Gokul Rajaram - Lessons from Investing in 700 Companies

00:00:00Most software companies try to maximize your time on their app to juice engagement. Ramp does the exact opposite. Ramp understands that no one wants to spend hours chasing receipts, reviewing expense reports, and checking for policy violations. So they built their tools to give that time back, using AI to automate 85% of expense reviews with 99% accuracy. And since Ramp saves companies 5%, it's no wonder that Shopify runs on Ramp, Stripe runs on Ramp, and my business does too.

00:00:26To see what happens when you eliminate the busy work, check out Ramp.com slash Invercors. invest. Open AI, cursor, anthropic, perplexity, and Versel all have something in common. They all use WorkOS. And here's why. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, Skim, Rback, and Audit logs. That's where WorkOS comes in. Instead of spending months building these mission-critical capabilities yourself, you can just use WorkOS APIs to gain all of them on Day Zero. That's why so many of the top AI teams you hear about already run on WorkOS. WorkOS is the fastest way to become Enterprise-ready. and stay focused on what matters most, your product.

00:01:02Visit WorkOS.com to get started. Felix by Rogo 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,

00:01:21and Felix sends back finished PowerPoint decks, Excel models, and sourced research. Felix works the way your team already does, delivering work quickly and accurately around the clock. Learn more at rogo.a.ai slash Felix. Hello and welcome, everyone. I'm Patrick O'Shaughnessy 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

00:01:52the people shaping business and investing. You can find Colossus along with all of our podcasts at Colossus.com. Patrick O'Shaughnessy 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 Some may maintain positions in the securities discussed in this podcast. To learn more, visit PSUM.v. My guest today is Gokul Rajaram.

00:02:29Gokl 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, Gokul 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 discussed the one thing Gokul believes is truly futureproof in AI,

00:02:59why 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. Goko shares lessons from working closely with Larry and Sergey, Mark Zuckerberg, Jack Dorsey, and Tony Shue, and what he learned from watching each of them build generational companies. Please enjoy my great conversation. with Gokal Rajaram.

00:03:30I thought of 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 Claude Code or Claude 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.

00:03:58You'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 technologists 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 roles. 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 in 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, long-running agent. I've

00:04:39experienced it myself. About six months ago, I tried to use Claude 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, 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.

00:05:10After I did that, I started talking to three kinds of companies. One, portfolio CEOs of companies I've 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 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 bottom-s-up approach where it's not doing by product management anymore.

00:05:48Product managers, the only thing they do now is they articulate what the customer needs are at the highest level and then they are 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

00:06:35with either codex or clot code into the actual production repository. Right now, engineers have to review the code, but you're going to soon see the clot code, 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 a prototyping interview. Now, the explicit interview in the interview loop called prototyping. It literally forces

00:06:59product 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

00:07:15between an extra designer and extra engineer, they're saying, you know what, the design systems are already laid out. Now, Now that we have the design system 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 little 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.

00:07:45And 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 a 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 Eval's in AI. And someone has to evaluate whether or not what the software is. producing is reasonable or not across various use cases. Obviously, there can be human evals, AI evils, et cetera. But who owns the e-vals? It's the PMs. It's the PMs and the researchers.

00:08:26So the PM's job is to be very clear at a high level of 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. Many 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 the 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 to have a product as well. 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

00:09:05services. This is an 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.

00:09:37Why are we building it? What customer need are we solving? Why is this a pain point? How intense it and how deep it is. And second, how does it add value to the company? If you build this thing, solving this customer rate, how does the value add to the company? And 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,

00:09:57but 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 value detracting for the customer. So balancing customer needs and businesses 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 defined the best product people,

00:10:20and 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. customer. Or if you do a poor job, they can go for becoming a loyal customer, becoming a churned customer. So these are all behaviors. Everything you do or build should be attuned to the

00:10:54goal 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

00:11:36customer, 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 thousand 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 ramp, they're just going to produce lots of code. Which of this code is even valuable?

00:12:14In an era when you can do everything, the question is which of these things matter and you should truly do. On the product side, it's judgment around what needs to be built and evaluating the output. On the engineer side, it's evaluating the code. Because if you don't understand what the code says, I think you can have AI engineers writing beautiful code

00:12:31that 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, to have human review at some point, especially a critical code that is in the core of your system. And similarly in design, you have to have judgment around, does it make sense in the broader design system? So I think this judgment is the number one thing that humans are going to bring. And of infinite productivity, the question is, what are the things we productive on and are we building the right things?

