so I thought this was a young a good way of thinking about where we are today to talk about the end of the beginning because it struck me that we've been looking at charts like this for most of the last 20 years they always go up and to the right and now we're getting to the point that we're kind of finishing now the access story is reaching the end because we've connected three quarters of people on earth and we're going to connect all of the rest and as we go forward though the other part of the story isn't close to being finished the access story is finished but the use story is just starting to begin and it feels like that's what the next 20 years


is about and so most people are online but most of the money is not and as we move towards addressing that we address any problems and we tackle harder markets and we probably change those markets a lot more than some of the markets we've addressed in the past and of course as we do that we have these two new fundamental layers to build things on so we spent the last ten years talking about and building stuff on social and on search now we think about machine learning and we think about building things on crypto currencies and so as we go into this I think it's useful just to start by thinking about market sizes and so the obvious one


ecommerce looks big in dollar terms u.s. e-commerce now is about four hundred and fifty billion dollars a year but if you zoom out and look at retail spending it's still only about ten percent and then if you add bars and restaurants which of course we're now starting to address it looks smaller and then it's interesting to look in some of that and ask what that retail spending looks like so gas stations for example are going to transform and perhaps completely disappear over the next 20 years and that's as big or bigger than us e-commerce and then there's other segments inside that as well that are kind of interesting so we spend over a


trillion dollars a year on cars and parts and maintenance all of that is going to go away or change or be completely transformed or relocated over the next 10 and 20 years but then retail of itself isn't the only story there's also all the rest of us consumer spending which is now over ten trillion dollars I used to do charts in billions of dollars this presentation is mostly trillions of dollars and so then if you zoom out and think about this the actual share we've taken so far of the opportunity is actually much smaller than it might look just if you look at commerce itself the same thing comes I think if you look at


housing so Internet is now the largest single category in global advertising and much the same in the USA so now close to 40% of us have budgets and advertising of itself doesn't change very much over time it tends to stay stable as a share of GDP and so this leads to people saying well maybe Google and Facebook are topping out maybe there's not much grace left for those companies maybe they've got everything and there's no room for anybody else but I think you have to look both at advertising and at marketing which is this kind of other block we don't talk about so much and if you look at within that block you see things like Direct


Mail and telemarketing which it seems kind of weird to me that we talk about a targeted ad on Facebook as advertising but we don't think about comparing and we compare that with TV advertising but we don't compare it with telemarketing or direct mail and the kind of a broader point to think about here if you buy space on Amazon if you buy placement in Amazon search results and we call that advertising if you buy exactly the same thing from Walmart then we call that marketing and somehow that's not the same thing but of course it is the same thing because what we're really talking about the job to be done is what you pay to reach a customer and then if you're


thinking about what you pay to reach your customer there's other pools of capital to think about there as well so retail rent is money that you spend to reach your customer it's money you spend instead of marketing or instead of advertising the same thing indeed for shipping or for service there are whole pools of capital out there that we've really only just started to address if you go globally just sales and marketing just advertising and marketing in total is now close to a trillion dollars I suspect a few um point this out to Jeff bezel send that line about your margin is my opportunity starts coming to mind but this global point I think is also


interesting because we really ought to think not just how big the opportunity but where else the opportunity is a good place to start in this is with another piece of global technology industrialization which much like the internet was sort of originated in one country and then spread to another big low-wage country on the other side of the ocean so this is the u.s. the UK inventing industrialization then the UK picking it up and the u.s. picking it up and taking it forward but then if we go forward essentially something else has happened that technology has died fused and he's gone to other places if we zoom in on that change where is that


technology gone where is that change happened well unsurprisingly most of that balance has gone to China you can see much the same thing if you look at computing which was again invented in the US and in Europe but those countries you to dominate it that was close to three quarters of computing capacity now it's much less than that and again of course a large part of that balance has gone to China which now has more smartphone users and the USA and Europe combined you can see the same picture if you look at usage this is global mobile in mobile internet traffic a pack is much bigger than North America and Western Europe


