The Exchanges

Q Do you see what I mean? So I'm just trying to understand if actually speed does matter, you learn more from being second, you can perfect more, and actually, is it sometimes best?

A I think it's good to get out and iterate. Personally, I think generally it's okay to be second, and we're totally fine being second. Catching up on the basics, and then trying to out-innovate. Like step, step, step. Like launch, catch up, overtake with innovation. I think is a very, very good model. You don't want to be third or fourth, and actually when someone's got to the point of product market fit, you really need to move fast. And the other thing that move fast gives you, and again, um, the lady from Growth Hackers was, was awesome. She was saying, like, you get to get more experiments in. I think Brian said, I think, look, I think you had multiple people in here say, The, the pace of learning really, really matters, and so no, getting out shipping and trying, the first version of Reels failed. We tried to put it in the stories spot, like we tried to integrate it that way, it hard failed. Getting a couple of revs on that, we were out before YouTube, we were out before anyone except TikTok with our competitor there, faster than Snap, who also cloned and copied TikTok despite everything they've said about that, um, but like we were out, um, faster than everyone else, and we got a couple, our first iteration failed, Second and third, we learnt a lot. Now we're actually innovating and adding really cool things that people aren't trying other than us. We wouldn't be here if we…

AI assessment note: “Personally, I think generally it's okay to be second, and we're totally fine being second.”

Q to really make everyone feel like they can come out when they feel they want to and feel welcome in whatever way they are? Like, I think there's, you know, people talk a lot about, you know, I, I feel I can now. I don't actually feel that that's the case at all in a lot of companies. Do you feel that we have a long way to go still?

A Yeah, I mean, I think that the trans community has it the hardest. So like, to be completely blunt, as a white cis gay man, I've got it, you know, Relatively easy compared to many people in the community. Um, at the same time, I've said that on stage before, and people have corrected me that everyone has their own journey, and so it's not that it's straightforward. You know, look around. How many boards do you serve on where there's another gay board member? How many investor conferences do you ever see someone gay on stage? Seniors, how many people have you had on this show who are openly gay, who are a senior executive at a tech company? There's still a gap, and that alone should tell you that there is still a problem, and You know, I'm, I'm very lucky. I work at a company. Mark had a gay board member with Peter. He had a gay co-founder with Chris. Like, I know he supports our community, and I feel very grateful for it. Cheryl too. And I feel that from my colleagues. But it's also, like, still very lonely. Um, in the senior teams I'm on, in the boards I've served on, like, I'm always the only gay guy. So yeah, there's a, there's a gap, and we have a long way to go. And I talk to many LGBTQ people, and again, look, trans people, way, way harder than where I stand. And many of them say to me, I can't be successful in my job, and I can't be out in my work. And I always say, that…

AI assessment note: “So yeah, there's a, there's a gap, and we have a long way to go.”

Q I'm so sorry. Why does no one in our circles use it then?

A Yeah. I mean, it's just, it's a bit more normie. Well, firstly, it's a huge success in like Japan and Taiwan. Let's start with that. Japan, interestingly, Is a text first country. That's why haikus come from Japan and all that stuff. It's a text first pseudonymous society. And so it's a really great product market fit for Japan. And we've always struggled actually. Twitter is bigger than I think Facebook and Instagram in Japan. Insane. And so threads is now really thriving in Japan. So firstly, segments that really care about this is different. Secondly, you know, in general, I think VCs don't tend to use Facebook very much either. And they all kind of act like Twitter is Facebook when they're talking about Facebook in public. You can kind of hear it. You listen to anyone talk about Facebook who's like a VC or a politician or policy elite, we'd call them, or a highly engaged news audience, we'd also call them. They don't really use Facebook or Instagram. They use Twitter. And they think Twitter is Facebook, which is not true. It is the most engaged community on Twitter, I think, is Facebook. VCs and tech people. Yeah, the normies aren't the VCs and tech people, and they use threads, but VCs and tech people use Twitter.

AI assessment note: “the normies aren't the VCs and tech people, and they use threads”

Q I'm so pleased we went for lunch beforehand, and I feel built a rapport because I can ask a harder question. Why Meta as a name? I think people instantly think of Metaverse, which is transient in terms of consumer excitement. Why, why Meta?