00:12:59As your business scales up, everything gets more complex, especially your compliance and security needs. With so many tools offering band-aids and patches, it's unfortunately far too easy for something to slip through the cracks. Fortunately, Vanta is a powerful tool designed to simplify and automate your security work and deliver a single source of truth for compliance and risk. There's a reason that Ramp, Cursor, and Snowflake all use Vanta. It frees them to focus on building amazing, differentiated products. Knowing that compliance and security are under control. Learn more at Vanta.com slash invest. I know firsthand how complex the tech stack is for asset management firms. And seemingly every new tool and data source makes the problem even worse, adding more

00:13:37complexity, more head count, and more risk. Ridgeline offers a better way forward, one unified platform that automates away that complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Ridgeline is revolutionizing investment management, helping ambitious firms scale faster, operate smarter, and stay ahead of the curve. See what Ridgeline can unlock for your firm. Schedule a demo at ridgeline.a.i. 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 slash invest. As your business grows, Vanta scales

00:14:20with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com slash 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 slash invest. The best AI and software companies from open AI to cursor to perplexity, use WorkOS to become enterprise ready overnight, not in months. Visit WorkOS.com to skip the unglamorous infrastructure work and focus on your product. Ridgeline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5X in scale, enabling faster growth,

00:15:04smarter operations, and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. 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.

00:15:34How should people think about building an application using a new? AI starting today. First and foremost, you've got to start with a deep and compelling problem. The good news is there's a tremendous number 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.

00:15:59The 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.

00:16:22A 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

00:16:49that 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. I 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 ChadGPD Enterprise, and they also have an agent builder product. And I have a thousand IT engineers who work for me.

00:17:15They 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 CEO 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

00:17:36of what can be built, multiple steps 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 as venture capitalists

00:17:49or even as an entrepreneur, your time or as in can't be building something that lasts for one year. And that's the biggest challenge. It's not building an application, is building an application that's durable, that basically will last a test startup. I think there are a few things around durability.

00:18:03One, 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,

00:18:28which 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,

00:18:57which 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 Clio, in sales at Salesforce, in healthcare, it's Epic. Now, for many years, these companies all had APIs. That if you enter that industry, you could build an agent company on top these APIs. In 2025, things changed. These companies started seeing that these agent companies, AI companies that are being built, they are starting to take on the functionality out of these companies

00:19:28and 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 Salesforce. They cut off access to Glean, where Glean can no longer access Slack data. And the reason is they don't want Glean to build on top of them

00:19:48and 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. Just to access data, the API was free.

00:20:09They're saying now it's $2 an API call. They're trying to make the model of these agent companies unviable. I think it's going to be very hard for an 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 but to also start building and 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, 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

00:20:45of record. I don't think that's an option anymore. The Slack example is a good one of a 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 Slack's in a lot of trouble. How do you think about that question? Obviously, public markets seem to think software's a lot of trouble. The multiples are really,

00:21:25really 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 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 tax a certain number of customer tickets. So that company should be worried because I can have an AI agent

00:21:57sit right next to Zendesk, and you can slowly siphon off. Instead of paying for 50 Zendesk, you can pay for 20, and I can have 30 AI agents sitting next to Zendesk, and that siphoning can happen over time. You don't have to have an 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 model to be based on outcome,

00:22:19and you need to actually build the product to be based on outcome. It's easy to set that done because literally you're going from a $20 or $30 per seat to maybe charging a buck or $0.50 or $0.20 per ticket resolved, 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-form transformation in private. I think it's going to be hard for them to say public.

00:22:44The companies that are less exposed the 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 state

00:23:00because 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.

00:23:20I know over the last year there's been a lot of AI-enabled ERP businesses, but there is no compelling reason to take NECSuite and say, I'm going to rip it out because it is career limiting to suddenly take NETSuite when you're a company running on NetSuite. So 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 agent top of it and bundle it.

00:23:44So essentially, I think the software public markets are not distinguished during these two types of companies. Companies with a half-level 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. Well, something like an ERP system or even Salesforce for sales, data, and records, those are real customer records. It's going to be hard.

00:24:06So what are AI-native companies 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 native company. They literally hired engineers in an Eastern European country for two years to build this migration transition tool. So you have to build a migration tool because who's going to migrate it?

