Keith Rabois on Barrels, Undiscovered Talent, and Why He Won't Let Colleagues Talk to Customers
Lenny's Podcast
Keith Rabois has worked at the center of several defining Silicon Valley companies. He was an executive at PayPal, COO at Square, and VP of Corporate Development at LinkedIn. He was an early investor in Stripe, Palantir, Airbnb, YouTube, DoorDash, and Ramp, and he is now a managing director at Khosla Ventures. In this conversation with Lenny Rachitsky, the central question is how companies build world-class teams, and how that changes as AI reshapes the work. Rabois's position is consistent and often deliberately contrarian. He believes team quality determines almost everything. He thinks the best talent is usually undiscovered. He argues that success should bring more pressure, not less. And he holds that consumer companies should stop asking customers what they want.
An iPad-only life since 2010
The conversation opens with a detail about how Rabois works. He was on an iPad, and he said he hasn't touched a computer since September 2010. When he joined Square, Jack Dorsey was running the company from an iPad, and Rabois converted immediately. Since then, he said, everything he does happens on his phone, his watch, or his iPad.
Lenny compared this to the recent trend of engineers such as Boris Cherny and Simon Willison coding from their phones by talking to AI. Rabois said he tries to stay ahead of the curve and joked that following Steve Jobs keeps you in good shape in technology. His reasons are partly about avoiding distractions and mostly about portability: the weight, the flexible screen angles, and being able to carry it everywhere. Unless you are doing heavy engineering, which he noted has not been his forte "although I may have to start," he sees no reason to use a heavier, less flexible machine.
"The team you build is the company you build"
Asked what the best companies do to attract top talent, Rabois went to first principles. The most important lesson he learned at Square came from Vinod Khosla, who sat on his board: the team you build is the company you build. People get distracted by the market, customers, product, and technology, he said, but with the right people everything else becomes easy, and with the wrong people everything becomes difficult.
He said he actually learned this at PayPal before Khosla put it into words. He explained PayPal's success, and the string of companies its alumni founded over the following 25 years, by the fact that Peter Thiel and Max Levchin gathered an extraordinary density of talent. Levchin hired essentially all the technical staff and Thiel hired nearly everyone else. Both relied mainly on their networks. It was very hard to get a job at PayPal without a first- or second-degree connection to the engineering team or to Thiel through Stanford. Rabois said this model works very well if your network contains unique talent, and that interviews are not a great substitute for it. He would not recommend it to everyone.
Learning to hire: from 50/50 to recruiting inside the building
Rabois admitted he was mediocre at hiring early at PayPal, roughly 50/50 between good and mediocre hires. That doesn't let you scale a team with an unfair advantage. David Sacks, then COO, told him he would not be promoted again until he demonstrated leadership leverage. Sacks had an equation for this: 1 + 1 must equal three or more, meaning each additional hire must produce disproportionate, non-linear returns.
Since his external hiring wasn't working, Rabois looked inside PayPal. He found people he thought were talented but underused relative to their potential and ambition, and he recruited them onto his team. It worked. The team got up to speed fast, produced important results, and he was promoted fairly quickly. The lesson he took was that he could identify talent. He just couldn't identify it in strangers. With people he had lunch with, ate dinner with, or ran around the PayPal campus with, his judgment was accurate. In a 20-to-45-minute interview, it wasn't. So his first move was to double down on people he knew. Over the following years he developed separate techniques for assessing strangers, which he said is unavoidable if you want to build an organization or invest as a VC.
He believes some of this can be taught to founders. He made a strong claim about its importance: if a founder shows early in their career the ability to assess talent "ruthlessly and accurately," they can go very far with no other abilities at all. He described hiring as a muscle. You try, study what worked and what didn't, work out what you could have known and why you missed it, and iterate.
He was careful about how far tactics can take you. In his view, tactics move you meaningfully within the middle of the bell curve. They cannot teach you to identify the top 10 to 50 basis points of talent. For that you have to deviate from the norm. If a playbook could get you there, by definition many people would be in the top 10 basis points.
Tactics that do help: references, framing, and a 30-day check
The first teachable skill Rabois named is what he calls ruthless referencing. It works less well for new graduates, whose references carry less context. His example was Tony Xu at DoorDash, who, Rabois said, does 20 references on every senior hire. He also described a rule David Sze taught at Greylock: keep referencing a founder until you hit a negative reference. Only then do you know you've exhausted the references.
Framing matters too. He illustrated this with Faire, where he has invested since the seed round. Faire was founded by former Square colleagues, including Max Rhodes and Jeffrey Kolovson, who had worked for him. According to Rabois, many VCs checking Rhodes's references asked whether he had been a good employee, and the answers were very mixed. That made some very good investors nervous. Had they asked whether Rhodes could be a world-class entrepreneur, he said, the answer would have been yes. Same person, wrong question, wrong result. Many passed on Faire and now regret it, even though they were calling people like Jack Dorsey for references.
For senior leadership candidates, Rabois always asks: "If you were CEO, what would you have done differently?" about the candidate's current company. He said the point isn't to get them to criticize their employer. He wants to see how much of the business model they've absorbed, whether they understand trade-offs, and whether they have ideas that could create an unfair advantage. His follow-up question is: why weren't you able to persuade the CEO to do it? In reference calls, he generally probes two things: what would make this person most successful, and, if things didn't work out, what the primary root cause would be.
Lenny noted that most people hire and then learn little from the outcome. Rabois cited research he had read: asking yourself, 30 days after any hire, whether you would make the same decision is about as accurate as evaluating a year or two later. That gives you a tight feedback loop, and you can ask the whole hiring team the same question. He said every company should do it.
Barrels and ammunition
The best-known framework in the conversation came out of a pattern Rabois kept seeing. A company raises a Series A or B and hires many people. Burn goes up, but output per week or quarter doesn't. After years of hearing frustrated CEOs describe this at dinners and in one-on-ones, he concluded that very few people in any company can independently take an initiative from inception to success. He calls them barrels. Hiring more people without adding barrels just stacks people behind the same initiatives. That adds coordination and collaboration tax, which creates drag.
He gave numbers. By his count, PayPal had about 254 people in Mountain View when it was acquired. Depending on how strict you are, it had 12 to 17 barrels, which he called "like an infinite number" and attributed to its exceptionally talent-rich network. He once asked Jack Altman how many barrels were at Lattice, which he called a big company, and the answer was two. Rabois said that is the more common answer, even for a very good company. The number of barrels, typically somewhere between two and fifteen, sets how many things a company can do in parallel or in sequence. More hiring doesn't change it and may reduce output.
He does not dismiss ammunition. Some projects need a designer, engineers, a PM, and analysts. Others can be done by a barrel alone. What matters is thinking deliberately about the ratio of ammunition to barrels for the problem at hand. That ratio, he said, determines how many important initiatives a company can pursue at once.
What makes someone a barrel: the smoothie test
Rabois defined a barrel simply. Point at a hill and say "get us over that hill." A barrel will motivate people, gather resources, and measure whatever is needed to get the company there. Anything less is not a barrel. The scope starts narrow and grows as trust builds. Sometimes the barrel has no idea how to solve the problem at the start. The core skill is "I'm going to take this off your plate": the CEO can fire and forget. If it isn't going to happen, a barrel comes back proactively, with enough time for the CEO to help, and explains the obstacles, what they've already tried, and their diagnosis of the root causes. Lenny suggested "agency." Rabois agreed it fits but said words like that tend to go in one ear and out the other, like "strategy."
His example was what he called the smoothie test, which he had described in a 2014 YC lecture. Square engineers often worked late, and he wanted them to have healthy food rather than junk food, specifically cold smoothies delivered at 9 p.m. Square had a sizable office team and executive assistants, and every attempt failed. The smoothies came warm or late, and then nobody could rely on them. He mentioned his frustration to an intern, Taylor Francis, on Francis's second day, and Francis said he'd solve it. Rabois was skeptical. The next night at 9 p.m., cold smoothies that tasted great showed up on the standing desk where the engineers gathered. Rabois said he thought, "Oh my god, I found a barrel," and later gave Francis almost everything to do.
Winning over proven talent, and building on undiscovered talent
For attracting people with proven talent who have multiple offers, Rabois said the standard pitch still matters: selling the mission and vision is indispensable. His more nuanced approach is to show a candidate that their specific skill overlaps with the company's critical blocker, so they are betting on themselves. If the company's main blocker is marketing, not product or technology, you can tell a world-class marketer that they are uniquely positioned to solve it.
That is how he ended up at Square. In 2010 he had just been acqui-hired into Google and planned to become a VC once his compensation vested. Square's investors called and said they had spent nearly a year looking for someone who understood financial services and was still entrepreneurial, and that there were only two or three such people in the world. That argument got him to leave Google after two weeks, which he said infuriated everyone, and to put off venture for three more years. Lenny wondered whether this was ego. Rabois called it impact: talented people want to be challenged and to do things that really matter.
His more important point, though, is that companies should be built on undiscovered talent and avoid competing for the people everyone wants. He said Thiel taught him this in his first week at PayPal, on a jog around Stanford: finding undiscovered talent is the only way to scale against incumbents with unlimited money. He compared startups to sports teams under a salary cap, except a startup's cap may be a tenth of its competitors'.
Asked for one tip on spotting it, he said to figure out why other people will misprocess this person. Recruiting at large organizations becomes a homogeneous black box, so he asks what Meta, Google, Block, or Coinbase would miss about a candidate, and why. Sometimes the answer is simply a lack of data. He acknowledged this can sound controversial, but said his approach tends to skew toward younger hires. The reason, in his account, is not that youth is the goal. Younger people have fewer data points. He compared it to credit scoring: past 30, there's enough data on you that the black box will process you like many others. With few data points, a homogeneous evaluation struggles, and that is where the "alpha" is. Lenny noted this is essentially the same skill as picking startups, and Rabois agreed.
Why the CEO should push harder when things go well
Lenny read a comment from someone who has worked with Rabois: no matter what numbers a team puts up, he pushes for more, and often pushes harder the better they do. Rabois agreed. He cited a story in which a CEO friend asked Mike Moritz what the best CEOs have in common, and Moritz answered, "the relentless application of force." Rabois said success breeds complacency, and the CEO's single role is to offset it. Unless you've built a network effect, which most businesses haven't, you can't afford to coast.
He added that as a board member he deliberately inverts his behavior. When a company is struggling, he is usually non-critical and acts more like a coach, because the founder already knows things are bad and criticism doesn't help. When a company is thriving and borderline complacent, that's when he identifies what will eventually become problems. He compared this to a good sports coach: polish the details while you're winning, and sell the future while you're losing. He also used the Super Bowl as an analogy. After a championship season, the record resets to zero. He said venture is like that too. He has had about 13 years of strong investments, but it doesn't matter if he doesn't find the next undiscovered founder.