combined and that of course was always reflected in the spread of spending power the global middle class is now a lot bigger than it used to be but also again it's distributed in different places and that flows through to things like e-commerce so from almost nothing China again is now has more ecommerce in the US and Western Europe combined all of this kind of means that as we look at the position of the u.s. here penetration of e-commerce is actually quite a long way behind some other leading markets China obviously is leapfrogging there's a leap frogging story there South Korea in the UK of


course are also well ahead of the USA although other parts of Western Europe on the other hand are quite far behind so there's an interesting picture of transition here from this being a US story to it really not been a u.s. story at all anymore we can see that again in company creation so these are the four big companies we spend all of our time talking about Google Apple Facebook Amazon in its I think it's kind of useful to get a sense of the relative spread of scale and growth in revenue in these companies because we tend to lump them all together there's also another company people talk about in this context which is Netflix


so that's kind of putting that on the chart to the same scale but I think much more interesting year to think about the three big Chinese Internet giant's which are smaller because they're not global in the same way but they are equivalent weight and certainly equivalent gross but those are just kind of the big giants the ones that people everybody talks about being scared of more interesting again I think to look at how many other billion five 10 20 50 billion dollar companies are being created outside the USA there's a lot of unicorns being created outside of the USA being created outside of Silicon Valley today and of course that's


infected in rich capital which again was mostly invented in the USA and relatively recently dominant was the US was really the only place that this happened now again that whole business model that whole approach has been diffused and so company creation is also being diffused that gets us back to the question well what's the opportunity there's us ecommerce which is four five hundred billion dollars in that in the US retail but then there's global retail and then there's global consumer spending so we go from thinking about a couple of hundred billion dollars to 40 50 trillion dollars potential opportunity that really means


we've only just started scratching the surface of what we might be able to address how is it that we address that what kind of things do we do that are different does the curve just kind of keep going on up and to the right well it feels to me that the things are going to change a little bit so we think about the first 20 years of the internet we really did kind of the easy things didn't feel terribly easy at the time there's kind of entrepreneurs who didn't think it was terribly easy as they were doing it but what we did was we did stuff that would work with low penetration and would work with little capital it would work with consumers who


weren't comfortable buying stuff online so they were kind of low touch goods things you didn't have to hold in your hand we tended to build tools rather than build entire stacks we tend to build information arbitrage we did sort of price comparison and plane tickets now we do things that need high penetration things that need lots of capital we invert all of these assumptions we build complete companies we build full stack companies we build businesses are based on information a good case study to think about this good illustration is to compare kind of a great company from the last 20 years like Yelp with businesses like doordash


today Yelp is a low capital though penetration business it's information arbitrage business it's selling tools Jordache has to get your hot meal in half an hour that's a different kind of business with different assumptions about what the internet looks like what capital you need what consumers are willing to do comfortable and and comfortable to be willing to accept doing online so if we look at that forty trillion dollars of consumer spending then there's a whole bunch of things in here that we've only just addressed very peripherally or not really addressed at all and even where we have addressed them we're going to address them in the


future in completely different ways so if you think at kind of the first 20 years what did we do with housing well we did listings and we did price comparison now open door will buy your house if you look at transport we used to do plane tickets now we do cars and we do autonomous cars and we do Airbnb up at the top of the stack with Health well we used to give you a website that would let you persuade yourself you had the bubonic plague now we'll edit molecules and we'll edit genes and we'll islet cells and create completely different kinds of cures and all the way across the spectrum we move kind of to a different character of business and


different way of addressing these problems the most visible place that you can see this happening today I think is in retail I think a good kind of conceptual model for thinking about retail is that there is retailers logistics and then there is retail as taste preference recommendation service and there's a spectrum between these two and the original Sears Roebuck hundred years ago did we tell us just excited as Walmart on the other hand we've never really managed to scale retailers taste outside big cities and outside small shops today we're addressing both of these so Amazon did retailer suggest expose successfully and