00:24:34You 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 though it was cheaper because they had gift cards, customer data, loyalty data, payments 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 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.

00:25:08And GDR atlasian contains what your product development. 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 customer, you should know where they came from, who bought them, who sold them. So all these three systems should be linked together, but they're all three different companies. So their companies, they're trying to unify 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.

00:25:41The data from G-Ran move to your instance, the data 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 just as a general concept when the friction for creators to build something

00:25:58that new is so low. You can do whatever you want 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 DoDash is sticky, not just because it has this beautiful app,

00:26:13but 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. You can't vibe code 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.

00:26:31Many 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. You also have to have money flowing to 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 a combination of financial services and software because of that. The third stickiness is from hardware.

00:27:00You 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 drip out the toast hardware.

00:27:15The fourth one is access to a unique asset. I was thinking of what 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,

00:27:33and they'll take his call. You can't really outsell bread. There's alpha in 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 underst 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

00:28:01well-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 with have built 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

00:28:40about, was a product called Caribou. Caribu was an internal code name for a product that was launched in April 1st, 2003. Publicly, it was called Gmail. I didn't believe that this 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 100x more storage. And this really epitomizes Larry and Segge'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

00:29:24ads 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, a billion or $2 billion or $10 billion. So the focus on scale and the focus on technological superiority and that investment, Google Street View, TPUs, way more. 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 happened, but it took a decade, and that's investing in technology capabilities. Before we leave Google,

00:30:02you 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 seconded to Eric for the weekly strategy or the annual strategy planning session. So I did it, 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

00:30:40words. 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'll use, but I want you to come up 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, AdWords, search, YouTube, AdSense, and then had to come up with a compelling image that was easily accessible to the whole company, yet represented what they did it. 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.

00:31:25For YouTube, it was a graph. It showed that the number of videos being uploaded every second, how it had changed from the time Google brought them to them. So it was 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. It's the line.

00:31:43The line would have to be like a you or something like that, but it went like that. Because we 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

00:31:56to being used by the largest companies of the planet. We showed the logo a very large Fortune 100 or Fortune 50 company that they're acquired. What did you earn from Zuck? Zuck was and is actually, I think the greatest mind on growing,

00:32:11building growth and engagement in 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 you would look at the flows and it'd say that is not going to be compelling to users. That is not something that the user is going to engage to.

00:32:31Change 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 by following. When I joined my task was to lead the ads product team. And Zach at that point knew a little bit. bit about ads because he had worked with Cheryl quite closely. Sherrill had worked on ads before.

00:32:59But then within, I think, about a year, he shadowed us. He came to the ads team. He basically sat with us. He came to many of our 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. is 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

00:33:37and say, look, instead of describing these customers, what did ads this do before? They would describe their customers. I think they are 25 to 35-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.

00:33:54So uploading that data into our system securely and doing it in a way that doesn't compromise an EPA, it was the key thing. And it all came from Zuck. How? Because Mark Pinker was the CEO of Zinga. Zinga was the largest aditorized on Facebook. So Zinga basically wanted to, like most gaming companies,

00:34:12they were very focused on acquiring whales. Because Wales, for any gaming company, casino, et cetera, 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 Zingo on the ad side because there were large spenders and ads. And they were constantly being yelling at us,

00:34:30saying we want to get more whales. We were like, yeah, you are getting users. 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, talk 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.

00:34:48Why 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 it was all Zuck's idea.

00:35:15He 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 Ive and 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.

00:35:42Every point of sale except square and things that have copied square. You have to train a barista still for several days after. join on 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 what does, traditionally, I mean, Square's 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

00:36:20that square at its code is a risk company. When you apply it to a bank for payment processing, in fact, the company was founded because Jack's co-founder, Jim was rejected many, many times to accept Amex by banks. He was a fairly successful glass blower in St. Louis, and he basically was selling $2,000, $3,000 glass cultures to people who would send him checks. So a woman called from Panama one day and said,

00:36:44I 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 your traveler's check. So he lost the sale.

00:36:55And 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 leaps you have to make to get there. But the number one thing that they realize is most small business are denied by banks. when they apply. Square instead said, we are going to accept 90 plus percent of people.

