Gokul Rajaram - Lessons from Investing in 700 Companies

Ramp is the only platform built to make your finance team leaner, faster and better, saving businesses 5% annually on average so you can stay focused on growth. Ram customers grew revenue 3.2 times faster than the average American business. Visa, Fersel, Cursor, Stripe, Notion, 11-Mibes Shopify, and 70,000 other businesses all run on Ramp. Mind those two and social doors. Learn more at ramp.com/invest. Felix Byrogo is a personal finance agent that turns a single prompt into finished, client-ready work using your firm's own templates, context and standards. Send Felix an email like "Take these comments and turn them for me" or "Update my tracker with the context of these emails" or "Run the ability to pay math on this buyer" and Felix sends back Finnish PowerPoint decks, Excel models and source research. Felix works the way your team already does, delivering work quickly and accurately around the clock. Learn more at rogo.ai/fuelix The best AI and software companies from OpenAI to cursor to perplexity use work OS to become enterprise-ready overnight, not in months. Visit workOS.com to skip the unglamorous infrastructure work and focus on your product. Hello and welcome everyone, I'm Patrick Ochanasi and this is Invest Like The Best. This show is an open-ended exploration of markets, ideas, stories and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at Colossus.com. Patrick Ochanasi is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.fc My guest today is Gokal Rajaram. Gokal is one of the most prolific product builders of the last 20 years. He's built the core ads and product businesses at Google, Facebook, Square and DoorDash, working at each company during its most formative scaling periods. Alongside his operating career, Gokal has invested in more than 700 companies giving him an unusually broad view into how products are built and scaled. This conversation is about how product building is changing with AI and what remains durable when software becomes increasingly cheap to create but hard to defend. We discuss the one thing Gokal believes is truly future-proof in AI, why companies like Zendesk and Slack are more exposed than Salesforce and NetSuite and the few sources of defensibility. We also talk about everything Gokal has learned from helping build the most important ads businesses including the only three ways an ad business can make money, how those constraints shape product decisions, and what consumer behavior change threatens every major platform. Gokal shares lessons from working closely with Larry and Sergey, Mark Zuckerberg, Jack Dorsey and Tony Schoo, and what he learned from watching each of them build generational companies. Please enjoy my great conversation with Gokal Rajaram. I thought an interesting place to start would be the changing nature of how people are building products. The biggest story by far technology seems to be cloud code or cloud co-work as well. The ease with which both technical and non-technical people are able to build something that they can imagine. It seems to have been just a complete explosion in their ability to do so. You've built a million things, you've invested in 700 companies watching people build things, you're about as prolific as they come as a product person. Maybe just give us your state of the union of how the world feels to you in terms of technology building products and how fast that's changing. What is interesting about product development is that 10 years ago or even 5 years ago they were very clearly defined rules. Product managers articulated what to build, designers designed it and engineers built it. Over the last few months I've been talking to many companies but over the last two months in particular December and January, December 25 and Jan 26. It's become very clear that something has fundamentally changed. And what that thing is, is the notion of a long horizon, a long-running agent. I've experienced it myself. About six months ago I tried to use cloud code in the early days to build something. I call it a video transcription tool. I've tried to build it. It kept failing and then I had to go in and try to debug it. Ultimately I gave up. Two weeks ago while watching some episode of some TV show, in 1 hour I was able to basically prompt my way to a good video transcription tool. Because these agents now are resilient to failure and you don't have to be very technical to use them, this changes the expectation of product teams. After I did that I started talking to three kinds of companies. One, portfolio CEOs of companies have invested in, second, the large AI labs and third, a bunch of AI native young companies. To see what the similarities are between them. A few things that emerge. First, product development as we know it is changing because the models and capabilities are growing so fast that if you try to be very strict and stringent about describing exactly what you're going to build up, prescribing what you're going to build, it is going to not work. So almost everybody has gone to a bottoms up approach where it's not doing the product management anymore. Product managers, the only thing they do now is they articulate what the customer needs are the highest level and they're the guardian of the why. But the actual product is built bottoms up by engineers, researchers and product managers and designers all working together on the code itself. So capabilities and models are changing very fast. Whatever you think of six months ago, if you continue thinking on that dimension, you're falling behind. So it's very, very important for the product managers to be understanding of what these models are capable of and to be hands on. So they sit with the engineers and the researchers and write code, do prototypes, do anything and everything it needs in a hands-on way. The first thing we are seeing now happen is that PMs are starting to check in code with either codex or slot code into the actual production repository. Right now engineers have to review the code, but you're going to soon see the slot code codex and other tools actually review the code itself before engineers commit. So all the companies are struggling with how to evaluate these people. Earlier, there was nothing called the prototyping interview. Now, the explicit interview in the interview loop called prototyping literally forces product managers to be hands on. Second, the product manager and designer role are merging increasingly. So the designer role is an interesting role in particular. A lot of companies are going through headcount allocation this year. And I'm hearing from many teams that when given the choice between an extra designer and extra engineer, they're saying, you know what the design systems are already laid out. Now that we have the design systems already laid out, we can use AI to do work around these design systems. So we need maybe a small number of designers at the company level to manage the design systems and the design language. But AI can leverage the design language to do designs. So please give us an extra engineer. So the number of designers and product managers, the number of engineers, when I was growing up in product, it used to be 1 to 3 or 1 to 10. It's going to 1 to 20 now. And then I think the other very, very important thing that's happened, which is fundamentally different is when I was growing up, products were deterministic. Where there was a workflow, you knew if a user did X, Y happened. Today, you could do X, Y happens. But if you do slight variation of X, something completely different happens. Non deterministic software. What that means is you have to be on the other side, an evaluation or what is called e-walls in AI. And someone has to evaluate whether or not what the software is producing is reasonable or not across various use cases. Obviously, they can be human e-walls, AI e-walls, et cetera. But who owns the e-walls? It's the PMs. It's the PMs and the researchers. The PMs job is to be very clear at a high level about what the user needs are and then have a very clear sense of whether this product is good to ship or not by evaluating it. Very times you've got to write AI yourself to evaluate the results of AI because humans can't. So PMs are good at coming up with evaluation techniques. It's the non determinism of software, the speed of which things are going. And overall, the notion that the capability frontier is being pushed out every two months, makes it an incredibly challenging, getting incredibly exciting data about it. If you think about, my friend Zach has a great way of thinking about AI, which is, we have the Industrial Revolution for Goods, and that basically this kicks off an Industrial Revolution for Services. This interesting opportunity to ask about what your philosophy of product is. You're such a product-centric person and builder that's what you've done, that's what you've invested in. As we face down this Industrial Revolution for Services, what is your broadest possible philosophy of product as we enter this era? Very simple, a product person or product manager if you call them. Their job is to balance customer needs and business needs. The product manager, there has to be somebody at the company who's a keeper of the why. Why are we building it? What customer are we solving? Why is this a pain point? How intense it is? How deep it is? Second, how does it add value to the company? If you build this thing, solving this customer, how does it value add to the company? I think balancing those two is a very delicate act. You can build something amazing that has a tremendous amount of value to the customer, but doesn't build any value to the business. You can do something that is awesome for the business by raising prices, but it is valid detracting for the customer. So balancing customer needs and business needs are the highest, there is what I think of the product and what it comes down to in my opinion, or the last 10 or 15 years I've really gone down to this notion of outcomes. Outcomes, I think, are what define the best product people and outcomes have to be defined in the form of customer behavior. [BLANK_AUDIO] because customer behaviors are leading indicators for every business outcomes. If you think about it, the simplest thing that a product does is to make somebody go from not a customer state to becoming a customer