A I think we're mapping out the future that we believe in. Like, we're a company that does connect people. The red thread in our brand, like, Meta is about connecting people in innovative and inspiring ways. At the extreme, that's virtual and mixed and augmented reality experiences, but honestly, that starts with intimate conversations over WhatsApp, and so our, our brands in our branded house are Meta, we connect people in awesome and inspiring ways, innovative. Facebook, it's about social discovery. Um, the first thing we ask you is find your friends, people you may know, pages you may like, groups you should join, social discovery. Instagram is connecting around creativity, whether that's resharing your favorite reel or posting a photo with a, with a, with a filter. And WhatsApp is intimacy through privacy. You can only be as intimate as you can possibly be and share the most important things to you if you know there are multiple layers of privacy protecting you. And so all of these things come together as ways people connect virtually, and what is the metaverse? It is a place where people connect virtually, and the end point of it is an embodied space that ideally goes with us the entire time because of augmented reality, but the steps on the way start with two D interfaces where you are connecting virtually.

AI assessment note: “Meta is about connecting people in innovative and inspiring ways.”

Q I was always chasing money. Um, uh, and then when I was 21, I, I, as I was before, but I, you know, I made my first million, and I realized that actually I was still the, you know, um, sad, quite depressed, lonely individual, uh, that I was, and hopefully less so now, but it wasn't my goal, and my goal changed then. When should we change your goals?

A I mean, when you have new information is probably a trite way to say it. I like to say whatever you do for a job shouldn't be economically stupid. You know, if it's stupid that you're doing the job economically, then you should think really hard about it. But if it's not, then focus on the impact, focus on the people around you. Like, so I, I, I'm with you on the money thing. There needs to be a base level, but beyond that, you should focus on other things. Yeah, I don't know. I mean, I think it's when you've got different information, but you should change your goals and your metrics very infrequently. Um, you should know what their flaws are, you should know what their drawbacks are, but you should, you should aspire to not change them very often.

AI assessment note: “when you have new information... but you should change your goals and your metrics very infrequently”

Q Should we have psychologists in our product teams and in our brand teams? When you say about creating an ad being that transformational moment and actually making a very significant shift, Should we have psychologists and people who understand human behavior much, much better integrated into our teams?

A Maybe. I mean, the lady who used to head our content design, Alicia, who now she's head of design and creative and content design for me for a third of the company. Amazing lady. She has a psychology degree. And she was an incredible friend and partner in actually getting these tests run. Um, at the same time, if we were American, we would say we want a lot of times at bat. We're not looking for home runs. We just want a lot of opportunities at bat. And so I also think you should just be willing to try a lot. If you think ahead of time, you can predict what people are going to respond to with a button color, a size of button, the words you put on the button, the flow that you've created. Like Brian gave you examples of this. There are flows where we made them longer. By giving people more targeting options where we got a higher conversion rate and a higher lifetime value. Whereas the growth standard is shorten the flow and take out steps. So I think you need to try more experiments because you are not a genius. And even if you are, you can't predict what every user is going to do or think based on what you say to them.

AI assessment note: “Maybe. I mean, the lady who used to head our content design, Alicia”

Q I absolutely love that. Can I ask, did it work straight away in terms of the monetization? Like from day one, did you make money or did, were there any mistakes made?

A Well, day one, I was just enjoying the traffic. So I had this thing where one day, back in the day, you could actually tell from the IP range which US military base was visiting your website, and NORAD one day was the majority of visits to my paper airplane website, and I could imagine all these bored people looking for ICBMs throwing paper airplanes at each other in NORAD. Um, so no, to start with, I just tried to have traffic, and the monetization was a side project, so it wasn't like mistakes or not mistakes, and then it started to be a reasonable amount of money, and I started to focus on that. And it wasn't mistakes, but I learned so much cool stuff. Uh, when I started to make money on it, about 18. I started the website when I was about 13, I think.

AI assessment note: “so no, to start with, I just tried to have traffic”

Q said there about kind of the amount of reps, meaning the increased rate of learning. Yes, but most people actually don't spend the time to learn and to really synthesize the lessons, the takeaways, what needs to change, what needs to be different. How do you actually think about instilling the most effective postmortems, whatever you want to call them, to instill lessons from the prior to impact the next?