00:37:25What 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. Every transaction, this transaction is risky. This is not. It's shifted the level. Shisted the level. And so that kind of lazy but brilliant onboarding is something that characterizes a lot of good thinkers. Sergey, very similar. When we're going to launch AdSense, in 2003. I'll never forget this. We were doing our final launch things. Sergei was a sponsor. He came and sat in the meetings.

00:37:56He said, what are you guys building here? We're like, website publishers are going to apply from 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 were like, what do you mean? Our ads are going to be running ads on these things,

00:38:12Google ads or ads powered by Google. You don't want to be on a porn side or something else. He's like, why not? We don't have a good answer to why. not. I 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, you know, get accepted. He was right. In some ways, we were just doing it to cover our asses, turns out. And so he said,

00:38:40kill all this. So 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 now you're telling us not to do. And instead, do it in real time. For every page that loads, because we had 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.

00:39:04We 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 intentional would wear and why most things don't even get to the level

00:39:22where 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?

00:39:36What 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,

00:39:59here's 10 things you should build. The best designers, the best product people, edit down things. Similarly, we have 100 features. What are the two things that really matter that will drive the customer outcome. So the best designers really is to 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 AI age, humans with amazing judgment, which is really editorial capabilities are the ones that are going to do well in thrive, I think. Apparently, 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.

00:40:40Ramp puts guardrails on spending before it happens. Real-time limits, automatic rules, zero firefighting. Try it at ramp.com slash 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 slash invest. Every investment firm is unique and generic AI doesn't understand your process. Rogo does.

00:41:02It'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.a.i slash invest. I wonder how that applies also to communication. Maybe this is a fun opportunity to ask you about the format that you've alighted 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.

00:41:28Talk 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 a 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 companies need to start putting into place. One is a notion of an all-hands. It seems cliched and unnecessary, but even with the 15-20 percent company, just getting together once a week and basically just shure.

00:42:06sharing what people have built and been working on in a way and then having the leader address everyone or one of the leaders address everyone. It's 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

00:42:28is during the course of the week, you start jotting down things that you think you want to communicate. And then you'd spend Sunday taking all of those things and adding it to 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 or serving your customers 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 have we added, subtracted, what changes have we made? And most importantly,

00:42:59don't be afraid of repetition. Because repeating it once, twice, thrice, 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 I've seen now, I've seen at least 15 CEOs adopted and to good effect is three sections. One is called top of mind. So this is product, business, and team.

00:43:23Doesn'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.

00:43:40I 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 a way.

00:43:53And 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 or 70% of your time on is top of mind. How transparent should one be in that as a leader of a business? I can tell you what'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.

00:44:23Where should one draw the line in terms of how candid they are? I personally think 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?

00:44:37What do you think we should do in this situation? I think people will rise up to the occasion. Especially when the company is small, we want people more input and there's a one way or decision that we're going to make where making it takes us one way or the other, I think it would be great to get feedback for more people. I want to talk about ads and everything you've learned

00:44:55about building an incredible ads product. You've built the two most important. or ad systems in the world. I always say as a company, 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.

00:45:13Three. 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, they expressed high intent, so Google is one of the most profitable ad businesses. Facebook, very similar.

00:45:34It took us a while to figure out what was coveted of both these users. Turns out what was coveted was the identity. We knew who 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 them. Chat GPT, the combination of intent and identity data is unparalleled. I mean, Google had intent data but not identity, Facebook identity, but not intent. These things have been both together.

00:45:58It's the dream of any advertising person. And these are complex, multi-phase searches. That's the other beautiful thing. You search, and each of the queries is kind of like a search. And then you search again, and you're just building up searches. At 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.

00:46:21So 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 App Lovin.

00:46:37App Loving is a hundred 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. Everyone wants to get mobile app installs. It was initially only restricted to gaming, but now every mobile app where they sought want mobile app install. So App Loving has built a massive information.

00:46:57structure. Now they control the buy side, they control the sell side, they even control the middleware. 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 mobile app installs at a certain cost. So that's the other way, second way to 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 & 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.

00:47:40You 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. It doesn't work with Google or Facebook as a first party. But App Lovin, I think only a little bit works on Google and Facebook.

00:48:08Mostly 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 capability on top of Google, tons of Google learns what you're building. And Google has the best engineers on the planet.

