Gokul Rajaram - Lessons from Investing in 700 Companies

Here's an interesting question to think about, if your finance team suddenly had an extra week every month, what would you have them work on? Most CFOs don't know because their finance teams are grinding it out on lost expense reports, invoice coding, and tracking down receipts until the last possible minute. That's exactly the problem that Bramps had out to solve. Looking at the parts of finance, everyone quietly hates and asking why are humans doing any of this? Turns out they don't need to. Bramps AI handles 85% of expense reviews automatically with 99% accuracy, which means your finance team stops being the department that processes stuff and starts being the team that thinks about stuff. Here's the real shift. Companies using ramp aren't just saving time, they're reallocating it. While competitors spend two weeks closing their books, you're already planning next quarter. While they're cleaning up spreadsheets, you're thinking about new pricing strategy, new markets, and where the next dollar of ROI comes from. That difference compounds. Go to ramp.com/invest to try ramp and see how much leverage your team gains when the work you have to do stops getting in the way of the work that you want to do. Investing is hard. It's an apprenticeship industry with messy data, complicated workflows, and decisions that demand judgment. Investing needs specialized AI, and that's why I'm so excited about Rogo. Rogo is an AI platform purpose-filled for Wall Street, not a generic chatbot, but a suite of agents designed around how bankers and investors actually work, from sourcing, diligence, and modeling to turning analysis into deliverables. Finance requires deep domain expertise far beyond your average chatbot. As listeners of this podcast know, every investment firm is unique, with its own thesis, internal notes, templates, and ways of investing. Generic AI can be impressive, but it doesn't actually understand your process, and that's where the advantage lives. For me, three things set Rogo apart. One, it connects directly to your system, so it can work with your actual data, internal, and external. Two, it understands your workflows. How work really happens across a deal or an investment? And three, it runs end-to-end and produces real outputs in the way that your best people do. A lot of the bull spreadsheets, investment memos, diligence materials, and slide decks that match your standards. Rogo is built by a deeply technical AI team with real finance DNA, large language models for finance professionals by finance professionals, and it's already being adopted by some of the most demanding institutions in the world. The teams that get this right early won't just move faster, they'll compound better decisions, train their own AI analyst, and the gap will widen. The Rogo team's vision is distinct. Make the most ambitious investors even better, and make finance an AI native industry. I'm fully bought into that vision and I think their work will fundamentally reshape investing. Learn more at rogo.ai/invest. If you're a long-time listener of this show, you've heard the same pattern play out across so many great companies. The moment a product finds early traction, the constraints shift from engineering curiosity to enterprise execution. And one of the biggest hurdles, whether you're open AI, cursor, perplexity, or sell, or a brand new startup is identity and access. SSO, SKIM, RBAC, audit logs, these are the capabilities that give enterprises the confidence to adopt your product at scale. That's where WorkOS comes in. It's become the default way fast growing software companies get enterprise ready. Instead of spending months building SSO or provisioning or permissions in house, WorkOS gives you all the core features enterprises require through clean, modern APIs. And in the era of AI, this matters more than ever. AI native companies scale faster than anything we saw in classic tasks. They can't afford to wait on an enterprise compliance. They need it on day zero. That's why so many of the top AI teams you hear about already run on WorkOS. If you're building software and want to unlock larger customers or just avoid reinventing a very unglamorous wheel, head to WorkOS.com. It's the fastest way to become enterprise ready and stay focused on what actually moves the needle your product. Visit WorkOS.com to get started. Hello and welcome everyone. I'm Patrick O'Shanasi 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 O'Shanasi 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.vc. 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 Shoe. 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 in 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 technologies building products and how fast that's changing. What is interesting about product development is that 10 years ago or even five 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 one hour I was able to basically prop 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, hopefully 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 are emerge. First, product development as we know it is changing because the models and the capabilities are growing so fast that if you try to be very strict and stringent about describing exactly what you're going to build or 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 at the highest level and then 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 fallen 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 an extra engineer they're saying you know what the design systems are already laid out. Now that we have the design systems are laid out we can use AI to do work around these design systems. So we may be 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 little number of engineers, when I was growing up in product it used to be one to three or one to ten. It's going to one 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 etc. But who owns the e-walls? It's the PMs. It's the PMs and the researchers. So the PM's 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 very 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 time. If you think about my friend Zach has this great way of thinking about AI which is we had 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? And 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? And I think balancing those two is a very delicate act. You can build something amazing that as a tremendous amount of value to the customer, but doesn't build any value to the business. And 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 that is what I think of the product. And what it comes down to, in my opinion, over 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, 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 to becoming a loyal customer, and then maybe to become a loyal customer to become a paying customer. Or if you do a good job, you