A I mean, this is where certainly my job at Meta, the most important job I have is data science and data engineering, the analytics role. Um, and I think you need analytics leaders who, um, are patiently right. This is the coaching I try and give people in analytics who are asking about influence because, because analytics is mostly an influence role. Um, you need to analyze stuff and people need to believe you and then take action on what you say. Um, so the way that I think about that is, um, you need analytics leaders who can explain what's happened, who could take out enough caveats They are correct in what they say. They are not lying with data. The first question you ask is, what does the other person need to know, even if it's uncomfortable for me to tell them? But sometimes we bury ourselves in caveats, and then leaders, like, lose the message we're saying, so you get the message through very clearly that you're trying to explain to the leader in question who's running the product, and then they may listen to you and they may not. If they don't, and then what you said would happen based on experimental or correlative data happens, You very politely, and again, this is a tech, this is a technique that's hard to do, basically say, I told you so, and hope they listen to you better the next time, and then over time, you build this learning function in with analytics that actu…

AI assessment note: “over time, you build this learning function in with analytics”

Q said there about kind of the amount of reps, meaning the increased rate of learning. Yes, but most people actually don't spend the time to learn and to really synthesize the lessons, the takeaways, what needs to change, what needs to be different. How do you actually think about instilling the most effective postmortems, whatever you want to call them, to instill lessons from the prior to impact the next?

A I mean, this is where certainly my job at Meta, the most important job I have is data science and data engineering, the analytics role. Um, and I think you need analytics leaders who, um, are patiently right. This is the coaching I try and give people in analytics who are asking about influence because, because analytics is mostly an influence role. Um, you need to analyze stuff and people need to believe you and then take action on what you say. Um, so the way that I think about that is, um, you need analytics leaders who can explain what's happened, who could take out enough caveats They are correct in what they say. They are not lying with data. The first question you ask is, what does the other person need to know, even if it's uncomfortable for me to tell them? But sometimes we bury ourselves in caveats, and then leaders, like, lose the message we're saying, so you get the message through very clearly that you're trying to explain to the leader in question who's running the product, and then they may listen to you and they may not. If they don't, and then what you said would happen based on experimental or correlative data happens, You very politely, and again, this is a tech, this is a technique that's hard to do, basically say, I told you so, and hope they listen to you better the next time, and then over time, you build this learning function in with analytics that actu…

AI assessment note: “builds in the muscle inside a company to actually learn rather than just do”

Q be for the person who's trying hard and not doing well. Do you have any tips for me in terms of delivering that feedback, in terms of what's worked, what hasn't worked for you? Because, you know, I think people see the shows, honestly, Alex, and I'm opening up here, But I'm still figuring this out, very much so, and I don't know what I'm doing, especially in these conversations.

A I think most fifty-year-olds are figuring it out too. I, I just, like, experience isn't the be-all and end-all. I mean, firstly, I've never actually had a conversation, for example, where I fired someone where that person hasn't been relieved, and hasn't actually been, and generally we always provide a good packet, and like, that does matter, but I think it's, it's actually very important that you put yourself in the other person's shoes when you're thinking through it. So the firing is the most extreme, sort of just giving performance feedback is the least extreme, and if you put yourself in the other person's shoes and know where they're standing, and you're like, look, this is feedback to make you better, or like, hey, this is not working out, and I think you know it's not working out, and again, if it's a surprise, you have mucked up as a manager, and that's your fault. So if you were along the way of giving them the actual guidance, like, I, I think it will work out well, and you have to be, again, management is about caring for your people, and doing the thing that is, that is really, truly caring for people. The people who care for you the most in your life are probably the people who've given you the toughest feedback in your life, because they're tied to you, and they truly care for you, and they're not, they're not gonna just, like, not tell you when your breath smell…

AI assessment note: “put yourself in the other person's shoes when you're thinking through it”

Q I was always chasing money. Um, uh, and then when I was 21, I, I, as I was before, but I, you know, I made my first million, and I realized that actually I was still the, you know, um, sad, quite depressed, lonely individual, uh, that I was, and hopefully less so now, but it wasn't my goal, and my goal changed then. When should we change your goals?

A I mean, when you have new information is probably a trite way to say it. I like to say whatever you do for a job shouldn't be economically stupid. You know, if it's stupid that you're doing the job economically, then you should think really hard about it. But if it's not, then focus on the impact, focus on the people around you. Like, so I, I, I'm with you on the money thing. There needs to be a base level, but beyond that, you should focus on other things. Yeah, I don't know. I mean, I think it's when you've got different information, but you should change your goals and your metrics very infrequently. Um, you should know what their flaws are, you should know what their drawbacks are, but you should, you should aspire to not change them very often.