Lenny said he saw this with Brian Chesky at Airbnb, and that during brief lulls morale actually dropped. Rabois said he agrees with nearly all of Chesky's views and called Lenny's observation subtle and important. Really talented people are like superb athletes with an internal tempo, and when everyone is coasting, the best people become unhappy.
Careers in the AI era: curiosity, and the CMO as top token consumer
On the anxiety in the job market, Rabois said AI will radically reorient many careers, "maybe including mine." His advice is to be intellectually curious. He does believe in working hard and in "no days off," but he sees curiosity as the way to future-proof yourself. His evidence was an observation from two large companies he is close to, both with many engineers, one of them Opendoor: the number one consumer of AI tokens is the CMO. According to Rabois, these CMOs sometimes build what used to be called analytics, sometimes produce actual campaigns, and sometimes give the CEO insights directly. They no longer have to go through "deputies and deputies and deputies" to get work product. He said this is very encouraging, especially for executives.
The product triad: why the PM role makes less sense
Rabois said a podcast featuring Peter Fenton convinced him that the traditional PM role makes little sense in the future. In his description, a PM gathers customer inputs and builds an organized, sequential roadmap for the next year. He believes that world no longer holds, because foundation models are improving so fast that a year-long roadmap is incoherent. Things impossible in November are easy by March. Companies need to change their roadmap almost on the fly, and intermediaries like conventional PMs fit poorly with that. Someone needs to notice that something is newly possible this week and exploit it by shipping new value next week.
Lenny pushed back. As AI eats the middle of the development process, the remaining hard part is deciding what to build and aligning people around it. Rabois agreed, but said that skill now looks more like being a CEO, "what are we building and why," regardless of whether the person was a PM, designer, or engineer. He cited Alfred Lin's analogy of a top chef who doesn't cook every dish but samples and edits others' work. Half of that chef's job is commercial: value proposition, differentiation, brand, segment, pricing, even location. Rabois summed up the enduring human skill as business acumen: understanding the company's business equation and being able to create things that move the needle on your own.
Lenny argued that great PMs are historically best at this. Rabois said that's true for exceptional ones, but many great engineers have always had strong commercial instincts. He named Max Levchin, whose instincts he called "on steroids," and Jeremy Stoppelman, who had them as an individual contributor at PayPal before founding Yelp. Rabois expects AI to put a big premium on such engineers because they won't need large teams. His example was a friend who is a director of engineering at Ramp. That person manages about 20 people and, according to Rabois, personally ships as much code as he did as an IC, using AI as a kind of second team that he directs.
Design and code are merging
On design, Rabois said design and code are merging. It isn't clear to him whether code will become design or design will translate automatically into code. He said he has made investments that bet on both, but either way they are no longer separate fiefdoms. Lenny said his own analysis shows open design roles have been flat for about three years, and mentioned Jenny Wen's point on an earlier episode that there's no time for a traditional design process when engineers ship many things a day. Rabois pointed to Shopify. By his account, for about two years Shopify has not let PMs present product ideas as slide decks. Every product presentation must be a working demo, and executives refuse to look at static descriptions of features.
Lenny suggested design should become more of a differentiator as the number of products explodes, and Rabois agreed. He said the alpha lies in storytelling, not in tools, channels, or metrics, much like in marketing. It is a kind of NP-complete problem: there are countless ways to express the same idea, and the person who finds the right frame, like "a thousand songs in your pocket," is worth more than all the tools in the world. When founders pitch him, one of the first things he looks for is how the product will cut through the clutter.
AI content, AI writing, and the brief's first paragraph
Lenny floated the idea that AI content will overtake human content, and Rabois called that inevitable. He predicted a split. One pole is curated content with a premium on provenance, where people want to know something was human-made, the way people value a real Warhol even though anyone could now produce a high-fidelity copy. The other pole is algorithmic ranking of whatever is best, AI-generated or not. He compared this to Ben Thompson's framing of curation versus algorithm. On companies that simulate humans for marketing tests, such as one Lenny mentioned, Rabois's question is what they're trained on. Without the right data, he said, claiming to simulate humans is dangerous.
Lenny found it ironic that large language models seem worst at writing. Rabois's hypothesis is that labs ration tokens to make their economics work, so quality falls noticeably as output grows from a short piece to a page, a chapter, or a book. What works for him now is short outputs, many examples, editing, and re-prompting.
This led to his years as a litigator. He said he spent about four and a half years as a law clerk and litigator, and that all the magic in a brief was the first paragraph. With three weeks to write a brief, he might spend a week or more walking around thinking about the first three sentences, and the answer sometimes came in the shower or on a run. Once he had them, he could write 30 pages in two days. He sees AI as good at the "power through the rest" part. You still need the first three sentences.
He said law occasionally helps. Weighing legal risk against business risk is useful, and he said it's no accident that many of his best investments, including YouTube back in the day, are in heavily regulated areas like financial services. But he considers most legal training at odds with entrepreneurship. Law school trains issue-spotting, finding everything that could go wrong, and it's easy to list reasons a company might fail. Solving them is the hard part. Lawyers also measure productivity in billable hours. He said it took him roughly a year and a half after moving into tech to stop logging his time in a notebook. He noted that Thiel quit law after a few months and that Sacks never practiced.
Why he refuses to let colleagues talk to customers
Rabois said many of his contrarian views have since become consensus, which is what you want as an investor: Airbnb started as a contrarian bet and had to become consensus to succeed. One view that still provokes disagreement is his stance on customer research outside the enterprise. "I hate talking to customers. I refuse to allow colleagues of mine to talk to customers," he said.
His argument goes beyond the familiar "faster horses" line. He believes customer feedback is often directionally wrong. Consumer purchases are subconscious decisions, and when people try to explain them consciously, they give misleading answers even when they're trying to be helpful. His example: ask anyone who drives a Porsche or a Lamborghini why they bought it, and 99% of the time they'll give every reason except the real one. He also said a staged research setting isn't a proxy for the real world, where a product must cut through the clutter while people are at their Barry's class, working, raising kids, or riding the subway. He added that "everything important you need to learn about humans is written by Shakespeare," and called Shakespeare better than all the customer research.
He makes an exception for serious enterprise sales. There, a decision maker is making a mostly utilitarian choice, and customer development works. He described an AI company he works with whose goal for the next two years is 30 must-win accounts. It can talk to all 30 decision makers and even influence their CEOs. But for consumer, SMB, and micro-merchant products, which he sees as anything below mid-market, including businesses like Square and DoorDash, he called customer research an "unmitigated disaster." Part of the harm, he said, is that anecdotes stick. He described meetings where someone admits eight conversations aren't statistically representative and then talks about them for an hour. After that, the anecdotes shape every later meeting.
In place of customer research, he uses the analogy of a movie. The goal is to sell tickets. If you aren't selling them efficiently, go back and ask whether the trailer, distribution, casting, or script is off, much like analyzing CAC and LTV. He also separated asking customers what they want from testing feasibility. For a business like DoorDash, you might ask restaurants whether they'd display a placard, or calculate how many deliveries per hour you need to break even and whether there's enough density. What you don't do is ask ten people in Palo Alto whether they want a button on their phone.
He said the best companies rest on a foundational insight whose logic can be pressure-tested. When Tony Xu and Evan came to pitch DoorDash, their statistic that 93% of US restaurants didn't deliver convinced him. Their description reminded him of Andrew Mason's line that phones should have two buttons, "I'm bored" and "I'm hungry," and he thought they were building the "I'm hungry" button. Chesky's Airbnb pitch included the number of Craigslist posts in the Bay Area from people wanting to rent out a bedroom, about 30. Rabois considered that significant because people had to come up with the idea and type it in themselves, and he was leaning in within minutes. Had Airbnb surveyed ten random people, he said, nine or more would likely have said no.
Lenny brought up a Taylor Swift speech about spending thousands of hours developing her craft alone before sharing it. Rabois said musician friends have described a related trap: a first hit that wasn't data-driven is followed by pressure from managers or labels to gather feedback, which produces derivative, less inspired work. He mentioned a conversation between Jack Conte and Alex from The Chainsmokers about a song that failed with their core audience but found a different one.
Ugly babies and evaluating AI startups
Lenny raised Ed Catmull's idea that great ideas start as "ugly babies." Rabois said he uses this as an investor. When he makes a seed or Series A investment, he wants about half his VC friends to literally laugh at him. He knows most of his competitors well enough to predict this, and if they'll laugh, it may be a great investment. Lenny said research he did with Terrence Rohan on early employees at generational companies such as OpenAI, Palantir, and Stripe found a similar pattern: people thought those ideas were crazy. Rabois added that his parents laughed at most of his tech jobs and worried he'd end up homeless, though his mother appreciated Stripe and lobbied him to invest until he did.
For AI startups, the existential question Rabois named is whether the foundation labs will become so capable that nothing else can breathe. A startup has to be durable for 8 to 20 years, and the pace of progress at multiple labs raises doubts even about companies that are thriving now. His second question, one he has asked for 25 years, is what accumulating advantages the company has, something that makes the business better, and eventually easier, over time. Network effects are only one type. At seed stage he doesn't expect proof. Maybe once every five years you can point to empirical evidence that early. He wants the founder to explain conceptually where those advantages could come from, and ideally when they'd start using or measuring them.
Overall, Rabois called himself a founder-driven investor. The only question at seed or Series A is whether the founder has a non-zero chance of changing an industry or the world, and whether this could be the next Brian Chesky. He noted that other successful investors work differently. He described Marc Andreessen as more technology-driven, Vinod Khosla as a mix, and his colleague David Weiden and Sequoia's Alfred Lin as more product- and market-driven.
Three traits of the companies that are thriving
Asked what distinguishes his best-performing portfolio companies, Rabois named three things. The first is speed, specifically an operating tempo that shows up very early. When Roelof Botha joined Square's board after leading its Series B, he told Rabois two meetings in that he hadn't seen that tempo since PayPal: a problem identified at one board meeting would be solved, shipped, and addressed by the next. Rabois's then chief of staff, Delian Asparouhov, said after shadowing two Faire board meetings that Faire was the one company that could get him to leave venture, for the same reason. By the next meeting, the team had found the root causes of a problem, shipped a fix, and measured its effect. Rabois said that speed compounds. It is also partly why he preempted Ramp's Series A. He led the seed around May 2019 and offered a term sheet in September, because Ramp was close to shipping cards in about three months, when in his experience it usually takes nine to twelve months at best.