state. And from becoming a customer state, you're becoming a loyal customer. And then maybe to become a loyal customer, to become a paying customer. Or if you do a board job, you're becoming a loyal customer, becoming a churn customer. So these are all behaviors. Everything you do a build should be attuned to the goal of what customer state change does it lead to? What customer behavior change does it lead to? So I tell every CEO I meet that is trying to hire the first PM or doing the first product review, you need to ask why? The only question he asks is why? Why are you launching this feature? And you should not let any feature go out if there's not a clear hypothesis behind this feature. And the hypothesis has to be articulated in the form of a customer behavior change. We believe that by launching this thing, the customers will go from doing X to doing Y or from spending X minutes a month doing this to Y minutes a month doing this. You have to have a hypothesis, which is grounded in some data or something you know about the customer, some secret about the customer. You mentioned at the start, the difference between the video transcriptions tool six months ago versus more recently and how quickly that changed. It's just such a hard feature to reason about given the pace of change. So how do you reason about it? Is there anything that can be truly a feature proof? >> Yes, the one thing I think that's going to be truly feature proof is judgment. Why? Because what is the biggest challenge you have when you have 1000 AI engineers writing code? You have the big challenge of AI slop. Every product you'd have talked to is extremely worried that because you have these engineers running rampant, they're just going to produce lots of code. Which of this code is even valuable? In an era when you can do everything, the question is which of these things matter and you should truly do. On the product side is judgment around what needs to be built and evaluating the output on the engineer side is evaluating the code because if you don't understand what the code says, I think you can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it and make sure you have to have human review at some point, a special critical code that is in the code of your system. And similarly in design, you have to have judgment around, does it make sense in the broad design system? So I think this judgment is the number one thing that humans are going to bring. Era of infinite productivity, the question is what are the things we productive on and are we building the right things? Vanta automate security and compliance for over 16,000 fast moving companies like ramp, cursor and Harvey, keeping them audit ready around the clock. It's the number one agentic trust platform and it now helps companies like yours watch for the risks that show up between audits across your vendors, your AI tools, and your whole environment. Every new tool your team signs up for, every vendor that turns on AI features is an opportunity for something to go wrong and most security programs weren't built for AI's pace of growth. The Vanta agent works like a 24/7 GRC engineer in the background, finding issues, drafting fixes for you, and cutting vendor assessment time by up to 50%. Whether you're a fast growing startup or a global enterprise, Vanta helps you earn and prove trust. Invest like the best listeners get a special offer for $1,000 off at vanta.com/invest. Rigline is the first end-to-end system of record with embedded AI for investment management firms, running portfolio accounting, reconciliation, reporting, trading and compliance on one unified platform. Firms are moving off legacy technology and onto Rigline because of how far ahead Rigline's AI features are compared to anything else in investment management software, which is why I believe that firms that come out ahead in the AI era will be the ones running on Rigline's unified platform. If you're serious about your firm's AI strategy, Rigline should be part of that conversation. You can request a demo at Rigline.ai. As you evaluate companies today, build things yourself and just think about the trajectory of these tools. Maybe walk through how someone should think about building an AI application. There's so many people excited about, it feels like a gold rush with this new technology, so many things that we can do that we couldn't do before, or things that specific people couldn't do because they weren't technical that they can now do. How should people think about building an application using AI starting today? First and foremost, you've got to start with the deep and compelling problem. The good news is there's a tremendous amount of deep and compelling problems to date, every vertical and every industry. Why? Because still today, till recently, software was used more as a tool for humans. We finally have software that is agentic in nature, which means it can do the job of people. The question you have to ask is, what industry are there roles of people that are highly paid, that are doing somewhat of a repetitive job, and that can be done by software? Every three months the answer gets deeper and deeper. You couldn't have told me that a designer's job could be automated by AI six months or nine months ago. You could have told me that an architect's job could be automated by AI. A lawyer's job could be automated by AI. It turns out, increasingly in every vertical, these capabilities are getting better and better. So you want to start with what industry do you want to be in, and what kind of job do you want to do? Second, you want to target a high value workflow. You want to target a workflow that is deep, that is complex, and that requires custom data. I think one of the challenges with this whole space is that the models are becoming so good, that if you try to build a company that is light, that is not a hard problem, the foundation model companies are going to eat you. I met with the CIO of a Fortune 500 company a few weeks ago, was asking him over a few startups I had invested in and worked with. He said, look, I don't know why I would use any of these startups. Gemina has an agent builder product, and I also use ChadDB, the Enterprise, and they also have an agent builder product. And I have a thousand IT engineers who work for me. They all want to be retrained as AI engineers. So I'm just going to put them using these horizontal tools to build my AI agents. Why do you need an startup? And so that's the kind of thing you're going to face that if the CIO of a company of your target customer can build what you're building using these agent building tools, you're not going to be successful. So you've got to really go one step ahead of what can be build a multiple subs ahead, and you've got to extrapolate to where can the capabilities of these agent building products come, and you've got to do something very, very different. So what that means is you've got to have durability, because ultimately, as venture capitalists are even as an entrepreneur, your time horizon can't be building something that lasts for one year. And that's the biggest challenge. They're not building an application. It's building an application that's durable. That basically will last a test startup. And I think there are a few things around durability. One, you need to have ownership of a scarce asset. A scarce asset could be a license of some kind. It could be a regulation of some kind where you have unique insight into it. Second, you might basically own a control point. A control point is a thing that controls how people interact with money or with data. Third, you want to maybe have hardware, which is hard to replace. Fourth, maybe you want to be part of an essential workflow. Fifth, you want to have network effects. You want to think about those things and figure out how after you take on that workflow, you can make it more durable. And finally, I think your ambition has to be to replace the entire system. In other words, increasingly what is going to happen, and I'm seeing this more and more, is every vertical has either a legacy or somewhat new, what is called a system of record, which is a system where most of the data is stored for that system. For example, in legal, there's a company called Filevine or another company called Cleo and sales its sales force in health care. It's epic. Now for many years, these companies all had APIs. If you enter that industry, you could build an agent company on top of these APIs. In 2025, things changed. These companies started seeing that these agent companies, AI companies that are being built, they're starting to take on the functionality out of these companies and are treating them like a dumb database. So you started seeing last year that these companies are cutting off access to APIs. Slack has done it most publicly. Slack is owned by sales force. They cut off access to Gleen, where Gleen can no longer access Slack data. And the reason is they don't want Gleen to build on top of them and then slowly suck out the value that Slack has. And I'm hearing from other verticals that they're doing one of three things. They're blocking access to APIs. They're offering their own agents for free bundled. I think that is a great and effective strategy. However, they're charging these AI agent companies to access the data. Just to access the data, the APR was free. They're saying now it's $2 in API call. They're trying to make the model of these agent companies unviable. I think it's going to be very hard for a end customer to use multiple companies. So you have a system of record and then you have this agent that sometimes doesn't work with it properly. So the agent companies have no option to also start building and offering a system of record. The company I know is now trying to figure out how do I build the entire platform and not just a system that does some workflows. I think last year, even I was like, oh, we can do workflows. We can build what is called the system of action and live on top of the system of record. I don't think that's an option anymore. This Slack example is a good one of last generation software company, which was very big and very successful. One of the most interesting and best questions and I'm curious for your answer from the perspective of a builder and a technologist is that the degree to which these horizontal model companies are going to destroy or