now Amazon and other companies are doubling down on that so same day delivery free delivery above everything else groceries but at the same time we move across that spectrum we'd have more and more things that addressing the other kind of retail that are not just kind of a specialized version of FedEx but actually a question of recommendation that taste preference discovery all of this change of course affects the US probably more than anywhere else because the US has massively more retail square footage than anywhere else so that picture was likely to change quite dramatically in the next ten years now as we think about


how we address those I'm actually old enough now to remember when he called us was asset light and buying crops was a really stupid idea in like kind of an exemplar of how everybody lost their minds in the late 1990s in fact the original Amazon business plan from 1994 said no warehouses no stock no shipping that didn't last terribly long in fact I think it lasted about three weeks but then of course that Amazon has become well not really an asset light anymore amazon has become an infrastructure business and the thing that drives his change now more than anything else and into the next 20 years he seems like groceries the interesting thing about


groceries is that it breaks the Amazon model in fact it breaks the whole ecommerce model because the whole point of Amazon is that everything is a commodity is one packet switching network and they don't have to know what's in the box they just ship it to you they just pull it off the shelf and ship it to you and so it's a commodity platform and of course you can't do groceries like that groceries needs almost a whole other company you need logistic different logistics different delivery different e-commerce platform and everything else but as the chart shows pretty clearly our groceries are so much bigger than e-commerce it's such


a big opportunity that it's worth building almost a whole other company to do that for yourself here again of course the USA is behind this is a chart of the online grocery market and billions of dollars fairly unsurprising that China is bigger than the USA because China is apparently quite a big place what's more useful I think is to look at the revenue per capita so you see other large developed markets that are way ahead of the US here and so again you will see really substantial growth in how people do groceries in the US a kind of catching up with some of these other countries again I think what's more interesting


though than just the war penetration is to think of how that change the industry so this chart shows you the number of items stopped in grocery stores in supermarkets over the last couple of decades and what you see here is that as the retail model changed the grocery business changed the number of SKUs there were change the way that you bought si and the really that the fundamental thing here is when you change how you buy things you change what people buy you change your purchasing journey you change what goes into the basket as we change that purchasing journey again whether that's kind of conventional ecommerce in any


other category but in particular in groceries will change what kind of categories get bought and so that means money moves around categories change money moves from advertising to marketing as I mentioned earlier we won't just buy all the same stuff but on the web we'll buy different stuff that of course is a good way to think about what happens as we move from just the logistics part to the taste preference recommendation curation part now I think a good way of thinking about this is that the internet lets you buy anything that you could buy in New York in fact that's exactly what Sears Roebuck did 100 years ago it let you buy anything


that you could buy in New York but it doesn't let you shop the way you can shop in New York and that's now starting to change we have a bunch of building blocks and a bunch of new ideas for how you might build a consumer internet business they give you different ways of addressing these so we have social we have new model economic models like rental or subscription we have this sort of sense that you know actually if you're an online brand maybe you want to have a shop and maybe that's a substitute for spending money on Instagram and so we have different ways of requiring customers it feels like an awful lot of current consumer retail


events are going to shift into advertising and a lot of advertising is going to shift into retail events and then of course we have machine learning changing the whole conception of what it is we might be able to recommend and suggest all of these building blocks give us things that you really shouldn't have work or things that would never have worked 20 years ago the idea that anybody would buy fashion online was about as insane as the idea that Bitcoin would replace fiat currency it was just kind of an obviously insane idea Warby Parker selling glasses online you're out of your mind cosmetics makeup that you haven't tried these are all kind of


obviously stupid ideas these are all things that are now starting to work as we have these new building blocks as we have more penetration as consumers are willing to do effectively everything online now this gets me back to the phrasing I used earlier as we think about new problems actually I think you're the way you could do this chart is what we did in the first twenty years was e-commerce and advertising what we do in the next twenty years actually is just everything else what kind of everything else well what a stable GDP look like actually you can tell I don't like log