The second trait is a critical density of talent that visibly improves over time, so that the team becomes deeper and better than the one he invested in. The third is a hiring philosophy that mostly skips senior, experienced hires in favor of growing people internally. He said this is especially true at Ramp and Trade Republic, while allowing that there are exceptions. He cited a framework from a blog post Asparouhov wrote about lessons from Rabois: if you're hiring for value preservation, experience helps, but for value creation it probably doesn't. Some companies use the chief of staff role as a talent factory. He described a company whose board meeting he attended that week, which did phenomenally by every metric. Its outstanding CMO was the CEO's previous chief of staff, and its new head of product was the current one. Lenny mentioned Ramp's emphasis on velocity and its running day count. Rabois said every Ramp board meeting opens with the day number on the first slide.
Criticize in public
Rabois said he learned from a founder he works with to criticize people in public. His reasoning is that private negative feedback optimizes for the individual rather than the system. Colleagues usually already suspect a problem. Addressing it openly shows them it's being handled, lets others offer help, and turns it into team-building instead of leaving the rest of the company worried about why the problem persists.
When Lenny asked whether that creates fear, Rabois said the goal is winning. He allowed that the best sports coaches probably mix public and private feedback. He was blunt about psychological safety: "High performance machines don't have psychological safety. They're about winning." He recommended The Jordan Rules and The Last Dance: to be Michael Jordan, you have to act like Michael Jordan. Asked whether psychological safety is negatively correlated with success, he said, "For the most part."
Failure, and a partial exception on psychological safety
For failures, Rabois pointed to Slide, the company that was acqui-hired into Google. It sold for about $187 million, but he said it fell far short of its ambitions and didn't achieve its product or company goals. He said investing is mostly about failure: a 30–40% hit rate at early stage is excellent, meaning most bets fail. He compared it to Nike ads about Michael Jordan's missed game-winners and a tennis great who loses a large share of points.
He also said he tries not to dwell on failure. At a recent board meeting of a company doing well, well-meaning board members proposed retrospectives on failures, and he pushed back. He doesn't want to discourage ambitious shots on goal. He acknowledged this is where psychological safety "maybe has some validity": people should feel free to be bold and volunteer for hard problems. The exception is when something foreseeable was missed.
Lightning round
His most-recommended book is The Upside of Stress by Stanford professor Kelly McGonigal, which he said makes a compelling case that more stress, not less, makes people happier, healthier, and wealthier. He recommended Nuremberg, saying he learned several things despite being a student of history and politics, and that it holds lessons for preventing historical tragedies. He named Eight Sleep as a product he's addicted to, disclosed that he is an investor, and restated his belief in eight hours of sleep a night.
His motto is "no days off," which he traced to Bill Belichick's chant at a Patriots championship parade. He said it applies to work, including weekends, and to exercise. He said he has missed only seven workouts in seven years, still regrets several of them, posts the count every year, and missed none last year. For him, "no days off" is shorthand for not believing in excuses. Asked whether anyone from the PayPal era surprised him by outperforming, he said no. He believed he had a good sense of who had founder-level ambition, and he apologized for not having a better answer.
Idea of a PM makes no sense in the future. The skill is more like being a CEO now, which is what are we building and why?
There's a lot of anxiety in the job market.
AI is going to radically reorient lots of people's careers and maybe including mine. What I've noticed in some of the best organizations is the number one consumer of tokens is the CMO. They don't need to rely upon deputies and deputies and deputies to get actual work product.
I want to hit on some contrarian takes that you have. Your advice you don't actually want to be talking to customers.
I hate talking to customers. I refuse to allow colleagues of mine to talk to customers.
You have this idea of criticizing in public versus in private.
High performance machines don't have psychological safety. They're about winning.
You're uniquely great at helping companies build world-class teams.
If a founder shows ability early in his or her career to assess talent ruthlessly and accurately, he or she can go very far with no other abilities whatsoever.
It feels like it's never been harder to attract the best talent.
Really talented people when things are going well,
they're not happy.
The morale actually does go down when people are skating. The single role for the CEO is offsetting that complacency. The better you're doing, the more the CEO should push.
Today my guest is Keith Rabois. Keith's resume both as an operator and investor is absurd. He was an early investor in Stripe, Palantir, Airbnb, YouTube, DoorDash, Ramp, and dozens of other companies. He's part of the famous PayPal Mafia where he was Executive Vice President Business Development and Policy. He's also been Chief Operating Officer at Square, VP of Corporate Development at LinkedIn. He's also a co-founder of two companies and he's currently Managing Director at Khosla Ventures. It's safe to say that Keith is in the 99.9th percentile at identifying talent, building teams, and operating world-class companies.
Before we get into it, don't forget to check out lennysproductpass.com for an incredible set of deals available exclusively to Lenny's Newsletter subscribers. With that, I bring you Keith Rabois.
Keith, thank you so much for being here, and welcome to the podcast.
It's a pleasure to be with you.
Okay, so when we were starting this recording, you told me you're doing this from an iPad, which I've never had, and you shared a crazy fact that you haven't used a computer in like years. Talk about what's going on there.
Yeah, so when I started working at Square, Jack Dorsey was running the company off an iPad, and so I immediately converted in September 2010, and haven't looked back. I haven't touched a computer since September 2010. Everything I do in my life is either done from my phone, my watch, or my iPad.
What's so interesting about this as you were talking is just there's this trend of engineers starting to code from their phone. Like Boris and Simon Willison, these two engineers that are like 10x engineers, and they're just like coding from their phone talking to AI. And I feel like you've been preparing for this for a long time.
Yeah, I'm trying to be ahead of the curve. Jobs is very good at being ahead of the curve. If you just watch what Jobs is doing and follow him, pretty good shape in technology.
And just understand the benefit, is it just avoid distractions?
Yeah, partially distractions, partially just the flexibility by taking an iPad with you anywhere is just super easy. You know, some laptops have improved since then, but like the screen flexibility angles, but like just the weight. Like I carry my iPad with me everywhere, so there's no reason, there's nothing you can't perform unless maybe if you're doing heavy duty engineering, which obviously has not been my forte in life, although I may have to start. There's no reason to use a more powerful, heavier weight, less flexible machine.
Wow, iPad maxing, Keith Rabois.
Saving up my Apple. As long as it's an Apple product, it works.
So appropriate.
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As I was preparing for this chat, there's just like so many directions we could have gone with this. You are so smart on so many things. I want to focus on something that I think you're uniquely great at, which is helping companies build world-class teams. And I want to start in particular with attracting the best talent.
And what's really interesting these days, from what I can tell, is there's just like a lot of people that are struggling to find a job. It's taking a lot longer to find a job. There's all these layoffs. On the other hand, it feels like it's never been harder to attract the best talent. There are so many amazing companies doing amazing things, so much money flying around, these hundred million-dollar offers and things. And so, from the companies that you are closest to that you see are best at attracting the best talent, what have they figured out? What are they doing differently? What are some creative things they do?
Well, let's start with first principles. The most important lesson I learned when I was working at Square from my board was Vinod Khosla was on my board and he said the team you build is the company you build. And that adage is the most important thing when you're creating a startup. People get distracted with the market, with customers, with the product, with technology. Ultimately, it's the team. If you have the right people, everything else will be easy and if you have the wrong people, everything else is going to be difficult.
So, Vinod distilled it, but I actually learned this back from my PayPal days. So, you know, in the early 2000s, why was PayPal so successful? Why were there such, you know, subsequent generations of successful interesting companies for, you know, 25 years now? It's because Peter Thiel and Max Levchin marshaled an incredible density of talent. So, it allowed PayPal to succeed where possibly we wouldn't have. And these people went on with interesting ideas, ambition, and talent to build epic companies, you know, in all kinds of verticals.
So, from day one of my technology career, I've always been focused on the importance of critical density of talent. How do you identify, retain, and promote people with that talent?
Back in the PayPal days when I first started my career in technology, I actually truthfully was not very good at this. Fortunately, Peter and Max were. So, Max basically hired all the technical talent in the organization and Peter pretty much hired everybody else. They used their network primarily, so it was very difficult to get a job at PayPal unless you had a first degree or second degree connection to the engineering team or to Peter through Stanford, which is a different type of recruiting model. It works really well if you have a strong network. I wouldn't recommend it for everybody, but if you have a network that has, you know, unique talent, there's no substitute. Interviews are not a great substitute for how strong they are in an interview.
But, when I started back for real, I was mediocre at, let's say, hiring people. Probably 50/50, you know, some good people, some mediocre people. That doesn't allow you to scale a team with an unfair advantage. But, what I learned to do is steal people from other people's organizations within PayPal very successfully.
So, I got feedback from David Sacks, who was the COO at the time, that I wasn't going to get promoted again until I could demonstrate leverage, like leadership leverage, which he had an equation for: 1 + 1 has to equal three or more. So, for every incremental person you hire, you have to show that you produce disproportionate returns, non-linear returns. And because I wasn't hiring that well, I wasn't really succeeding at that leverage.
So, I took the feedback into account, and I said, "Hmm, okay, I really want to get promoted, what do I do?" So, I found people within the organization that I felt had talent, that were not being leveraged to their highest potential and ambition, and I recruited them to my team. And that was very successful. And then I did get promoted, actually fairly quickly, because these people actually were up to speed, they were able to learn really fast, and we produced a lot of really important results for the company.
The lesson though that I took away was, well, that's great, because what it showed to me is I actually could identify talent, I just couldn't identify strangers with talent. So, people that were in the building that I have lunch with or dinner with or go for a run around the PayPal campus with, I was accurate at diagnosing their abilities, I just couldn't do it, you know, in a 20-minute, 30-minute, 45-minute interview.
So, the first thing is just double down on people I know. That doesn't scale perfectly, but learn to be excellent at, if I had contacts, assessing people's abilities, superpowers, and you know, weaknesses, then over the next X years, try to identify a different technique for identifying, assessing random people, because ultimately to build an organization, ultimately if you're going to be a VC, you can't just invest in people that you already know. So that took some years and required some training.
Anyway, I think you can teach some of this to a founder. But one advantage a founder has that's going to thrive is if a founder shows the ability early in his or her career to assess talent ruthlessly and accurately, he or she can go very far with no other abilities whatsoever.
The hiring is like a muscle. You need to exercise it. You need to try, learn what worked, what didn't, what could you have known, what you missed, why, and you know, riff on that and try to get better at it. There are tactics you can learn. I think the tactics work pretty well within the middle of a bell curve distribution of moving yourself 10, 20 degrees within that bell curve. I don't think the tactics can really teach you how to identify, call it like top 10 basis points, top 50 basis points of talent. There you have to deviate from the norm and I think that's actually true of most lessons in life. If you're going to be extraordinary in any skill you can't follow a playbook, otherwise by definition lots of other people would be in the top 10 basis points. But you can get a lot better by learning techniques.