become a becoming a loyal customer to become the 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 their first PM or doing their first product review. You need to ask why? The only question you need to ask 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 future to reason about given the pace of change. So how do you reason about it? Is there anything that can be truly future proof? Yes, the one thing I think that's going to be truly future 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 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 on 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 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? Customer trust can make or break your business and the more your business grows, the more complex your security and compliance tools get. It can turn into chaos and chaos isn't a security strategy. That's where Vanta comes in. Think of Vanta as you're always on AI-powered security expert who scales with you. Vanta automates compliance, continuously monitors your controls and gives you a single source of truth for compliance and risk. So whether you're a fast growing startup like cursor or an enterprise like snowflake, Vanta fits easily into your existing workflows. So you can keep growing a company your customers can trust. Get started at Vanta.com/invest. To me, Ridgeline isn't just a software provider. It's a true partner in innovation. They're redefining what's possible in asset management technology, helping firms scale faster, operates smarter and stay ahead of the curve. I want to share a real world example of how they're making a difference. Let me introduce you to Brian. Brian, please introduce yourself and tell us a bit about your role. My name is Brian Strang. I'm the technical operations lead. I work at Congress asset management. How would you describe your experience working with Ridgeline? Ridgeline is a technology partner, not a software vendor, and the people really care. I get sales, calls all the time and ignore them. Ridgeline sold me very quickly. We went from 7 billion to 23 billion and the goal is 50 billion. Ridgeline was the clear frontrunner to help us scale. In your view, what most distinguishes Ridgeline? They reimagined how this industry should work. It was obviously they were operating on another level. It's worth reaching out to Ridgeline to see what the unlock can be for your firm. Visit Ridgelineapps.com to schedule a demo. 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 today at every vertical and every industry. Why? Because till today, till recently, software was used more as a tool by 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 couldn't 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, increasing 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-findered 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 any startups? 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 once they're prepared of what can be built a multiple subs ahead, and you've got to extrapolate to where can the capabilities of these agent building products go, and you've got to do something very, very different. So what that means is you've got to have durability because ultimately 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 start. But 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 need to, 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, and healthcare its epic. Now, for many years, these companies all had APIs that if you enter the 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 have been 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. Or, they're charging these AI agent companies to access the data. Let's just to access the API as 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, where 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 an offering a system of record. So, every 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, when I was like, oh, we can do workflows. We can build what is called a 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 investor 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 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's 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. The software company 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 acts 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 more time. 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 world to be based on outcome, and you need to actually build the product to be based on outcome. It's easy said that done, because literally you're going from a 20 or $30 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 one transformation in private. I think it's going to be hard for them to say public, and the companies that are less exposed are 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 said, because the data in Slack is not timeless. Half-life is very short, but if you have ERP is a great example. Somebody uses net suite as a ERP. Now, I don't know how net suite 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 net suite. I know over the last year there's been a lot of AI enabled ERP businesses, but there is no compelling reason to take net suite and say I'm going to rip it out because it is career limiting to suddenly take net suite out when you're a company running on net suite. So I think those companies are much more insulated. And I think obviously, and you could argue that net suite has more time to build AI agents on top of it, because they have the data. They can train the agents on top of it and bundle it. So essentially, I think the software, public markets are not distinguishing these two types of companies. Companies with a 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 sales force for sales data and records. Those are real customer records. It's going to be hard. So what an ANA 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 force instance to your own company's platform. One of my companies is an ANA company. They literally hired engineers in a European country for two years to build this migration then transition tool. So you have to build the migration tool because who's going to migrate it? You can just present your spanking 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 that it was 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 that took us months or years to build it for a simple POS. For something like sales force, 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 0 or at least contains what your product development team is building. Now all of these 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 sales force data and move it to your instance. The data from Gira and move to your instance is Zendesk and move to your instance. So literally, it's 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 whatever you want really fast. How is it 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 do dash is sticky, not just because it has this beautiful app, but it's because it's a network of restaurants and dashers and consumers. So you're going to attack one, you've got to go. You can't vibe your way to those two 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 sale. 