be very bad for old software companies because over time it will be trivial to us. spin up your own slack that has features that you want for your company and it's very reliable in all the same ways that slack is and therefore, slacks in a lot of trouble. How do you think about that question? Obviously, public markets seem to think software is in a lot of trouble. The multiples are really, really low. How much would you be worried if you ran a good, solid, but older software company today? There are two kinds of legacy companies. One are systems of records and one are things that are price based on outcomes. So software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Literally Zendesk prices seats and each seat comes with utility. In other words, each seat corresponds to customer service agent that taxs out in a number of customer tickets. So that company should be worried because I can have an AI agency right next to Zendesk and you can slowly siphon off instead of paying for 50 Zendes seats. You can pay for 20 and I can have 30 AI agents sitting next to Zendesk and that siphoning can happen. You don't have to have all in one decision. It can be a two-way-door decision. Those are the most endangered companies in my opinion. For these companies, you need to change your pricing on utility based on outcome and you need to actually build the product to be based on outcome. It's easy to say that done because literally you are going from a 20 or 30 dollars per seat to maybe charging a buck or 50 cents or 20 cents per ticket result and you don't know how that's going to turn out. So you've got to change your pricing model and I think that's a very challenging thing. That's why I think many of them probably need to go private because they have to make this business money transformation in private. I think it's going to be hard for them to say public. The companies that are less exposed to ones where the utility is not based on seats but it's based on data that has been collected and captured over a period of time. The more timeless the data is, the more protected they are. Slack, for example, I would say, might be in a little bit more precarious because the data in Slack is not timeless. Half life is very short but if you have ERP is a great example. Somebody uses NetSuite as an ERP. Now I don't know how NetSuite actually charges but it doesn't matter how many seats you buy. The reality is it runs your whole business and there is no compelling reason for someone to put their career at stake by ripping out NetSuite. I know over the last year there's been a lot of AI enabled ERP businesses but there is no compelling reason to take NetSuite and say I'm going to rip it out because it is career limiting to suddenly take NetSuite out when you're running on NetSuite. I think those companies are much more insulated and I think obviously and you could argue that NetSuite has more time to build AI agents on top of it because they have the data. They can train the AI agents on top of it and bundle it. Essentially, I think the software public markets are not distinguishing these two types of companies. Companies with half-life data is low and where you can actually have, you can literally take half of the value of this company and put it onto an AI company that sits next to it while something like an ERP system or even Salesforce for sales data and records. Those are real customer records. It's going to be hard. So, what an AI native company is doing. The first thing you've got to do if you ever have to compete against them is you've got to spend a year or two first building a system that literally takes, migrates your sales for instance to your own company's platform. One of my companies is an AI native company. They literally hired engineers in a European country for two years to build this migration then transition tool. So, you have to build a migration tool because who's going to migrate it? You can just present your spanking new system but this data is still there. Even for Square, for a small business, I remember they had a point of sale. They wouldn't move to us. Even they were cheaper because they had gift cards, customer data, loyalty data, payment data, all of that, even credit cards. So we had to build scripts and it took us months or years to build it for a simple POS. For something like Salesforce, you can't just say, am I much better CRM? If you look at CRM, what does the CRM contain? It contains your customer record. Your customer support system contains what your customers are complaining about and Giro or at least Cien contains what your parable of an team is building. Now all of these things should be linked because there is no linkage. You should be addressing the biggest complaints of your customers which are in Zendesk. And those Zendesk customers, you should know where they came from, who bought them, who sold them. So all these three systems should be linked together where they're all three different companies, so their companies will identify these things and it's a great value prop. But guess what? None of your customers is ever going to move unless you build a simple, seamless way to take the Salesforce data and move it to your instance. The data from Giro and move to your instance is Zendesk and move to your instance. So, it literally needs a two-year effort to build migration otherwise. You've got to get Accenture. How do you think about stickiness in this era? It just does a general concept when the friction for creators to build something that new is so low, you can do it every one really fast. How is anyone going to use anything for a long period of time? In the age of AI, stickiness, I think comes from a few sources. One, you need to have network effects. So don't actually stickie. Not just because it has this beautiful app, but it's because it's a network of restaurants and dashers and consumers. So you can't just attack one, you've got to go five-curge away to that. Exactly. And so, network effects. The second example of stickiness is when you have financial or money moving through you. I think that's another way to be sticky. Many of the system of records, for example, toast, have payments going to them. And I think that really is interesting because you can't just start building the point of saying you also have to have money flowing through it. And I think if you look at the banks, banks are a good example. Once you have something like Mercury as a business bank, your money flowing through it is hard to then switch because you have regulations and other stuff embedded. So I like things that are combination of financial services and software because of that. The third stickiness is from hardware. You can actually have hardware. Toast is a good example where toast gives you hardware for free. But if you try to return the hardware, you have to pay them. But either case, the hardware is there and somebody can't just build software. They also have to take hardware and put it into the thing and rip out the toast hardware. The fourth one is access to a unique asset. I was thinking about a good example and I came up with the example of Sierra, which I think unique asset is Brett Taylor. I mean, they have full control of Brett who's one of the best salespeople, Chairman of Open AI. He can make a call to any company, any country, and they'll take a call. You can't really outsell Brett. Because I'll find that you need one of these four or five things, which are basically indicators of durability. The half-life of software today is so short that, unless you're one of these things that make it durable, Harrison Helmer has this thing called seven powers. And so you've got to have a few of those seven powers that basically are embedded in the business model from day one. You've been so lucky to work for some of the most well-known CEOs and founders of this modern era. I'd love the chance to ask you a little bit about each of them and what you learned from them. And then more generally, just things you've learned about what great leaders do to run companies. But maybe going all the way back to Google and starting with Larry and Sergey, what did you learn from watching them operate and lead? One of the most interesting things about all the leaders that I've worked with the type of generation companies is that they have a superpower that is very aligned with what the company needs to succeed. And the company was really shaped in their image. The company, the culture, the early hires, the products, I joined Google in 2003. The first product I got exposed to actually which I didn't know about was a product called Caribou. Caribou was an internal code name for a product that was launched in April 1st, 2003. Publicly it was called Gmail. It didn't believe this is product existed because in the internal alpha it said, this gives you one gigabyte of storage. Back then, remember Yahoo Mail was the dominant product and it gave 10 megabytes of storage. So this thing had 100 export storage and this really epitomizes Larry and Sergey's philosophy which was basically built the best technology on the planet. They were deeply technical and every product was held to technology and scale. And I'll never forget, AdSense was the fastest growing product in Google history and we went in to reviews and Larry would be disappointed in us and we asked why. He's like, what percentage of all ads on the internet are you? Less than 1%. He didn't care about the revenue he cared, the Google is involved in serving every single ad on the planet versus making a business of whatever $2 billion or $10 billion. So the focus on scale and the focus on technological superiority and that investment, Google Street View, TPUs, Waymo, all of these I think show the 10 plus years of investment to an uncertain future but knowing that if you invest in technology good things are going to happen and good things happen when it took a decade and that's investing in technology capability. Before we leave Google, you had this interesting idea about communication and Eric Schmidt, obviously another key Google person. Can you tell the story about him presenting the company strategy using nothing but images? This is an interesting example of communication. Eric would give a product leader, we would become seconder to Eric for the weekly strategy or the annual strategy planning session. So I did it in I think in 2007 where my job was to go