So for example, let's share a couple. One thing I think you can learn to do is be excellent at references. It doesn't work for hiring people right out of college or something, because the reference context is going to be a little off. But I think without getting better at interviewing, assessing, if you just learn to extract the right information from ruthless referencing. So for example, ruthless referencing to me means Tony at DoorDash does 20 references on every single senior hire. 20.
Wow.
I bet you he's pretty good. I bet you he's been pretty accurate, too. So you can learn that. That's like a skill that's teachable, that being absolutely, you know, incredibly dedicated to your craft, you can just get better at.
Back in the day, there was an investor at Greylock who was on my board at LinkedIn, David Sze, very successful investor, notable for both LinkedIn and Facebook investments. He used to teach at Greylock, you couldn't stop referencing a founder until you hit a negative reference. So, you would know you'd exhausted the reference when you finally hit a negative reference. And so, I think there are tactics there and, you know, muscle building: how do you get the right information from the right people, how do you frame the questions, etc. that will lead you in the right direction.
Now, you have to be careful. Let's say, I'll give you an example where this can go wrong. I've been a long-time investor from the seed round of a company called Faire, founded by two of my colleagues at Square, Max Rhodes and Jeffrey Kolovson, who worked for me at Square, and then the two other co-founders also worked at Square. When people were reference checking Max, often most VCs asked the wrong question, which was, was Max a good employee? The answer to that is very mixed. And so, some venture capitalists, including some very good ones, were nervous about investing in Faire.
If they framed the question slightly differently, which is, is Max capable of being a world-class entrepreneur, the answer was yes. So, again, it's like a tactic, you have to understand like what exactly am I trying to extract? Same person, wrong question, wrong result. And many people passed on Faire and they regret it. And these are actually quite talented investors. They just didn't frame the question correctly when they were calling someone like Jack Dorsey up for the reference.
Any other questions you find really helpful in extracting the right information?
When I interview candidates for senior people in leadership positions, I always ask them, you know, look at whatever company they're at and say, "If you were CEO, what would you have done differently?" And you get a feel for their strategic mindset of, you know, can they drive value creation? Because almost by definition, they've come from a company that's had some traction and success. So, can they add it? So, for your case, I would have asked you, you know, "If you were CEO of Airbnb, what would you have done differently?" And you learn a lot from that question.
On references specifically, I think a general arc that's pretty good is asking the person, "What would lead to this person being most successful?" And "If something were not to work out, what would be the primary root cause that you can identify of something going wrong?" I think generally probing those two arcs leads to a lot of insight.
And that first question is for the candidate or is that in the reference?
Candidate. That's for the candidate specifically.
Got it.
Because it's not like I want them to criticize Airbnb. I don't think that's productive. But you can tell how much of the current business model they have absorbed, how much they understand tradeoffs, and then can they create an unfair advantage, you know, do they have insights into afterburners? And then I'm going to ask a follow-up question, which is using gold, which is, let's say I asked you this question about Airbnb and you give me this great answer. I'm like, "Well, why weren't you able to persuade Brian to do it?"
So, you made this interesting point that there's like tactics that can help you get better at finding and identifying talent. A lot of this is just the feedback loop of doing it a bunch, it sounds like. I find the feedback loop is so hard to actually, like most people interview, hire, and then don't really learn much from how it ends up going. There's this gut thing that happens, but they're not really thinking about it. Do you have any advice for just how to make the most out of the lesson of seeing how something went?
Sure, I've read some research on the topic, and if you ask yourself 30 days after any hire, would you make the same decision? That 30-day loop is pretty useful, and it's basically as accurate as measuring a year or two years out. So, you've got a pretty tight feedback loop and you can ask the entire hiring team. So, I think that's just a technique that every company should use.
I want to talk about this framework that you have, barrels and ammunition, because this is really mind-expanding and helping people understand who to even hire.
So, look, most companies raise money, they have some traction, they raise their seed round, it gets launched, gets some traction, then they raise a lot of money, whether it's a Series A or Series B. And then they hire a lot of people, infallibly, or at least historically. And then the CEO almost without exception gets frustrated because they've hired a lot of people, their burn rate has increased a lot, and they don't feel like more is getting accomplished per unit of time, per day, per week, per month, per quarter. And they get frustrated, and so then they sit around at a dinner with other CEOs or people like me, or in one-on-one conversations with me, and they're incredibly unhappy and disappointed that I'm spending all this money on all these people, but we're getting less done or the same done, and why, why, why, why.
After years of sitting through these conversations at dinner with other CEOs or COOs, I realized that the fundamental driver of this is that the number of people that can independently drive an initiative from inception to success is very limited within any company. And if you hire more people without expanding the number of what I call barrels that can drive from inception to success, all you're doing is stacking people behind the same initiatives. And so, you're wasting time, energy, and increasing your collaboration tax, your coordination tax, and so that's what causes the drag coefficient.
So, for example, at PayPal, we had about 254 people in Mountain View when we were acquired. Of those people, depending on how strict you really want to be, and it is considered one of the best talent-rich networks of all time in technology, there were between 12 to 17 barrels in the organization. That's like an infinite number. I once asked Jack Altman on a podcast, at Lattice, which is a pretty damn big company, how many barrels are at the company? The answer was two. That's a more common answer, for a very good company.
So, you have between two and, let's say, 15 barrels at a company. That defines the unique number of things you can do in parallel or sequentially. And just hiring more people is not going to change that. If anything, it's just going to cause a collaboration and coordination tax and you're going to have drag coefficient and you're going to do less. So, the key to me is if you want to do more, or need to do more, your market requires you to do more, or your business model requires you to do more, VCs require you to do more, you need to have more barrels. Now, the question is how and when, and there's a lot of details there, but fundamentally the ratio of barrels to ammunition is what dictates the number of important initiatives that can be pursued simultaneously.
And you're not saying you don't want ammunition. Like, it's valuable. To make an impact, you need ammunition in addition to the...
Yeah, you definitely need ammunition, and it depends on what kind of project. There are types of projects where an individual barrel may be able to succeed with very limited or no ammunition. Sometimes you need a designer, an engineering team, a PM, data analysis, blah blah blah. So, it depends on what the project is, what the problem you're trying to solve is, what's the proper amount of ammunition. But once you think about the ratios of ammunition to the problem, you can be much more constructive and deliberate and intentional about the team construction.
Most people hearing this, assuming they are barrels, what helps you understand if someone is truly a barrel?
Can they take an idea and make it happen? Basically, there's a hill over there. That's the hill. Get us over that hill. And one way or the other, they will motivate people if they need to, they will accumulate resources if they need to, they will measure what they need to, and they're going to get your company across that hill. That's a barrel. Anything less than that is not a barrel.
And so this is skills like internal org stuff, resource, like... Yeah, it's kind of the collection of all the things to get something...
Collection of all those things. It's just basically there's an outcome.
Mhm.
The CEO, founder wants an outcome. And come hell or high water, this person is going to deliver that outcome. The outcome can be fairly narrow and not that difficult in the beginning, and then you expand the scope of the complexity, the difficulty that you basically entrust to your barrels. And sometimes they have no line of sight of how to solve it when you start. Sometimes you have a preliminary idea. So it ranges, but ultimately it's that skill of: I'm going to take this off your plate. You can fire and forget, and this is going to happen. And if it's not going to happen, I'm going to come back to you proactively with the issues I'm confronting, what I've already tried, the diagnosis of the root causes, and ask for your help with sufficient time for you to intervene and try to brainstorm with me to get us to the right answer.
Agency is the word that comes to mind when you talk about this role.
Yeah, I think agency is accurate. The problem I have with terms like agency is it's a little bit like strategy. It goes in one ear for a lot of people and out the other, and they don't really process the meaning.
Yeah. What are some examples of barrels that make this real so people can understand what you're talking about?
You know, I talked in my YC lecture in 2014 about how to operate. They can be as simple as the now somewhat famous in technology smoothie test, which is: we used to have engineers work pretty hard at Square and pretty late. And I always wanted them to have food, so they wouldn't be famished, they wouldn't be distracted, and I didn't really want them to eat junk food, because I actually think junk food's bad for you, bad for your brain, etc. So, I settled on delivering, and really wanted to provide, at 9:00 p.m., cold smoothies.
And we had at that time a pretty substantial team at Square, office team, EAs. This was not a lean, mean organization. And so, I tried through the office team, EAs, and nothing. We never got healthy, delicious, and cold smoothies delivered at 9:00 p.m. It just kept failing. I was getting frustrated, because if the smoothies aren't cold, then no one's going to eat them. If they don't arrive at 9:00, then no one can really bank on the refreshments. Everything went wrong.
And then I had this intern named Taylor Francis. And I was explaining just my frustration. And this was his second day of work. And he's like, "I'll solve it." And I was like, "Okay, kid. Good luck with that." I was like, "Sure, you try." Anyway, the day goes by. 9:00 p.m. arrives. And lo and behold, smoothies show up at 9:00 p.m., delivered on the standing desk table where the engineers would congregate. I sample them, they're cold, they taste great. And I'm like, "Oh my god, I found a barrel." And I later gave him almost everything to do.
I want to go back to actually the first question. You shared some amazing advice for how to identify great talent, but I'm still curious, when you find that barrel, for example, when everyone's throwing money at them, there's all these amazing teams to join, what are some things that companies do to attract and convince them to join their team?
There's standard stuff that's still true. Mission, selling the vision and mission, is indispensable. Most people with proven talent, at least in the current world, are going to attract offers for multiple opportunities. And so you've got to convince them that your opportunity is very special. I think one way to do that that's a little bit more nuanced is to convince them that their particular skill overlaps with the critical blockers to the current company, meaning they're betting on themselves. So for example, if they are superb at, let's say, marketing, if the biggest blocker in the company's current success is not technology, not the product, but we believe it's marketing, it's really easy to go to a world-class marketing person and say, "Not only is this great company building something really cool and interesting that you'll be proud of, but your particular ability is very unique and differentiated and you can solve this."
This is actually how I wound up at Square. Back in 2010, I had just been acqui-hired by Google and was planning on being a VC next, after I was kind of vesting whatever Google was going to compensate us. And then the investors in Square called me up and they said, "Hey, we've been looking for almost a year now for someone who knows something about financial services yet is still entrepreneurial." And they're like, okay, at the time, 2009, there's only really two or three of you in the world. So would you be interested? I said, "Well, maybe." But that was the argument that made me leave Google early, after two weeks, and infuriate everybody, and bypass venture for another three years, which had been my plan: because they made the argument that I was one of the three people in the world that could actually do this job.
