Sequoia VC Reveals: The One Trait That Built Airbnb, DoorDash & Zappos
What this covers
Crucible moments make companies. Sequoia’s Alfred Lin on how Airbnb, DoorDash, and Zappos won when it mattered most.
In this conversation: * infinite games, first-order issues, and the daily inputs that compound into edge * zappos from zero sales after 9/11 to $1.6B: cash discipline, flow over batching, and world-class service * the counterintuitive truth about returns: your best customers might return the most—and why that’s good * airbnb’s trust problem: removing friction with Instant Book and how “fringe” becomes mainstream * doordash’s suburban wedge: be different (and right), density where others don’t look, and sequencing expansion * hiring for slope, not intercept: potential over pedigree, and how to reduce regrettable turnover * force vs. obstacle removal: when to push, when to redesign the system, and how boards actually help * compounding advantage: CAC paid back on day one, repeat-first growth, and free cash flow equals freedom
what you’ll learn * a first-order issue checklist to find root causes fast * the “slope, not intercept” hiring screen that predicts who scales * how to turn high returns into higher LTV (without killing margin) * a playbook to remove marketplace friction (trust, time, and instant confirmation) * a wedge strategy you can copy: start where value is highest and density is hidden
About Alfred Alfred Lin is a partner at Sequoia Capital and former COO/CFO/Chairman of Zappos. He’s backed companies including Airbnb and DoorDash, and is known for helping founders navigate high‑stakes “crucible moments” with discipline, focus, and compounding logic.
Timestamps: 00:00 Introduction 01:07 From Taiwan to entrepreneur 04:08 Infinite games and life philosophy 10:00 Inputs vs. outputs: daily priorities 11:43 First‑order issues: solving root causes 16:33 LinkExchange to Zappos 41:48 9/11 crisis and zero sales 42:37 Creative financing and running breakeven 46:40 Customer service and high return rates 51:18 Zappos culture and growth 01:08:08 Crucible moments and first principles 01:12:04 Navigating the pandemic 01:25:24 Company values that endure 01:30:58 Investing in changing markets 01:35:24 The AI revolution’s impact 01:59:43 Standardization vs. customization 02:02:31 Working backwards vs. forwards 02:08:40 Process as success
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Alfred Lin argues that sustainable business success comes from disciplined execution of first-principles thinking, compound growth, and maintaining alignment between founder values and organizational culture, rather than from seeking dramatic breakthroughs or external validation.
- 1% daily compounding yields 37x returns—larger than seeking 10x ideas—and is achievable through consistent process focus
- Founder values must be embedded in company culture and decision-making frameworks, especially during crucible moments when normal playbooks fail
- Type 1 (irreversible) vs Type 2 (reversible) decisions require different decision speeds; process quality matters more than outcome timing
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At Link Exchange, the company hired conventionally qualified people (those with the right resume for the role) but they did not fit the company's values or operating model, and this mismatch between talent and culture meant that when the company was sold to Microsoft, Tony Shay realized the company he built was no longer the company he wanted to work at, which motivated the intense culture-first hiring at Zappos.
“at link exchange where we didn't Define the values of the company we started hiring people that were conventionally right for the positions in the job and one day he woke up and realized the company that he had founded and built was no longer the company he wanted to work at”
Company velocity depends on two dimensions—speed (how fast you're going) and direction (where you're going)—and a company's velocity doesn't increase unless you keep pushing; the best companies maintain this push continuously, otherwise they slow down and decelerate.
“you use the word velocity velocity as opposed to speed because speed is just how fast you're going but velocity velocity also has Direction and I think the combination of two is quite important but the whole speed of a company generally doesn't get any faster unless you're pushing and the best companies they keep pushing and otherwise you're just going to go slower and slower and slower”
The first-order issue is the root cause of a problem that, when solved, tends to solve other downstream issues, and the key is identifying the first-order issue rather than treating symptoms; at Zappos, a slow website's first-order issue was not picture quantity or search result length but the need to cache search results and develop technology solutions.
“if I get this problem it I have a problem on my hands if I get to the the first order issue and get to the root cause of that usually that helps solve that problem and there are other issues that are not first order”
An infinite game (per James Carse, cited implicitly) is one without a finish line, where the goal is not victory but continued play and enduring impact; this contrasts with finite games (chess) where victory is the goal, and recognizing which game you're in fundamentally changes how you should operate.
“it's the whole concept of having an infinite game and thinking through not some thing some Finish Line some goal but just just think about what you want your enduring impact to be and what do you want to do and what do you want to accomplish and when the world doesn't give you a finished line we all have the same 24 hours in a day what do you want to decide to accomplish in that 24 hours we have an unknown number of years on this planet what do you want to get accomplished that sort of shaped the way I sort of started thinking about the world”
Predicting the future is difficult because the world is non-stationary; better than prediction is building a company machine that can sense opportunities and pounce when conditions align; this requires both forward planning (scenario thinking) and opportunistic response.
“I think the consensus would tell you that it's very very hard to predict the future and you're un your ability to predict the future is uneven because in the world that you know you may be able to be very good at predicting the future but the world is not stationary and the world changes and in this new world trying to predict the future when you don't have many facts or many patterns that you can go against uh it's much better to have machine that knows when to pounds than to try to predict what's going to happen”
Zappos made profitability on the first order a constraint by requiring that customer acquisition costs (CAC) had to be paid back within the first order; this forced them to develop alternative growth channels like word-of-mouth, repeat customers, and customer service excellence rather than relying on marketing budget.
“you can build a company by having CAC be profitable on the first order by being focused on customer service and not focused on marketing”
Zappos achieved remarkably fast shipping (next-day delivery) not through expensive logistics innovation but by working closely with UPS, FedEx, and USPS to negotiate favorable shipping rates and then integrating reverse logistics (returns) as part of the customer experience, making returns frictionless rather than punitive.
“we decided to work very very closely with UPS in particular and then FedEx and USPS to figure out how to get um the shipping rat as low as possible we started shipping so that it it was you know 5 to 7 Days um ground shipping to eventually overnight shipping so that the customer got it the next day we figured out logistics uh reverse Logistics so we bring the shoe to your home um we heard lots of reasons why people didn't uh want to order shoes on the internet we knew that before before we invested and we knew that we needed to bring this the store to your home have you try it on and then return the things that you did not uh that didn't work for you you did not want anymore”
Having well-understood company values makes sequencing decisions much easier during crises, because values become a filter for decisions; without clear values, decisions feel arbitrary and lack coherence, but with clear values, the sequence of decisions naturally follows from 'what matters most to us.'
“when you have these well understood values it makes the sequencing a lot easier and often people forget they write down their values for for a good reason because when you don't have a Playbook anymore all you have left is the essence of what the company is which is the values of the company often that's the essence of the founder the values of that founder and how they want to operate but you forget that because it's noisy lots of people lots of different parties um wanting your time and your attention”
If you take a dollar and compound it 1% every single day, you get $37 to $38 after one year, which is a 1-to-38 leap that is larger than and often more impactful than pursuing a single 10x idea, because founders obsess over seeking 10x ideas when consistent 1% daily improvement yields even greater returns.
