The Exchanges

Q Has the way that you influence changed over time? Often say when you're younger, you may take a more dogmatic binary approach with passion and Chandra, you've got to. And over, has your approach changed?

A Yeah, it's patent recognition, Harry. I actually think that over a period of time, you do so much of it because that's all I practiced. At Facebook, if you think about what I did the most was influence over a period of time. And then you have So many different characters and each of them just becomes a cast of characters and you start to understand what ticks with them, what does not. And once you do that, there is a way of approaching influence. So I actually think it's, uh, I, I, it's an art. You have an idea and say, oh, this type of person, they can be influenced through data. You need to be really good at storytelling. For example, Harvey, you go to try to influence Harvey. You just throw the data. Don't give me anything other than just data. Just tell me the data. Don't tell me the story. You got a Chris Cox. Don't just throw data at me. Tell me the story, please. So there is these types of, and they both are extremely well-meaning, but there are multiple different spectrum of people that you work with and you have to understand who they are. I also found that when I worked at Sequoia, I think I found four different types of founders, people who love data and knew data and wanted to embrace. That's one. There are people who love data, thought they knew a lot, but would not listen to you because they thought they knew more than you. And then there was a third who did not k…

AI assessment note: “Yeah, it's patent recognition, Harry. I actually think that over a period of time”

Q Listen, I've learned just as much, so I think it's a pretty cool job that I have. I would love to start, though, with some chronology. I heard you got some seminal advice early on from one of your managers at PayPal, Rohan. So I'd love to start with this. What was the advice from Rohan at PayPal and how did it change your mindset?

A Yeah, so I was actually, uh, Rohan was my manager and I think he went on to lead a bunch of different teams at, at, at PayPal. And I was, uh, uh, working at, at, at PayPal and was primarily on risk management and doing a bunch of different analysis. I actually got caught in a crossfire between two senior leaders. And what ended up happening was it became really, really frustrating for me, and I couldn't actually do my work. And, uh, basically what I did at that point was I was so frustrated that I wanted to quit. And, uh, rather than address the problem, I wanted to quit. And I went and told Ron and said, you know what, I don't want to stay here. I actually want to quit. And for which he basically said, you know what, you never Want to be a quitter? And he said, set things right, fix things. And then when you're in a better state of mind, come back to me and I'll see what I can do. So I stayed on for another six to nine months. And at that point I got into a much better state of mind, fixed all the issues I had with the senior management, and then fix the problems there was and try to get our, uh, and actually got, uh, the, the PayPal trajectory back on track. And then I went back to Rohan. Six to nine months later, and then basically told him, okay, man, I fixed a bunch of different stuff. And I still feel like PayPal is not the right place for me for several reasons. And, uh,…

AI assessment note: “he basically said, you know what, you never Want to be a quitter”

Q What does it mean to focus on impact versus not? Cause everyone says they have a big vision and they have ambitious and grand goals. What does it actually mean?

A Impact is, I mean, uh, is basically, uh, essentially the thing that you're doing, is it a needle mover? That's basically what it is. Is that, does it move the more needle? The thing, are you always prioritizing on the most important things all the day? And if you are able to do that, you actually focus on impact. Now, how do you measure that and how do you do that? So I think of it as a, in my own, Uh, framework. And I, I talked to companies about it. I also did that internally at Facebook is that I think of impact measured in three different ways. One is you, uh, move a metric. If you take a specific metric that you have in mind, which is maybe you're not star metric and you want to move that, that essentially is one way to create impact. The second is influence, uh, a product decision. That could be like, you're doing things to identify an opportunity to Help set a roadmap or a strategy. Those would be another way of, uh, creating impact. And the third was influencing and changing your process, which is be like, Hey, it's some things that are being done manual and I can now automate it. And that would also relate to creating impact. And I tell, I used to tell people at Facebook that if you're not doing one of this, if something you're doing, an activity doesn't come into one of these things, you're probably not having impact. Then what ends up happening is that you confuse mo…

AI assessment note: “I think of impact measured in three different ways. One is you, move a metric”

Q How do you select Northstar metric? How do you advise founders on choosing the right one?

A The Northstar metric itself, a lot of, I mean, there's a lot of thought that is obviously a lot of people have multiple thoughts on how do you actually select the Northstar metric. I actually think that for your specific company, there's, there is a mission. And it needs to tie to something in your mission. For example, at Facebook at that time that we were there, it was like making the world open and connected. So naturally was you wanted to get everyone in the world on it. So it just naturally meant that you wanted to get the largest number of people to use a product. So MAU made a ton of sense in terms of what you're trying to do. So that's one way to think about is like try to get all of that.