00:48:30So do Facebook, they will take your capabilities and incorporate into their platform. Let's see if I'm proven right on top. My take is that there's going to be almost a cottage industry of companies that are going to come and say, I'm going to help you optimize ads in chat, GPT. And there's already companies that help you optimize placement in what is called these answer engines,

00:48:47called AEO instead of SEO. All of those are not going to create durable and 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 could go through Uber and Amazon in the mix, Stor Dash, 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,

00:49:23then could you put those repeat things on autopilot through an agent and you never open the app? And so you lose opportunities than advertise. And you lose the relation with a 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 Chad GPD opened up their apps platform,

00:49:43all 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 Chad GPD account. I'm going to look to see these people who have connected, how's their behavior on my app? Are they going to my app or not? Are they opening up much less frequently?

00:50:01Because 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 we 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 ChatGBTGBT. 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

00:50:30using 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.

00:50:54Now, some might have more urgency to monetize than others, but Gemini doesn't need to monitor us anytime 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 strategic move for them might be to say, I'm 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 Open AI has done a good job of articulating this,

00:51:20ad should not influence the content that is served to me or the recommendations 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 improved, is that once you start showing ads in an previously unmonetized zero ads surface,

00:51:45engagement of 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 there's many holdout 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?

00:52:02First, you need to have a holdout 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 is from each quantum of ads,

00:52:19and 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 News Feed 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

00:52:34was we can't take more than X percent dip in engagement overall for News Feed. picking 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 to customer value. So for example, if customers are doing well, the North Star metric

00:53:08should 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 not star metric was DA use. It was actually monthly active users, then it over time went 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 its Nostra

00:53:47metric, it is 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 DoDash case, you could say, I want to grow GMV, which is the gross merchandising value, which is the Nostra metric. Now, GMV is the total order of total value of all the orders that go through the marketplace. I could make it grow up by setting delivery if you do zero by setting everything to zero. And what happens then? The company's revenue goes to zero. So you basically want a check metric around the health of the customer

00:54:14and a check metric around the health of the company. There are the guardrails around this North Strametric. So in the case of DoorDash, 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

00:54:40someone can just go use it without talking to a human and it just works for their problems. 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 at four qualities, which is, I think, was gross margins, low cost to acquire the customer, high retention, and a tight sales cycle, which maybe maxed that kind of the self-serve thing. Talk about the relationship between those two

00:55:10things. The sales 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, millions of customers using us. There were a lot of small businesses, but they 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.

00:55:38So 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 the 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 meaning to show it,

00:55:54but 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. He's like, why did you build it? We're 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.

00:56:09End 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. in terms of the smaller customers adopted it much faster because some of these things we were building

00:56:31had advanced knobs and so on that we didn't think they wouldn't use. Turns out the sales 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,

00:56:48it'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 up your system to self-serve, you learn so much more about the capability of your product than if you basically, it's your sales team doing it on their behalf. In fact, I'll never forget. In AdSense, I think we had some of the largest publishers in the world

00:57:11sign up and start using us on a self-serve basis, and then we engage with them after that. And I think companies like Atlassian Square, I think we had Nike, signed up for a square device and self-servo onboarded and started using in one of this. 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 onboard, not just use, but on board and use the product without ever talking to or engaging with a single member

00:57:46of 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 onboard. 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 sales product, you don't even think about. In a sales sub product, you think about it every day. It's like a consumer product or a salesman business product. And then second, what it does for you is it opens up the aperture to your customers.

00:58:15Because with, say, 100 salespeople, yeah, you can reach maybe 10,000 customers. But with the salesor product, with the right word of mouth, you can reach millions of customers. Look at Cursar, for example. It is used in every large company, I bet only maybe one percent of companies is maybe the top-down motion. 99.9% of companies, some engineer got it. Great example is a company, it'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, because I didn't design.

00:58:45I said, you've got to use Figma. Designers refused to use it. They're using a tool called Sketch, and they said, we'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,

00:59:02and 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 direct sales motion could never have produced them. 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 skip the unglamorous infrastructure work and focus on your product.

00:59:28Ridgeline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5X in scale, enabling faster growth, smarter operations, and a competitive edge. Visit Ridgeline apps.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,

01:00:07hiring middle management very, very quickly, and hiring C-level 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 even 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 a PM at Meta, who's non-technical, but who basically built a bunch of AI agents to do his job as a PM so well that even his engineers are 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.

01:01:01You 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. And 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.

01:01:23So 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.

01:01:41Engineering 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. Do stuff. Yeah, do stuff. Everywhere else, you can just BS your way without doing stuff.