“if you take a dollar and compound it 1% every single day you get this ridiculous result you get $37 $38 when I hear about making a Leap Forward 1 to 38 is a big leap and it's on a scale of figuring out what's a 10x idea the sequence of how you do something often determines whether remembered or not remembered”
Distribution flow and process design (organizing work into batches by stage rather than by task) is a first-order issue that outweighs localized optimization; solving for flow creates more value than optimizing picking, packing, or shipping independently.
“the flow was broken and so uh there was too many handoffs uh across all of these different discrete processes and so we had to sort of pop up a level and figure out what the flow of from when a customer order something when it gets through the Distribution Center how is going to be pck packed and uh packaged and shipped and when you look at that from a flow perspective you start thinking about new solutions that allowed there to be much better flow throughout the Distribution Center than been then to batch things for picking batch things for um packing P batch batch things for uh for shipping”
You can't just be better; you have to be different too, and you should not compete head-on with larger competitors because they have more money, more people, and more history—instead, compete where they are not competing, an approach Lin calls 'advantageous divergence' where you must both diverge from the crowd and be correct.
“you can't just be better you have to be different too you don't want to compete with someone bigger than you head on because they have more money they have more people they have more history you just want to compete with them where they're not competing”
Zappos discovered that its best customers (highest lifetime value) had the highest return rates, which at first seemed counterintuitive until analysis revealed that high-LTV customers understood how to use Zappos, ordered more, returned more items, but also kept more, indicating they were willing to try new things because the liberal return policy removed purchase risk.
“we did this analysis um and this is the type of analysis I really enjoy doing is like let's take our best customers and let's take our worst customers and look at their return rates and it turned out that our best customers at the highest ltvs return the most and I'm like that that is crazy how is that possible”
DoorDash started on college campuses rather than in cities, which initially caused Sequoia to pass on the seed round, but this was strategically correct because suburban and college-campus density actually exceeds urban density when examined properly (main streets, university areas), and the suburbs had lower competition than cities.
“door Dash sort of Fringe too and when mainstream did they start in like the suburbs or something go started more Fringe than even the suburbs it started on a on on a college campus and the reason uh we we pass on the seed round at Sequoya is were concerned that the this is like just something that college students did with their parents money um and then they started out um focusing on Stanford and then P out town they went to other suburbs”
Zappos' core values evolved from a nebulous cultural understanding to a defined set of 10 core values (led by 'deliver wow through service') developed by soliciting company-wide input on what values Zappos embodied and what employees valued, rather than top-down imposition.
“at some point Tony decided to just ask the company what do you think the values of zapus are what are your personal values and what do you not like about zapus and just parsing through that we got a lot of responses and in his book delivering happiness he talks about the fact that we started with 38 different values that you yeah these are all saus values and combined them shrunk them and we ended up with 10 core values”
Zappos operated with a holacracy-influenced management philosophy where the CEO (Tony Shay) viewed his role as creating a 'greenhouse' to help each employee grow as tall and strong as possible by allowing people to focus on their strengths and hiring others to cover their weaknesses.
“the management philosophy was um was different partly because we wanted to hire people that could just self-run and self- sustain and so so there was an element of allowing people to do what they love the most and it and pair them with other people who love other things and make it sort of homegrown I think Tony's perception of his job was that he was to create his his idea of creating a operating system for the company was to basically build a greenhouse was his analogy”
Growth rate should be constrained by the ability to maintain customer experience and internal culture; exceeding this limit results in loss of customers and culture degradation, though culture itself is not static and should evolve intentionally as the company matures over years.
“the easy if you're growing so fast and the customer experience starts to degrade you're hurting yourself and so yes you can grow so fast that it's just a complete mess you're losing customers because you're not servicing them correctly and at zos we were very mindful that whatever customer experience that we delivered it was the best customer experience that we can deliver at that growth rate”
Regrettable turnover (loss of high performers) is different from unregrettable turnover (loss of poor fits), and companies should manage these separately by understanding why they're losing good people and why they hired wrong fits in the first place, rather than simply managing to a single turnover metric.
“have you break the problem down that way you get finer reads on what the issue is what the turnover I really like thinking about it in terms of regrettable versus unregrettable turnover um a lot of people when they're hiring the sort of we need this job I want to know somebody who's done it at the next level cuz that's where we're growing to so they're trying to like anticipate where they're growing and one of the problems that I hear commonly is that people run into well that person might have done the 100 million to 300 million growth but they had a different team than we have they have a different system different resources how do you think about that when it comes to hiring my observation is that when you try to hire someone that is from a company that is one chapter or two chapters ahead”
DoorDash's pandemic response differed from Airbnb's: while Airbnb had to right-size, DoorDash proactively helped restaurants survive lockdowns by uploading menus to the platform and offering simple terms ('auto-accept deliveries or opt in'), not waiting for restaurants to negotiate deals; this helped DoorDash grow and also served a social purpose.
“he knew that restaurants wouldn't survive they have less than 30 days of cash and you know that's less than 30 days of cash when they actually are running at full speed so now they're they have less they have less cash the the restaurant is is uh shut down for a period of time people didn't know whether they can order fol and and would be okay as soon as we figured out that the restaurant shouldn't be shut down and the restaurants can remain opened for delivery and take out he went to full force and making sure that the business could help help Merchants bridge the gap”
Sequencing (the order of decisions and actions) is as important as the decisions themselves; in Airbnb's pandemic response, Brian Chesky sequenced layoffs last rather than first because values-aligned leadership meant protecting employees until all other options were exhausted.
“Tony said that it's about many good decisions about sequencing we all know what we need to do do but sequencing it right is is actually what matters um and the sequence of how you do something often determines whether you're remembered or not remembered in in the example that we talked about for Airbnb there's a sequence of like what is easiest what is the what is the values that I have for the company and let's go through the sequence that most matches the values so Brian want to take care of the employees the most and so the layoff was the last thing that he did”
Foundation models for AI are becoming so good that certain tasks will be automated, but the bigger opportunity is to reimagine customer experiences (like how the internet reimagined travel booking and search), not just to automate existing workflows.
“in the next year these Foundation models are getting so good that you can see certain things being automated that we used to do that we're not going to do as much but I think you know the next step after that is if you think about lots of people talk about customer service and how we can automate some of the customer service emails or calls or and things like that okay let's say we do that what's next well then you should reimagine the customer experience and so AI will help us automate some of these things and there's be massive of cost savings but AI should also allow us to reinvent the customer experience”
When evaluating AI startups, Sequoia looks to avoid companies that are just wrappers over OpenAI/GPT, roadkill that will be crushed by platform companies like OpenAI/Google/Meta, companies that look good (high usage) but have poor unit economics or high churn, and companies that sound interesting but aren't real businesses.
