What We’re Reading (Week Ending 21 May 2023) - 21 May 2023
Reading helps us learn about the world and it is a really important aspect of investing. The legendary Charlie Munger even goes so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 21 May 2023):
1. The Borlaug Report #3: Bioprocessing – Borlaug
A small molecule drug is basically any of the pills in your average household medicine cabinet – they are chemicals, synthesized and pressed into a solid tablet or coated in dissolvable pill plastic. Most of the drugs that dit this description are very popular – meaning lots of them need to be made. This has traditionally been done in a stainless-steel fermenter – such as the one below:
The process for making drugs this way, in large batches, is fairly simple logistically – you are combining active pharmaceutical ingredients and blending them to create your drug, adding things like excipients along the way as you remove moisture, mill, and blend some more. Finally, you remove everything, press the substance into pills, and coat the pill as needed. Run complete!
Before the next run, one must thoroughly sterilize these large steel tanks with cleaning chemicals. Logistically, this is a perfectly acceptable way of manufacturing chemicals at scale, and versions of this have been done for decades.
However, things are changing. The future of the pharmaceutical industry is looking increasingly biological in nature, and producing biologics requires a little more TLC (and money).
How Larger Molecules are Made
While most of small molecule manufacturing can be done with just a couple of discrete pieces of equipment, making a biologic drug has a plethora of steps that can be divided into upstream and downstream bioprocessing. I would add a third category to make clear that parts of “upstream” are generally for R&D purposes only.
R&D (Scale-Up): Before biologic drugs are commercially manufactured, there is a manufacturing component – scientists have to figure out how to ensure the drug can be scalably manufactured without compromising the effectiveness or safety profile of the drug itself. This is usually called “scale up”. The process is basically a guess-and-check exercise of finding cells that excel in a smaller (150mL) bioreactor, and keep finding the best cells as they multiply and test them in larger and larger bioreactors until you’re up to 1-2,000 liters or more. Other conditions, like what goes into the cell culture media, how much oxygen is let in, temperature, stirring speeds, etc. are all tinkered with here. Once the “process” is defined, R&D is over and production can proceed. This has become a key value proposition of a lot of contract manufacturers, because it can be extremely hard to do, especially in gene therapy.
Upstream: Basically, what you are doing in upstream bioprocessing is taking a bunch of cells (the “active ingredient” per se) and putting them in a soup of nutrients (media) that stimulates them to multiply at high rates based on the R&D process you tested out. In doing so, you are getting to a giant vat of soup that has an adequate volume of those cells (the drug) floating inside. In the image below, most of this is “production” in the manufacturing process itself. It’s actually a lot like the stainless steel process up until here, given everything is going into a bioreactor – the reactor is just smaller in this case.
Downstream: Once you have your cell soup, you engage in the “downstream” half of the process which separates those cells from all of the things that you don’t want in your final product. Once you’ve purified and filtered everything, it goes into a freezer (“cryo-preservation”) and is then shipped elsewhere to be put into the right delivery mechanism (IV bags, syringe vials, etc.) and boxed/packaged – the “fill-finish” process. This is the part that is fundamentally different – in small molecule production, you’re much closer to the finished product when things come out of the bioreactor. In biologics, you are separating the active ingredient a lot more carefully from the other stuff you put in the soup.
Most of these drugs are made in smaller batches – they often serve more targeted populations of people than some of the small molecule blockbuster drugs of old. The exception here is antibody drugs, which are still finding themselves going after large populations. Cell and gene therapies, however, are a much different story. After all, healthcare was never going to be one-size-fits-all. If you tried to apply the old method of making drugs to this new reality, you’d realize quickly how much time you are spending cleaning the tanks after every run.
The Single-Use “Innovation”
As mentioned above, the economics of manufacturing small batches of a drug in a stainless steel tank stops making sense very quickly when you have to shut down the process afterward to follow strict sterilization protocols, using lots of water, chemicals, and energy just to be able to start the process up again using the same equipment. Fortunately, the industry has already adapted by commercializing single-use technology.
Single-Use Saves Money
Instead of cleaning out the fermenter every time you use it, you can just line it with a disposable bag made of a fancy polymer that guarantees the same level of sterility. Kind of like using a trash bag instead of washing out the trash can under your sink every time you empty it. The same goes for all of the tubing connecting each subsequent piece of equipment in the workflow, as well as the cartridges, capsule and columns within the machines themselves. After a run is over, downtime can be short – just replace everything and start over.
Turns out, at lower batch sizes, net of energy/water/sterilization costs, this can actually be significantly cheaper, both on COGS and capital investment…
…You should care because this is an easily investable trend for few key reasons:
Durable Usage Trends: Manufacturing in biopharma is different from the R&D tools themselves – there is no “fad” factor like you might see in genomics, for example, where researchers will crowd into a hot new space and use the relevant technology until the next thing comes along. These changes can be quick and violent. You know what doesn’t change? The bag you line the bioreactor with and the tubes that connect it to the clarification system. That’s the same regardless of whether someone invents a new gene therapy, a cell therapy, an antibody, or an mRNA drug.
Companies selling this technology don’t benefit from one type of therapy – they benefit from the complexity of all therapies moving through the clinic.
