deck meeting is when something goes wrong. Like, let's say that you're in a real estate investing group. And so you invested in a particular property based on your model. And the appraisal comes in 10% lower than what you expected. Like, everybody's in a room, right? You're all having a discussion. You're all examining the model, you're trying to figure out. But what happens when the appraisal comes in 10% higher than expected? Is everyone in the room going, what happened here?

• 9:49Marc Andreessen?

  Now, there is the obvious reality, which is like, we don't get paid in process, we get paid in outcomes. Poker players, you don't get paid in process, you get paid in outcome. And so there is a

• 9:57Speaker 00

  Incentive alignment.

• 9:58Marc Andreessen?

  It's not completely emotional. There's also an actual, there's a real component to it.

• 10:02Speaker 00

  Yeah, so two things. One is, you have to make it very clear to the people who work for you that you understand that outcomes will come from good process. That that's number one. And then number two, what you have to do is try to align the fact that as human beings, we tend to be outcome driven to what you want in terms of getting, getting the, an individual's risk to align with the enterprise risk. Because otherwise, you're going to get this CYA behavior. And the other thing is that we want to understand if we have the right assessment of risk. So one of the big problems was with the appraisal coming in 10% too high there. Could be that your model's correct. It could be that you could have just a tail result. But it certainly is a trigger for you to go Look and say, was there a risk in this decision that we didn't know was there?

• 10:46Speaker 00

  And it's really important for deploying resources.

• 10:49Sonal?

  I have a question about translating this to say, non-investing context. So if, in the example of Mark's matrix, even if it's a non-consensus wrong, you are staking money that you are responsible for. In most companies, people do not have that kind of skin in the game.

• 11:07Speaker 00

  Right.

• 11:07Sonal?

  So how do you drive accountability in a process-driven environment? That the results actually do matter? You want people to be accountable, yet not overly focused on the outcome. Like, how do you calibrate that?

• 11:17Speaker 00

  So let's think about how can we create balance across three dimensions? That makes it so that the outcome you care about is the quality of the forecast. So first of all, obviously, this demands that you have people making forecasts. You have to state in advance, here's, here's what I think. This is my model of the world. Here are where all the places are going to fall. So this is what I think. So now you've stated that and the, the whether the outcome is quote unquote, good or bad is how close are you to whatever that forecast is? So now it's not just like, oh, you won to it or you lost to it. It's was your forecast good? So that's piece number one is make sure that you're trying to be as equal across quality as you can and focus more on forecast quality

• 12:00Speaker 00

  as opposed to like traditionally what we would think of as outcome quality. So now the second piece is directional. So when we have a bad outcome and everybody gets in the room, when was the last time that someone suggested, well, you know, we really should have lost more here?

• 12:17Sonal?

  Right, right.

• 12:19Speaker 00

  Nobody's saying that, but sometimes that's true. Sometimes if you examine it, you'll find out that you didn't, you didn't have a big enough position. It turned out, okay, well, maybe we should have actually lost more. So you want to ask both up, down and orthogonal. So could we have lost less? Should we have lost more? And then the question of should we have been in this position at all?

• 12:42Marc Andreessen?

  So in venture capital, after a company works and exits, like says, sells for a lot of money, you do often say, God, I wish we had invested more money. You never, ever, ever, ever, I have never heard anybody. What do you say on a loss, we should have invested more money?

• 12:55Speaker 00

  See, I wouldn't be great if someone said that. Like, wouldn't you love for someone to come up and say that to you?

• 13:00Sonal?

  I actually still don't get-

• 13:01Speaker 00

  That would make you so happy.

• 13:02Marc Andreessen?

  And what would be the logic of, what would be the logic of why they should say that?

• 13:03Sonal?

  I still don't get the point. Exactly. Why does that matter? I don't really understand that.

• 13:06Speaker 00

  So let's, can I just, like, simple in a poker example?

• 13:09Sonal?

  Yeah, yeah.

• 13:09Speaker 00

  So let's say that I get involved in a hand with you, and I have some idea about how you play. And I have decided that you are somebody that if I, if I bet X, you will continue to play with me. Let's say this is a spot where I know that I have the best hand, but if I bet X plus C, that you will fold. So if I go above X, that I'm not going to be able to keep you coming along with me, but if I bet X or below, that you will. So I bet X. You call, but you call really fast in a way that makes me realize, oh, I could have actually bet X plus C. You hit a very lucky card on the end, and I, I happened to lose a pot. I should have maximized at the point that I was a mathematical favorite.

• 13:50Marc Andreessen?

  Your model of me was wrong, which is a learning independent of the winner or the loss.

• 13:53Speaker 00

  Exactly. So you need to be exploring those questions in a real honest way.

• 13:58Marc Andreessen?

  Right. Because it has to do with how you size future bets.

• 14:01Sonal?

  This is exactly like a company betting on a product line.

• 14:03Speaker 00

  Correct.

• 14:03Sonal?

  And then like ticking like, you know, what the next product line is going to be, and then not having had the information that would then drive a better decision-making process around that.