AI assessment note: “it needs to tie to something in your mission. For example, at Facebook”

Q growth team being independent, a standalone growth team. The alternative could be that you have designers, you have marketers with a growth slant towards them, more analytical, more rigorous in that way. Um, you have PMs in the similar vein, and they work as an integrated part of the existing org. Do you think growth teams need to stand independently or do you think they can function within the org?

A I think there are two answers to this. I think the answer at an earliest stage of your growth, I think they should be a standalone team. I think it's for two reasons. One is I think it's the, is for the best practices, meaning that they can learn from each other and then they can go solve problems across the company. Suddenly you separate this team and Put them into the different parts. I don't know if they'll be able to build the same culture of the noob. A lot of it is knowing how to do this really, really well. And all of this transfer, if you went from, let's say I worked on many parts of this from pages growth to games growth, to address the growth to, you know, and then when you have all of these types of growth, what ends up happening is that these sort of knowledge does translate and imagine that all this was not part of one single team and they were separated all over. I actually don't think the learnings will be there. So My feeling at the earliest stage, you should all, I mean, it should be centralized. Now, once you get a large enough team, if you get to a large enough team, I actually think that it can start to be decentralized and work, go into product teams, but I actually think that early on it should be centralized. So the more important thing is that somewhere in the interim, you probably have a role where you embed people into teams. You embed people into tea…

AI assessment note: “at an earliest stage of your growth, I think they should be a standalone team”

Q Has the way that you influence changed over time? Often say when you're younger, you may take a more dogmatic binary approach with passion and Chandra, you've got to. And over, has your approach changed?

A Yeah, it's patent recognition, Harry. I actually think that over a period of time, you do so much of it because that's all I practiced. At Facebook, if you think about what I did the most was influence over a period of time. And then you have So many different characters and each of them just becomes a cast of characters and you start to understand what ticks with them, what does not. And once you do that, there is a way of approaching influence. So I actually think it's, uh, I, I, it's an art. You have an idea and say, oh, this type of person, they can be influenced through data. You need to be really good at storytelling. For example, Harvey, you go to try to influence Harvey. You just throw the data. Don't give me anything other than just data. Just tell me the data. Don't tell me the story. You got a Chris Cox. Don't just throw data at me. Tell me the story, please. So there is these types of, and they both are extremely well-meaning, but there are multiple different spectrum of people that you work with and you have to understand who they are. I also found that when I worked at Sequoia, I think I found four different types of founders, people who love data and knew data and wanted to embrace. That's one. There are people who love data, thought they knew a lot, but would not listen to you because they thought they knew more than you. And then there was a third who did not k…

AI assessment note: “Yeah, it's patent recognition, Harry. I actually think that over a period of time”

Q What do you think makes Sequoia so good, Chandra, having seen it internally?

A First, I think the quality of the founders, I mean, of the investors themselves are exceptional. I actually think that brand for several, several years, I mean, nobody doesn't talk to them, right? I mean, you have everyone talking to Sequoia, which actually gets them all the leads that they want to, and that's pretty exceptional. The third is the diversity. Of the people that are in the group is like you have all the way from, you know, I mean, during those times is Mike Moritz and Jim gets and, and rule off and, and Pat, and of course so many other people. And they have this diversity people with different types of skills. And I think their collaborative decision-making is also excellent in the way that it's, uh, the collaborative decision-making. I think the process that they take in terms of how they go through the, you know, the, from the one pages, from the time that they, Actually, uh, source the deal to going through the due diligence process to getting to the one pages and, you know, to actually talk about it and then going through the decision making process. I love the way that they do that process. They keep talking about one thing, everyone going into the room, they talk about this prepared man. I keep talking about it since to my team and so on is like people who go into the room, there's already, if you have a Monday morning meeting, they circulate the entire memo…

AI assessment note: “First, I think the quality of the founders, I mean, of the investors themselves are exceptional.”

Q That's so interesting. I interviewed someone the other day. I found it. I can't remember who, I think it was Brian at, um, HubSpot. And he said that when you put someone on like an improvement plan, it never works. Just get rid. Do you agree?