01:01:52So at Square, we established work projects where even for CorpDev, 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 synergy should be. So the best candidates are 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.

01:02:17that we were thinking about, and we would just say, here'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 customer-facing 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,

01:02:34and they did it in a beautiful way. They went and talked to 10 customers on the street. So brilliant, they said, I talked to 10 customers. They were all square users, and we found that none of them want this premium insights product, so we don't build it, we're going to build this other thing 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

01:02:56the premise in the first place. Square 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 Howdy's thing? Nodeash had the best work project ever. He would give people either $10 or $20 and asked him to acquire a thousand customers, a thousand customers for Dodash 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 would literally opt 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

01:03:33flyers 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 be 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, as I call them, who stayed at a job for 12 to 18 months and then they move to the next job.

01:04:09And then they said 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 at a 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.

01:04:40Okay, you left in 18 months. But if I'm seeing two or three jobs back to back, immediate rest. flag. You do a massive disservice 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 your new firm Marathon,

01:05:13on 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 countries I've 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?

01:05:38It 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 do 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.

01:06:07I really advise them not to do that because just going on 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 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 B2B marketplace. Max Rhodes the CEO worked for 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.

01:06:47Turns 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? And there's so many of them. How do you go in and pitch to them? So you realize that that problem is the one he wanted to focus on.

01:07:08other manufacturers who wanted to get access to local retail. Are there any other questions that you 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 started the problem, but then there are many different solutions, many different ways to solve it.

01:07:29Why is you just this way versus another 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, all this one. I think good example is the Collison's, 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

01:08:05understand why all the prior companies took the decision and I did they stand on the shoulders of giants were able to build this company. The dimension we 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 Trade Desk. 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 of being on boards

01:08:35is that it gives you a much better perspective of what it means to be an executive by being on a board. Once a company gets a certain size, I think the CEO needs to try to see

01:08:43they 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

01:08:54and 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

01:09:01now increasing with product and engineering experience. In fact, every tech company cares 10 or 15 years ago. You would probably see zero product to tech people on boards. Now, every good board has one or two product to tech people. Second, you need a voice of the customer on the board. You need somebody who represents customers.

01:09:18So at Square, we got the CEO of Shake Shack, Randy Garuti on the board, and he was amazing because your 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.

01:09:43Have them come to a few board meetings. Have them meet to 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 feels 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, five hours, discuss topics. Maybe we'd bring in the management team person for one slice, the CFO, and then they would leave.

01:10:12Now, 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 the different part 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,

01:10:38I've now 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

01:10:55anything the management member has. You can see that the different board personas that 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 else is a buddy 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 matters, all the things between the board meetings that are the real thing when things get done.

01:11:22I 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. For consumer focus companies, the big thing is how to scale influencers. They've become much more powerful in how people, especially younger people, consume products and even choose products. Like somebody said that TikTok is the best local search engine. And I think that's right.

01:11:58My kids have discovered when you go traveling, crazy restaurants and TikTok that Google Maps would not really show or Yelp doesn't show it. So how do you reach influences on TikTok? And there's a set of companies that's coming out that's essentially making it easy. The problem is influences on TikTok. Obviously, there's head influences, 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

01:12:24brands 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?

01:12:48Oh, 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 you solve it, it pays 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

01:13:12reaching out to companies is you cannot lead with what your product does anymore. You've got to lead with what is the outcome you can deliver or ideally even have delivered. I'll never forget this example. What is crazy is that companies always look to other companies in the vertical. This never will change. So for example, if you get J.P. Morgan to use your product, I promise you, every single bank will then evaluate your product. But if you get Procton Gamble, J.P. Morgan doesn't care if Procton 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 lighthouse effect. You want to go after the

01:13:51best 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 had never been a product manager before. I'd been an engineer. I 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. He was a Sequoia-funded company, one of the hottest companies in the

01:14:26valley. 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 when I do something for someone. What created the spark in you? Where did the spark come from? 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. But for the grace

01:15:13of 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. Coco, 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-edited transcripts. You can also subscribe to Colossus, our 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 slash subscribe. Your finance team isn't losing money on big mistakes.

01:16:12It'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 slash 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 slash invest. Ridgeline is redefining asset management technology as a true partner,

01:16:38not just a 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. 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.a.ai slash invest. The best AI and software companies from OpenAI to cursor to perplexity,