• 14:11Speaker 00

  Right. So think about the learning loss that's happening because we're not exploring that. The negative direction is, and now you should do this on wins as well. So if you do ever discuss a win, you always think like, how could I press? How could I have won more? How could I have made this even better? How could I do this again in the future? Should we have won less?

• 14:27Marc Andreessen?

  We oversized the bet and then got bailed out by a fluke.

• 14:29Speaker 00

  We should have actually had less in it, and sometimes not at all, because sometimes the reasons that we invested turned out to be orthogonal to the reasons that it actually ended up playing out in the way that it was. And so had we had that information, we actually wouldn't have bet on this at all. Because it was completely orthogonal, like, we totally had this wrong. It just turned out that we ended up winning, and that, that can happen. I mean, obviously, that happens in poker all the time, but what does that communicate to the people on your team? Good, bad, I don't care. I care about our model. I want to know that we're modeling the world well and that we're thinking about how do we incorporate the things that we learn because we can generally think about stuff in two kinds, stuff we know and stuff we don't know. There's stuff we don't know we know, obviously. So, well, we don't worry

• 15:12Speaker 00

  about that because we don't know we don't know it. But then there's stuff we could know and stuff we can't know. It's things like the size of the universe or the thoughts of others or what the outcome will actually be. We don't know that.

• 15:23Sonal?

  I have a question about this, though. What is a timeframe for that forecast? So, let's say you have like a model of the world, a model of a technology, how it's going to adopt, how it's going to play out. In some cases, there are companies that can take like years to get traction. You want to get your customers very early to figure that out, right? So you can get that data. But how much time do you give? Like, how do you size that timeframe for the forecast? Like, so you're not constantly updating with every customer data point? And so you're also giving it enough time for your model, your plan, your forecast to play out?

• 15:54Speaker 00

  You have to think about very clearly in advance, what's my time horizon? How long do I need for this to play out? But also, not, don't just do this for the big decisions because there's things that you can forecast for tomorrow as well, so that you end up bringing it into just the way that people think. And then, once you've decided, okay, this is the time horizon of my forecast, and you would want to be thinking about what are forecasts we make for a year, two years, five years for the specific decision to play out. And then, just make sure that you talk in advance at what point you'll revisit the forecast. What, so you want to think in advance, what are the things that would have to be true for me to be willing to come in and actually revisit this forecast? Because otherwise, you can start, as you just said, like, you can turn into like-

• 16:38Sonal?

  You're like a leaf in the wind.

• 16:40Speaker 00

  Right, exactly. Because then you're like one bad customer and you suddenly like over rotate on that when in fact, it could have been- Right. So if you include that, if you include that in your forecast, here are the circumstances under which we would come in and check on our model, then you've already got that in advance. So, that's actually creating constraints around the reactivity, which is helpful.

• 16:59Marc Andreessen?

  Two questions on practical implementation of the theory. So, what I'm finding is more and more people understand the logic of what you're discussing. Because people are getting exposed to these ideas and kind of expanding in importance. And so more and more people intellectually understand this stuff. But there's two kind of, I don't know, so call it emotion driven warps or something that people just really have a hard time with. So one is they, you understand, this could be true of investor, CEO, product line manager in a company, you know, kind of anybody in one of these domains, which is you can't get the non consensus right results unless you're willing to take the damage, right? The risk on the non consensus wrong results. But people cannot cope with a non consensus wrong outcome. They just emotionally cannot handle it and they would like to think that they can and they intellectually understand that they should be able to. But as you say, when they're in the room, it's such a traumatizing experience that it's the touching the hot stove.

• 17:44Marc Andreessen?

  They will do anything in the future to avoid that. Is that just a, and so like one interpretation would be that's just simply flat out human nature. And so to some extent, the intellectual understanding of here doesn't actually matter that much because there's an emotional override. And so that would be a pessimistic view on our ability as a species to learn these lessons? Or do you have a, do you have a more optimistic view of that?

• 18:01Speaker 00

  I'm going to be both pessimistic and optimistic at the same time. So let me explain why. Because I think that if you move this a little bit, it's a huge difference. You sort of have two tacks that you want to take. One is how much can you move the individual to sort of train this kind of thinking for them? And that means naturally they're thinking and forecasts a little bit more that when they do have those kinds of reactions, which naturally everybody will, they right the ship more quickly so that they can learn the lessons more quickly. Right? I mean, I actually just had this happen. I turned in a draft of my next book, the first part of my next book to my editor, and I just got the worst comments I've ever gotten back. And I had a really bad 24 hours, but after 24 hours, I was like, you know what? She's right.

• 18:43Speaker 00

  Now, I still had a really bad 24 hours and I'm the like, give me negative feedback like queen because I'm a human being, but I got to it fast. Like I sort of got through it pretty quickly after this. I mean, I, you know, the, you know, on the phone with my agent saying, I'm standing my ground. This is ridiculous. And then he got a text the next day being like, no, she's right. And then I rewrote it and you know what? It's so much better for having been rewritten and now I can get to a place of gratitude for having the negative feedback. But, but I still had the really bad day. So it's okay. It doesn't go away. Right? Yeah. And it's okay. Like we're all human, like we're not robots. So number one is like, how much are you getting the individuals to say, okay, I improved 2%. That's so amazing for my decision making and my learning going forward.