to Eric and say, Eric, how do you want to present the strategy of the company? He's like, well, it's very simple. I want you to go and interview each of the different leaders of the different teams. There's only one constraint I have. I'm like, what is that? You can't use any words to describe what they're doing. I'm like, what do you mean? They already use words. Nope, you've got to use only images. I'm like, why is that? He's like, people don't remember words. They remember how things made them feel and you can put words in the speaker notes I use. But I want you to come with the most compelling image that exists for what they're describing. So it was a crazy thing because I never thought of doing a presentation that way. So I went to each of the businesses, adverts, search, YouTube, adsense and then had to come up with a compelling image that was going to be a great deal. was easily accessible to the whole company, yet represented what they did. Do you remember a specific image? I'm so interested by this exercise. It seems potentially productive for anyone to try to jam what they're trying to say into only images. And so I'm trying to pin down an image and how you arrived at it. For YouTube, it was a graph that showed that the number of videos being uploaded every second, how it had changed from the time Google brought them to them. So it does not even a graph, it was literally showing this incredible hockey stick that happened over the last 18 months. And then it had, I think we could even show the numbers. So the thing had to be compelling enough that the line would have to be like a U or something like that, but it went like that. If you just showed like this, you have to say something 100x or something where you couldn't say that. Google search appliance, I think we wanted to show that Google search appliance has gone from being used by small and mid-sized companies to being used with the largest company of the planet. We showed the logo a very large fortune, 100 or fortune 50 company that they're acquired. What did you learn from Zach? Zach was, and it's actually, I think the greatest mind on growing, building growth and engagement and building consumer products broadly. I've seen him basically sit in a room and critique a product team would have come in with a very well thought out consumer product flow. And he would look at the flows and he'd say, that is not going to be compelling to users. That is not something that the user is going to engage to, change it to this. And you could say, my God, why didn't I see that before? So he's very, very good at thinking about how consumer product should be designed to maximize engagement and maximize, just growth is probably the best way to put it. The second thing he's amazing at is learning by following. When I joined my task was to lead the ads product team. And Zach at that point knew a little bit about ads because he had worked with Cheryl quite closely. We've Cheryl had worked on ads before. But then within, I think about a year, he shadowed us. He came to the ads team. He basically sat with us. He came to me here for meetings. And within a year, he got to the point where he was generating ideas for the ads team. One of the most foundational ideas of Facebook ads came from what is called custom audiences. Custom audiences is a foundation of most ad systems now. It's the idea that as an advertiser, you want to reach people who are similar to your customers. So if you're a bank and you have say 100,000 customers, how can you give this set of customers to your ad platform and say, look, instead of describing these customers, what did ads just do before? They would describe their customers. I think they are 25 to 34-year-old women. That's not good enough. Instead, if you can just tell us who your customers are and we can map it to our users, we can then find people similar to them. So uploading that data into our system securely and doing it in a way that doesn't compromise in API was the key thing. And it all came from Zuck. How? Because Mark Pinkers of the CEO of Zingga. Zingga was the largest editor on Facebook. So Zingga basically wanted to, like most gaming companies, they were very focused on acquiring whales. Because whales, for any gaming company, casino, et cetera, 80% of all revenue for any gaming company comes from whales. So he was very frustrated at us. We would do these quarterly reviews with Zingga on the ad side because they were large spenders and ads. They were constantly being yelling at us saying, we want to get more whales. We were like, yeah, you're getting users. If you're your idea, you need to figure out how to get whales from your games. What do you want us to do? We can help you acquire users. So he once, I think, talked to Zuck and Zuck came to us and said, why can't they just upload their whales into our system? We know who the whales are. Why can we just find them people similar to those whales? We were like, that's interesting. But we actually didn't know who the whales were. So they needed to tag it for us, who the whales were. And basically, we started doing it similarly. We started finding users similar to the whales that they had. And it worked so well. Then he said, why don't we take this approach and use it for other types of customers who we didn't have data on. It became truly a transformative thing for ads and those all Zuck's idea. He just has something about making connections between disparate domains, which is pretty amazing and unique. What did you learn from Jack and Tony? Jack is, I think, on par with Johnny Iven Steve Jobs in terms of his thinking with design. I understood what good design means. Good design doesn't mean visually pleasing. It means a product that is designed so well that you don't have to give your customers a manual on how to use it. They should be able to see the product and use it. Think about your point of sale. Every point of sale accepts square and things that have copied square. You have to train a barista still for several days after his join and how to use the point of sale. Square is something you can download from the app store and start using it as a point of sale to run your business. A category where you had to train somebody for weeks. That's the example of a good design. He brought that to every part of the company and removing friction from waters, traditionally, I mean squares, whole premise was removing friction from small businesses applying for financial services. And that extended to the product. That also extended to risk. One of the most interesting things that I didn't realize is that square at its core is a risk company. When you apply it to a bank for payment processing, in fact, the company was founded because Jack's GoFounder Jim was rejected many, many times to accept amics by banks. He was a fairly successful glass blower in St. Louis. And he basically was selling two $3,000 glass cultures to people who would send him checks. So a woman called from Panama one day and said, I want to buy this on his website here. This beautiful piece of glass. He said, great, they agreed on the price. And she said, can you take my credit card number? He said, I don't accept credit cards. So she said, sorry, I can't send you a traveler's check. So he lost the sale. And so he went to his friend Jack Dorsey. They had never built hardware. They had never done any of that stuff. But they brainstormed and realized that the iPhone, which had just been released a couple of years ago, had this thing called the audio jack that could be used to put a piece of hardware in and process cards. I can't even imagine the leaves you have to make to get there. But the number one thing that they realized is most small business are denied by banks when they apply. Square and said, said, we are going to accept 90% of people who what they did was they put risk at the transaction level. So they accepted you as a person as a business. But then once you started processing transactions, they would then run machine learning models and every transaction, this transaction, risky. This is not. - They shifted the level. - Shifted the level. And so that kind of lazy, but brilliant onboarding is something that characterizes a lot of good things. The surge, very similar. When we're going to launch AdSense in 2003, I'll never forget this. When we're doing our final launch things, surge was a sponsor. He came and sat in the meetings. He said, what are you guys building here? Well, like website publishers are going to apply for all across the world. It just sells the product. They have to review them and say, we should approve them, not approve them to run AdSense. He's like, why do you need to approve them? You will be like, what do you mean? Our ads are going to be running ads on these things. Google ads are ads powered by Google. You don't want to be on a pawn side or something else. It's like, why not? We didn't have good ads, why not? I was like, well, standards or policies. But what if they lie? He was right. What if they lie? We had so many people applying with Nike.com, for example. It's true. It was very hard to know who owns a domain. I could apply with your domain and get accepted. He was right in some ways. We were just doing it to cover our assets turns out. And so he said, kill all this. So we had literally spent half of an engineering team building this complex approval system with ops and so on. Ops, a super excited. They hired a lot of people. And I was telling us not to do it. And instead, do it in real time. For every page that loads, because we have the JavaScript on it, we know what URL it is. Look at the content at that point. And we were like, it's too slow. We won't be able to look at the content because it's billions of pages. That's fine. Let it note for 100 times. And after 100 impressions, if any URL hits 100 impressions, then start reviewing it. It actually makes sense. Not trying to put lots of checks up front, but being in touch would wear. And why most things don't even get to the level where you care about. In both these amazing examples, and then you also said that Jack would do this across the company, and Matt just in the product. How would you sum up the process of great design that you've observed from the people that are the best at design? What is the method that they're going through over and over again as they apply it to different parts of the company or product? The number one thing I've seen is they try to minimize the number of steps. Everything should be in one page, and you need to cut down things. In fact, Jack called the product manager, old product editor. Why? Because he believed rightly so. The role of the product manager is not to add more features. Any of us can look at a product and say, here's 10 things you should build. The best designers, the best product people, edit down things. Similarly, we have 100 features. One of the two things that really matter that will drive the customer outcome. So the best designers really take 10 pages of design and say, cut out all the experience. So I think it's the process of editing. And this goes to judgment. In an AIH, humans with amazing judgment, which is really editorial capabilities, are the ones that are going to do well and thrive, I think. Fairly Rick Rubin would say that he wasn't a producer. He was a reducer. Great example. Reducer, I like that. Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions nobody's watching. Ramp puts guardrails on spending before it happens. Real-time limits, automatic rules, zero firefighting. Try it at ramp.com/invest. As your business grows, vanta scales with you. Automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest. The best AI and software companies from OpenAI to cursor to perplexity use WorkOS to become enterprise-ready overnight, not in months. Visit workOS.com to scan. skip the unglamorous infrastructure work and focus on your product. RidgeLine offers one unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Schedule a demo at RidgeLine.AI. Every investment firm is unique and generic AI doesn't understand your process. Rogo does. It's an AI platform built specifically for Wall Street connected to your data, understanding your process, and producing real outputs. Check them out at rogo.ai/invest. - I wonder how that applies also to communication. Maybe this is a fun opportunity to ask you about the format that you've allighted on that a leader can send to his team on a weekly basis, I think. It seems like this idea of reducing and simplifying can be applied in so many ways by great leaders. Talk about it in terms of communication from leadership to a team. - One of the things that people, especially founders of startups, don't realize this initially, most startups start with two or three people, and then they go to people who are all sitting in the room together. Everyone can hear what you're saying, but as soon as the company goes into, I call it two rooms, where they're not in the same room together, then you have to communicate. You have to let people know what's going on, and there are a few artifacts that come easy to start putting into place. One is a notion of an all hands. It seems cliched and unnecessary, but even with the 15, 20% company, just getting together once a week, and basically just sharing what people have built and have been working on in a way, and then having the leader address everyone, or one of the leaders address everyone, is a great way to get people together. The second thing is a weekly CEO email, and I think this is a very powerful way for the CEO to get across to the team, what is on their mind? The best way I think is that I've done myself is during the course of the week, you start jotting down things that you think you want to communicate. And then you spend Sunday taking all of those things and adding it to a two or three things that matter, that you want to get across. Most businesses, I think, can be communicated along three dimensions. Product, business, and team. What's happening on the product? How is it becoming more remarkable as starting a customer's better? What's having on the business side? How are we doing better as a business? And then what's happening on the team front? Who are we, added, subtracted? What changes have we made? And most importantly, don't be afraid of repetition, because repeating it once, twice, twice, four times, that's when actually it seems to be a bonus. What is the literal format that you do in your email? What is the structure that you do personally? I've used in the past and what I recommend and what people have seen. Now I've seen at least 15 CEOs adopted and the good effect is three sections. One is called top of mind. So this is product, business, and team. Doesn't need to be all three. What's keeping you up at night? I think this is the thing that literally everyone is hanging on to. I mean, because I remember seeing it from Jack, from Mark from Cheryl, seeing it put in paper or put in an email, is just so powerful. That's one. The second thing is performance update. I think everyone wants to truly understand how's the company doing? How's the company doing on the dimensions? This is where, especially being a startup, I think most people are one dimension removed from how the company is doing. They all want to know that they're doing well. I think this is the way. And the third is miscellaneous. It's things like recognizing specific people. It's quotes from customers. It's maybe an off-site announcement. But the most important section where you should spend 60 years every person with time on is top of mind. How transparent should one be in that? As a leader of business, I could tell you it's top of mind, but a lot of it either might be sensitive or I would worry about scaring people or worrying people about something that I'm thinking about or worrying about, what keeps me up at night might create stress in the business. Where should one draw the line in terms of how candid they are? By proceeding more candid is better than less why? Because if you're more candid, you can actually ask people to suggest ideas. If you have good talent at the company, if you actually ask them, what do you think I should do? What do you think we should do in this situation? I think people will rise up to the occasion. Especially in the company, small, we want people more important. There's a one-way-door decision that we're going to make. We're making it takes us one way or the other. I think it'd be great to get feedback from more people. I want to talk about ads and everything you've learned about building an incredible ads product. You've built the two most important ads systems. And I always say as a company, do you either die or you live long enough to become an ads company? And so we are seeing now with OpenAI, it's happening. Now how do you build an ads business? There are three fundamental ways to succeed in the ads business. Three. And only three. One, you need to own a very coveted group of users and you need to have a surface on which those users interact. Google searches again, example, it's a surface on which a very coveted set of users interact with. Obviously, the express high-intense of Google is one of the most profitable ad businesses. Facebook, very similar. It took us a while to figure out what was coveted about these users, turns out what was coveted was the identity. When you do these users word, and you could match them to customer and other data. And so you could precisely target these people with messages you wanted. And you could find people similar to that. Chat GPT, the combination of intent and identity data is unparalleled. I mean, Google had intent data, but not identity. Facebook, identity, but intent. These things been put together. It's the dream of any advertising person. And these are complex, multi-faced searches. That's the other beautiful thing. You search, but each of the queries is kind of like a search. And then you search again. And you're just building up searches. And Google, you typically search. And then you lose the person because they go off and click. And you don't hear. These are natural language queries ripe for amazing, amazing targeting. So that's one example. There's one way of making money where you have to own a first party product. You have to be the first party. Second, you have to drive outcomes. That's another way of making money. Where you don't own any inventory, but you can drive outcomes that advertisers. The best example of this is a company called App Loving. App Loving is a $100 plus billion company. They drive one outcome really well. Mobile app installs. And no one believed that people would need that many mobile app installs turns out everyone wants to get mobile app installs. It was initially only restricted to gaming. But now every mobile app where they saw it want mobile app installs. So App Loving has built a massive infrastructure. Now they control the buy side. They control the sell side. They even control the middle way. So you could argue that they control the auction for most mobile apps in a way that almost Google used to control or people say they control for the web. But App Loving has built an amazing engine to deliver you mobile app installs at a certain cost. So that's the other way. Second, you do it. You deliver an outcome at a certain cost. The third way to do it is if you are the exclusive provider for a large advertiser or a large source of demand, a good example is a company called the Trade Desk where Procter and Gamble, for example, go through Trade Desk and say, I spend with Google. I spend with Facebook, all my other display budget. Trade Desk here you go. You can figure out how to distribute it and how to run it. And so those are the three ways. But you've got to be exclusive. Those are the three ways that you can make money. No other ways of making money. What business ideas don't work in advertising? What are the business models that just are doomed to fail? Trying to be a middleman on top of these large platforms. From my understanding, Trade Desk, I know, doesn't work on Google or Facebook at all. Doesn't work with Google or Facebook as a first party. But App Loving, I think only little bit works on Google and Facebook. Mostly they do their stuff on the unwashed web, basically, outside. So you've got to stay out of Google and Facebook's ecosystems because if you're trying to build a business on top of Google and Facebook or probably soon open AI as an ad company, you're going to get squeezed. Every time you build a new capability on top of Google, turns out Google learns what you're building. And Google has the best engineers in the planet. So to Facebook, they will take your capabilities and incorporate it to their platform. Let's see if I'm proven right or not. But my take