So look, there's a, I don't know if it's ego, but it's also just impact.
Yep, well, exactly. Impact. If you have talent, you want to use it, and you want to feel that you're challenged every day and that what you're doing really, really matters. So, I think that can be extremely helpful.
My more important arc in this is I think you have to build a company on undiscovered talent. I don't think you really want to compete for the people that everybody else wants, right? And I learned this at PayPal. Peter taught me this literally the first day and first week of my job at PayPal, while we were jogging around the Stanford campus: that the way to build a company is you've got to find this undiscovered talent. That's the only way to scale an organization against these large incumbents with infinite money, etc. And I've been on that crusade for 25 years. For those who are interested, you can link to it. I gave a speech at Ramp on how to hire. The talk's in detail. I also recommend Eric's, CEO of Ramp's, speech, which is fairly similar. Both videos are online.
That's such interesting advice and makes so much sense. You're not going to be able to afford the people that have done the thing at top companies. And also, they're just probably not the people to join at an early stage.
Also not maybe the people you want, so there's adverse selection, but it's like a salary cap. Most sports these days have salary caps. And when you're a startup, not only do you have a salary cap, you probably have 1/10 the salary cap of the people you're competing with. So, you've got to figure out how to leverage fewer assets to more success.
What's just one tip when you're looking for undiscovered talent that's a sign of, okay, this person is really special? I know you have a lot to talk about here, but just, what's one tip?
I think it's basically isolating why other people aren't going to process them correctly. Most of the recruiting at large organizations becomes sort of a homogeneous function. And so, if you understand why this person is going to get thrown into this black box kind of thing and not get processed accurately, it's pretty easy. So, I always think about, let's say this person was interviewing at Meta or Google or Block these days or Coinbase. What are they going to miss? And then why? And then that leads to, oh, perfect.
So, sometimes it's just lack of information. Sometimes it's controversial to say this, but one of the reasons why the net impact of my hiring of undiscovered talent is you wind up skewing younger, it's not because you need young people, it's that younger people have by definition less data. We use credit scoring, FICO scores. It's the same thing for employment. By the time you're over 30, there's so many data points about you that this black box machine is usually going to process you like many other people. If there's no data points, it's very hard for a black box machine that does homogeneous evaluation to evaluate you. So, there is alpha, so to speak, by definition, for people who have no data points.
It's interesting how this is the same skill as being an investor, picking startups to invest in.
Yeah, absolutely.
Okay, I want to talk about something else. I asked a few people that know you well, that work with you at various companies, what to talk to you about, and when I asked one person what to talk about, he said, "My immediate reaction is that he is a bar raiser. No matter what kind of numbers we put up, he pushes us to do more. In fact, often it seems like the better we do, the harder he pushes." Does that resonate?
Yeah, I think that's true. I mean, look, ultimately, I'll channel someone else's feedback, but it's the same thing. A friend of mine who's a CEO once asked Mike Moritz, "What's the most common denominator of the best CEOs ever?" And he said, "It's the relentless application of force." Quote. I think that's the job of the CEO. People eventually get comfortable, complacent. The more success you have, the more complacent the organization tends to get, and the single role for the CEO is offsetting that complacency.
So, to put the point, the more success you have, the better you're doing, the more complacency naturally kicks in. And unless you've erected a network effect, you do not want to get complacent. Even then, you need to debate whether you should, but fundamentally, most businesses are not network effect businesses. They're not going to run on their own for a long time. So, I think that's one insight: the better you're doing, the more the CEO should push.
Secondly, it's a little bit like sports when you're growing up. People, when they're winning, take advantage of feedback better than when they're losing, usually. So, for example, now what I do is mostly VC, mostly a board member, mostly I could conceivably narrate to a founder. And maybe what's less intuitive, and you may have picked up on this in your research and interviews of people who know me, is that when a company's struggling, I'm actually usually very non-critical and more like a coach and supporter, because the founder knows they're struggling. Being critical doesn't really help them solve their problems. That's when being supportive can actually, somewhat counterintuitively, be more important.
But when the company's thriving, it's really important to be critical and isolate things that will eventually be problems while everybody in the company's really happy and borderline complacent. So, you kind of want to be the opposite as a default. And that's similar to a really good sports coach. When you're winning is when to polish everything and really master the details. When you're losing, you definitely also have to be exciting people and embracing the future and selling the future.
So, is the advice, say someone's listening, a founder or product leader, the advice here is just keep pushing harder, set the bar higher, even if you're doing great?
Yeah, if you're doing great. Well, also you have to remember, like, I remember
giving a speech once and it's where it's like you get to a certain threshold, you create an inflection. Momentum gets you to a certain, you know, valuation and all these attributes. But it's kind of like winning a Super Bowl. The last year was great. Last four quarters were wonderful. It's like winning the Super Bowl. You got to come back next year and start your record, zero and zero again. And you got to remember that.
Actually, venture's like that. You know, I'm only as good as my last investment. I've had like 13 years or whatever of pretty damn good investments, but truthfully, I have to wake up every day and find some undiscovered founder that's going to change the world. And if I don't do that, it doesn't matter what I've done the last 13 years. And a company's kind of like that. The company can skate on autopilot for a while. Venture, you really can't ever skate.
I definitely saw this with Brian Chesky. He just felt like things were going great. And we just shipped amazing products and growth is up. And he's just always like pedal to the metal, no matter what. Just like, "Come on, when are we going to take a little break?" And it's interesting because when we did have little breaks here and there, morale actually went down because people are like, "What am I working on? I don't know. It's not that exciting."
Brian and I are usually in sync a lot. There's a really good interview where I interviewed him also at the same conference of how to hire, where he talks mostly about founder mode. But I generally subscribe to virtually all of Brian's views. He even taught me some of these things himself. But the more important point I think you identified, which is very subtle, is really talented people are like superb athletes. And when things are going well and people are really kind of coasting, they're not happy. They have an internal clock tempo. They just want to create things and create value and drive, drive, and, you know, the morale actually does go down for the best people in the world when people are skating.
Okay, so actually along those lines, there's a lot of anxiety in the job market about the future of careers. Am I going to have a job? Where are things going? And it just feels like people are working very, very hard. They're just putting in a lot of hours, especially the most AI-pilled people. It just feels like they're working harder than ever. I don't know if you saw this thing Tyler Cowen put out of just, work harder. Now is the time to work harder because AI is eating away at your value. You probably talk to a lot of people looking for career advice of just, this feels scary and I feel like I'm working too hard. What should I do? Do you have any advice for folks?
Well, AI is going to radically reorient, you know, lots of people's careers, including mine. So, I think that's actually true, and I think the way to thrive in a rapidly emerging technology world is to be intellectually curious. So, for example, you know, I'm a business person historically. I did actually code when I was really young, but basically professionally just a business person. What I've noticed in some of the best organizations is the number one consumer of tokens is the CMO.
CMO?
They are intellectually curious. And so, they're like, "Wow, there's all these cool things I can do now with my hands. Either I had to rely on other teams or never got access the way I wanted and blah blah blah, or a lab, and they just do it." This is actually true at Opendoor. It's true at another great company that I'm on the board of that's incredible. So, I think you can be intellectually curious and future-proof yourself more than just... Yes, you can work harder, and I'm a big subscriber to no days off and working all the time and all that stuff, but fundamentally the intellectual curiosity is how you learn new things and that is how you embrace the future.
So, and you said CMO is who's using the most?
CMO. In both of these two companies—
That's interesting.
—both massive, you know, awesome companies with lots of engineers. And I think that's very encouraging, you know, for the executive particularly. This is definitely the most exciting of the company.
And what are they building? Is it like landing pages and paid tests?
Well, sometimes it's more like what we would have thought of as analytics.
Mhm.
Sometimes it's actually campaigns. Actual campaigns. It's just that they don't need to rely upon deputies and deputies and deputies to get actual work product. And so they're just shipping things, or shipping, you know, drops of things, or giving the CEO insights into things themselves.
I want to get your take on the future of specifically the product triad. You work with a lot of product people, engineers, designers. Everyone's always wondering what the hell's going to happen to my career. Thoughts on just the future of those three specific roles?
Well, I listened to this podcast that Peter Fenton did and he convinced me that the idea of a PM makes no sense basically in the future. If you think about decomposing the logic, what does a PM usually do? They take these inputs from customers, they create this sequential road map that's well organized over the next year, blah blah blah blah blah. That world is ridiculous. Right now, the capabilities of foundation models or companies like Lambda School and, you know, things like that are just improving at such a rapid rate that it makes no sense to have a year-long road map. They're just incoherent. There are things that were impossible to do in November that are actually pretty easy to do right now in March.
And so I think you need to build an organization that's incredibly adept at... yeah, people say nimble and all this stuff, but incredibly adept at changing the road map almost on the fly. And I think intermediaries like conventional PMs don't make a lot of sense versus being prepared, intellectually embracing and exploiting, noticing. So someone needs to notice that, oh wow, we can actually do this, but then exploiting it this week is the future. A high-growth, stellar startup will notice that something's now possible this week and create new features and new value for customers next week.
That's such an interesting area of discussion. A lot of people are saying things about PMs. So let me try to defend that role, just to see if I can convince you otherwise. And by the way, I will say Marc Andreessen had this really good visual of just what's happening here: all three of those functions are like the standout, where they're all like, "I'm taking it. The future is my role. The future is design. Engineering is the future." So the way I see it is, as AI makes it easier to build and kind of eats the middle of the software development process, just anyone can build. You tell AI, here's what I want. The hard part, the gap, at least for now, is figuring out what to build and then aligning everyone around what to build.
I agree with that. I actually think whether you talk about someone who used to be a PM or someone who used to be a designer or called an engineer, the skill is more like being a CEO now. Which is, what are we building and why?
Exactly.
And to be a successful engineer, that trait's critical. To be a successful designer, because the tools and the ability to actually create the thing, an object, is going to be easier and easier. But the art is now what to build. You know, another competitor of mine, Alfred Lin at Sequoia, likes to talk about being a chef. When you're a chef at a prime restaurant, you're not actually cooking the dish. You're sampling your colleagues and editing their work a little bit, but fundamentally it's half a commercial role. Being a chef in a famous restaurant is: what's our value proposition? How do we differentiate ourselves? How do we brand ourselves? What's our segment? What's our pricing, etc.? What's our location, even? That's what makes a famous chef. It's not that they're literally cooking the dish all the time.
Okay. I 100% agree. Interestingly enough, PMs are often called mini CEOs, and I think the important thing is that it's not what do you call this person. I think the question is what skill will be most... Where are human brains still going to be necessary?
Business acumen. It's basically business acumen.
Right. Like what will help this company grow and succeed?