• 19:27Speaker 00

  And then the second through line is what are you doing to not make it worse? Because obviously, for a long time, people like to talk about I'm results oriented. I feel like the worst sentence that could come out of somebody's mouth.

• 19:40Sonal?

  Why is that the worst? I've heard that a lot. What's so bad about it?

• 19:42Speaker 00

  Because you're letting people know that all you care about is like, did you win or lose? That's fantastic. Be results oriented all you want. You should pay by the piece. You will get much faster work. But the minute that you're asking people to do intellectual work, results oriented is like the worst thing that you could say to somebody. So I think that we need to take responsibility and the people in our orbit, we can make sure at minimum that we aren't making it worse.

• 20:04Marc Andreessen?

  Yeah.

• 20:05Speaker 00

  And I think that that's pessimistic and optimistic. I don't think anyone's making a full reversal here.

• 20:10Marc Andreessen?

  So the second question then goes to the societal aspect of this. And so we'll talk about the role of the storytellers, or as they're sometimes known, the journalists.

• 20:19Speaker 00

  Yeah, the editors. I love it.

• 20:20Marc Andreessen?

  And the editors, and the editors, and the publishers. And so the very first reporter I ever met when I was a kid, Jared Sandberg at the Wall Street Journal, when the internet was first emerging, like, there were no stories in the press about the internet. And I used to say, like, there's all this interesting stuff happening. Why am I not reading about any of it in any of these newspapers? And he's like, well, because the story of something is happening is not an interesting story. He said, there are only two stories that sell newspapers. He said, one is, oh, the glory of it. And the other is, oh, the shame of it. And basically, he said, it's conflict. So it's either something wonderful has happened or something horrible has happened. Like, those are the two stories. And then you think about business journalism as kind of our domain. You're going to think about it as like, those are the only two profiles of a CEO or founder you'll ever read. It's just like, what a super genius for doing something presumably not consensus and right. Or what a moron. Like, what a hopeless idiot for doing something non-consensus and wrong.

• 21:03Marc Andreessen?

  And so, and so since I've become more aware of this, like, it's actually gotten, it's gotten very hard for me to actually read any of the coverage of the people I know, because it's like, the people who got not consensus right, they're being lavished with too much praise. And the people who got not consensus wrong, they're being damned for all kinds of reasons. The traits are actually the same in a lot of cases. And so I guess as a consequence, like, if you read the coverage, it really reinforces this bias of being results oriented. And it's like, it's not our fault that people don't want to read a story that says, well, he tried something and it didn't work this time, right?

• 21:34Speaker 00

  Yes, exactly.

• 21:35Marc Andreessen?

  And so is there a-

• 21:35Speaker 00

  But it was mathematically pretty good. If we go back to Pete Carroll, this is a pretty great case. If we think about options theory, that just quickly, the pass preserved the option for two run plays. So if you want to get three tries at the end zone instead of two, strictly for clock management reasons, you pass first.

• 21:51Marc Andreessen?

  And that's not going to kick off ESPN SportsCenter that night. And so optimistic or pessimistic that the narrative, the public narrative on these topics will ever move.

• 22:00Speaker 00

  I'm super, super pessimistic on the societal level, but I'm optimistic on if we're educating people better, that we can equip them better for this. So I'm really focused on how do we make sure that we're equipping people to be able to parse those narratives in a way that's more rational? And particularly, you know, now there's so much information and it's all about the framing and the storytelling. And it's particularly driven by what's the interaction of your own point of view? We could think about it as partisan point of view, for example, versus the point of view of the communicator of the information? And how is that interacting with each other? You know, in terms of like, how critically are you viewing the information?

• 22:44Speaker 00

  For example, I think this is another really big piece of the pie and somewhat actually related to the question about journalism, which is that third dimension of the space. So we talked about two dimension, which is sort of outcome quality and how are you allowing that you're exploring both downside and upside outcomes? In a way that's really looking at forecast? How are you thinking directionally? So that you're more directionally neutral? But then the other piece of the puzzle is how are you treating omissions versus commissions? So one of the things that we know with this with this issue of resulting is here's a really great way to make sure that nobody ever results on you. Don't do anything.

• 23:21Sonal?

  Right.

• 23:22Speaker 00

  Okay, so like, if I just don't ever make a decision, I'm never going to be in that room with everybody yelling at me for the stupid decision I made because I had a bad outcome. But we know that not making a decision is making a decision. We just don't think about it that way. And it doesn't have to just be about investing. You can have a shadow book of your own personal decisions. So, you know, it's really interesting. I remember I was giving somebody advice who was like, I think he was like 23. And, you know, so obviously, you know, newly out of college, had been in this position for a year and was really, really unhappy in the position. And he was asking me like, I don't know what to do. I don't know if I should change jobs. And I said, well, you know, so I did all the tricks, you know, time traveling. And so I was like, well, okay, imagine it's a year from now. Do you think you're going to be happy in this job? No.