A I think when you put up someone on a performance plan, it's three months too late. It's three months before you should have intervened and tried to do the right thing. What happens most of the times is that people put them on the improvement plan when they've already decided there's no chance of success. And that is why it doesn't work. If you think there's a twenty-plus, if, if you think there's a 70% chance of there, a 60% chance of them succeeding and you put them on a performance plan, then it might work. But what ends up happening is that we time it so badly. We time it at 10% or five percent or not even one percent. And I think it's the timing which is a problem. And most managers take too late to interview. And so, and they're not willing to have honest direct conversations. And because they don't have direct conversations, it becomes that much harder. Largely because most of us are conflict-averse and we won't have those conversations. And it becomes too late. And then what do you do? Try to go into a performance plan. I think it's less about the performance plan is when you time it, but regardless, I don't think you need to call it that. Just why do you call it? The label is not great anyway. Just go help them out. If you can't help them out, make sure that you, they can see reason. Almost everyone, I would say barring a couple of people that I've, I've actually, peopl…

AI assessment note: “I think when you put up someone on a performance plan, it's three months too late.”

Q What do you think makes Sequoia so good, Chandra, having seen it internally?

A First, I think the quality of the founders, I mean, of the investors themselves are exceptional. I actually think that brand for several, several years, I mean, nobody doesn't talk to them, right? I mean, you have everyone talking to Sequoia, which actually gets them all the leads that they want to, and that's pretty exceptional. The third is the diversity. Of the people that are in the group is like you have all the way from, you know, I mean, during those times is Mike Moritz and Jim gets and, and rule off and, and Pat, and of course so many other people. And they have this diversity people with different types of skills. And I think their collaborative decision-making is also excellent in the way that it's, uh, the collaborative decision-making. I think the process that they take in terms of how they go through the, you know, the, from the one pages, from the time that they, Actually, uh, source the deal to going through the due diligence process to getting to the one pages and, you know, to actually talk about it and then going through the decision making process. I love the way that they do that process. They keep talking about one thing, everyone going into the room, they talk about this prepared man. I keep talking about it since to my team and so on is like people who go into the room, there's already, if you have a Monday morning meeting, they circulate the entire memo…

AI assessment note: “First, I think the quality of the founders, I mean, of the investors”

Q Is it always obvious being able to tie data to hypothesis? Like where does the challenge come in that transition between the two?

A There are multiple problems here. One is, I think when you have the data, um, it is possible. I mean, you have a hypothesis, you can't even check it. For example, at Facebook, we would have saying that, Hey, by the way, we would, uh, we would want to know why advertisers are churning. And there's no easy way to find it. I mean, you actually need to do a survey. It takes a long time. And then they would basically say ROI. When they say ROI, we still want to understand what ROI meant to them because we don't actually know the data behind it. So a lot of this time, I mean, there are things that you can actually find out through the product. And so it's already in the product and it's in the data and you can actually provide the type of hypothesis to validate the hypothesis many, many times. You can't do it through just data. You need to do it through essentially user experience research. And, and so on. So there is a problem of just being able to validate your hypothesis, because typically speaking, a lot of times you don't have the data. The flip side is also true. You may not even be able to come up with the right hypothesis. And I've seen that happen too. It's like, you don't know what went on and suddenly you realize, uh, what happened. For example, what happened at, uh, Facebook and it happened became a hypothesis very, very much, much later is like, We found that there's cer…

AI assessment note: “There are multiple problems here. One is... you have a hypothesis, you can't even check it.”

Q I totally agree with you. Um, I do want to go back to the core question of like the impact versus activity, because I can, I can go off in many tangents, Chandra. So don't worry about that. Was there any other takeaway that you want to highlight from Facebook?

A I think the second one I would say is the, is the, Uh, I learned what it meant to build a world-class organization or a world-class team that was happy. And again, this came a lot from, uh, from the growth team at Facebook. I think both, uh, I would attribute Alex Shills and Harvey to it. They knew they get a very, very high bar at their first. I think high bar in terms of the people that they had, the high bar and expectations about them, but, and in the way that they cared. So they found a way that in terms of, I mean, we talked about impact earlier. I think it's the impact per capita. So the way I think about it is like impact is equal to impact per capita or impact divided by the number of people times the number of people. They always cared about impact per capita. How much can each person do and then multiply it by the number of people? So as a result, what they would have is the growth marketing team, which, uh, which, which, uh, Alex ran had Brian Hale, which, who was on the show. Uh, and there are so many other people who are on the show. I think Ryan was in the show. So there are multiple people on the show and this is all Alex. And it was like a seven people team or a six people team. And I would think like, how can six or seven or eight people have such enormous output? And this is a camaraderie, the way he built teams, the way that he would make sure that every sin…

AI assessment note: “I learned what it meant to build a world-class organization or a world-class team”

Q That's really interesting to hear in terms of that transition from centralized to decentralized. Founders are always told, hey, you need to hire for 18 months ahead of time. Uh, for the future company that you will be, do you agree with that given the many different hiring experiences and scaling journeys you've seen?