“I think we're trying to make sure that something persists and what if it persists it has its unique distribution it's embedded into your workflow um it has true Roi from a long period of time and it changes the The Experience um other things i' you know I'd say we try to avoid is um things that are roadkill along the way of a company like open AI or Google or Amazon or meta so small refinements into what the model doesn't do well today that's just going to be real kill along the way and then um I think we're trying to avoid things that are that sound good but they're not good businesses you know back to you know 1999 there were a lot of things that had lots of usage that not had no revenue and so right now there's there's a different example where lots of there's a lot of test Revenue but the turn is very high because people don't stick”
During DoorDash's founding period, it would have been misguided to hire someone who had led a company from $100M to $300M in revenue, assuming they could immediately apply that playbook, because they may have had different teams, systems, and resources that don't transfer to a startup context.
“on this on your particular point about the system I do think that if you hire people who are 10 chapters ahead and they have a whole system in place even even though they took it from 100 to 300 in a product division inside of a large large company they probably had a lot of guardrails that allowed them to not make a bunch of mistakes and so you have to dissect whether that operating system works the same way as your operating system most startups don't have an operating system so the thing that you have to sort of assess is how well can this person operate when it's just more nebulous it's just less clear”
Bureaucratic entropy (accumulating process, slowing decision velocity) is a natural consequence of organizational growth; it arises when leaders prioritize 'having a good process' over making fast, reasoned decisions, and can be diagnosed by observing whether decisions are made faster/slower than a baseline snapshot.
“when you you know the reason I always take a snapshot of when I when I go into a company for the first time to see how fast they're moving and then I tell them you PL today is a great day this hopefully you will move faster than today and I hold that to as AAR and if you don't have that mentality it will SL start to slow down um and so what what's the settlement like the process becomes instead of making Fast good fast decisions the the thing that people value is having a good process that slows you down to make sure you have the right decision”
Airbnb during the COVID-19 pandemic lost 80% of revenue as cross-border travel ceased, but management recognized this as a crucible moment requiring reimagination rather than mere cost-cutting; by establishing principles (focus on long-term survival), mapping the problem (both guests and hosts wanted refunds), raising capital ($4 billion) to cover both sides, and identifying new demand (local/domestic travel), Airbnb emerged stronger.
“you know when the pandemic had uh you can decide to do a variety of things and you know there there's all these pressures there's the investors who wants you to raise enough Capital so that you can you you you can go through and weather the storm there are employees that want to know that they're going to be employed there are hosts that want to uh know that uh even though guests can't travel that they have a non-refundable cancellation policy they're going to get the money you have guests who want to uh figure out how to get their money back because they're not traveling you have a business that went from a business that was growing uh 20 30 40% on a year to a business that declines and you lose 80% of your Revenue”
In 2021, valuations reached irrational levels, but Sequoia continued investing because: (1) LPs expect returns in good and bad times, (2) the texture of company quality is lost if you stop meeting companies, (3) market-wide hot periods often coincide with genuine technological breakthroughs (internet, cloud, mobile, AI), so missing the period means missing the winners.
“we can make those assessments but the hard part is the environment is also different right so 2021 valuations were nutty was it the issue of making those investment decisions over Zoom or was it the environment that drove valuations higher so therefore the returns are going to be more difficult more challenged when valuations are higher why do you play When the valuations are higher when when sort of like the this the game is loaded against you in a way like why choose to keep playing why not back away and then come back when it when you the odds are in your favor well historically valuations have gone up but if they keep going up then you you how does that work like I think rlps pay us to make money during good times and bad times and and here's the thing that is most interesting to me um you can decide to shut down but then you won't get the texture of those companies being developed and sometimes it's you got to keep meeting companies right like so you don't shut things down”
Nine-year-olds in college (Lin's son) showing early patterns of thinking they're smarter than everyone else and being cynical can be reframed through a simple conversation about attitude: a positive attitude makes the world look better; a negative attitude creates a self-fulfilling prophecy of a worse world; 'yes and' thinking (seeking options) is more generative than 'no but' thinking.
“my son a few days ago was being um quite negative about his school and you know he's start he's 13 he's going to be 14 this year he's starting to be like me when I was younger and think that he's smarter than the whole rest of the world and he said hey attakus do you want to be do you want to have negative attitude because you'll spin into this negative spiral um and by the way if you have a negative attitude the world just looks worse when you have a positive attitude the world just looks better and we played this let's use yes and for a bunch of things and let's create options and then you're going through the no butt situation and it doesn't work so let's try to just change your attitude about some of these things and I I thought that was quite an interesting conversation where just by simply changing the framework he became much more positive”
Success is the process of living according to your values and priorities every day, not the destination or outcome; if you have a good process aligned with your values, you're already successful regardless of external validation or results.
“the the success is just the process and having a good process because if you live the if you have a process that consistent to who you are and your values and you live that every single day and you get up every day and follow follow through on that process you're already successful um you know lots of people talk about success is not the destination it's the journey I think it's just the process before the journey”
Great companies were founded during the 1999 dot-com bubble (Google, Salesforce, PayPal, Zappos, OpenTable) at reasonable valuations relative to long-term value; paying market prices during a hot market for good companies is often better than waiting for lower valuations when those companies may no longer be available or not raising at that moment.
“in 1999 which was one of the if you go back in history and look at Megatron in in investing you know I'm 52 years old right now when I was in junior high school one of the things I did as a business was to build PCS clone PCS because the IBM PC XT at they were really expensive and and so there is one that was one Mega Megatron which is the PC Revolution then in then there was the internet Revolution and then more recently the Cloud Revolution the mobile Revolution some right now we're in the AI Revolution and the internet Revolution when I first started working professionally after college was Ed link exchange and then we started investing in 1999 uh that's when vent frog started and if you decided not to invest in that time you would have missed out on Google Salesforce PayPal zapo open table there are a lot of great companies that were still founded during that time and paying market prices for those Investments would have been just fine and you can better than just fine would have been better than just fine”
Real businesses must have unit economics that work, where each transaction or unit is profitable or moves toward profitability, rather than relying on continuous capital raises or betting on future scale to fix the business model.
“I think building a real business is really important um many of the companies that were founded in 1999 in 1998 99 2000 they were not real businesses they had lots of eyeballs they had lots of users um but that's not really enough and at Sequoia we often talk about the fact that we own shares in a company we don't know shares in the founder we don't own shares in the product we don't own shares in their Market strategy we own shares in the company and that company needs to have a business”
The internet analogy shows how platforms enable new experiences: previously you had to call a travel agent, then you could search travel options yourself, which changed the entire experience of travel planning by giving control and imagination back to the traveler.