• 24:07Speaker 00

  Okay, well, maybe you should go and choose this other. Maybe you should go and try to find another position. And this is what he said to me, and this I think shows you how much people don't realize that the thing you're already doing, the status quo thing, choosing to stay in that really is a decision. So he said to me, but if I go and find another position and then I have to spend another year, which I just spent trying to learn the ins and outs of the company, and it turns out that I'm not happy there, I'll have wasted my time. And I said to him, okay, well, let's think about this, though. The job you're in, which is a choice to stay in, you've now told me it's 100% in a year that you will be sad. Then if you go to the new job, yes, of course, it's more volatile. But at least you've opened your, you've opened the range of outcomes up.

• 24:50Speaker 00

  But he didn't want to do it because it doesn't feel like staying where he was didn't feel like somehow he was choosing it. So that he felt like if he went to the other place and he ended up sad, that somehow that would be his fault and a bad decision.

• 25:03Sonal?

  So profound. In my case, this might be getting a little too personal, but in my case, it was a decision that I didn't know I had made to not have kids. And it's still an option, but it's probably not going to happen. And my therapist kind of told me that my not deciding was a choice. And I was like so blown away by that, that it then allowed me to then examine what was going on there in that framework in order to not do that for other arenas in my life where I might actually want something. Or maybe I don't, but at least it's a choice that there's intentionality behind it.

• 25:33Speaker 00

  Well, I appreciate you sharing. I mean, I really want to thank you for that because I think that people, first of all, should be sharing this kind of stuff so that people feel like they can talk about these kinds of things, number one. And number two, in my book, I've got all these examples in there of like, how are you making choices about raising your kids when it feels so consequential?

• 25:50Sonal?

  When you're doing decisions for other people.

• 25:51Speaker 00

  Right. And you're trying to decide like, should I have kids or shouldn't I have kids?

• 25:54Sonal?

  Or this school or that school?

• 25:55Speaker 00

  Or who am I supposed to marry? Or where am I supposed to live? Or, and the thing that I try to get across is, you know, we can talk about investing, like I'm putting money into some kind of financial instrument, but. We all have resources that we're investing.

• 26:09Sonal?

  That's right.

• 26:10Speaker 00

  It's our time.

• 26:11Sonal?

  Your time, your energy, your heart. It could be whatever, your friendships, your relationships.

• 26:15Speaker 00

  So you're deploying resources.

• 26:17Sonal?

  Yes, I love that.

• 26:18Speaker 00

  And for the kind of decision that you're talking about, it's like, if you choose to have children, you're choosing to deploy certain resources with some expected return, some of it good, some of it bad. And if you're choosing not to have children, that's a different deployment of your resources toward other things.

• 26:34Sonal?

  And you need to know that there are limits. Everything isn't a zero-sum game.

• 26:38Speaker 00

  No.

• 26:38Sonal?

  But approaching the world and the fact that evolution has approached the world as a zero-sum game, and our toolkit makes it a zero-sum game, means that we need to still view everything as a zero-sum game when it comes to those trade-offs and resources. Because you are losing something every time, even in a non-zero game.

• 26:54Speaker 00

  Right. So I don't feel like the world is a zero-sum game in terms of like, we can, most of the activities that you and I would engage on, we can both win to.

• 27:01Sonal?

  Right.

• 27:01Speaker 00

  But it's a zero-sum game, to go back to your therapist, it's a zero-sum game between you and the other versions of yourself that you don't choose.

• 27:08Sonal?

  Exactly. Or an organization and the other versions of itself that doesn't choose.

• 27:11Speaker 00

  Exactly. So there's a set of possible futures that result from not making a decision as well. So on an individual decision, let's put things into three categories: clear misses, near misses, and hits. There are some that would just be a clear miss, throw them out, and there's some that I'm going to sort of really agonize over, and I'm going to think about it, and I'm going to do a lot of analysis on it. And so the ones which become a yes go into the hit category. And the other one is a near miss. I came close. What happens with those near misses is they just go away. So what I realized is that on any given decision, let's take an investment decision. If I went to you, or you came to me and said, well, tell me what's happening with the companies that you have under consideration, on a single

• 27:56Speaker 00

  decision, when I explain to you why I didn't invest in a company, it's going to sound incredibly reasonable to you. So you'll only be able to see in the aggregate, if you look across many of those decisions, that I tend to be having this bias toward missing, toward saying, you know what, we're not going to do it, so that I don't want to stick my neck out. Now, this, for you, is incredibly hard to spot because you do have to see it in the aggregate because I'm going to be able to tell you a very good story on any individual decision. So the way to combat that and again, get people to think about what we really care around here is forecast, not really outcomes, is actually to keep a shadow book. The anti-portfolio should contain basically all of your near misses, but then you have to take a sample of the clear misses

• 28:39Speaker 00

  as well, which nobody ever looks at because the near misses tend to be a little in your periphery.

• 28:44Marc Andreessen?

  Right.

• 28:45Speaker 00

  If they happen to be big hits.