Exactly. I understand the company's business equation, where we're trying to go and what the inputs and outputs are, and I can, on my own, create things that move the needle or potentially move the needle. It's very exciting because you can actually drive impact much more easily now as an individual.
My conclusion based on what you just shared is, of the three roles, which role is best at that? Historically it'd be PMs, obviously. I think the important thing here is that great PMs or great engineers and designers will do well. But interestingly, what you're describing sounds like what a great PM would be really good at, or potentially good at.
If they were exceptional, I think that's right, but a lot of the best engineers I've worked with have commercial instincts. Max Levchin has his on steroids. Jeremy Stoppelman, who worked with me very closely at PayPal before he started Yelp and got promoted to be engineering director and vice president of PayPal, had commercial instincts back when he was an individual contributor. So, I think there are great engineers who are technically proficient that have always understood the business building.
Yeah. I think that's the ultimate unicorn: an engineer that is also very business-minded.
I think in the age of AI this will put an incredible premium on that, because they're not going to need a large team. You're not going to be marshaling the forces. Another example is a good friend of mine who is director of engineering at Ramp. He has a team of about 20 people. He personally ships as much code as he used to as an individual contributor while he's managing a team of 20. Because the tools are so great and he's become a leading pioneer in the usage of AI. And he's basically using AI as a second team. He's basically like, okay, you're the team manager, you do this, you do this, you do this, put this together, check this out, blah blah blah. And I think that is definitely the future.
I 100% agree. Engineers that are very good at that are just extra valuable. What's your take on the future of design, the value of design?
Well, you know, it's interesting. Design and code are merging, and it's not clear to me who triumphs. Is it that code becomes design, or design just translates automatically to code? I made some investments that bet on both in some ways, but I think they're merging in a way where they're not separate fiefdoms anymore.
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What I'm seeing is something really interesting happening with design. On the one hand, I just did some analysis on the job market for design, and it's basically plateaued in terms of the number of open design roles over the past 3 years. It just hasn't gone anywhere. It's flat. We had the head of Claude Design, Jenny Wen, on the podcast, and she had this insight that there's no time for the traditional design process. Engineers are shipping 17 things a day. There's no time to sit there and help mock and prototype and all these things.
Well, let me give you a couple concrete examples. So, at Shopify, they've been doing this for over 2 years now. So, this may seem normal, but they have not let PMs provide PowerPoint or Keynote presentations on product for 2 years. Every presentation on product has to be a workable demo. And they just expect the PMs to create the products. And the execs just refuse to look at static, you know, "we're going to have this feature." No, I want everything working. This is for 2 years. So, I think that, again, everything's just merging together.
That's so interesting. You would think, though, because there are so many products launching every single day, there are just endless things to pay attention to, you would think design would be a differentiator more and more.
I do agree with that, actually. I think the alpha is in design, just like in marketing. It's not the tools, it's not the channels, it's not the metrics. It's the storytelling. It's how do you cut through the clutter in the snappiest, most compelling possible way? There's kind of an NP-complete problem. There are so many different words you can use to express the same concept. But the person who can say, "This is the way to frame it," you know, the proverbial thousand songs in your pocket, is worth all the tools in the world.
Yeah, so that's the other part of my insight recently: as AI makes it easier to build, it's kind of expanding from the middle out. And what remains is figuring out what to build and iterating on the idea. And then at the other end of the spectrum is distribution. Getting anyone to pay any attention to what the heck you've done, because again, there's so much happening every single day.
Yeah, cutting through the clutter. I mean, that's always been critical. When people are pitching me as an investor, it's one of the things I'm dialing into immediately: how the hell is this going to cut through the clutter? It's one of the reasons why I don't like to take customer feedback into account, because by definition, when you put something in front of a customer, that's not a proxy for the real world. In the real world, you have to cut through the clutter while they're going to their Barry's Bootcamp, while they're doing their job, while they're raising their kids, etc., etc. While they're walking, while they're on the subway. An isolated fake experiment doesn't give you actionable insights and often is directionally wrong.
Interestingly, on that line, there are a few companies that are launching, Simily is one, that are simulating humans. I don't know if you heard about this company. They basically are building AI models of actual people, so that you can simulate your marketing launch and your product experience with people before you launch.
I don't know that I've seen that specific company. I have seen one or two sort of pitches. My general question as a refrain on those types of companies is, what are they training on? Because, again, if they're not
training on the right data, it's dangerous to say you're simulating humans.
Yeah. Yeah, that is the question. Oh man, what a weird world. Along these lines actually, I have this, I don't know if you call it a hot take, that AI content is going to surpass human content and that's just the future.
Oh, yeah. That's inevitable.
Well. Someone was, I was talking to someone and she was saying in like the Chinese TikTok app, it's just like all AI videos now and it's like very good. She like actually enjoys watching these videos and these stories.
I think there'll be like a binary sort, maybe. I could see products and content thriving that is clearly still human generated and that there's some desire for authenticity. Just like, for example, you know, this piece of art is a Warhol. Anybody could create this now, high fidelity, but there's still an appreciation for this was created by Andy Warhol. I think there's going to be a curated experience with a premium of provenance, you know, that you know is human created. And then there's just going to be a sort of rank filtering of what's the best content.
And whether it's AI generated or not, it's a little bit like the Ben Thompson Stratechery thing of curation, you know, versus algorithm. There's going to be two poles, and the curation may be for human created stuff, and then there's going to be the algorithm, which is just what's the best.
I 100% believe that. That makes so much sense. I was just thinking the other day, it's so interesting that AI is getting very good at video, like videos that are actually fun to watch that are AI generated. And then images are getting really good, but writing is still really bad that is AI generated. And it's ironic that it's called a large language model. It's all text trained, and that's the thing it's least good at, which is really weird.
Well, I think part of that is the economic decision of token rationing by the LLMs. Like they basically are, when you prompt, they're kind of trying to make their economics work within a bell curve distribution. And so if, for example, I've used prompt to know to write something that's very short, the quality is significantly better than if it's a page, paragraph, I mean page to chapter to book. I think it's token rationing versus actual quality.
You would think that, you know, like I don't know if it was Hemingway, of just like, "If I had more time, I would have made it shorter." Like it's more work than that.
But then you have, I think the writing right now, what works best is short, many short examples, and then you can, picking, editing,
Yeah.
re-prompting. It's a little bit like when I used to be a litigator 25 plus years ago. The hardest part of writing a brief, all the art, I mean all the magic, was the first paragraph. If I could write that first paragraph really well, the chance I would win the case and convince the judge would go through the roof.
So what I would actually do is I might have 3 weeks to write a brief. I might spend the first week or more walking around the office thinking through, how am I going to nail the first three sentences? Once I figured out how I wanted to frame those first three sentences, I could write 30 pages in like 2 days. But getting that right could take a week or two.
Sometimes it would occur to me in the shower, or it would literally, you know, shower or in the middle of a run. It's like, oh my god, I just still it. Then I could just sit down and power through the rest of the brief. And I think it's a little bit like that. The power through the rest of the brief works well. You still need the first three sentences.
Is there a story from that time in your life that would be interesting to share? I didn't even know about that.
So yeah, not everybody knows. You know, I spent the first four and a half years of my professional career as a law clerk and then a litigator. But it occasionally comes in handy, truthfully. Like sometimes trading off business risk against legal risk is a valuable thing to do. It's not accidental that many of my best investments are in financial services, in heavily regulated areas, because I think I can sort of do the legal risk assessment in my own brain. This was definitely true back in the day when I invested in YouTube. But I think most things that lawyers learn are very inconsistent with being an entrepreneur.
So, when you're being trained as a lawyer, you learn every exam in law school virtually is issue spotting. So, you get credit for identify, there's like five powers of, identify all the issues and then resolve them. So, you learn to identify everything that can go wrong. Moderately useful, but very not useful as an entrepreneur. I mean, sure, you can identify all the reasons a company could fail, not that difficult to do. The hard, you know, solving those. So, you know, not the best training.
And then you also measure your productivity by hours worked. You know, literally you bill per hour. It took me 2 years, and maybe a year and a half after converting to technology, to stop tracking all my time. I used to literally write down in my notebook, "Half hour this meeting, 20 minutes on this, you know, blah blah blah." Just couldn't get it out of my brain.
That is so funny. And David Sacks was a lawyer, too. It's like interesting how he
That's true. Peter was a lawyer. Peter was smart enough to quit after 5 months and 4 days, I think. David never practiced, so maybe even smarter than both of us.
Okay, I'm going to hit on some hot takes, contrarian takes that you have. You have a number of these. I heard you share in a podcast recently, they asked you, why don't you have as many contrarian takes these days? And you're like, "Well, they've just all been proven right."
And that's the problem, you know, if you have good ideas, eventually you want them to be adopted. It's a little bit like, you know, when you're an investor, you want to be contrarian. So, Airbnb, you start with a contrarian take, but eventually, if the company's going to succeed, it has to become consensus. Like everybody in the world has to use it and believe in it and trust it. So, you want that inflection. Like you don't want to just have contrarian takes and then nobody believe it. So, you do need a refresh rate. And then the question is, how do you find new ideas? But you want to actually exhaust them.
Okay, so one that I think people still would disagree with is that your advice is, unless you're building an enterprise company, you don't actually want to be talking to customers.
Yeah, I hate talking to customers. I refuse to allow colleagues of mine to talk to customers. You know, you can talk about the famous stuff, the Steve Jobs, you know, the faster horses and all this stuff. But I think more important is it's often directionally wrong. Customers don't know what they want, and they're very bad because it's a subconscious decision, especially for consumers. Like what I purchase, what I wear, is not a conscious decision. And when you're consciously trying to answer a subconscious decision, you actually give misleading information even when you're trying. You know, the proverbial example I like to use, but it's instructive, is ask anybody who drives a super fancy car, like a Porsche or a Lamborghini, why they bought the car. 99% of the time they will tell you every reason except the real reason. Once you realize that, you're like, I'm never asking customers anything.
Now, if it's hardcore enterprise, customer development does work because there is a book, there is a decision maker. And the decision maker is mostly making a utilitarian decision. And yes, there are political forces within the organization, and you may or may not be able to tap into those, but fundamentally, extracting that information is valuable. But a consumer, SMB, micro merchant product, unmitigated disaster.
And so the implication here is you need to rely on your instincts and gut and experience.
Yeah, I mean, humans are humans. I have this other line I like, which is everything important you need to learn about humans is written by Shakespeare. Just read Shakespeare. Like that's better than all the customer research.