“you could in the internet happen we could book um things we can book travel on the internet we can have to call a travel agent it change the experience we could search that changed the experience it broadened you know I had to imagine where I wanted to go and call someone to get me a ticket or to get until now I can search so my my imagination could be broadened and that just changed my my experience of of travel”
If you're afraid of incumbent tech companies' advantages (scale, capital, talent), you should 'punch out'—but history shows that Microsoft, Google, and Apple each had periods of losing to newer competitors despite their advantages; the winner was determined by internal management issues and regulatory constraints, not raw capability.
“to the honest I don't know but I'll tell you this in the history of Technology investing that I've been involved with if you're afraid of the incumbents you should just punch out but in 1999 you could have been afraid for Microsoft because they have lots of money and lots of servers and yet they didn't win search someone else won won't search Microsoft won the browser War for a hot sucket it was NE ncape against uh Internet Explorer I don't know many people use Internet Explorer today most people I know use Chrome so this is not a static situation I think you just have to sort of have an open mind on why you will win um and often the reason why large companies don't win is because they have their own internal issues that slowed them down so Microsoft during the internet it was it was the it was the antitrust situation and that slowed them down they could no longer bundle IE into into the operating system”
Great companies compound at very high rates in their core business for long periods of time (Google in search, Amazon in e-commerce), pursuing adjacent category expansion within the same operational model; pursuing new business lines far from core competencies creates strategic diffusion.
“a number of places if you just look at Great companies they compound at a very high rate for a long period of time in their Core Business Google for a long period of time was searched Amazon for a long period of time was e-commerce and there's a difference I think there's a difference between act two and category expansion so in Amazon they went from books to music to electronics to a whole bunch of they just went category by category but it was the same real like Core Business which is pro getting product to the Distribution Center pick pack and ship”
Crisis moments differentiate founders: some see crises as opportunities, others as pure existential threats; founders who stay calm, look around 360° to understand the full landscape, and then imagine a solution tend to emerge stronger; those who panic or get paralyzed by competing stakeholder demands rarely do.
“I I think we were you know I hate to say this and it's maybe TR but going through the pandemic we all came out stronger it was a shared experience sometimes when you go through crucial moments and crises you don't have the shared experience but I to answer your question more uh more succinctly I think the there are people who knew that the crisis uh was an opportunity and then there are those who just thought of it as a crisis and I think it was Andy Grove that says that you know good companies are get better and they're defined by a crisis where where as you know there are a lot of companies that are destroyed by a crisis”
Founders like Brian Chesky (Airbnb) and Tony Shu (DoorDash) maintain momentum by continually imagining the next transformation or product innovation for customers rather than being satisfied with current success, which is a core driver of continued competitive advantage.
“Brian chesky thinks about what's the next thing what's the transformation that we're going to create what is the next thing for the customer experience that's going to be great Tony Shu thinks about the next product that to to power the the local economies what's the next set of people that we're going to help um and I think you know if you sort of go back in the history of any business you notice that customers are just enormously impatient they're enormously unsatisfied everything that becomes that is new and novel becomes standard and basa had this line about how customers are just always always dissatisfied”
Some problems are better solved through sequential (serial) thinking where dependencies matter, while others benefit from parallel solutions where independent problems are solved separately and combined; most people are trained for serial thinking, but managing teams requires breaking problems into parallel workstreams.
“I think most people are trained to do things in serial they they take a problem they break it down into pieces and they do one piece at a time step number one solve the problem number one solve problem number two because we need the solution to problem number one to feed in problem number two and they eventually uh go down the path and a lot of like if you're an individual contributor you just you write code you just keep writing the code and you finish the code and you submit it um but if you're managing a team you need to break down this piece of software into components so that you can give it to your team members you have all 10 of them working on it”
The risk of focusing on two problems simultaneously (e.g., restaurants AND groceries) is diluting focus and resources; startups benefit from singular focus on a narrowly-defined problem until that problem is solved at scale and pull signals emerge for the next adjacent category.
“is the biggest risk there that you try to tackle two problems at once like they I'm assuming they knew they wanted to get into groceries so part of the risk at the start is like if we're focusing on restaurants and groceries all the time we're spending on one of those two things and not all of it but a lot of it's coming at the expense of the other or do you see that as as no it's not it's a very sharp Insight that you have I think the one the one thing that you'll find is that there are lots of examples that um that I could use to support your conclusion there because before door Dash um happened there are plenty of other Ser Solutions and most notably there was GrubHub”
Type 1 decisions (irreversible) require running out the clock, gathering all available information, and making high-confidence decisions because you cannot go back; Type 2 decisions (reversible) should be made quickly and iteratively because the cost of being wrong is low.
“I think the one that I learned from Amazon is whether this is a type one or type two decision and you know if it's a type one decision I've learned from Brian chesky to run out the clock because you can't go back as a type two decision and you you know you just move the move forward make a call and of course CFT along the way type one being irreversible and type yeah so if it's irreversible run out the clock meaning like get all the information make sure that that's a high confidence decision type two if you can always change it make a fast decision and keep iterating”
Act Two (fundamental business model shift) is different from category expansion (same business model applied to new categories); Amazon's AWS was an Act Two (new business, different margins, different dynamics) but it was still framed as 'building distribution centers for bits instead of physical goods,' showing how founders who survive long-term integrate new ventures with core insights.
“eventually all companies need an act two AWS was an act two that was very different than the than the e-commerce business but even the way that Amazon thought about the their web services business is like well we're very good at building distribution centers here yeah originally the Distribution Center that we built was for physical things and here we're building a distribution center for electronic things for bits like even the way to sort of think about it was quite interesting”
You should hire for slope (potential and learning rate) rather than intercept (current experience level), because startups solve novel problems that require learning and adaptation rather than applying playbooks from previous roles, and high-slope, low-intercept hires often outperform experienced hires who grow slower.
“we have this concept that a lot of people have it's in sequa we hire for slope not intercept so experience obviously matters but if you just hire for the experience and their slope is not fast that's going to become a problem at some point and so we really really ask Founders to think about what is the person's potential what is their slope um and we much rather bet on someone with high high slope and low intercept”
GrubHub failed to capture the full restaurant delivery market because it only worked with restaurants that already had their own delivery infrastructure; DoorDash identified and fixed this first-order problem by building a delivery network that allowed any restaurant (with or without existing delivery) to participate, thereby expanding the market.
“before door Dash um happened there are plenty of other Ser Solutions and most notably there was GrubHub mhm that was just the website and then they passed the order to the restaurant and the restaurant delivered and Tony's observation was that's not deep enough of a solution and so why was it not deep enough well there are a lot of restaurants out there that don't have their own delivery staff yeah and why don't we just you're creating problems for them in a way exactly and so the only restaurants that would be on grubhub's website were all the companies that already had delivery staff available so what door Dash did was to expand the market and by expanding the market they were very focused on that problem”
Drivers were more abundant than Sequoia initially expected for DoorDash because: (1) some people prefer delivery work to rideshare (lower social interaction), and (2) people with adequate cars for delivery but not for passenger safety standards will accept delivery work, so the labor market for delivery is distinct from the labor market for rideshare.