AI assessment note: “when you have new information is probably a trite way to say it”

Q be for the person who's trying hard and not doing well. Do you have any tips for me in terms of delivering that feedback, in terms of what's worked, what hasn't worked for you? Because, you know, I think people see the shows, honestly, Alex, and I'm opening up here, But I'm still figuring this out, very much so, and I don't know what I'm doing, especially in these conversations.

A I think most fifty-year-olds are figuring it out too. I, I just, like, experience isn't the be-all and end-all. I mean, firstly, I've never actually had a conversation, for example, where I fired someone where that person hasn't been relieved, and hasn't actually been, and generally we always provide a good packet, and like, that does matter, but I think it's, it's actually very important that you put yourself in the other person's shoes when you're thinking through it. So the firing is the most extreme, sort of just giving performance feedback is the least extreme, and if you put yourself in the other person's shoes and know where they're standing, and you're like, look, this is feedback to make you better, or like, hey, this is not working out, and I think you know it's not working out, and again, if it's a surprise, you have mucked up as a manager, and that's your fault. So if you were along the way of giving them the actual guidance, like, I, I think it will work out well, and you have to be, again, management is about caring for your people, and doing the thing that is, that is really, truly caring for people. The people who care for you the most in your life are probably the people who've given you the toughest feedback in your life, because they're tied to you, and they truly care for you, and they're not, they're not gonna just, like, not tell you when your breath smell…

AI assessment note: “put yourself in the other person's shoes when you're thinking through it”

Q I absolutely love that. Can I ask, did it work straight away in terms of the monetization? Like from day one, did you make money or did, were there any mistakes made?

A Well, day one, I was just enjoying the traffic. So I had this thing where one day, back in the day, you could actually tell from the IP range which US military base was visiting your website, and NORAD one day was the majority of visits to my paper airplane website, and I could imagine all these bored people looking for ICBMs throwing paper airplanes at each other in NORAD. Um, so no, to start with, I just tried to have traffic, and the monetization was a side project, so it wasn't like mistakes or not mistakes, and then it started to be a reasonable amount of money, and I started to focus on that. And it wasn't mistakes, but I learned so much cool stuff. Uh, when I started to make money on it, about 18. I started the website when I was about 13, I think.

AI assessment note: “so no, to start with, I just tried to have traffic”

Q get to you, uh, when you don't hit a metric or a goal, teams are dejected, and they're sad, and you kind of want them to, you want them to feel, but you also don't want them to be too demoralized. It's like, no, we, we get on, next, we push. How do you strike that fine balance between ambition for the next, even when you fail on the last?

A One of the best things that Cheryl actually said in my entire time working with her was the saddest thing is when a team fails having hit all its goals on the way down. I, and it really, it stunts on me. Because people are not, Because people worry about everyone being sad, and so you do a forecast, and you set the goal off the forecast, but the goal is a losing path. Like, you need to set a goal that puts you on a winning path at the absolute base level. If your goal, if you hit it, and you repeatedly hit them, the metric that you're using describe it, the goal that you've set out, and you're sad, then you've set the wrong goal. If you set the right goal, and you miss it, then the team should be sad, because you've set the right goal and the right metric. Like, get it right.

AI assessment note: “If you set the right goal, and you miss it, then the team should be sad”

Q get to you, uh, when you don't hit a metric or a goal, teams are dejected, and they're sad, and you kind of want them to, you want them to feel, but you also don't want them to be too demoralized. It's like, no, we, we get on, next, we push. How do you strike that fine balance between ambition for the next, even when you fail on the last?

A One of the best things that Cheryl actually said in my entire time working with her was the saddest thing is when a team fails having hit all its goals on the way down. I, and it really, it stunts on me. Because people are not, Because people worry about everyone being sad, and so you do a forecast, and you set the goal off the forecast, but the goal is a losing path. Like, you need to set a goal that puts you on a winning path at the absolute base level. If your goal, if you hit it, and you repeatedly hit them, the metric that you're using describe it, the goal that you've set out, and you're sad, then you've set the wrong goal. If you set the right goal, and you miss it, then the team should be sad, because you've set the right goal and the right metric. Like, get it right.

AI assessment note: “Because people worry about everyone being sad, and so you do a forecast”