scale charts pretty much so what does global GDP look like what pieces of that might need won't we address well how about cars Tesla this kind of little Californian company has been doing quite well they clean you may have read about this in fact Tesla is now outselling the other premium car manufacturers in the USA but if we actually think about the total opportunity for cars for software for electric then again we get another of these charts that really ought to be a log scale chart but actually tells you a clearer story if it isn't what is a total opportunity here and again this is just see USA not globally which is even bigger more interesting though than just


looking at numbers of cars I think is looking at what's inside the cars so this chart shows you the component cost of a conventional car on the right which is the OEMs and the tier ones and then how much companies from the electronics industry are going to eat that because as we move to electric as we move to batteries and then again as we move to autonomy you have a completely different mix of components and mix of suppliers inside the cart software eats the car more interesting again though software changes what the car is so as we go to autonomy we change what we think a car is it won't just look like today's car but without a steering wheel it will


look different it will do different things it will go in different places will unbundle the car journey entirely into different sorts of vehicles different modalities what are you going to be doing inside that car if you're not staring at the wheel well you should probably invest in alcohol companies in TV and TV is another interesting to think about here software each TV well Netflix and Amazon are now top-tier content producers they have equivalent budgets to the other major US entertainment companies in fact this is a great quote from back in 2010 that Jeff books at Time Warner said this was like the Albanian aren't being worried


about the Albanian army I hope somebody is keeping an eye on the Albanian army now I think more interesting though is to ask what do we actually mean by TV so watching people play games is now bigger than Netflix or bigger than HBO about bigger than ESPN the latest um triple-a console game had a big opening weekend than any of the recent Hollywood franchises watching people play games is a big deal eSports is now an equivalent size to any of the local US sports not equivalent to any of the global sports but the US ones will do for now but then if you look at the revenue here this has yet to catch up and so that's another place where you'd expect to see


an awful lot of kind of interesting Grayson is interesting businesses being created going up to the high level TV viewing is going down internet consumption people looking at their phones is going up tech industry spent 20 years trying to get into the living room and it did get into the living room but it didn't do it with TVs it did it with mobile phones and so we have this fundamental shift in where the attention is and what kind of things you're going to be doing with that I've talked a lot about money software weeks money is kind of an interesting topic to talk we're hearing from Angela later on today talking about


this we had this this is interesting idea that all the money being put into FinTech is is enormous and that's clearly too much in the market won't be able to absorb this and yes there's a lot of money going in it's just kind of starting to address some of the most obvious pain points but again if we think about the overall opportunity there are trillion dollar pools of capital here that are going to be addressed by software and going to be addressed by technology in sterling it's worth adding housing from an earlier side onto this just to get a sense of them how much money there is in money but then as we look at this as an awful


lot of people still untouched no matter how big those segments are portion of the u.s. population is unbanked much larger population of the global population is unbanked and those people will not be addressed by giving them all a paper check and a credit card they'll be addressed in totally different ways with software with the internet with mobile and in the u.s. incidentally there's a lot of people who are sort of notionally banked but actually aren't banked at all there's a common saying here that the u.s. basically has two banking systems as a banking system for the people in this woman there's a banking system for the other people and


they get a much worse deal and that again is something that a lot of people are going to think about changing in the next 10 and 20 years time as we look at how some of those tools again the USA is not in the lead so on the Left we have mobile penetrant penetration on the right we have mobile payment value it's fairly obvious that something interesting is happening in China here again and that's something again that's that's going to start spreading around the world so we have here a bunch of building blocks a bunch of new ways of building FinTech new ways of building financial services applications we have vastly more data we have completely


different kinds of data we have totally different consumer expectations of what it is you ought to be able to do and what a service ought to look like we have the capability to unbundle things from the big traditional conglomerates and aggregators like retail banks and again we have machine learning is a new way of bringing understanding to that information I'm talking about money the only thing left is to talk about death we have a death fund sorry a bio Fund and drug discovery is 75 billion dollars this feels like a big market it's an interesting market is one that venture capitalists have addressed for a long