A This comes back to the product growth, right? I think that if you think about it from a, I mean, I have while at Facebook, uh, so there's, I'll give you an example at Facebook. Uh, when I joined Facebook, uh, analytics was all about counting numbers. And then it was creating dashboards, and then it was doing A-B testing, and then it was going towards goals, roadmap, and strategy. So initially the types of person that we needed to hire were basically people who can just count numbers. And secondly, so it was a bunch of people who can create infra to create dashboards. The third was people who actually were statisticians who could do A-B testing. And then Finally, it was people who could influence. And even now, I think it's Facebook is like, uh, the analytics team is largely about influence, even inside the growth team and so on throughout it's about influence. So the point is that if I had actually hired three years earlier and said, I'm going to hire people for influence, what would ended up happening was people wouldn't have been able to do the same people who do the AB testing who need stats background are not the ones who can actually influence. And what would happen is that you wouldn't have actually taken the journey in the right way. So what ended up happening was that We, we build a dashboard, we automated it. A-B testing , we build something called Deltoid, automated i…

AI assessment note: “if I had actually hired three years earlier and said, I'm going to hire people for influence”

Q Could you not argue that it's your fault? Say there's a skill gap. There's a knowledge gap. Your process wasn't, not yours, but like the hiring process wasn't rigorous enough to determine that in the process.

A A hundred percent right. A hundred percent right. And it's most times it is that because at the end of it, think about it. It's a two way thing. If I knew what I knew two months later would I've done. Hiring is a, is a terrible process. I mean, I know you ask a ton of questions of what do you look for? What do you look for? And I know that honestly, I can say all I want, It's useless. At the end of it, you, it's easiest when they work with you or you ask referrals from people you really care about. That's the only one that really, really works. You can do something in the interview, judge a few things, and even I said this, like, oh, simplicity and all this nonsense, but honestly, we just don't know until they join. There is so many unknowns here. They really don't know.

AI assessment note: “A hundred percent right. A hundred percent right. And it's most times it is that”

Q How does the skill set before a quick fire promise, but how does the skill set change between those that are good to great and bad to okay? Like what different people are they?

A As I mentioned, great at strategy, great at vision, not that great, not necessarily great at execution, uh, great at At bringing people along and making people feeling great about it. Empowering the next set of leaders to be amazing. All the kinds of things that you want. The bad to okay is like, is like, Essentially firing the entire squad, giving very hard messages, saying everything is crazy, having a center set of loyal groups of people that they can bring on who can completely change everything and then have a sort of, they got to get into a very strong execution mode. I want to get shit done. I need to go to, okay, that's all I care about. They're like a machine and they don't care that much about how, how do people feel? How does, Ah, should I make people, everyone happy? Culture? None of that actually matters. It matters only when you get to okay. But in the process, you don't need to be. So you're so much tougher in how you handle it. And so, and you need both. You actually need to go inside a company, you need to do both. But not the same person can do it. You can't get the same person to do both. They don't, they don't even think like that.

AI assessment note: “great at strategy, great at vision... The bad to okay is like... Essentially firing”

Q Is it always obvious being able to tie data to hypothesis? Like where does the challenge come in that transition between the two?

A There are multiple problems here. One is, I think when you have the data, um, it is possible. I mean, you have a hypothesis, you can't even check it. For example, at Facebook, we would have saying that, Hey, by the way, we would, uh, we would want to know why advertisers are churning. And there's no easy way to find it. I mean, you actually need to do a survey. It takes a long time. And then they would basically say ROI. When they say ROI, we still want to understand what ROI meant to them because we don't actually know the data behind it. So a lot of this time, I mean, there are things that you can actually find out through the product. And so it's already in the product and it's in the data and you can actually provide the type of hypothesis to validate the hypothesis many, many times. You can't do it through just data. You need to do it through essentially user experience research. And, and so on. So there is a problem of just being able to validate your hypothesis, because typically speaking, a lot of times you don't have the data. The flip side is also true. You may not even be able to come up with the right hypothesis. And I've seen that happen too. It's like, you don't know what went on and suddenly you realize, uh, what happened. For example, what happened at, uh, Facebook and it happened became a hypothesis very, very much, much later is like, We found that there's cer…

AI assessment note: “There are multiple problems here. One is, I think when you have the data”

Q What are the biggest mistakes people make when trying to influence people, have you found?