“the one thing that um you know if you sort of beli that it was more profitable to to transport humans than deliver food every then you would come to the conclusion that Uber and Lyft would get all the drivers and door Dash would not get any of their drivers and it turned out that well a there's some people who would prefer to deliver food or package over delivering people they didn't want to have to have social interactions and then they're seted people with perfectly fine cars but they're not perfectly fine cars to to transport humans and so um early on we thought it was going to be a problem but it was less of a problem than we we had originally imagined”
When scaling to new merchant categories (e.g., Zappos adding clothing or DoorDash adding groceries), the accordion principle applies: start rigid on standardization at the beginning (pull accordion), then stretch to accommodate merchant variations (accordion expands), then slowly standardize again as scale and network effects provide advantages to merchant buy-in; trying to over-standardize at the start prevents acquiring the first customers.
“I think it's a I I use I use the accordion example um often which is you know you you you pull the accordion too far and then you have to push it back in and you know at some level if you are super rigid you're not going to win your first few customers so at the very beginning the accordion is completely folded and you you you do pull the accordion and you allow things that you may not have allowed you you may not want to allow in that very early days and it gets super far stretched and you're like oh shoot I need to standardize a bunch of things and then for you're not going to go back on these customers so you or or Merchants so you're going to go back you're going to go into the next inning with a lot more standardization”
Airbnb's early friction was due to lack of trust between hosts and guests; the company addressed this by requiring Facebook authentication to check identity, but even 24-72 hour verification delays were too slow, leading to the innovation of 'instant book' to remove friction and enable mainstream adoption.
“if you sort of take the definition of a Marketplace you have to complete the transaction and you just not only have to complete the transaction you have to remove as much friction as possible and so Airbnb in the early days had a calendar held the money paid out the money but there was this big friction big big friction and it was because there was not enough trust uh between the host and the guest”
Zappos had a liberal return policy (365 days) and other competitors copied it (30 days, then 90 days, then 365 days), not because returns were optimal, but because it was a competitive escalation strategy to signal commitment to customer experience and stake a claim in the market.
“I think we changed the whole industry and it originally was just a competitive response we had a liberal return policy in 30 days other people copy 30 days then it was 90 days other the people copy 90 days and then we made it 365 days and not everybody can copy that some did but by doing that it would put a stake in the ground that we want people to try the zapus experience and have a great experience”
External accountability from people slightly outside your immediate work environment is valuable because they ask naive questions that expose flaws in your thinking; if you can't explain something to an external person, their questioning may reveal deeper problems than you saw.
“I think it's valuable to have people who are slightly outside of where you work to keep you accountable it's like hey how's this how does this work just by simply asking questions you get into a situation where like wait I can't explain that question I can't answer that question suly I can't explain it maybe that person's question has more insight than I would have expected what are some of the lessons you learned from link exchange”
Many companies founded in 1998-2000 were not real businesses in that they had users and eyeballs but no path to profitability; real businesses must eventually generate free cash flow, and eyeballs alone do not constitute a business.
“many of the companies that were founded in 1999 in 1998 99 2000 they were not real businesses they had lots of eyeballs they had lots of users um but that's not really enough”
Open source and closed source will both play roles in AI, similar to the internet era; Google built a large business on open source (Linux and related tools) while also maintaining proprietary systems, and the same mixed model will likely emerge in AI.
“open source is a very very important aspect of um what has happened in technology and you have these religious fights between closed and open and you have religious fights between Apple and Microsoft you or or apple and IBM it's let's get let's go back to ant the world is built on Ant um and you know open source in the internet days there are lots of things that were built on open source and some of it was closed source and some of it is open source and I think the same will be true with with uh with um AI”
Nvidia evolved from a graphics company to the primary enabler of AI by championing parallel processing when CPUs were the standard; GPUs lost earlier competition due to Moore's Law limits on serial processing, but their parallel processing advantage became dominant in the age of deep learning.
“I think Nvidia is uh is a very great company for a variety reasons one of which is it went from a graphics Processing Company to being the way we power all of AI and they fought for so long about this idea of parallel processing where the CPU worked a certain way the G GPU worked a different way and the GPU is now shown to be more powerful after we sort of uh got to the edge of Mo's law the GPU is winning out because they can they can process things much more efficiently”
Markets are generally good at pushing innovation because capital flows to opportunities where investors see potential, creating competitive pressure; this market-driven push is often more effective than government policies at encouraging technology adoption and investment.
“the market is pretty good at pushing when they see opportunity you that more and more Capital goes into it more people go into school to you know in almost every single technology Revolution I've been part of there are too there are too few people who understand that technology so when when there was uh when it was the PC industry there are few people there are some people who understand rain FRS very few people understand PCS more and more people more and more investment went into PCS”
The best way to call out poor performance or misalignment is to be fact-based and provide specific examples of what is and is not working, rather than vague criticism, making the conversation easier and more actionable.
“the way I do it is try to be fact-based and um just give examples specifically of what has been working and what has not been working and I that tends to work pretty well”
Hiring slowly and thoroughly to understand cultural and values fit is more important than speed; when someone doesn't fit the operating values and mission, they are usually mercenary rather than missionary, and this misalignment persists regardless of skill.
“at Link exchange we hired back to like conventional and you know we we hire the conventional right person we were looking for a marketing person we're looking for a marketing person that marketed to small medium-sized businesses they understood the internet they they fit all the specs that you would have in a job description um but they didn't fit the way we operated they didn't fit the way we Val what we valued and you know it's easy to sort of limit that down to like they're just a a professional marketer and they're mercenary not a missionary”
By changing one's attitude or framework about a difficult situation from negative to positive, and using 'yes and' thinking to generate options rather than 'no but' thinking that closes options, you can transform your emotional state and problem-solving capacity.
“he said hey attakus do you want to be do you want to have negative attitude because you'll spin into this negative spiral um and by the way if you have a negative attitude the world just looks worse when you have a positive attitude the world just looks better and we played this let's use yes and for a bunch of things and let's create options and then you're going through the no butt situation and it doesn't work so let's try to just change your attitude about some of these things”
Google succeeded at search despite Microsoft and other incumbents having more money and resources because Google focused on algorithmic search (page rank) rather than directory-based search, and the incumbents were slow to recognize the shift because they had invested heavily in directory models.
“Google the longtail keywords more valuable than you know the head and most of advertising was broadcast advertising you start from the top and this is a bunch of like longtail keywords and they think a lot of great companies um whether it's intentional or not um try to do things very differently than what exists today Apple they weren't the first to many things they were you know they didn't make the first uh personal computer they just made the user their focus was always about the user experience”
Zappos' philosophy of staying ahead of complacency was encapsulated in 'you're only as good as your next investment' and the understanding that one bad customer experience (such as a wedding-day shoe failure) can ruin all the reputation built through years of good service.