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, other stuff embedded. So I like things that are a 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 give 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 OpenAI. He can make a call to any company, any country, and they'll take a call. You can't really outsell Brett. There's alpha in that. You need one of these four of 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, how does the hardware 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 Sergei, what did you learn from watching them operate and lead? One of the most interesting things about all the leaders that have worked with the type of generational 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. I didn't believe this was 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 a hundred extra storage. And this really epitomizes Larry and Sergei's philosophy, which was basically built the best technology on the planet. And 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 that Google is involved in serving every single ad on the planet versus making a business of whatever billion or two billion or ten 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? You have to use words. No, 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'll use what I want you to come with the most compelling image that exists for what they describe. And so it was a crazy thing because I never thought of doing a presentation that way. So I went to each of the businesses, AdWords, Search, YouTube, AdSense, and then had to come up with a compelling image that was easily accessible to the whole company. He had 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 couldn't 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 companies of the planet. We showed the logo a very large fortune hundred or fortune fifty company that they're acquired. What did you learn from Zach? Zach was and is actually, I think the greatest mind on growing, building growth and engagement in 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 he's 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 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 my 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 Sheryl quite closely. Sheryl 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 you 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 Zingha. Zingha was the largest advertiser on Facebook. So Zingha basically wanted to, like most gaming companies, they were very focused on acquiring Wales. Because Wales, for any gaming company, Casino, etc., 80% of all revenue for any gaming company comes from Wales. So he was very frustrated at us. We would do these quarterly reviews with Zingha on the ad side because there were a lot of spenders and ads, and they would constantly be yelling at us saying, "We want to get more Wales." We were like, "Yeah, you're getting users. You need to figure out how to get Wales from your games. What do you want us to do? We can help your users." So he once, I think, talked to Zuck and Zuck came to us and said, "Why can't they just upload their Wales into our system? We know who the Wales are. Why can we just find them people similar to those Wales?" We were like, "That's interesting." But we actually didn't know who the Wales were. So they needed to tag it for us who the Wales were. And basically we started doing it similarly. We started finding users similar to the Wales 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 it was all Zuck's idea. He just has something about making connections between disparate domains. We're just pretty amazing and unique. What did you learn from Jack and Tony? Jack is, I think, on par with Johnny Ivan Steve Jobs in terms of his thinking about 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 instead of using it as a point of sale to run your business. A category where you have to train somebody for weeks. That's the example of a good design. He brought that to every part of the company and removing fiction from waters traditionally. I mean, squares, whole premise was removing fiction from small businesses applying for financial services and that extended to the product. They're 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 to a bank for payment processing, in fact, the company was founded because Jack's go for the gym 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 $2,000,000 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. He had 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 checklist." So he lost the sale. So he went to his friend Jack Dorsey. They had never built hardware. They've 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 leaps 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 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 malls and every transaction, this transaction risky. This is not. The shifts at the level. Shifted the level. And so that kind of lazy but brilliant onboarding is something that characterizes a lot of good things. The Sergei, very similar. We're going to launch AdSense in 2003. I'll never forget this. We're doing our final launch things. Sergei 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 a product. We 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?" We're like, "What do you mean? Our ads are going to be running ads on these things Google ads or ads part by Google." You don't want to be on a porn site or something else. It's like, "Why not?" We didn't have good ads. Why not? It was like, "Well, you know, standards or policies, okay, 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 asses turns out. He said, "Do I kill all this?" We had literally spent half of an engineering team building this complex approval system with ops and so on. Ops are super excited. They hired a lot of people and I was telling us not to do. Instead, do it in real time. For every page that loads because we have the JavaScript on it, we know what you are. Look at the content at that point. We won't be able to look at the content because there's billions of pages. That's fine. Let it load 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 with where 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, not 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 role product editor. Why? Because he believed rightly so that 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. Producer. 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. 