• 28:46Marc Andreessen?

  So here's the problem. So the good news, bad news. So the good news is we have actually done this. And so we call it the shadow portfolio.

• 28:52Speaker 00

  Awesome.

• 28:53Marc Andreessen?

  And the way that we do it is we make the investment. We take an equivalent, we take the other equivalent deal of that vintage of that size that we almost did, but didn't do. We put that in the shadow portfolio and we're trying to do kind of apples to apples comparison. In finance theory terms, the shadow portfolio may well outperform the real portfolio. And in finance terms, that's because the shadow portfolio may be higher variance.

• 29:11Speaker 00

  Yes.

• 29:11Marc Andreessen?

  Higher volatility, higher risk, and therefore higher return.

• 29:14Speaker 00

  Correct.

• 29:14Marc Andreessen?

  Because the fear is you're the ones that are hitting are the ones that are less, they're less spiky, they're less volatile, they're less risky.

• 29:20Speaker 00

  Right. So what's wonderful about that, when you decide not to invest in a company, you actually model out why that's in there.

• 29:28Marc Andreessen?

  It's often, by the way, it's often a single flaw that we've identified.

• 29:30Speaker 00

  Yeah.

• 29:30Marc Andreessen?

  Like, it's just like, oh, we would do it except for X.

• 29:33Speaker 00

  Right.

• 29:33Marc Andreessen?

  Where X looks like something that's like potentially existentially bad.

• 29:36Speaker 00

  Right. And then that's just written in there. And so you know that. So, and then just make sure people, like those ones that people are just rejecting out of hand.

• 29:43Marc Andreessen?

  That's my question. So we never do that. But let me ask you how to do that, though. So that's what we don't do. And as you're, as you're describing, I'm like, of course we should do that. I'm trying to think of how we would do that because the problem is we reject 99 for every one we do.

• 29:54Speaker 00

  Yeah. So you just literally, it's a sample. You just take a random sample.

• 29:58Marc Andreessen?

  A random sample, okay.

• 29:58Speaker 00

  I mean, as long as it's just sort of being kept in view a little bit because what that does is it basically just asks as pushing against your model.

• 30:06Marc Andreessen?

  Yeah.

• 30:07Speaker 00

  You're just sort of getting people to have the right kind of discussion. So all of that communicates to the people around you, like, I care about your model.

• 30:15Marc Andreessen?

  So let me ask you a different question on, because you talked about groups of decisions. So the other question, portfolios are decisions. So the other question is, so I, early on in the firm, I happened to have this discussion with a friend of mine, and he basically looked at me and he's like, you're thinking about this all wrong. You were thinking about this as a decision. You're thinking about invest or not. He said, that's totally the wrong way to think about this. You should be thinking about this is, is this one of the 20 investments of this kind, of this class size that you're going to put in your portfolio? When you're, when you're evaluating an opportunity, you are kind of definitionally talking about that opportunity. But it's, it's very hard to abstract that question from the broader concept of a portfolio or a basket.

• 30:51Speaker 00

  Yeah. What I would suggest there is actually just doing some time traveling, that as people are really down in the weeds to say, let's imagine it's a year from now, and what does the portfolio look like of these investments of this kind? So I'm a big proponent of time traveling, of just making sure that you're always asking that question. What does this look like in a year? What does this look like in five years? Are we happy? Are we sad? If we imagine that we have this, what percentage of this do we think will have failed? We understand that any one of these individual ones could have failed, so let's remember that. And I think that that really allows you to sort of get out of what feels like the biggest decision on earth, because that's the decision you have to be making and be able to see it in the context of kind of all of what's going on.

• 31:31Sonal?

  It's fantastic. One of the most powerful things my therapist gave me, and it was such a simple construct. It was sort of like doing certain things today is like stealing from my future self.

• 31:41Speaker 00

  Oh.

• 31:42Sonal?

  It blew me. It blew my mind.

• 31:44Speaker 00

  So beautiful.

• 31:45Sonal?

  It's so beautiful. And it seems so like, you know, hokey, like personal self-helpy, but actually I had never thought of, because we, we're on a continuum by making discreet individuals like Sonal in the past, Sonal today, Sonal, this woman in the future I haven't met yet. Wow.

• 32:00Speaker 00

  Yep.

• 32:01Sonal?

  Like the idea of stealing from her was like, I.

• 32:04Speaker 00

  That's really a lovely way to put it.

• 32:06Sonal?

  She's a fucking awesome therapist.

• 32:08Speaker 00

  I have an amazing therapist.

• 32:09Sonal?

  I like talking publicly about therapy because I like not giving a stigma on it.

• 32:11Speaker 00

  I'm very, very, I'm very open about, like, let's not hide it. It's totally fine.

• 32:15Sonal?

  There's no fucking reason to hide it. I totally agree.