is that there's going to be almost a certain cottage industry of companies that are going to come. And so I'm going to help you optimize ads and chat GPT. And there's already companies that help you optimize placement in what is called these answer engines, called AEO instead of SEO. All of those are not going to create your own willing income. What would you be worried about if you were one of these fairly monopolistic owners of a massive ad network like the ones we've discussed? We could get there over at Amazon in the mix, start Ash, Facebook, Google. If you were there running their ads businesses, what would scare you? Consumer behavior change, where they don't open up the apps anymore, but they use agentic interfaces. They use AI to face which are not owned by my company, this company, to do their transactions. If you assume that a big percentage of things are repeat, then could you put those repeat things on autopilot through an agent and you never open the app? And so you lose opportunities to then advertise. And you lose the relation with the customer over time, because the customers are trusting the AI agent. You can't bury your head in the sand. You have to go and experiment. That's why when chat GPT opened up their apps platform, all of the commerce platforms are experimenting. And the thing I would look for very carefully is, there are going to be early adopters in the app. Obviously they're going to connect, there are Uber account with the chat GPT account. I'm going to look to see these people are connected. How's their behavior on my app? Are they going to my app or not? Are they opening up much less frequently? Because if that's the case, then obviously, this experience is so compelling that I would then have a choice to make. How do I make this experience? Maybe not as compelling as my app experience? But how do we incentivize them here? Open up my app. There's a new battle happening for that first category, which is a new interface to be owned. We know chat GPT does-- I'm curious if you think being the first mover matters to build a new ad network, because there's Gemini, there's Anthropic, there's a bunch of people that have tons of users using this new interface. How do you think about the landscape of the new potential entrance to build the next dominant ad? Now, work with advice. Would you give these various parts? The good news is being first doesn't matter because especially if you're in category one which we described you control your first party inventory In fact being second or third you can learn from the iteration mistakes as the first one makes your inventory is not going anywhere Now some might have more urgency to monetize in others But Gemini doesn't need to monitor at any time soon. So they can just sit back They have a lot of ads expertise and data from Google. They can sit back and wait till they need to monetize In fact a good strategy for them might be to say I am the zero-add platform Google can claim that Gemini has no ads in it and there is a certain set of customers are consumers who care about that The biggest thing is and OpenAI has done a good job of articulating this Add should not influence the content that is served to me or the recommendation that AI gives to me I think they should be relevant But they should not be influencing the recommendations and second You have to keep a high bar for engagement and usefulness Unfortunately, however relevant ads are the reality is that this was in proven is that once you start showing ads in an previously Unmonitized zero ads surface Engagement users goes down over time Because some of the engagement gets siphoned off by ads and some of it gets siphoned off in different ways But this many hold out groups across many companies are proven this So the question for any one of these companies is how much engagement are we willing to take in exchange for monetization First you need to have a hold out group of people who never ever see any ads because that's your fresh group that never sees ads and you need to understand that's their behavior And then you need to always understand how people with ads are behaving And then you need to figure out what the engagement hit us from each quantum of ads And you need to then give your ads team a certain engagement budget So that's what at Facebook there was an engagement budget every year that between the newsfeed team and the ads team We had to adhere to in other words. Yes, we wanted this much revenue But the check metric on the revenue was we can't take more than X percent dip in engagement Overall for newsfeed Taking that well you've talked about like a North Star metric What are the attributes of a good North Star metric? What advice would you give someone that's trying to pick the thing around which the company is going to optimize? The North Star metric is a metric that is an indicator of Company growth and customer value. So it actually balances customer value and business value nicely North Star metrics in my opinion should not be revenue. It should be something that is Directly correlated customer value. So for example if customers are doing well the North Star metric should go up into the right But it's also lead the business doing well For example for square the North Star metric was G PV which is volume of payments processed. It was not going to revenue to somewhat correlated to revenue But it most importantly showed that the number of the amount of payment process to the company was continuing to grow at Facebook The North Star metric was DA use it was actually monthly active users then it over time meant to daily active users because it was an Indication of how engaged uses were now one of the most important things about an NSM is that it needs to be coupled with what we call check metrics In other words incentives drive behavior. So if you tell a team go and optimize this North Star metric It's going to go up 100% but then many things that you don't want to go down could go down So for example in the road ash case because I want to grow GMV which is the gross merchant value which is the North Star metric Now GMV is the total order of total value of all the orders that go to the marketplace I could make it grow up by setting delivery fee to zero by setting everything to zero and what happens then the company revenue goes to zero So you basically want a check metric around the health of the customer and the check metric around the health of the company There are the guard rails around this North Star metric So in the case of door dash it might be I want to maintain a certain gross margin percentage or I want to maintain a certain customer retention percentage Margin is typically a good one to use because in some ways that is a Indicator of the company health There's these two ideas that we talked about when we first met one was the need for the very best software companies to stand alone in the sense that Someone can just go use it without talking to a human and it just works for their problem So like fully fully self-serve so I'd love to hear you talk about that and a related idea was that's sort of on the builder side on the investor side You mentioned to me that all the great investments that you've had the companies that have really had explosive growth Have had a high number of one-up four qualities which is I think was gross margins low cost to acquire the customer High retention and a tight sale cycle which maybe max back on to the self-serve thing talk about the relationship between those two things The cells of notion actually came from Google was the first company I worked at which achieved massive scale and What happened at Google was within the ads team? We basically had a wide number of customers using us the millions of customers using us There were a lot of small businesses, but there are also large companies What we ended up doing to serve the large companies large companies didn't want to use the product themselves They had agencies using it for them on their behalf and they also had internal people at Google Support and sales and operations people using them So on the product side we built a lot of tools for our internal colleagues for our sales and operations colleagues to Manage the system for a large customers one day. I think we were at a Larry review and we were showing these what we called ICS internal customer systems to Larry We were not mean to show it but I think to show him a demo be someone got into it. It's like what is that? Well, it's a system used by our internal teams. It's like why'd you build it? We were like well, we have to help our large customers. He said you mean our small customers don't have access to it We're like no End it right now. I want to make sure that everything you're building for large customers is also available to small customers so we basically had to Take everything we had built over years in this ICS system and make it available to customers and turns out an interesting thing happened Turns out the smaller customers adopted it much faster because some of these things we were building had advanced knobs and so on that we didn't think they were news Turns out the cells of customers were the most sophisticated users because if you do something that's interesting There's all these small agencies entrepreneurs Hustlers if you can help them make more money It's a testament to human creative identability. They exploit the system in ways that you never even know and you learn a lot from working with them So I've seen in every case when you open a pre-system to cells serve you learn so much more about the capabilities of your product Then if you basically it's your sales team doing it on their behalf in fact I never forget in at sense I think we had some of the largest publishers in the world sign up and start using us on a cell so bases and then we engage with them after that And I think companies like at least see and square. I think we had Nike signed up for a square device and Self-so-one-booted and start using in one of their stores. It does two things one It makes your product better because these folks they use the product in ways that you don't expect or anticipate and it forces you Because what is the definition of cell serve the definition of cell serve is the customer can Unbored not just use but on board and use the product without ever talking to or engaging with a single member of the employee