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. The best AI and software companies from open AI to cursor to perplexity use work OS to become enterprise ready overnight, not in months. Visit work OS.com to skip the unglamorous infrastructure work and focus on your product. I wonder how that applies also to communication. Maybe this is a fun opportunity to ask you about the format that you've highlighted 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 a company goes into, I think 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 clichéd 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 into 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 asserting a customer's better? What's happening on the business side? How are we doing better as a business? And then what's happening on the team front? Who have 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 seeps into their bones. 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. It 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, it's 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 courts from customers. It's maybe an off-site announcement. But the most important section where you should spend 60 or 70 percent of your 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? I personally, 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 the company is small. We want people more important. There's a one-way road 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 built the two most important ads systems. I always say as a company, who you either die or you live long enough to become an ads company. We are seeing now with open AI, it's happening. How do you build an ads business? There are three fundamental ways to succeed in the ads business. 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 search is a great 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. We knew these users were and we 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 our identity, Facebook identity, but our intent, these things been both together. It's the dream of any advertising person. And these are complex multi-phase searches. That's the other beautiful thing. You search when 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. That'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 for advertisers. The best example of this is a company called Apploving. Apploving is a 100 plus billion dollar 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 one mobile app installs. So Apploving has built a massive infrastructure. Now they control the buy side. They control the sell side. They even control the middle. 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 Apploving has built an amazing engine to deliver you mobile app installs at a certain cost. So that's the other way. Second, 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 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 doesn't work on Google or Facebook at all, doesn't work with Google or Facebook as a first party. But Apploving, 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 your 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 cable in top of Google, it turns out Google learns what you're building. And Google has the best engineers on 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 sending 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 within good 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 get their Uber and 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 interfaces, 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 and 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 their Uber account with the chat GPT account. I'm going to look to see these people who 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, or how do I incentivize them here to 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, 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 network? What advice would you give these various parties? 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 iterations and mistakes as the first one makes. Your inventory is not going anywhere. Now some might have more urgency to monetize than others, but Gemini doesn't need to monetize anytime soon. So they can just sit back, they have a lot of ad 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 ad platform. Google can claim that Gemini has no ads in it and there is a certain set of customers or consumers who care about that. The biggest thing is and OpenAI has done a good job of articulating this ad should not influence a 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 an improvement 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 have 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 will 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 with customer value. So for example, if customers are doing well, the North Star metric should go up and to the right but it should also lead the business doing well. For example, for Square, the North Star metric was GPV which is volume of payments processed. It was not correlated to revenue, it was 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 users 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 is going to go up 100 percent but then many things that you don't want to go down could go down. So for example, in the door dash case, because I want to grow GMV which is a 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 an 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 problems to 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 at four qualities which is I think was gross margins low cost to acquire the customer high retention and at tight sales cycle which maybe maxed back onto the self-serve thing. Talk about the relationship between those two things. The sales of notion actually came from Google was the first company I worked at which achieved massive scale and what happened in Google was within the ads team we basically had a wide number of customers using us, millions of customers using us. There were a lot of small businesses but there were 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 our 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 we somehow got into it. It was like what is that? Well, it's a system used by our internal teams. It's like why did 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 would use. 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 creativity and ability. 