Now, you are producing a movie, and ultimately this movie doesn't just need to be critically acclaimed. You have to sell tickets. So if you're not selling tickets, you have to question, okay, is the trailer wrong? Is our distribution, you know, where we're trying to meet people to let them know about the movie, is that wrong? Fortunately, unlike a movie, you can go back and say, have I cast this somewhat incorrectly? Is the script slightly off, you know, etc. But the goal is selling tickets, and that's what you want to optimize for. But if you don't sell tickets successfully, economically, efficiently, you definitely want to go back in a loop and try to reorient things so that you are selling tickets.
It's like CAC LTV kind of stuff, is what I'm hearing here. And so your insight here is just like, it's not only not going to help you, you're saying more so it's actually harmful.
It's harmful. And then people will say, yeah, like I've sat in so many meetings, and this is going to infuriate me, where people will be like, "I talked to eight customers, blah blah blah blah blah, and I know that this isn't statistically representative." But then they pontificate for an hour. And then they're like, "Oh, I know this is not, you know, blah blah blah." But once you hear this stuff, you can't take it out of your brain. And then every other subsequent meeting, this stuff is just locked in the customer's brain. So yes, in the enterprise, when you have, like, I work at a company in AI that has 30 must-win accounts. That's like the goal for the company over the next 2 years: make sure all 30, and if we're doing really well, we get all 30 using our product. Great. We actually can talk to all 30 customers, and we can actually meet the decision maker at all 30 customers, and we can influence the CEO, right? All 30 customers. That is a useful exercise. If you're targeting a billion people on the planet, you are not getting representative feedback.
Being a contrarian take, many people would not believe this is good advice. Do you have a story, maybe, or an example of just like, wow, someone talking to a customer, we were going in the wrong direction for a while?
Oh, all the time. They're called failed companies. You know, there's a reason why there's a Darwinistic efficiency to this, too, which is just like, hey, there are things you can, like, is it feasible to do XYZ? So, for instance, let's go like DoorDash. I don't think customers told us that we want a button on our phone to click to deliver food. But you could talk to restaurants and say, hey, would you put this placard here so that people walking into your store know in the future they can get delivery? Okay, yeah, maybe. Then could you run an experiment of how many deliveries per hour would you have to do to, you know, break even? And is there enough density, you know, within a... Like there are ways to improve the odds that you can make the business work.
But I don't think launching the company saying, hey, we found 10 people in Palo Alto, you know, do you want this button on your phone? So, you know, when Tony and Evan walked into my office originally, the epiphany I had was, well, they had a stat, which is 93% of restaurants in the United States don't deliver. I was like, okay. Seems like it should be a higher percentage than seven. Convinced.
And then when they were describing what they wanted to create, Andrew Mason of Groupon fame had famously said these phones, these devices, should have two buttons: I'm bored and I'm hungry. And I was like, oh my god, you're the I'm hungry button. And so it just clicked in my brain, and then it was like, "Okay, now we need to make it economically possible to scalably do this. Good luck, guys."
And this advice is not just consumer. You're also talking like DoorDash, which is like SMB-ish.
Yeah, like Square and things like that.
Square, yeah.
Yeah, Square is a good example. Like anything sub mid-market, I think it's directionally dangerous.
And the advice here is basically trust your insights. Like you need to have the insight yourself. You can't find it by
Typically the best companies,
Yeah.
there's foundational insight. And you know, people don't necessarily want to hear that, but there's logic you can acid test or pressure test. Like, you know, to some extent, when Brian first pitched me on Airbnb, there was some interesting evidence he already had that this was going to be successful. The number one that stuck with me at the time was he gave me the exact number of Craigslist listings that said, "I want to rent someone's bedroom." And it was actually a reasonable number. It was like 30 in the Bay Area. But given that you had to literally type it in and, you know, sort of have the epiphany yourself, I was like, "That's a lot, actually. That's probably a real market there." And as soon as he said that, I was already leaning in. And by the time he finished his 3-minute model, I knew this is the coolest thing ever. I need to invest.
Yeah, and I think Airbnb is a good example where he was solving his own problem. Saw an opportunity. Wasn't talking to people, "Hey, would you do this?" sort of thing.
And people would have said, "No." You know, if you sampled the wrong people, you definitely would have got feedback that was like, "No." Like very, very high risk. That's a good example where if you had sampled 10 random people, good chance that nine plus would say, "No, I wouldn't do that."
You know what's really interesting? I was just watching Taylor Swift's acceptance speech at this award show, iHeartMedia something or other, and she gave this really powerful speech that when she was starting out, she was just kind of at home working on songs, learning piano, just in a room on her own, and had thousands of hours to just iterate on, learn, and get better. Versus today, if you were to do this, you'd be posting it, sharing it, people giving you feedback constantly. And her advice is just, find ways to not expose yourself to people for a long time.
So, I have a couple of friends who are artists in the music industry. And I think what she's saying is one of the reasons why it's sometimes difficult for artists to recreate the success. Because the first success was not data driven, was not customer feedback driven. It was like, I'm creating this and it's resonating. Then, because they have an audience, someone, either they or their manager, whoever, the label, blah blah blah, wants them to get feedback. And it creates derivative, you know, sort of works, not strictly legally, but derivative works that are less inspired.
There's a podcast that Jack Conte did with my friend Alex from The Chainsmokers. He actually talks about this at some length, that they created this song that actually didn't resonate with their core, their normal audience, but actually resonated with a different audience, which is interesting. So, I think you can get trapped with success. It's a good illustration, actually.
There's also this concept of the ugly baby in creativity. I don't know if you read that book by Ed Catmull, about every idea at Pixar, like every great idea starts as this ugly baby that no one wants to help and pay attention to, and it's just like, get this out of here.
I should have started with that. I mean, that is actually the start of it. Like I use this prism as an investor, which is when I make a seed investment or series A investment, let's say, I want half of my friends who are VCs to laugh at me. Like literally laugh, because I know most of the people I compete with pretty
well. And so I'm running this algorithm through my brain: are these people going to laugh? If so, this is a great investment, potentially great investment, because it's an ugly baby. And ugly babies are the ones where there's real alpha.
That's so interesting you say that. I did some research recently on what are signs... We interviewed, me and Terrence Rohan, I don't know if you know him, a VC. We interviewed people that have joined early generational companies many times. They joined OpenAI early before anyone knew about it, Palantir really early, Stripe. And so we asked them what did you look for, and there's three patterns, and one of them was exactly that. The idea people laughed at them. They thought it was crazy. This is never going to work. Palantir, for example, OpenAI, for example.
Yeah, my parents used to laugh at almost all my jobs in tech. You know, they used to be very funny. They thought I was going to be homeless because most of them did not make sense to them.
That's classic parents. No idea what the hell people do in tech. Yeah.
They did appreciate Stripe, though. My mom always appreciated Stripe and was always trying to lobby me to invest, and I finally listened.
Nice. Good job, mom. She earned her keep. Okay, we just shifted perspective because Keith's iPad was dying. A classic, that's maybe the downside of the iPad.
The downside of the iPad is I use it too much.
It's like, that's product market fit. Okay, I want to actually follow up on this discussion we're having about just finding great companies. A lot of people are starting AI companies now. There's so many launching. As an investor, I'm just curious, what's the sign that this is a worthwhile idea, considering the endless number of startups launching, and maybe what are some flags that, okay, maybe don't work on that idea?
Well, the existential question everybody talks about these days is, are the foundation labs just going to be so proficient that there's no oxygen? Because if you're building a successful startup, you need to build for like 8 to 20 years into the future. Whether you use discount or capital analysis or some other prism, it doesn't matter. Ultimately, you have to build for something that's durable for decades. And the rate of progress by the foundational labs, and not just one, multiple of them, really does start creating questions about the sustainability of even companies that look like they're thriving in the short term. So, that's one question. The second question I'd ask, I've always asked this question for like 25 years, which is: what are the accumulating advantages of the startup? You do want to believe that over time you create an unfair advantage. And there are different species of accumulating advantages. The one that people immediately gravitate to, but it's only one illustration of a set of options, is network effects. But you want something that over time makes the business better and better and better, arguably easier and easier at some point.
Do you see those sorts of things at the beginning, like when you're seeing a seed stage startup?
Yeah, it's a great question because I think people can conflate two things. There's a difference between seeing it and understanding the potential. So, what I'm looking for when I meet a founder is: can they articulate where the accumulating advantages can be, in theory, conceptually? They don't have to have demonstrated it. Yes, there's an occasional example once every 5 years where early you can actually point your finger on it empirically, but that's way too strict as a bar for an early stage investor. But I personally want the founder to articulate to me where they can build accumulating advantages, and maybe even sequentially identify when they would start either taking advantage of them, leveraging them, or measuring them.
So, when you're evaluating startups these days, I know this is a very hard question to answer, but is there anything in particular you're looking for that you get really excited about?
I'm a founder-driven investor. So, the only thing I really care about is: does this founder have a non-zero chance of changing an industry or the world? And if they do, for a seed or series A investment, I'm in, period. Don't ask any of the other questions. That's all I need to identify.
Not every investor who's been successful has the same algorithm they're running. There are technology-driven investors, like I would say Marc Andreessen's probably someone like that. Vinod is a mix. He's both founder-driven and a technology-driven investor. There are investors who are sort of product/market-driven investors. My colleague David Weiden, I'd say, is that. I think Alfred Lin at Sequoia's mostly that. So, you can have different sort of approaches, mental models, paradigms. But for me, it's: is this founder extraordinary? Do I have reason to believe that this founder is the next Brian Chesky?
You mentioned that you're an investor in all these companies you listed that are doing incredibly well. And you're on the boards of a lot of really successful, incredibly good teams and companies. Is there just something they are doing, the way they operate, that is different from companies that are not as successful?
I think the subtle signal, let's say very early, is speed. And it's one of those things that's easy to say, but let me try to be more concrete. There's a tempo, an operating tempo, that a successful company develops very early in a company's trajectory and is incredibly impressive. I remember when Roelof Botha was on my board at Square, he led the series B. So, he joined our board. And 6 months in, so two board meetings in, he said to me, "I haven't seen this kind of tempo since our PayPal days." And he'd been a VC at that point for 9 years. And I was curious, so I said, "What are you noticing?" And he's like, "At board meeting X, you guys identify an opportunity or problem, and by the next board meeting, you've shipped solutions, addressed it, featured, constantly, consistently."
And I think that's right. So the time between the seed and series A of Faire was pretty tight. And I remember at the time, my chief of staff was Delyan Asparouhov. And Delyan said to me after the second Faire board meeting that he shadowed me at, "If there's one company in Silicon Valley that would cause me to leave being a VC, it'd be Faire." And I was like, "Interesting. Why?" He's like, "The pace of execution." And his answer was exactly the same as Roelof's. He's like, "There is something slightly off, and by the next board meeting, not only have they identified the root causes, but they've shipped and reacted and measured the impact of the solution." And that compounds. That speed really does compound.