A The biggest one I used to make, and I think most people make is the, is, ah, is confusing the what and the how. It's like, what message do you want to deliver, and how do you deliver the message? And so when you deliver the message, we are all human beings. If you can do it in a way that is easier for that person to handle, I think, or they can resonate with them, uh, or all the influencing skills I talked to you about, then I think it makes your job much more easier. I've seen many, many people try the influence, but they, they fail. I mean, for example, I knew a very senior leader at, at Facebook who would be like, I'm just, they'd be so blunt and say, this is it. Take it or leave it. Or, and you would never resonate because they didn't try hard to influence. They just wanted to say the facts, but they didn't try to say, is that person actually, I mean, at the end of it, influence is not about just saying, it's about having the impact, making sure you're able to influence into making a change in the direction that you think should be the right way to do it. It's not just about saying things. It's actually making the change. For that, you need to go far more than just Saying things in any way you want. So you got to start to understand people and psychologies and all these things.

AI assessment note: “confusing the what and the how. It's like, what message do you want to deliver”

Q You worked with Mark for many years at Facebook. What was your biggest takeaway from working with him?

A Being able to up level to the highest level and go to, you know, the 10 feet level is incredible. So he would be able to say, here, we want to become, I mean, we're going to be a mobile first company. Or something. And that's essentially what he wants us to do. And then he will outline a five page document on every single, why it is, and then he'll talk about the strategy and then why it is that important, then he'll talk about the strategy. Then he'll talk about every single team and the roadmap for each team and get to the level of, he won't get to the level of which person does what, but he gets to the level of roadmap, maybe even, and then even initiatives inside of it. You may not get to the specific tactics and, and, and so on, but his ability to go all the way from the top, take a big problem, break it down all the way down to initiatives for such a large problem in a five page document, which I think he writes in such short time. I mean, I think he wrote his S one in one sitting on a mobile phone. I mean, it's astonishing.

AI assessment note: “his ability to go all the way from the top, take a big problem, break it down”

Q Can you just, for those listening who don't know the difference between motion and progress, how do you define the difference between motion and progress? I'm loving this.

A Yeah. Um, motion is about doing tons of work. And I recall when I used to be younger, I would say I worked 24 hours. I didn't sleep three nights in a row. And that's just basically saying you did a bunch of different things, lots of activity. But if you ask those three days of activity, what was the impact? What is the value of the value of that activity? And you can't actually say much. Oh, I did. 2000 things. And I think what ends up happening is that we, we, I think it's a, it's a rite of passage. I think at the earlier phase of life, you actually work hard and you feel good about it. And working hard is the most important thing. I still think it's the most important thing, but by the way, but If you work hard and don't work on the right things and you don't prioritize it, that doesn't need to impact. And so the idea is that the motion is all about activity, lots of different activity. And the moment you think it's, it's kind of like a vanity metric. I mean, it's like saying I got, I mean, uh, I, I have these billions of installs where I, the, the retention is like one person, right? It's not something that you really want to, it's sort of like a vanity metric. I, I think, uh, That's like a vanity material.

AI assessment note: “motion is about doing tons of work”

Q What would you most like to change about the world of growth?

A One of the things that we don't do enough is counter metrics, and I think I saw that at PayPal and at Facebook, where you would grow a metric like at PayPal, for example, there were two teams. One was growing revenue, and then one was actually stopping revenue, which is fraud, and neither team had the other as a counter metric. So the, the PayPal's growth team would keep increasing revenue, and the fraud team would keep stopping them. But neither wanted the other to succeed or they didn't put it as a counter metric. And if the two teams can work together at two different metrics, which can actually fight with each other, you know, and be in conflict is a big problem. So you should have counter metrics.

AI assessment note: “One of the things that we don't do enough is counter metrics”

Q Does activity not lead to progress though? And what I mean by that is by doing lots of things, even if you are directionless, you get data that will direct you in certain progressive directions.