• 32:17Speaker 00

  Some of the ways that we deal with this is actually prospectively, employing really good decision hygiene, which involves a couple of things. One is, some of this. Good time traveling that we talked about where you're really imagining what is this going to look like in the future so that that's metabolized into the decision. Two is making sure that you have pushback. Once there's consensus reached. Great. Now let's go disagree with each other. Then the next thing is in terms of the consensus problem is to make sure that you're eliciting as much input not in a room with other people. So you know, when somebody has a deal, they want to bring to everybody that that goes to the people individually, they have to sort of write their thoughts about it individually. And then it comes into the room after that.

• 32:58Marc Andreessen?

  As opposed to the pylon effect.

• 33:00Speaker 00

  As opposed to the pylon effect and that reduces the sort of effects of consensus. Anyway, so now this is how you then come up with basically what your forecast of the future is that then is absolutely memorialized because that memorializing of it acts as the prophylactic. First of all, it gives you your forecast, which is what you're trying to push against anyway. You're trying to change the attitude to be that the forecast is the outcome that we care about and it acts as a prophylactic for those emotional issues, right? Which is now you it's like, okay, well, we all talked about this and we had our red team over here and we had a good steel man going on and we kind of really thought about why we were wrong. We questioned if somebody, you know, let's if somebody has the outside view, what would this really look like to them by eliciting the information individually?

• 33:45Speaker 00

  We were less likely to be in the inside view anyway. We've done all of that good hygiene. And then that acts as a way to to protect yourself against these kinds of issues in the first place. Again, you're going to have a bad 24 hours, I'm just saying, like for sure, but you can get out of it more quickly, more often and get to a place where you can say, okay, moving on to the next decision. How do I, how do I improve this going forward?

• 34:10Marc Andreessen?

  Yeah. So building on that, but returning real quick to my optimism pessimism question. If society is not going to move on these issues, but we can move as individuals. So one form of optimism would be more of us can move as individuals. The other form of optimism could be there will just always be room in these probabilistic domains for the rare individual who's actually able to think about this stuff correctly. Like there will always be an edge. There will, there will always be certain people who are like much better at poker than everybody else. There will still-

• 34:32Speaker 00

  Oh, I think that's for sure.

• 34:33Marc Andreessen?

  Okay. Because most people simply, most people just simply can't or won't get there? Like, a few people in every domain might be able to take the time and have the discipline and willpower to kind of get all the way there, but most people can't or won't?

• 34:44Speaker 00

  I think that in some, in some ways, maybe that that's okay. Like, I mean, I sort of think about from an evolutionary standpoint, that kind of thinking was selected for, for a reason, right? Like, it's better for survival, likely better for happiness.

• 34:56Marc Andreessen?

  You mean the conventional, conventional wisdom?

• 34:58Speaker 00

  Yeah.

• 34:58Marc Andreessen?

  Of, don't, don't touch the burn stove twice.

• 34:59Speaker 00

  Yeah, or run away when you hear rustling in the leaves.

• 35:02Marc Andreessen?

  Right, right.

• 35:02Speaker 00

  Don't sit around and say, well, it's a probabilistic world. I have to figure out how often is that a lion that's gonna come eat me?

• 35:07Marc Andreessen?

  Most people shouldn't be playing in the World Series of Poker.

• 35:08Speaker 00

  I have people come up to me all the time and be like, oh, you know, I play poker, but it's just a home game. You know, and I'm like, what are you saying, just a home game? Like, there are different purposes to poker. Like, you probably have a great time doing that, and it brings you a tremendous amount of enjoyment, and you don't have an interest in becoming a professional poker player. And why? Just be proud of that. I think that that's amazing. Like, I play tennis. I'm not saying, oh, but, you know, I'm, I'm just playing, we, you know, I'm just playing in, like, USTA, like, 3.5. Like, I'm really happy with my tennis. I think it's great. So I think we need to remember that, like, people have different things that they love. And this kind of thinking, I, I think that I would love it if we could spread it more. But of course, there are gonna be some people who are going to be ending up in this category

• 35:52Speaker 00

  more than others, and that's okay. Like, not everybody has to think like this. I think it's all right. So one of the things I get asked all the time is like, well, we can't really do this because people expect us to be confident in our choices.

• 36:03Sonal?

  Yeah.

• 36:03Speaker 00

  Don't confuse confidence and certainty. So I can express a lot of uncertainty and still convey confidence. Ready? I'm weighing these three options, A, B, and C. I've really done the analysis. Here's the analysis, and this is what I think. I think that option A is gonna work out 60% of the time. Option B is gonna work out 25% of the time, and option C is gonna work out 15% of the time. So option A is the clear winner. Now, I just expressed so much uncertainty in that sentence.

• 36:32Sonal?

  But also a lot of confidence.

• 36:33Speaker 00

  But also a lot of confidence.

• 36:34Sonal?

  Yeah.

• 36:34Speaker 00

  I've done my analysis. This is my forecast. And all that I ever ask people to do when they do that is make sure that they ask a question before they bank. The decision, which is, is there some piece of information that I could find out that would reverse my decision that would actually cost, not that would make it go from 60 to 57. I don't care modulating so much. I care that you're going to actually change.

• 36:54Sonal?

  And your point is that organizations can then bake that into their process. Correct. Not just in the forecasting, but in arriving to that decision so that then the next time they get to it, right or wrong, they make a better decision.