base of the company So when you do that that means you have to think about how do they actually get set up with the product So it really puts a lot of effort on onboarding because onboarding is one of those things where most people drop off if you don't do a good job And then you've got to get them to a moment of delight very quickly all of those things if you're not building a cell support You don't even think about in a cell support you think about it every day. It's like a consumer product or a self-service Product and then second what it does for you is it opens up the aperture to your customers because with say a hundred sales people Yeah, you can reach maybe 10,000 customers But with the self-service product with the right word of mouth you can reach millions of customers look at cursor for example It is used in every large company. I bet only maybe one person of companies is maybe the top-down motion 99.9% companies some engineering got it great example is a company is figma actually after I invested in figma I joined square one and a half years later. I tried to basically push figma top down into the design team because I didn't design I said you got used figma. It is a few to use it. They're using a tool called sketch and they said we're not going to use it It's catches much better and so I felt okay It's not my place to tell them what to use so I backed off two years later a mid-level design manager came in and they brought in Figma from their prior company and they got it to be used across and it kicked out sketch So I think with self-service you can get into these things where even there's an incumbent where you can infiltrate and be an Insurgent in a unique and powerful way which a direct sales motion could never have produced them One of the other dimensions that's changing fast is careers I'm curious what you think about the sorts of people that will thrive best in this new era So if you're a person hiring someone What are the sorts of things that you would place extra emphasis on now in the AI era? The number one thing I think is going to be the focus on doing and building I think CEOs have gotten too comfortable over time and I think this is changing Hiring middle management very very quickly and hiring seal old people Instead, I think you're going to see the rise of AI agents doing a lot of work But then humans who manage the AI agents and are ic's So I think what the number one skill that is going to be relevant two years from now probably one year from now is To become a functional expert that knows how to build AI agents to do that function And orchestrate an army of AI agents to do that function well There was a great article the other day I read about an PM at Meta Who's non-technical but to basically build a bunch of AI agents to do his job as a PM so well But even if the engineers like teach me how to use AI agents well And so I think that's what you want you want somebody who is essentially acting as a manager But not of humans but of AI agents And management has to be a full-time job What I mean by that is if you manage three, five, ten people that's all enough You either need to be managing 50 humans for you need to be an ic There is something called span of control, which means how many people you manage. When so span of control less than 10 should not be allowed at any company at this point. Because think about it. If you are managing even 15 people, maybe you meet with them once a week. That's 15 hours. What are you doing for the other 25 or 30 or 40 hours? You should be working. So I think you got to go back to doing. So I literally, and on the company side, don't hire managers as long as possible, hire doers, hire builders. What is your favorite way to assess whether or not someone is that interfering them or learning about them? Best way is to give them a work project. Engineering does a great job. Engineering is always in a great job. Every company I've been at, they would have engineering coding interviews, programming interviews. They do stuff. Everywhere else, you can just be as you're away without doing stuff. So it's where we establish work projects. Where even for core dev, our work project was give me one company that's where it should buy and analyze the company and tell us why we should buy it and tell us what the city should be. And we can just add to do that. Every function needs to have a work project that you need to put them in a room without AI and get them to do the project, get them to do the work. That is ideally very similar to the work they're going to do. For product managers, we would take a product we were thinking about and we would just say, "Yes, a product we're thinking about. Figure it out. Should we build it?" The first and most important thing you want for these kind of thing is, especially for customizing rules, they need to take the voice of the customer. In other words, they need to justify the why. The best PM candidates rejected the premise completely and they did it in a beautiful way. They went and talked to 10 customers in the street. So brilliant. They said, "I talked to 10 customers. They were all square users and we found that none of them wanted this premium insights products. So we don't build it. We have a winner build this other thing." And said, "It was amazing. That's what you want to see. You want agency. You don't want people to just say, "Give me what to do and I'll do it." You want people to reject the premise or question the premise in the first place. Squares should not buy a company. That would be great. Tell me why. That's the kind of thinking you're looking for. What was the earliest thing? Oordash had the best work project ever. He would give people either $10 or $20 and ask them to acquire a thousand customers. A thousand customers were doodas, consumers. And literally some people would say, "I'm not going to take this challenge. I'm not ready for it or something." And great. They literally out of it. And then some people would take it. Nobody even came close to acquiring a thousand or even a hundred, I think. But the goal was to see how many different things they were able to try in the course of a few hours. Someone went to the gym, printed flyers out and gave it out. People tried all kinds of things. But it was a brilliant way to just filter out people who didn't want to do stuff. Is there any other advice that you would give the person building the career? We talked about evaluating and being a builder and all these sorts of things. How should one think about managing a career in the AI era? Stay at every job long enough to have impact. Over the last 18, 24 months, I've been seeing this phenomenon of job hoppers or job optimizers that call them who say they're a job for 12 to 18 months and then they move to the next job. And then they say, "12 to 18 months and move to the next job." That is one of the biggest red flags as a hiring manager that I see because I don't think you can achieve anything of value. You can't have any impact on a company in 12 to 18 months. I think it takes minimum three to four years to have impact on the company. So my top advice is stay long enough to have an impact. Build a network, have fun. From the moment you start a job, don't be thinking about what my next job is. Once in a while, maybe one job, it didn't work out amongst a series of jobs. Okay, you left it 18 months. But if I'm seeing two or three jobs back to back, immediate red flags. You do massive disservice and you wouldn't even know the problem is, you'll get rejected, you would know what happened. But people want people who stick around and build. Who's going to hire you if they see that's your behavior? So I think it's very short thinking. You've got to build something of value and that comes with time. So much of the theme here has been identifying a superpower, having one in the first place, evaluating one, matching it to a problem with the leader and so on. With your investor hat on and your new firm, Marathon, how do you assess the capacity or existence of a superpower in a person? How have you learned to do that? Well, the most important thing I look for is founder authenticity. Three of the four categories I've worked with. Google, Facebook and Dordash, all started in colleges. And they all started as a way to just a toy problem almost that the founders are curious about and they started with an authentic curiosity. Can this be built? It got built and it started and similarly, Jack and Jim, they started with solving real problems. So my first question to every founder is, tell me your founding story. Why do you decide to start this company? The founding story in my opinion expresses why they chose this problem and ideally touch on what the superpower is and what compelled them to work on this problem. I've had many people work with me for forming who have gone out to start companies with the only reason being, well, I have my buddy and we both want to start a company together. I really advise them not to do that because just going on a starting company because you want to start a company with your friend is the wrong reason. So I want to understand, is there an authentic lived experience that they've had in their life that compels them to work on this problem? Dylan from Figma, if you talk to him, he's seeped in design. He thinks about the design of things. He thinks about how to make things more compelling. It was very clear that he had a vision for what this thing would be. A good example is a company called Fair. It's a market place. Max roads a CEO work from me at Square. And Max, when he left Square, he actually tried many different ideas and turns out, and none of them were authentic to him. And Fair turns out the idea that worked was fair. When he was an undergrad student, he had an umbrella company that he created. And this umbrella company, he was trying to get distribution for it in local retail. It was extremely hard for a brand. How do you get local retail? There are so many of them. How do you go in and push to them? So he realized that that problem is the one he wanted to focus on. Other manufacturers who wanted to get access to local retail. Are there any other questions that you'd love to ask in a first meeting learning about the company other than tell me your origin story? The other one is IDMAs. Tell me about how you navigated the IDMAs. Yes, you want to tackle this problem. Because