A I have a framework for this. So if you think about your activity and if you think about it, everything feels like a, uh, in terms of if you take a completely new activity, right, you're actually learning Up in the, in a, in a curve, and then you start a flat note, right? I mean, if you look at it, you go down straight line, you keep growing as you go along, and then after a point in time, you, you, you asymptote, you don't grow anymore. Let's take, for example, basically this thing, brushing your teeth. I mean, brushing your teeth is now second nature. You can't say that if I spend two hours on it, you're going to get that much better. Probably not incremental. There's opportunity cost to it. So as you, in terms of activity, if every single activity that you do, Where on the straight line that every single hour that you spend, every single day you spend improves or increases or you're better each day, then I think you should be spending time on all kinds of different types of activity and you'd be okay. But I think if you spend 80% of your time actually saying that you're, all you're trying to do is, you know, provide a, I mean, basically your traffic ticket at the New Jersey Turnpike and you're handing it out, that can't be If my 80% of your time is just doing that, you can't see I'm getting better and better at it. So I think it's a kind of activity to do whether you are on t…

AI assessment note: “whether you are on the growth curve of the activity or in the asymptote”

Q What does it take to do so what well? Like what does a good so what Lead to?

A The so what is all asking the question of, okay, this thing increased by .1 person or .5% or one person. So what? That's all he's asking. And if you ask the so what question, you are basically saying, so what? Yes. Oh, if I do that, he'll increase my, wow, my North star metric or Mao, my North star metric by a 100,000 users or by 200 users. So if it's 200 users, you see, duh, It's no value to me, but if it's a 100,000 users, wow, that's super cool. That's what I want to know. So when you look at the, so what you have to have a sense of something is material or not. Material basically means you have to have a sense of what your overall goal is. If you have an overall goal, is this the highest opportunity you can have or one of the high opportunities that you can. So you've got to tie whatever you're trying to do back to something into a North star metric. Even if it's not, this goes to the art and science, but even if it's not an exact You should have a sense of how much you're going to drive without asking the so what question. That's a problem. And what I've realized was the difference between good analytical people and the, who can be good at insights, but the ones that can, that are good at actionable insight, the muscle is really the so what question. It's not the analysis. They can be great at coming out with lots of indexing and analysis, but coming on, they don't ask so …

AI assessment note: “tie whatever you're trying to do back to something into a North star metric”

Q What are the biggest hiring mistakes you've made?

A Early on, the big mistakes that I used to make, and I make less of it now, I think I'd probably still make them, is, um, I think about slope and asymptote. Asymptote is how good are you? Slope is how fast are you growing? And so what I would hire more for is People with asymptote, which basically means that, oh, they have such a good profile, et cetera. They've done so much, et cetera, but they wouldn't look at the growth and they may actually flatten out on the growth part. And that is probably much of my mistakes. You go back to it. One big one would be the hiring for asymptote rather than slope. Now I don't mind. You can imagine what it's just a matter of catch up, right? People with a slower asymptote, the faster growth is, are going to overtake. And I generally tend to invest in people over a very long period of time, but within reason, within two people, Within slope and this, I know that basically the, the effect of compounding will just overtake the person. And if you're willing to invest over time, you could.

AI assessment note: “One big one would be the hiring for asymptote rather than slope.”

Q growth team being independent, a standalone growth team. The alternative could be that you have designers, you have marketers with a growth slant towards them, more analytical, more rigorous in that way. Um, you have PMs in the similar vein, and they work as an integrated part of the existing org. Do you think growth teams need to stand independently or do you think they can function within the org?

A I think there are two answers to this. I think the answer at an earliest stage of your growth, I think they should be a standalone team. I think it's for two reasons. One is I think it's the, is for the best practices, meaning that they can learn from each other and then they can go solve problems across the company. Suddenly you separate this team and Put them into the different parts. I don't know if they'll be able to build the same culture of the noob. A lot of it is knowing how to do this really, really well. And all of this transfer, if you went from, let's say I worked on many parts of this from pages growth to games growth, to address the growth to, you know, and then when you have all of these types of growth, what ends up happening is that these sort of knowledge does translate and imagine that all this was not part of one single team and they were separated all over. I actually don't think the learnings will be there. So My feeling at the earliest stage, you should all, I mean, it should be centralized. Now, once you get a large enough team, if you get to a large enough team, I actually think that it can start to be decentralized and work, go into product teams, but I actually think that early on it should be centralized. So the more important thing is that somewhere in the interim, you probably have a role where you embed people into teams. You embed people into tea…

AI assessment note: “at an earliest stage of your growth, I think they should be a standalone team.”