• 37:04Speaker 00

  And, and if the answer is yes, go find it. Or sometimes the answer is yes, but the cost is too high. It could be time. It could be.

• 37:12Sonal?

  Accurately cost.

• 37:13Speaker 00

  Whatever. Exactly. So then you just don't. And, and then you would say, well, then you all recognize as a group, we knew that if we found this out, it would change our decision. But we've agreed that it would, the cost was too high. And so we didn't. So then if it reveals itself afterwards, you're not sad.

• 37:24Sonal?

  Well, you've talked a lot about how people should use confidence intervals and communicating, which I love because we're both ex PhD.

• 37:30Speaker 00

  Yes, exactly.

• 37:31Sonal?

  PhD psychology people, neither finished. So I love that idea. One thing that I struggle with though, is again, in the organizational context, like if you're trying to translate this to a big group of people, not just one-on-one or small group decisions, how do you communicate a confidence interval and all the variables in it in an efficient kind of compressed way? Like honestly, part of communication and organizations is emails and quick decisions. And yes, you can have all the process behind the outcome, but how do you then convey that? Even though the people were not part of that room of that discussion?

• 38:05Speaker 00

  I think that there's a simpler way to express uncertainty, which is using percentages. Now, obviously sometimes you can only come up with a range, but for example, if I'm, if I'm talking to my editor, and this is very quick in an email, I'll say, you'll have the draft by Friday, 83% of the time. By Monday, you'll have it 97% of the time. Those are inclusive, right?

• 38:25Sonal?

  It's another way of doing a confidence interval, but without making it so wonky.

• 38:29Speaker 00

  Without making it so wonky. So I'm just letting her know, most of the time you're going to get it on Friday, but I'm building, like my kid gets sick, or I have trouble with a particular section of the draft, or whatever it is. And I set the expectations for that way.

• 38:42Sonal?

  Fantastic. I mean, we've been trying to do forecasting even for like timelines for podcasts, editing and episodes.

• 38:46Speaker 00

  Right.

• 38:47Sonal?

  And I feel frustrated because I have like a set of frameworks, like if there's accents, if there's more than two. Voices, if there's, you know, a complex thing, room tone, like interaction, feedback, sound effects, I know all the factors that can go into my model.

• 39:00Speaker 00

  Right.

• 39:00Sonal?

  But I don't know how to put a confidence interval in our pipeline spreadsheet for, you know, all the content that's coming out.

• 39:06Speaker 00

  Yeah. So one way to do it is think about what's the range, what's the earliest that I could get it? And you put a percentage on that. And then you think about the latest day they're going to get it.

• 39:14Sonal?

  I love.

• 39:15Speaker 00

  Put a percentage on that.

• 39:16Sonal?

  I love that idea.

• 39:17Speaker 00

  What's wonderful about that is that it's a few things. One is I've set the expectations properly now so that I'm not getting, you know, yelled at on Friday, like where the hell's the draft?

• 39:28Sonal?

  Exactly.

• 39:28Speaker 00

  And I think that.

• 39:29Sonal?

  Which is half the battle.

• 39:30Speaker 00

  And a lot of what happens is that because we're sort of, we think that we have to give a certain answer, it ends up boy who cried wolf, right? So that if I'm telling her I'm going to get it on Friday and, you know.

• 39:40Sonal?

  Honestly, against your own best judgment sometimes even.

• 39:43Speaker 00

  Right. 25% of the time I'm late, she just starts to not put much stock in my, in what I've said anyway.

• 39:48Sonal?

  Right, right.

• 39:48Speaker 00

  So that's number one. Number two is what happens is that you, you really kind of infect other people with this in a good way where you get them, it just moves them off of that black and white thinking. So like.

• 39:59Sonal?

  I love that.

• 40:00Speaker 00

  One of the things that I love thinking about, and this is the difference between a deadline or kind of giving this range, is that I think that we ask ourselves, am I sure? And other people, are you sure? Way too often. That's, it's a terrible question to ask somebody because the only answer is yes or no.

• 40:18Sonal?

  So what should we be asking?

• 40:19Speaker 00

  How sure are you?

• 40:20Sonal?

  How sure are you? I have a quick question for you on this because earlier you mentioned uncertainty. How do you as an organization build that uncertainty in by default?

• 40:30Speaker 00

  So first of all, we obviously talked a little bit about time traveling and the usefulness of time traveling. So one thing that I like to think about is not overvalue the decision that's right at hand, the thing, the things that are right sitting in front of us, right? So you can kind of think about it like, how are you going to figure out the best path? What is it, you know, as you think about what your goals are? And obviously the goal that you want to reach is going to sort of define for you what the best path is. If you're standing at the bottom of a mountain that you want to summit, let's call the summit your goal, all you can really see is the base of the mountain. So as you're doing your plan. And you're really worried about how do I get the next little bit, right? How do I start? But if you're at the top of the mountain, having attained your goal, now you can look at the whole landscape. You get this beautiful view of the whole landscape, and now you can really see what the best path looks like.