“we talked a lot about um about how easy it is to ruin a good reputation you just with the next order if that's not good for a customer you have you built you built all this effort to build a good reputation with a customer and one bad order on an important order like their wedding day and you ruin that reputation”
Building an early-stage company remotely is very difficult because trust is built through persistent in-person interaction, and most communication is non-verbal (body language, reactions); while some work (memo-writing) is better done individually or remotely, culture building and team synchronization require in-person time.
“I think it's very very hard to build an early stage company remote and the reason I say that is unless you you've worked with each other before I I view I view there to be a well of trust that is created when you work together in this you know the reason why people who have worked together for a long period of time can like anticipate each other as movements and what they're going to do next is because they've been around each other for a long time and as you know that most of our communication is not verbal there's body language and how you sit how you react”
Being 'and' instead of 'or' means solving for multiple objectives simultaneously (e.g., fast shipping AND selection, not one or the other), and this is particularly important at scale; many companies fall into either-or thinking when the answer is to figure out how to do both.
“there are two things that zapo that I um I I pushed very hard and popularized one was the um was the power of and because I found too many people trying to figure out ways to do either or and uh wasn't like okay we're going to ship product more quickly but the website's going to be slower like those are you got to do both and if you if you think about the little things that we do at zos it was about just compounding 1% every single day”
Working backwards (from future vision to today) is valuable but incomplete without working forwards (from today through 1-3 years); if these don't align, you're likely not on the trajectory you think you are, and mapping the intermediate steps is necessary to identify what's missing.
“I've also seen lots of Founders struggle to take it from the future which they have this great vision of the world and really map it all the way back to today they map it somewhere five years out 10 years out but they can't map it today and I also tell Founders okay we that's the future that you're aiming for here the realities of today what does it look like one year ahead two years ahead three years ahead that's working forwards and if the two don't match it probably you're not on the same trajectory”
Zappos was founded when Nick Swimmer left a voicemail about starting an online shoe business because he couldn't find the right size, color, or style across physical stores; Tony Shay and Lin funded it for $500,000, recognizing that mail order was already 5% of shoe sales (a $2 billion market) and the internet would grow larger than mail order.
“zapas was this is this weird idea we I can't even believe uh we funded it because that this was a this is originally founded by Nick swimmer he had called and left a message message on on our answering machine this is how old and back we were going in 1999 and Tony and I were running a seed fund a venture fund uh an incubator called Venture frogs and uh Nick said hey I have this crazy idea I'm a Web Master at uh Auto byel which is an auto um website on the Web Master there I think it would be great to just um start something for shoes because I want to one store couldn't find the right size one to another store couldn't find the right color one to another store they didn't even have the style that I'm looking at”
Applying force to identify obstacles is as important as removing obstacles once identified; when you push against a problem and hit resistance, you discover the actual constraint, which then allows you to develop solutions to work around or solve that constraint.
“I think many times applying Force um is what what leaders try to do which is just apply a forcing function and make you make a choice and often I think removing obstacles are just as important as as applying the pressure to keep going on and on and on but often you know when you apply Force you realize where the obstacles are because you you butt against that obstacle and then you realize okay I keep buting and againsts this maybe I have to figure out a way around it”
Breaking large problems into smaller problems and solving them individually is effective for local optimization, but you must first ensure the problem is at the right altitude; global optimization requires popping up and understanding the full landscape before decomposing.
“so I think there is local optimization and Global optimization you're talking about that's a much better way to work it if you want to solve a global optimization problem you need to pop up and if you're trying to solve a local optimization problem you want to go down and um you so I think the problem first and foremost has to be at the right altitude and then you can break the problem down from there”
Decision quality at the moment of decision is assessed by how deeply you've researched and reasoned about the problem, not by the eventual outcome; looking backward to assess decisions (what went right, what went wrong) is rarely done by companies but should be a core part of strategic planning.
“you can't necessarily at the the moment in time um you can think of about things at the moment in time is how reasoned how reasoned how deep have you thought about the problem how much research have you done and you can sort of at least say well you researched the problem you understood it deeply and you picked a course and hopefully that's the right decision and in hindsight you can always look back and look at whether those decisions are right or wrong and I don't think enough companies look at that enough”
Free cash flow equals freedom because a real business eventually generates real free cash flow that allows you to not have to raise money, invest in new areas, pursue growth without quarterly pressure, and have the freedom to make strategic choices unconstrained by funding cycles.
“free cash flow equals Freedom eventually a real business generates real free cash flow you can't just be better you have to be different too you don't want to compete with someone bigger than you head on because they have more money they have more people they have more history”
The September 11th attacks caused Zappos' sales to drop to zero overnight; this crucible moment forced the company to return to first principles and rebuild around profitability rather than growth, which paradoxically enabled long-term success.
“the most important thing back then was because it was an e-commerce company and we were going from 1999 to 2000 it was growing from 2000 to 2001 I was like uhoh we have a situation and the day after 911 then the company had zero on sales zero you went from whatever it was which was small to zero and that was the first Crucible moment um using the term because sequa uses term cruci one what we're going to do about that so have shook the company and we basically went back to basics and we wanted to build a company that was profitable”
Apple was not first in personal computers, mobile phones, MP3 players, or many other categories, but succeeded by focusing relentlessly on user experience and design rather than technical specifications, which other companies competed on; being first is less important than being right.
“Apple they weren't the first to many things they were you know they didn't make the first uh personal computer they just made the user their focus was always about the user experience whether it was the computer the phone the watch everything they do is about having a great user experience that was not the conventional thing that people thought about it was about you know in the early days of the PC it was about processing speed and which processor was the fastest etc etc uh when the phone came out it was about the keyboard we don't use the keyboard anymore the Apple thing is fascinating”
While hybrid work has tradeoffs, it can work if systems are designed to support it; the key is being intentional about what gets done in-person versus remote, and recognizing that multinational corporations have always managed hybrid (offices in multiple locations connected by telecom), so it's not a new problem.
“I think it's best if you take a stance take a side hybrid I would cribble with the fact that hybrid doesn't work at all I I think you can be in person you can be a remote you can be hybrid you just need the systems around it to to make up for the fact that you're going to operate in this way every multinational corporation when they have multiple locations was doing some form of hybrid right”
Today there are probably too few people who really understand AI and its applications, but valuations for AI companies are high and many people are entering the field, which suggests the market is already responding; within a year or two, there will likely be an oversupply of GPU capacity and AI-built applications, but this is a natural market cycle where excess eventually becomes cheap and enables new use cases.