So, that's just one trait, and you see it. It did lead me to, for example, preempt the series A of Ramp. So, I led the seed in like May-ish of 2019, and gave a term sheet to preempt the A in September. So, pretty quick. One of the two signals was how fast Ramp was able to be on the precipice of shipping the cards. I'd been working in financial services for a long time at that point, 19 years or so. And there's just a lot of moving pieces to ship a card. You need these program managers, you need the sponsor bank, and this and this and this. Usually takes 9 to 12 months, best case nine. Ramp was on the precipice in like 3 months, and I was like, "Oh my god, I've just never seen that velocity." That was one of two, maybe three inputs, and I was like, "Yes, makes sense to double down already, even if we hadn't shipped anything yet."
So, I think that's one. Critical density of talent. You see companies just creating an unfair advantage. The team was excellent you invested in was not. Wow, this team is getting better, deeper, better, etc. So, that's another signal. The third thing that I've noticed, though, is I think they have a different hiring philosophy ultimately. And maybe there's exceptions to this, but most of the companies I work with that are thriving have basically skipped hiring senior people, senior experienced people. Mostly internally grown talent. And I think that model has worked really well, especially true of Ramp. Definitely true of Trade Republic. It seems to be mostly a common ingredient, but there's probably exceptions.
Wow, that is an incredible answer, and three traits. Just to be clear what you're saying in that third piece: it's not hire fancy VPs from other successful companies, and instead develop people internally as a trait of—
Internally, and almost turned it into a competitive advantage, being your strategy. Like, we're just not even going to interview people. We're not going to try. We're just going to promote from within. And I think in some roles, it's not like you're hiring a GC typically right out of law school. Although we have done that once, and it worked out pretty well, believe it or not. But I wouldn't recommend that. Delyan wrote this blog post of lessons he learned from Keith, and one talks about hiring senior people, and the rough prism is: are you hiring for value creation or value preservation? If you're hiring for value preservation, typically some experience is useful. On the value creation side, it's probably not.
It's interesting how much of this comes back to just your initial point about hiring and the team being everything. So, number two was talent density, and three is helping people develop into the role versus finding someone. And then obviously, speed all trickles down from just who you're hiring.
Yeah, I mean, I've watched people use even chief of staff roles to grow talent. One company board meeting I was at this week that did just phenomenal on any metric. And the last two... his CMO, who's fantastic, is performing miraculously, was his last chief of staff, and his new head of product probably is his current chief of staff. And he just created this institution of a factory where you can absorb ambitious, talented people and, over one or two years, in osmosis, train them to be senior successful leaders.
When you talk about speed, I think about Ramp, for sure. When Jeff, their CPO, was on the podcast, our title was velocity, velocity, velocity. And I know they have days, if you go to days.ramp.com, it's the number of days since they launched, and they're just always looking at that number. How long is it there?
Oh yeah, every board meeting starts with that, the first slide. Day 1,184.
And they're like, what are they worth? Like a hundred billion? Not quite, but they're—
Probably not quite that much, but a reasonable fraction of that.
Okay, that was incredibly valuable. Okay, one last hot take that I know you have that I want to make sure we share is this idea of criticizing in public versus in private. Talk about that.
Yeah, so this is a lesson I actually absorbed from one of the great founders I work with. And like many great founders, he had his own management philosophy, and one of the most important tenets is: criticize people in public. And when you decompose the logic of it, it's so obviously true, but almost no one does this, and very few people talk about it even if they do it. So, if you think about it, when you give people negative feedback individually, you're optimizing for the atomic unit, not the system. The reason to do it in public is it's more important for all the colleagues to understand that there's an issue and it's being addressed. They usually have suspicions, let's say, or concerns. And if you channel the negative feedback to the individual, they don't know that you're addressing this and you're on top of it, you're aware, you're addressing it. Now, it's a collaborative... And then also it lets other people kind of raise their hand and say, "You know what? I can kind of help with that." Or, etc. And so, it becomes like a team-building exercise in some way, versus, "Oh, you have this deficiency, go fix it yourself." And then the rest of the company is nervous about why this problem is persisting.
When people hear this, it may feel aggressive to criticize everyone in public, call them out. Any advice for how do you not make it this, I don't know, scary environment? Or is that part of it?
Well, I think you want to win. And there's probably an art to this. I would say some of the best coaches in sports probably do a bit of both. There's things they will say in front of the team, and then there's things they'll probably channel to the individual player. So, it's probably a mix, to be very effective, too.
It feels like you're not a focus on psychological safety as a core tenet.
No. No, I don't believe in that at all. High-performance machines don't have psychological safety; they're about winning. For those who want to, a good book that solves central casting for you is read The Jordan Rules, or watch The Last Dance if you like, but fundamentally, read The Jordan Rules. If you want to be a Michael Jordan, you've got to act like Michael Jordan.
Do you feel like that's negatively correlated, this idea of psychological safety with success? There's just—
For the most part.
Yeah, interesting. I'm going to take us to failure corner. Okay, so failure corner. You talk about all these things you've done that went incredibly well, these companies you invested in, all these businesses you built, PayPal, all these things. People don't realize there's also a lot of failures along the way. Is there a story of a time you failed in your career or investing that might illuminate the downside, when things don't go great?
Well, I mentioned one, I alluded to one by accident. I talked about being acquired or whatever into Google and being stuck there. That was so clearly not successful. That was a slide. So, we did sell for like 187 million, but nowhere near the ambition. We didn't really achieve any goals product-wise or company-wise.
Investing teaches you mostly about failures. If you're a world-class investor in the early stages, a 30 to 40% hit rate is great and golden. By definition, that's like 60, 70% failing. It's a little bit like those old Nike commercials, where there's the Michael Jordan one where it's like, I've missed 109 game-winning shots in my career, or there's the tennis one, I think it's Federer, that's something like, I win 60% of my points. I mean, he's like the best tennis player ever, but he loses 40%. So, there's a lot of that in venture. You definitely have failures all day long. I think one of the arts is not getting too caught up in failure, actually. I actually gave this feedback in a board meeting recently, where someone well-meaning, one or two board members, were like, "Well, let's do retros on our failures." And the company's doing really well, so I was like, "You know what? Honestly, I'm not sure I would do this. I don't want to deter people from taking ambitious shots on goal. And if you overemphasize failures, and people think they're going to get criticized..." This is where the psychological safety maybe has some validity, which is: damn it, just be bold. Don't worry about the failing part, unless there's things you missed that could have been factored in. But you want people to take risk, and you want people to be excited about raising their hands for very difficult problems and challenges, because that's how you create value.
And so I was like, "No, let's really not do these retros. Let's just focus on winning."
Contrarian takes all around. Keith, is there anything else you wanted to share, anything else you want to leave listeners with before we get to our very exciting lightning round?
I'm excited for your lightning round. This is usually one of the best parts of your podcast.
Okay, first question. What are two or three books that you find yourself recommending most to other people?
So, the number one one is called The Upside of Stress by Kelly McGonigal, she's a professor at Stanford. And basically it argues in an incredibly compelling way that if you want to be happy, healthy, or wealthy, you need more stress in your life, not less. So, it's magic. The evidence she marshals is effectively uncriticable. At the outcome level, at the biochemical level, it is transformative to people to read this book, so I highly recommend it.
Favorite recent movie or TV show you've enjoyed?
TV, I actually just watched Nuremberg Trial. Highly recommend Nuremberg. There's a lot of lessons there that are applicable to the modern world. So, I won't spoil it all, but even I'm kind of a student of history and politics, and watching the movie, I probably learned five or 10 things that I knew before. So, highly and it's I mean, obviously not an exciting thrilling movie, but it's an extremely well-produced movie and incredibly useful to understand, you know, some of the tragedies of history and how to prevent them in the future.
Where do you find this? Is that one of the streaming services?
It's either on Netflix or iTunes or both.
Sweet. Okay. Is there a product that you've recently discovered that you really love?
Rarely. You know, I do find products that I'm addicted to like, you know, I've got this crusade about Eight Sleep, which is another one of my convictions is, you know, you must sleep eight hours a day, you must prioritize sleep even when you're very busy. I am an investor and somewhat biased in Eight Sleep, but it transforms people's lives. So, I'm still addicted to that one. I don't know if there's like a new product that, you know, I've been fanatically addicted to recently.
Eight Sleep chance. Do you have a life motto that you find yourself coming back to in work or in life?
No days off. Hashtag no days off. I don't believe in taking days off for workouts. I don't believe in taking days off for work, period. The derivation for those who are interested is when Bill Belichick won the Super Bowl for like whatever billionth time with the Patriots, it's back-to-back Super Bowl wins. I think he started the championship celebration parade with this chant of no days off. So, that's kind of our mantra.
And when you say no days off, are you saying like work every day? Like, you know, work the weekend sort of thing or what do you
That too, but like So, let's talk about the workout side. I believe I've missed seven days in seven years of working out. And it still kills me like half of those I still am annoyed that I missed. Like, I'm still like, "Damn it, really had reoriented my schedule. I should have been able to hit at least four of those." And I measure it and I post it at the end of every year. Last year I missed none, so I was very happy, but I don't believe in excuses, basically. No days off is a proxy for I don't believe in excuses.
And do you work out every day? Is that the rule?
I mean, literally, yeah, there's only 7 days in the last 7 years I haven't worked out. That includes all kinds of illness, sickness, travel, international, time zone travel, weddings. There's like no excuses.
Like actually every day. All right.
More than once, typically more than once a day, but
And you told me before we started recording you had a Barry's class this morning, you have another one later today.
I do. And a lift.
Okay, final question. So, you were famously part of the PayPal Mafia. I'm curious if there was someone there that over-performed. Someone that you worked with that you never thought would be that good.
Honestly, no. A lot of investing in, you know, most of the derivative companies and stuff, and so I think I had a good spidey sense of which people, you know, had at least founder-level ambition, and could potentially build something. Sorry, I wish I could give you a better answer.
They would have been mad at you anyway, so this is the safer answer.
Well, it depends. If they've been super successful, they'd be okay. Peter Thiel, no, just kidding.
Yeah, yeah, yeah, yeah. Elon Musk. Keith, thank you so much for doing this. I learned so much. This is going to help a lot of founders, a lot of people building stuff. Two final questions, where can folks find you online if they want to reach out, and how can listeners be useful to you?
Yeah, so @keith rabois.com, I tweet prolifically. You mentioned my pinned tweet, so that's probably the easiest way.
Sweet. Keith, thank you so much for being here.
Pleasure to be with you. Thanks for the invitation.
Thanks for accepting it. Bye, everyone.
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