Q was like, huh, that's a very annoying answer. Um, but I totally agree with you, and I love that separation between the what and the how. I do want to touch on the hiring process. You've hired many incredible teams. I spoke to Alex about your hiring process and the incredible people you've brought. How do you think about the hiring process for how you add great people to teams?

A I think very dimensionally, which basically means that I don't think about a person as a person. I think of them as a body of skills. So what that basically means that are they Peaking in one or two or three different things and not a liability in the others. That's kind of how I think about every person. So the point is that, so if that's what it is, I would think like, oh, this person is exceptional in A, B, C, they can bring a lot to the table. At the end of it, what you're trying to do is hire a bunch of different people who are excellent what they do, that they can learn from each other and become better each day. So what are you really trying to assemble overall is if you think about why anyone comes to work, It's for four, four different reasons. One is they love what they do. Number two, they love the people they work with. Number three, they Feel like they can learn from the people that they work with and for the company is going up into the right. If one of these four does not work, they will leave. So that's what you're trying to do. So essentially what you mean is if you have the people with the same skills, all of them being exactly the same skills, they're not going to learn from each other. If you're going to have people that you feel like you don't love working with and they're all jerks, how are you going to stay? If the company's not doing very well, it's actu…

AI assessment note: “I think very dimensionally, which basically means that I don't think about a person as a person.”

Q was like, huh, that's a very annoying answer. Um, but I totally agree with you, and I love that separation between the what and the how. I do want to touch on the hiring process. You've hired many incredible teams. I spoke to Alex about your hiring process and the incredible people you've brought. How do you think about the hiring process for how you add great people to teams?

A I think very dimensionally, which basically means that I don't think about a person as a person. I think of them as a body of skills. So what that basically means that are they Peaking in one or two or three different things and not a liability in the others. That's kind of how I think about every person. So the point is that, so if that's what it is, I would think like, oh, this person is exceptional in A, B, C, they can bring a lot to the table. At the end of it, what you're trying to do is hire a bunch of different people who are excellent what they do, that they can learn from each other and become better each day. So what are you really trying to assemble overall is if you think about why anyone comes to work, It's for four, four different reasons. One is they love what they do. Number two, they love the people they work with. Number three, they Feel like they can learn from the people that they work with and for the company is going up into the right. If one of these four does not work, they will leave. So that's what you're trying to do. So essentially what you mean is if you have the people with the same skills, all of them being exactly the same skills, they're not going to learn from each other. If you're going to have people that you feel like you don't love working with and they're all jerks, how are you going to stay? If the company's not doing very well, it's actu…

AI assessment note: “I think very dimensionally, which basically means that I don't think about a person as a person.”

Q Do you find it tough because at Facebook you are inundated with data, you know, you put something live and there's a hundred million people on it if you want to, by the end of the day, with, with any new product, it's like you fight and claw for every new customer. Is that tough to transition to?

A Yeah. So I think what I've started to develop while at Facebook was creating frameworks. To think what it is basically when you start to develop frameworks, like a formula as a framework, right? And at Facebook, we used to develop from a formula as like you have a formula for the entire company, which is if you look at revenue as the driving metric that you carry out, you have number of users, and then you have time spent per user, and then you have ads per time spent is formula. So those are ways actually to think in terms of frameworks. So if you think about things in frameworks, you don't need that much of data. What do you really need to think about is In, in terms of that. And which is why when I went to Sequoia, there's so little data compared to Facebook, there's so little data. And then I needed to kind of think about abstractions. How do you create abstractions and frameworks? So then what we realized what all the companies at Sequoia, for example, we can classify for the types of companies phase Sequoia had was eight different types of companies, e-commerce, two sided marketplaces, uh, you know, consumer subscription, consumer ads, and, and, and, and, and, and SaaS obviously, and so on. So there are these seven or eight Different types of companies, eight formulas. And then what tends to happen is that then you don't need to have a lot of data. You, all you really nee…

AI assessment note: “when I went to Sequoia, there's so little data compared to Facebook”

Q Talk to me, what progress did you make there? And how did you come to answer that question of how fast can we say no and focus our attentions more effectively?

A There was a company where we would actually find out that the, they were growing really well. Everything was going right to the right. And then we would find out, we asked them for the marketing expense and we would find the marketing expense. The reach of the marketing, when we looked at the marketing reach, it had, uh, it, uh, it was very close to the addressable market. So basically they already talked to everyone, in which case we realized that that one thing is not. Another company we find out that, uh, the reason why we did not invest was we realized that their, um, their, all the older cohorts were doing really, really well, retaining well, uh, and engaging well, but we found that the more recent cohorts We're actually starting to decline and we could see it in the data. And that is the one reason that we did not invest in them. So these are just two examples, but every time that we would look at, we will stress it and saying, how can I say no to the company?