time but it's now being addressed in new kinds of ways so machine learning again a recurrent theme changes discovery but things like in more interesting things like social and wearables change trials if you actually want to get 10,000 people who have a condition social means a completely different way of getting these people wearables mean a completely different way of monitoring those trials and of course now we now now have ways of actually programming genes and programing cells which my colleague Holger will talk about later that means we can do totally different kinds of cures but the 75 billion dollar number but then there's other numbers to


think about so this drug discovery and then there's a drug market and then there's health insurance but then there's a global market for health care what actually gets spent spent on you when you're sick and that's seven over seven trillion dollars how do we address some of those well seven trillion dollars is spent on health care but that's kind of the cost of being sick if I did any part of the cost of being sick but it's more interesting you think well what's the cost of not being sick what hat is the value of not getting sick what's the value of not dying what's the value of never having to cure any of these things in the first place and


those are things that we can now start thinking about addressing a good way of sort of thinking about what's happening here is that we've sort of gone through all of the easy monsters and now we're getting to the death tell each other to the god mode we kind of killed the foot soldiers now we've got the giant robotic brain with the Gatling gun and so we're kind of addressing different character of problem a harder problem harder markets to address than we addressed in the past what tools do we have to do that well we have kind of interesting new fundamental layers if you think about what happened in the first twenty years we went from these kind of blind


alleys of a well in the information superhighway and interactive TV and then the Internet and the web came along and this gave us kind of decentralized permissionless innovation you didn't have to ask AT&T or Time Warner for permission to put up a website and that was what enabled the explosion then it turned out we needed some kind of organizing layer on top of that and we got Google and we got Facebook and we've spent the last ten years thinking about Google and Facebook and how they organize things and those platforms are centralized by design and they capture meaning and intent and their form can capture value they're also kind of


highly abstracted they don't really know what a thing is itself they can only look at it a kind of tools we removes now we have two new fundamental layers we have crypto and we have machine learning which among other things are swinging away from centralization what do we mean by that what would those things do well what is this well how would Google or Facebook or Amazon answer that question what is this thing well Google will say it's on pages that say wishbone and Hanna's Wagner Facebook will say people who like furniture shared links to this Amazon will say it's a SKU I don't understand the


question people who bought this Scoob or other SCU's and not really very much else what are we going to be able to do with machine money well we have more in more levels of meaning and more levels of understanding so we will know it's a chair that would be a good step we can kind of do that now we could never do that before now we can do that we can say it's a chair and then we'll say well it's a modern Scandinavian design classic but actually you go another level of meaning in and you say right well if you like that chair you're not going to like Disney cruises so we won't show you Disney cruises ads will show you something else that's to say we get


to successive levels of meaning of what a thing is rather than kind of guessing at it's through multiple levels of levels of abstraction from who linked to it or from or page it we shared on this of course is not just a consumer story if we go back and think about by oh well machine learning means I can look at an x-ray and tell you whether you've got cancer and do that at massive scale and massive automation but I can also say it looks like you're going to have a heart attack in the next couple of days or I can say well change your behavior or you're likely to have a heart attack in the next day or two that's to say we get to successive levels of meaning which


successive kinds of value in successive kind of kinds of addressability the fundamental framework for thinking about machine learning it's a tool to scale people but to scale people in two very different ways one of them is I have a million pictures in the basement and I now have a million interns that I can send down to look at all of those that's one kind of machine learning it automates a very basic human task but something we couldn't automate before but the other is I have a million pictures in the basement now I can send one intern to go and look at all of them and come back in half an hour and say well when I looked at the third hundred


thousand this interesting picture started coming out and so that's to say we get a superpower in a sense we get things we could never see before so we think about machine learning we also think about crypto this is a different kind of crypto why does crypto matter well imagine in 1993 asking why does the internet matter first you'd have a long argument about whether you should say Internet or internet or web or world wide webs and then you would say well this is a distributed decentralized permissionless network anyone can build anything you don't need to get permission from the phone company to build it so it's a great story that