• 41:15Speaker 00

  And so we want to do this, not just physically, like standing up on a mountain, but we want to figure out a cognitive way to get there. And that's to do this really good time traveling. And you do this through backcasting and pre-mortem. And now let's look backwards instead of forwards to try to figure out, this is now the headline. Let me think about why that happened. So you could think about this like as a simple like weight loss goal. I want to lose a certain amount of weight. Within the next six months, it's the end of the six months. I've lost that weight. What happened? You know, I went to the gym. I avoided bread. I didn't eat any sweets. I made sure that, you know, whatever. So you now have this list. Then in pairing with that, you want to do a pre-mortem, which is, I didn't get to the top of the mountain. I failed to lose the weight.

• 41:59Speaker 00

  I failed to do whatever it is.

• 42:01Sonal?

  And then all the things you can do to counter program against that.

• 42:04Speaker 00

  Exactly. Because that's going to reveal really different things. It's going to reveal some things that are just sort of luck, right? Let me think, can I do something to reduce the chance, the influence of luck there? Then there's going to be some things that have to do with your decisions. Like, I went into the break room every day and there were donuts there. And so I couldn't resist them. So now you can think about, how do I counter that, right? How can I bring other people into the process and that kind of thing? And then there's stuff that's just, you can figure out, it's just out of your control. Like, it turned out I had a slow metabolism. And now what happens is that you're just much less reactive and you're much more nimble, because you've gotten a whole view of the landscape and you've gotten a view of the good part of landscape and the bad part of landscape. But I'm sure, as he told you, people are very loathe to do these pre-mortems,

• 42:45Speaker 00

  because I think that the imagining of failure feels so much like failure, that people are like, no, and you should posit, you know, positive visualization.

• 42:54Sonal?

  I mean, in fact, even in brainstorming meetings, everyone's like, don't dump on an idea. But the exact point is, you don't have to dump on an idea and kill the winnowing of options. But as part of the process, you should be then pre-mortuming it.

• 43:05Speaker 00

  There's wonderful research by Gabrielle Adenzen that I really recommend that people see, that the references are in my book. In across domains, what she's found is that when people do these this sort of positive fantasizing, the chances that they actually complete the goal are just lower than if people do this negative fantasizing. And then there's research that shows that when people do this time travel and this backwards thinking that increases identifying reasons for success or failure by about 30%, you're just more likely to see what's in your way. So like, for example, she did she did like one of the simple studies where she she asked people who were in college, you know, who do you have a crush on that you haven't talked to yet? She had one group who,

• 43:49Speaker 00

  you know, it was all positive fantasies. So like, oh, I'm going to meet them and I'm going to ask them out on a date and it's going to be great and then we're going to live happily ever after and whatever. And then she had another group that engaged in negative fantasizing. What if I ask them out and they say no, like they said no, and I was really embarrassed and so on and so forth. And then she revisited them like four months later to see which group had actually gone out on a date with the person that they had a crush on. And the ones that did the negative fantasizing were much more likely to have gone out on the date.

• 44:17Sonal?

  That's fantastic.

• 44:18Speaker 00

  Yeah. So one of the things that I say is like, look, when we're in teams, to your point, we tend to sort of view people as naysayers, right? But we don't want to think of them as downers. So I suggest divide those up into two processes. Have the group individually do a backcast, have the group individually write a narrative about a pre-mortem. And what that does is when you're now doing a pre-mortem, it changes the rules of the game where being a good team player is now actually identifying the ways that you fail.

• 44:47Sonal?

  I love what you said because it's like having two modes as a way of getting into these two mindsets.

• 44:52Speaker 00

  Right. Where you're not stopping people from feeling like they're a team player. And I think that that's the issue. As you said, it's like, don't sit there and like, you know, crap on my goal. Well, because what are they really saying? You're not being a team player. So change the rules of the game.

• 45:05Sonal?

  You had this line in your book about how regret isn't unproductive. The issue is that it comes after the fact, not before.

• 45:12Speaker 00

  So the one thing that I don't want people to do is think about how they feel right after the outcome. Because I think that then you're going to overweight regret. So you want to think about regret before you make the decision. You have to get it within the right timeframe. What we want to do instead is right in the moment of the outcome, when you're feeling really sad, you can stop and say, am I going to care about this in a year? Think about yourself as a happiness stock. And so if we can sort of get that more 10,000 foot view on our own happiness, and we think about ourselves as we're investing in our own stock, our own happiness stock, we can get to that regret question a lot better. You don't need to improve that much to get really big dividends. You make thousands of decisions a day.

• 45:54Speaker 00

  If you can get a little better at this stuff, if you can just, you know, de-bias a little bit, think more probabilistically, really sort of wrap your arms around uncertainty to free yourself up from sort of the emotional impact of outcomes a little bit. It's going to have such a huge effect on your future decision making.

• 46:15Sonal?

  Well, that's amazing, Annie. Thank you so much for joining the A6 and Z podcast.

• 46:19Marc Andreessen?

  Thank you very much.

• 46:20Speaker 00

  Yes, thank you.