again, this is a classic product thing. You start with the problem, but then there are many different solutions, many different ways to solve it. Why is this way versus the other way? You could have chosen. I will basically try to throw them off course or off-kilter by asking them five, six other ways to solve the same problem. Understand, if they are students of either history or their industry, the same way this problem could not be better tackled in this way. So I want to understand that they have studied, or read approaches, historical approaches all this way. I think good example is the Colissons, I think, bought a book on payments and they studied exactly why all the payments companies did what they did and how they failed and how they succeeded. And I think the best founders are students of history in that industry and they understand why all the prior companies took the decision and I did this stand on the shoulders of giants and they were able to build this company. But eventually I haven't talked about is the role that, not just the role, but the perspective that being on boards offers. Here are lots of interesting boards. The big ones are Coinbase, Pinterest and TradeDesk. Maybe from those three, what lessons have you gleaned from? Being a member of those boards, watching how boards operate, the role that they play, anything else that comes to mind from that unique experience. One of the most interesting things about being on boards is that it gives you a much better perspective of what it means to an executive by being on a board. Once a company gets a certain size, I think the CEO needs to try to see if they can join a board because I think it helps them figure out how to deal with their board by being on the other side. The good board is composed of people who can help the company in the things where the company needs the most help on an ongoing basis. For example, every company needs somebody with maybe one or two people now increasing with product and engineering experience. In fact, every tech company cares 10 or 15 years ago. You would probably see zero product or tech people on boards now. Every good board has one or two product or tech people. Back in, you need a voice of the customer on the board. You need somebody who represents customers. So at Square, we got the CEO of Shake Shack Rande Guruji on the board and he was amazing because he was a voice of the customer. The other thing I always recommend to CEOs is a board role is like a marriage. Once you get into it, it's very hard to get out of. So never, ever, ever invite anyone to join your board before spending at least a year with them. Have them join an advisory board. Have them meet with everybody on the management team. And time with them, come to a few board meetings. Have them meet with the other board members. Have three or four people in your advisory board and then make one of them a board member. If you like them, if you feel they're adding value, if your team feel they're adding value, etc. The other thing I've seen with boards over the last 15 years is the management team getting involved. 15 years ago, it would just be the CEO, the co-founder, maybe, and the board. We'd meet for four or five hours, discuss topics, maybe bring in the management team person for one slice, the CFO, and then they would leave. Now, most companies, they have the management team attend the entire board meeting. I think that is awesome because I think management team and board get to meet each other as part of a board. You want to understand who's on the management team, who could be successor to the CEO, what are the capabilities of different parts of the management team, and then as the management team, you want the management team to be able to leverage the board for help. I think one of the best practices I've seen done, I've now tried to push other companies to do it, is the notion of a board buddy. So everyone on the board should become a buddy to the management team member. They would then meet with that management team member multiple times between board meetings. So once a month or even text with them, anything they're almost like a sounding board, anything the management team member has. You can see that the different board personnel have described, they map nicely. So I generally am the buddy for the head of product and the head of engineering. Somebody else is a buddy to the CFO. someone has the body to the CRO. I think the meetings in between the board meetings are actually just as important as a board meeting themselves because there's a lot of things going on. That's the other thing I realize. It's not the board meeting that truly matches all the things between the board meetings that are the real thing when things get done. I think the only thing we haven't talked about in this grand art of company building and product creation is the job of acquiring the customer positioning the product, marketing the way it presents itself to the outside world. What's the dispatch from the cutting edge that you're seeing of how people do this? One of the most interesting things now, it's different between enterprise focus and consumer focus. The consumer focus companies, the big thing is how to scale influencers. They become much more powerful and how people, especially younger people, consume products and even choose products. Somebody said the TikTok is the best local search engine. I think that's right. My kids have discovered when they go traveling, crazy restaurants and TikTok that Google Maps would not really show or yet doesn't show it. How do you reach influencers on TikTok? There's a set of companies that's coming out that's essentially making it easy. The problem is influencers on TikTok obviously there's head influencers but there's a long tail that go viral for different reasons. You want to capitalize on those viral waves if possible. There is a set of companies that is building products to see if they can help brands connect with these influencers in scalable base. On the enterprise side, the most interesting thing I'm seeing is not really a acquisition channel as much as it is an onboarding channel. It is basically presenting an outcome to a customer and saying let's collaborate on outcomes. Palentiates does that very well. Palentiates goes to customers and say, what's your most important business problem? Oh, here it is. Okay, great. Give us six months to solve it, engage with us. If we can't solve it, fire us. Don't pay us anything. If we solve it, pay us a lot of money. So it's truly taking ownership and I think this goes to outcome based pricing, how your product is priced and your confidence in your ability to deliver that outcome. So I think outcome based selling is one of the most interesting ways of changing and in fact one of the top piece of advice I have for founders reaching out to companies is you cannot lead with what your product does anymore. You've got to lead it. What is the outcome you can deliver or ideally even have delivered it? I'll never forget this example. What is crazy is that companies always look to other companies in their vertical. This never will change. So for example, if you get JP Morgan to use your product, I promise you every single bank will then evaluate your product. But if you get Proctin Gamble, JP Morgan doesn't care if Proctin Gamble use your product. Even when you go to market, you've got to target instead of trying to be too horizontal unless it bottoms up on a sales side, you've got to try to go after one or two very specific verticals because there is a very clear light. So in fact you want to go after the best one and get the best one and then you basically win all the other ones in your world in that vertical. I was a business school student on the East Coast. I was a visa, I wanted to get a job in Silicon Valley. I was somewhat unqualified. I'd never been a product manager before I'd been an engineer and never worked in photonics, optical networking before. And Bob saw a spark in me and said, you know what, I'm going to make a bet on you and I'm going to hire you and I'm going to bring you to Silicon Valley. It was a Sequoia funded company, one of the hottest companies in the valley. He could have had a pick of anyone but he bet on me. So I basically have taken this approach that I try to pay it forward and I have no expectation and I do something for someone who created this spark in you. For me it's all about just knowing how fortunate I am to be healthy, to have a family that loves me and to know that in almost every run of the simulation I could be in a million different worst circumstances. That I am today. And so just gratefulness and gratitude about where I'm sitting. I mean we are sitting in literally the top 1% of the 1% of the 1% situations right now. So literally I think I feel pain when I see somebody suffering. As I say, therefore the grace of God, go I in some ways and but for the grace of God. And you basically realize that you're very lucky to be given this one life and you have a responsibility to the world and yourself to be grateful and to need the best life you can. Go go this was incredibly fun. Thank you so much for your time. Patrick, thank you my friend. If you enjoyed this episode, visit Colossus.com. You'll find every episode of this podcast complete with hand out of the transcripts. You can also subscribe to Colossus or quarterly print digital and private audio publication featuring in-depth profiles of the founders, investors and companies that we admire most. Learn more at Colossus.com/subscribe. You know how small advantages compound over time that's true and investing and just as true and how you run your company. Your spending system is your capital allocation strategy. Ramp makes it smarter by default, better data, better decisions, better economics over time. See how at ramp.com/invest. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. The best AI and software companies from open AI to cursor to perplexity use work OS to become enterprise ready overnight, not in months. Rigline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5X and scale enabling faster growth, smarter operations and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. Rogo does. It's an AI platform built specifically for Wall Street connected to your data, understanding your process and producing real outputs. Check them out at rogo.ai/invest.