Steve Jobs said hey have you seen this internet thing we should buy it it's country and work like that anymore changed how this stuff worked now how do we think about what those applications were going to be well we had no idea so this is web service in ninety and Internet traffic in the early 90s Mac had more share of web service in Linux and the world wide web was 3% of Internet traffic these were applications built on that network these were not the important applications everything we see now is in that little purple box at the top right so you have the network in the you had the things built on the network you


didn't know what the things were going to be that were importantly what was important was the capability the same thing with cryptocurrency we have a distributed decentralized network anyone can build applications with native trust native value exchange payment and mechanisms for understanding meaning built into it so we will come back to this some this pendulum from closed to open to close to open we think about what these things can do we have new ways of finding meaning in intent new ways to understand what a thing is and what it might mean that you're interested in a thing new ways to build networks on that building networks on


that that a decentralized sort of permissionless and also of course a market reset whenever you have a fundamental change in technology that just kind of shakes the trees and brings new companies out of that so a final thing to think about here I called this presentation the end of the beginning this is what the beginning looked like this adorable young man is called Geoffrey Bezos and he's just entered the books business this is Geoffrey bezels today he is not in the books business anymore and this is Geoffrey bellows in the next 20 years and what other things he might be building so thank you you

Key Themes, Chapters & Summary

Key Themes

  • Detailed Leadership Versus Micromanagement

  • Integration of Product Management and Marketing

  • Organizational and Cultural Transformation

  • Personal Work-Life Balance

  • Continuous Learning and Growth Mindset


  • Leadership in the Details

  • Rethinking Product Management

  • Structural and Cultural Evolution at Airbnb

  • Balancing Professional and Personal Life

  • Embracing Continuous Learning and Adaptability


The podcast transcript, "Brian Chesky’s New Playbook," is a deep dive into the leadership and strategic philosophy of Brian Chesky, the CEO and co-founder of Airbnb. The conversation covers various aspects of Chesky's approach to managing and evolving Airbnb, his personal beliefs and practices, and his perspective on the future of the company and technology.

Leadership and Micromanagement: Chesky starts by outlining his approach to leadership, emphasizing the critical difference between being detail-oriented and micromanaging. He believes that understanding the minute details of one’s business is essential for effective leadership. This approach has been a driving force in Airbnb's strategic decisions, particularly in shifting the focus from traditional growth metrics to prioritizing a superior user experience and organic growth.

Product Management and Marketing Integration: A significant part of the discussion is dedicated to Chesky's revamp of product management at Airbnb. He talks about integrating product management with marketing to create a cohesive strategy across the company. This integration involved reshaping the product team to be smaller but more senior, combining inbound product development with outbound marketing, and shifting certain responsibilities to program managers. Chesky's approach is to have a single roadmap that guides all departments, ensuring that every team is aligned and moving in the same direction.

Organizational and Cultural Changes: Chesky also delves into the cultural and structural transformations at Airbnb. He discusses the shift from a divisional to a functional organizational structure, which he believes has led to more efficient operations. The focus has been on aligning everyone in the company toward a common goal and ensuring that the organization's culture fosters this alignment.

Work-Life Balance: On a personal note, Chesky shares his strategies for maintaining work-life balance and avoiding burnout. He emphasizes the importance of regular exercise, a healthy diet, sufficient sleep, and nurturing relationships with friends and family. For Chesky, maintaining a balance is crucial not just for personal well-being but also for sustaining effective leadership.

Continuous Learning and Growth: Lastly, Chesky discusses the importance of continuous learning and maintaining a growth mindset. He advocates for staying curious, open to new ideas, and constantly seeking personal and professional growth. For Chesky, this mindset is not just about business success but also about personal fulfillment and development.

In summary, the transcript provides a comprehensive look into Chesky's unique approach to leading Airbnb. It covers his detailed involvement in the business, the integration of product management and marketing, organizational changes, personal work-life balance, and the importance he places on continuous learning and growth. Through these insights, Chesky presents a holistic view of leadership that encompasses both professional and personal growth.