“the the main frame that happened in the internet most people didn't know how to build um a website more and more people learn how to program in HTML and Python and wrote and Linux and learn how to use Linux to build uh today and that happened with cloud and mobile look so today we have probably too few people who really really understand the technology and its application but you have so many people going into it today because they see the future is going to be powered by Ai and so wait a year or two I bet you there's plenty of push today there's that's why the valuations are high for AI companies um and wait a year or two there's going to be a lot of things that are going to be built in fact the hot take is that many things will be overbuilt so maybe we we're building too many gpus for a year or two years out maybe there are too many data centers that have gpus is a year or two years out and maybe those things will get cheap and when they get cheap we'll find new applications when it gets really really cheap that would be sort of the history of Market actually”
Policy should favor light-touch regulation of AI in early stages to allow experimentation and innovation, avoiding the regulatory overreach that could have slowed the internet; regulate applications and harms (similar to how cars are regulated for safety, not engines for raw power) rather than the underlying technology.
“I'm maybe overly optimistic about human nature and so I believe that you want to have as little uh regulation as possible in the early days let people experiment let people try things and is is it all going to be good no but if we had over regulated the internet it would not have grown to the scale that it is today”
Zappos was funded with approximately $10 million from Tony Shay's own investment and a small seed round, but generated $1.6 billion in sales by the time of its Amazon acquisition, primarily by focusing on profitable unit economics (customer acquisition cost paid back within the first order) rather than venture capital-fueled growth.
“most of the company was financed from a small seed round Tony invested $10 million of his own money but most of it was financed through being very creative figuring out how to get Merchants that we we we ordered from to give us credit and to increase the credit line we had a eventually got a a line of credit from Wells Fargo but the burned very little cash and for a company that went from zero when we sold the company it had $1.6 billion in sales”
The 'hugs of much success' (from Jim Collins' research) is the first warning sign of organizational decline; successful companies must actively work against complacency or they will inevitably decline, and this requires constant vigilance rather than assuming success is durable.
“if you read Jim Collins's book why the Mighty Fall or it's the first sign is the huus of much success us and we you know it's AOA we're just never complacent but you really work not to be complacent we actively work not to be complacent and almost every single company to make sure that you're not complacent successful companies just think that way”
Link Exchange was sold to Microsoft for $265 million when it had only $15 million in revenue, which clearly indicated a bubble; you could tell the market was irrational when the valuation multiple (about 17.7x) was so far from fundamentals that it didn't make sense even to contemporaries.
“and we sold that to Microsoft for $265 million and um that was quite the experience did you know at the time we were sort of in a bubble or how did you think about it back in the late 90s I mean we had a business we had $15 million in Revenue you can kind of tell that we're in a bubble when someone would be willing to buy a company that had $15 million in revenue for $265 million um but also you know it was the third largest acquisition at the time”
Companies tend to overestimate what happens in one year and underestimate what happens in ten years (attributed to Bill Gates), making it important to think beyond immediate trends and plan for longer-term trajectories that are harder to predict but more durable.
“it's funny because I think in the history of Technology changes it's and then bill I think Bill Gates said this it's easy see we we almost always uh overestimate what things are going to happen in a year and we underestimate what's happened in 10 years yes it's harder to imagine 10 years out but you know in the business I'm in at sequa we are paid to make investments and to hold them long term and we do have to sort of Imagine 10 years out”
Sequoia would be concerned about Nvidia if Jensen Huang (CEO) stepped down because the company has had only one leader throughout its cycle; succession risk at companies built around a visionary leader is real and unpredictable.
“I worry about um that they've only had one leader in their whole cycle I worry about what happens when Jensen decides not to uh be at the head of Nidia yeah that is the question I guess right I think that's the question a lot of people have Jensen's a remarkable sort of CEO”
Mountain climbing as an analogy for business: top-down planning involves plotting the path and alternative paths before climbing; executing is then following one foot in front of the other; if the path isn't working, you shift to an alternative pre-planned path rather than getting lost in the moment.
“if you're trying to climb a mountain and you know the top down problem is what's the path so even before you climb the mountain you're you're going to plot the path before you get onto the mountain but once you're on the mountain then you have a path you're just going one step in front of the other on that path and if you find that the path is not right hopefully you've had some backup paths and backup plans that you can go one foot in front of the other path a doesn't work well path B might be a little better because I plotted the alternative plot to path it to path B so that's an example of like planning top down on your path and your Alternatives and doing a bunch of scenario analysis and then when you're executing on a day-to-day period you just literally just go execute”
It's never worth fighting against technology progress; examples from history (printing press, plows, engines) show that attempts to over-regulate or control productivity-enhancing technologies have always failed and always been wrong—regulation should happen at the point of application (where consumer harm is possible) not at the research level.
“if you want to start applying regulation there's there's maybe a slightly different framework that I would use which is you want you know as an example with the combustion engine nobody regulated the engine we regulated what engines can go on the street what can go into a plane you regulated how is applied but in a lab and people were you know sort of doing research and trying to make the combustion engine even more powerful you being more fuel efficient you don't regulate that you regulate it when it gets in the hands of a consumer”
Large tech companies to watch in the AI era: Microsoft has stayed relevant through multiple transitions; Google faces regulatory headwinds; Apple has historically waited for customer demand, experience clarity, and then executed at scale in new categories; Nvidia dominates GPU supply but CEO succession is a long-term risk.
“if you want to use don't fight the tape when I when when I started my technology career Microsoft was the largest technology company and today they're the largest company and so they seem to have figured out through their ups and downs how to stay relevant and stay on top um I think Google Google's having some challenges with their own regulatory issues and Apple don't ever count Apple out because back to they weren't the first to come up with the PC they weren't first to come up with the mobile phone they weren't there's so many other mobile phones they just wait until they can create a great customer experience and then when they do they pounce”
Founder mode and manager mode are false dichotomies; great companies blend 'fire' (entrepreneurial spirit and creative compulsion) with 'ice' (disciplined facts, management rigor, and attention to detail); the best leaders develop both capacities.
“I have a concept of Fire and Ice the best companies are both this huge fire they have this entrepreneurial spirit and they run hot because the idea is so compelling and interesting but they also have this icy side it's just cold facts it's management it's about getting to the details and the best companies have both um and it it pains me to see that you have to choose one or the other because the best companies do have they they figure out how to make make sure that both are in this in the company”
Crucible moments are high-stakes, one-way-door Type One decisions that permanently alter company trajectory; they are defined by having all stakeholders with competing needs pulling in different directions, and they require principles-based reasoning rather than precedent-based decision-making.
“Crucible moments um is is the term we use at stop as ADD Sequoia for things that are basically very important type one decision and I've had to deal as an operator before Sequoia we didn't call them Crucible moments but I've gone through a fair share of Crucible moments you know link exchange do we want to do we want to sell the company to Microsoft at um tell me networks when we're burning $60 million a quarter how do we get through that and how do we pivot the company from a consumer business that wasn't working into an Enterprise business these are decisions that change the trajectory of a company”
A sixth-grade teacher (Mrs. Einstein) challenged the speaker's view that success means 'starting first and finishing first with the least amount of work possible' by asking 'what happens in life when there's no Finish Line,' introducing him to the concept of infinite games.