AI assessment note: “we will stress it and saying, how can I say no to the company?”

Q That's really interesting to hear in terms of that transition from centralized to decentralized. Founders are always told, hey, you need to hire for 18 months ahead of time. Uh, for the future company that you will be, do you agree with that given the many different hiring experiences and scaling journeys you've seen?

A This comes back to the product growth, right? I think that if you think about it from a, I mean, I have while at Facebook, uh, so there's, I'll give you an example at Facebook. Uh, when I joined Facebook, uh, analytics was all about counting numbers. And then it was creating dashboards, and then it was doing A-B testing, and then it was going towards goals, roadmap, and strategy. So initially the types of person that we needed to hire were basically people who can just count numbers. And secondly, so it was a bunch of people who can create infra to create dashboards. The third was people who actually were statisticians who could do A-B testing. And then Finally, it was people who could influence. And even now, I think it's Facebook is like, uh, the analytics team is largely about influence, even inside the growth team and so on throughout it's about influence. So the point is that if I had actually hired three years earlier and said, I'm going to hire people for influence, what would ended up happening was people wouldn't have been able to do the same people who do the AB testing who need stats background are not the ones who can actually influence. And what would happen is that you wouldn't have actually taken the journey in the right way. So what ended up happening was that We, we build a dashboard, we automated it. A-B testing , we build something called Deltoid, automated i…

AI assessment note: “if I had actually hired three years earlier and said, I'm going to hire”

Q I, I listen, I love that. It makes me feel a little bit better because I've made many mistakes. You said like, we just don't know, we just don't know. Before we move into a quick fire, why do so many senior execs fail, Chandra?

A I'd say two different, uh, answers to it. One answer is that I think Uh, what I've noticed is that this happened even at Facebook and, uh, and while I worked with over a hundred portfolio companies, I think there are, I think of it as from an exec perspective, I think there are three types of execs. People who know how to take companies from bad to okay. And people who know how to go from okay to good. And there are people who are good at going from good to great. I mean, Chris Cox, excellent exec. For going from, at Facebook, Kristoff is excellent at good to great. I don't think he was good at okay to bad to okay, which means that bad to okay requires a lot of firing. This whole thing is bad. Turn them around, get a completely new, you have to have a different type of mindset to be able to do that. The good to great are people who are superb at being visionaries, who are able to, to bring everyone along. Everything's already in a decent place. They can know what, Kind of products you need to be dreaming for the next stage of evolution of the company. They're fantastic at it. What ends up happening is that at least at the levels at which I've seen newer execs, even chief product officers, et cetera, whatever execs you look at, what ends up being is that the, you just go by resume and say, Oh, let's do this. You don't actually ask the question of what does the company actually n…

AI assessment note: “You don't actually ask the question of what does the company actually need”

Q thought of like fix what's broken before moving on. I always think about the opportunity cost of time. Sometimes it can take nine months, 18 months, two years to fix something that's broken. Do you still think that it's worth spending the time to fix it if bluntly a lot of it's out of your control and the end state isn't even one that you would want to be in?

A You know, I mentor a lot of, uh, uh, uh, I mean, basically, uh, high school kids and undergraduates, and I tell them the number one most important thing that you need to learn as a, as a kid, especially at their ages, because they're extremely talented. They're very smart. They can do things as character building. To me, I think it was a character building exercise. The fact is that you need to build, uh, you not quitting is a character building exercise. I mean, as we are a child, we've been told don't lie, which I think is a character building exercise. Uh, just crossing any line that you want to That, that you think you shouldn't is basically a character building exercise. And I think it was a very strong character building exercise for me. So yes, specifically how long it takes. I think it's a, it's going to hit you regardless at some point or other, it's going to hit you if you don't build character. So I think, uh, two years would have been a very long time, but I think six to nine months, I think it is worthwhile because otherwise I might never have done it. And that has helped me so much later because when it became very tough situations at Facebook, I knew how to handle it. I didn't back away. I didn't say I would run away from a problem. I stayed on with it, and it was a very, very good six to nine months, uh, time spent.

AI assessment note: “I think six to nine months, I think it is worthwhile because otherwise”