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 self-serve, you learn so much more about the capabilities of your product than if you basically it's your sales team doing it on their behalf. In fact, I never forget in that sense, I think we had some of the largest publishers in the world sign up and start using us on a self-serve basis and then we engage with them after that and I think companies like ATLEC and Square, I think we had Nike signed up for a Square device and self-serve on board it and started using 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 self-serve? The definition of self-serve is the customer can on board 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 self-serve product, you don't even think about. In a self-serve product, you think about it every day. It's like a consumer product or a self-serve business product and then second, what it does for you is it opens up the aperture to your customers because with say 100 salespeople, yeah, you can reach maybe 10,000 customers but with a self-serve 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 person companies, some engineer got it. Great example is a company that's 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 and designing design. I said, "You got to use Figma." Designers, if you used to use it, they're using a tool called Sketch and they said, "You're not going to use it. Sketch is 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-serve, 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. 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. Richline is redefining asset management technology as a true partner, not just to software vendor. They've helped firms 5x in scale, enabling faster growth, smarter operations and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. 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 sealer 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 ICs. 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 that even his 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 not enough. You either need to be managing 50 humans or 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're managing even 15 people, maybe you meet with them once a week, that's 15 hours. What are you doing for the other 25, 30, 40 hours? You should be working. So I think you've 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 and stuff. They do stuff. Everywhere else, you can just BS you away without doing stuff. So it's square. We established work projects where even for core dev, our work project was give me one company that square should buy and analyze the company and tell us why we should buy it and tell us what the city should be. So the best candidates had 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, there's 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 product. So we don't build it, we have to 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, a question the premise in the first place. Squares should not buy a company. That would be great. Why? Tell me why and so that's the kind of thinking you're looking for. What was the earliest thing? Rodash 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 for Rodash 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, if they are 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 I call them who say the job for 12 to 18 months and then they move to the next job. And then they start 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 this service and you wouldn't even know the problem is you'll get rejected, you won't know what happened. It's that 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 term 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 a leader and so on. With your investor hat on, and you're new for 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 carries are worked with Google, Facebook and DoorDash, 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 with Jack and Jim, they started solving real problems. So my first question to every founder is, tell me your founding story. Why did you decide to start this company? The founding story in my opinion, it 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 or for me 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 out and starting a 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 we 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 could be. A good example is a company called Fair. It's a money to be marketplace. Max goes to see you work from me at square. When 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 a 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 by this problem could not be better tackled in this way. So I want to understand that they have studied, alternate approaches, historical approaches to solve this one. I think a good example is the Coliseons, I think what the book on payments and they studied exactly why all the payments companies did what they did and how they failed and how they succeeded. 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. You're on 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. Second, 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 of the 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. Spend time with them. Have 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 managing attendee 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 not tried to push other companies to do it, is a notion of a board buddy. So everyone on the board should become a buddy to a management team member and they would then meet with that management team member multiple times between board meetings. So once a month or even text with them and anything, they're almost like a sounding board, anything the management team member has. You can see that the different board personers 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 a buddy to the CRO. I think the meetings in between the board meetings are actually just as important as the 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 matters 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 that TikTok is the best local search engine and 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. So how do you reach influencers on TikTok and 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 and you want to capitalize on those viral waves if possible. So 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, it's not really a acquisition channel as much as it is a onboarding channel. It is basically presenting an outcome to a customer and saying let's collaborate on outcomes. Palantir does that very well. Palantir 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 you can't solve it, fire us. Don't pay us anything. If you 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 leave it. What your product does anymore? You've got to leave it. What is the outcome you can deliver? I really 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 hose effect. You want to go after the best one and get the best one and then you basically win all the other ones in that vertical. I think you might know my traditional closing question that I ask everybody. What is the kindest thing that anyone's ever done for you? There are so many. A guy called Bob McDonald. I was a business school student on the East Coast. I was in 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. What created the 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 they 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. "Koko, this was incredibly fun. Thank you so much for your time. Patrick, thank you my friend." 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