“she said to me that's a great answer for a sixth grader but what happens in life when there's no Finish Line what are you going to do then and that sort of put me back uh and I didn't quite understand it until maybe now that it's the whole concept of having an infinite game and thinking through not some thing some Finish Line some goal but just just think about what you want your enduring impact to be”
A lesson from land investor John Bragg: overpaying for an asset that is rarely available for sale (e.g., land) may still be worth it if the asset's strategic value justifies it; the payback period may extend from 10 to 12 years, but missing the asset entirely is worse than overpaying.
“John brag said this thing in in my recent interview with him that I I had never fully appreciated I don't think which was he had a reputation for overpaying for all of the land he was acquiring and I said why do you do that he's like well we're easy to deal with people want to deal with us and he's like these assets only go for sale once and he's like so maybe it takes 12 years instead of 10 to get our payback but it doesn't really matter because there's no opportunity 10 years from now to buy it again”
DoorDash's entry into grocery succeeded because they waited until multiple conditions aligned: the company had built the operational machine (logistics), customers were ready (e.g., Instacart demand), the market was ready (grocery needed omnichannel), and the delivery mechanism was equivalent—rather than forcing expansion, they let demand pull them in.
“and you can predict that customers want this before they want it or you can just wait until you see lots of customers bang on the door riding into door Das hey can you also get my groceries and so it's a matter of what do you want to be pushing the customer to do what you want or do you want the customer to pull you in the direction that they want to go”
The first (primary) Zappos core value was 'Deliver Happiness Through Service,' interpreted to mean providing exceptional service not just to customers but also to employees, partners, and investors.
“the first one was was to deliver well through service it was the you know was in some sense the most important core value but we meant it uh in the way not just to deliver while through service to customers but also to employees to um our our partners our business partners and to investors”
Lin's father taught him at age 6 or 7 that 'you can learn anything from you can learn many things from every single person on this planet' and demonstrated this by showing him the different people he learned from, shaping Lin's approach to learning from individuals across skill levels.
“I value people for who they are my father um I learned this from my father where he he told me once because I was like oh okay I'm just so much smarter than everybody else because a little cocky little uh kid and he said well actually you can learn anything from you can learn many things from every single person on this planet I think I was probably six or seven at the time and he was uh he'd show me all the different people that he learned from and that the collection of these lessons from many many different people is what you become”
Being suspended from computer lab for creating a game that distracted students taught Lin that some rules exist for good reason, but being invited to join the math team by Mrs. Petosa, who asked him to teach others his problem-solving tricks, taught him the value of teamwork—that individual brilliance means little without the ability to enable others.
“she also ran the MTH team and she said well you I'm sorry the principal wants you out of the computer lab but you should join the mou team and I joined the mou team there and um one of the things I was really good at was math and she told me that if you want to be a leader and you want the team to win it's not good enough for me to just solve the problems but figure out how to get the rest of the team to perform and so I started teaching the rest of the math team some of the reasons why I was able to solve some of these problems more quickly than they were they're very talented but I had figured out tricks that they had not figured out and they had taught me tricks that I had not figured out so we got better and better by riffing each off each other and so I learned the value of teamwork”
Lin works out every single day as an input discipline, rather than negotiating which days to work out, because negotiation leads to days skipped; having the habit as non-negotiable ensures consistency.
“I I hear that you work out every single day because instead of trying to figure out which days you're going to work out it's always a negotiation with which days and some days you don't feel like um exercising you just work out every day I have the same philosophy you just get up every single day and do the things that are important”
Lin's top 2-3 mental models are: (1) Type One vs. Type Two decisions (reversibility determines decision-making speed), (2) working backward/forward to align vision with execution, and (3) consistent daily compounding rather than seeking breakthroughs.
“I think the one that I learned from Amazon is whether this is a type one or type two decision and you know if it's a type one decision I've learned from Brian chesky to run out the clock because you can't go back as a type two decision and you you know you just move the move forward make a call and of course CFT along the way type one being irreversible and type yeah so if it's irreversible run out the clock meaning like get all the information make sure that that's a high confidence decision type two if you can always change it make a fast decision and keep iterating that's one model the other mental model I think about is um you know working backwards working forwards that's also top down versus bottom up is a similar sort of idea”
Core personal values include focusing on inputs and process for clarity of execution, consistent compounding through daily 1% improvements, honesty and directness, learning from every individual person, and maintaining strong family and friend relationships as accountability.
“I think the the values for me are when you me when you want to accomplish something it's about the inputs it's about the process by which you go about getting the outputs I think it's very very important to have that and I value that Clarity of input eventually leads that output and focus on the inputs I value uh consistent compounding and just getting every single getting up every single day and just making small improvements every single”
High variance and high beta personality traits—the willingness to try unconventional approaches and accept risk—can lead to either genius or idiocy, but when paired with introspection and value alignment, they become assets for building differentiated businesses.
“they were very concerned whether there was any permanent damage and things like that and my mom kept bringing me back to the hospital again and again and the doctor said don't worry I think he's fine I think he's fine and eventually he said well is there going to be any problem with you know his development he's like well he's either going to be um a genius or he's going to be an idiot he's one or the other I mean so that's that's how my parents would describe me high high variance and high beta”
Comparing 'don't fight the Fed' to 'don't fight technology': the Fed's ability to change money supply and interest rates has dramatically wider effects than any single technology, yet both principles suggest alignment with inevitable forces rather than resistance to them.
“it's interesting that you brought up don't fight technology there's a saying in investing don't fight the FED it's sort of the same sort of and then what the FED is way more powerful in many respects than technology no well I think the FED can constrain or can loosen money supply in a very dramatic way so it it applies throughout the whole economy as opposed to just about technology”
The speaker was born in Taiwan to two commercial bankers and from a young age exhibited high variance and high-beta behavior, including attempting to jump off a dresser at age 2, leading doctors to suggest he would either be a genius or an idiot.
“I guess I was born in Taiwan um to two parents who um were both commercial Bankers um in an early age they from what they tell me I was always a little I saw the world a little different differently and did things a little different the story that they like to tell about me being different was when I was about 2 years old there's a new dresser that was delivered through our apartment in new uh in um Taiwan and I figured out a way to get to the top by pulling out the first drawer crawling into it then pulling out the second drawer pulling it uh crawling into that and then getting all the way to the top and when I got up there I thought I could fly so I jumped off”
Jensen Huang is a remarkable CEO with a unique management style; his approach to leadership and communication is different from other tech CEOs and demonstrates distinctive management practices.
“Jensen's a remarkable CEO and he does things very differently than anybody else we had him speak at our base camp which is our annual Retreat for our Founders and he just came out with so many great stories about Nvidia about his personal life but also about his management style that is so different I remember being there and that was that was awesome”