Highly recurring revenue with deep moats: Once you file a drug with the FDA, a lot of things get set in stone – one of these things is the manufacturing process and the equipment that goes into it, specified down to the vendor. Recently, companies have been specifying second sources from a second vendor into these filings to deal with supply chain risks, but the fact remains that once something is “spec’d” into the process, it’s painfully difficult to remove or change it.
This discourages new entrants to the market because the only share you can win is for clinical-scale dosage for new drugs – meaning your initial “TAM” is extremely small. In bioprocessing, scale is a massive barrier to entry and the FDA is a massive barrier to scale.
2. Google I/O and the Coming AI Battles – Ben Thompson
If there is one thing everyone is sure about, it is that AI is going to be very disruptive; in January’s AI and the Big Five, though, I noted that it seemed more likely that AI would be a sustaining innovation:
The story of 2022 was the emergence of AI, first with image generation models, including DALL-E, MidJourney, and the open source Stable Diffusion, and then ChatGPT, the first text-generation model to break through in a major way. It seems clear to me that this is a new epoch in technology.
To determine how that epoch might develop, though, it is useful to look back 26 years to one of the most famous strategy books of all time: Clayton Christensen’s The Innovator’s Dilemma, particularly this passage on the different kinds of innovations:
Most new technologies foster improved product performance. I call these sustaining technologies. Some sustaining technologies can be discontinuous or radical in character, while others are of an incremental nature. What all sustaining technologies have in common is that they improve the performance of established products, along the dimensions of performance that mainstream customers in major markets have historically valued. Most technological advances in a given industry are sustaining in character…
Disruptive technologies bring to a market a very different value proposition than had been available previously. Generally, disruptive technologies underperform established products in mainstream markets. But they have other features that a few fringe (and generally new) customers value. Products based on disruptive technologies are typically cheaper, simpler, smaller, and, frequently, more convenient to use.
It seems easy to look backwards and determine if an innovation was sustaining or disruptive by looking at how incumbent companies fared after that innovation came to market: if the innovation was sustaining, then incumbent companies became stronger; if it was disruptive then presumably startups captured most of the value.
My conclusion in that Article was that AI would be a sustaining innovation for Apple, Amazon, Meta, and Microsoft; the big question was Google and search:
That Article assumed that Google Assistant was going to be used to differentiate Google phones as an exclusive offering; that ended up being wrong, but the underlying analysis remains valid. Over the past seven years Google’s primary business model innovation has been to cram ever more ads into Search, a particularly effective tactic on mobile. And, to be fair, the sort of searches where Google makes the most money — travel, insurance, etc. — may not be well-suited for chat interfaces anyways.
That, though, ought only increase the concern for Google’s management that generative AI may, in the specific context of search, represent a disruptive innovation instead of a sustaining one. Disruptive innovation is, at least in the beginning, not as good as what already exists; that’s why it is easily dismissed by managers who can avoid thinking about the business model challenges by (correctly!) telling themselves that their current product is better. The problem, of course, is that the disruptive product gets better, even as the incumbent’s product becomes ever more bloated and hard to use — and that certainly sounds a lot like Google Search’s current trajectory.
I’m not calling the top for Google; I did that previously and was hilariously wrong. Being wrong, though, is more often than not a matter of timing: yes, Google has its cloud and YouTube’s dominance only seems to be increasing, but the outline of Search’s peak seems clear even if it throws off cash and profits for years.
Or maybe not. I tend to believe that disruptive innovations are actually quite rare, but when they come, they are basically impossible for the incumbent company to respond to: their business models, shareholders, and most important customers make it impossible for management to respond. If that is true, though, then an incumbent responding is in fact evidence that an innovation is actually not disruptive, but sustaining.
To that end, I take this Google I/O as evidence that AI is in fact a sustaining technology for all of Big Tech, including Google. Moreover, if that is the case, then that is a reason to be less bearish on the search company, because all of the reasons to expect them to have a leadership position — from capabilities to data to infrastructure to a plethora of consumer touch points — remain. Still, the challenges facing search as presently constructed — particularly its ad model — remain.
3. An Interview with Peter Lynch in 1996, Six Years After Retirement – Conor Mac
When you first went to Fidelity, what was the market like?
Well, after the great rush of the ’50s, the market did brilliantly and everybody says, “Wow, looking backwards, this would be a great time to get in.” So a lot of people got in in the early ’60s and in the mid-60s. The market peaked in ’65-66 at around a thousand, and that’s when I came. I was a summer student at Fidelity in 1966. There were 75 applicants for three jobs at Fidelity, but I caddied for the president for eight years. So that was the only job interview I ever took. It was sort of a rigged deal, I think. I worked there the summer of ’66 and I remember the market was close to a thousand in 1966, and in 1982, 16 years later, it was 777. So we had a long drought after that. So the people were concerned about the stock market early in the ’50s. They kept watching and watching, not investing. It started to go up dramatically and they finally caved in and bought big time in the mid-60s and got the peak..
…But the market really didn’t do much between ’77 and ’82, between the beginning of that bull market, and yet your fund performed quite spectacularly. What do you do?
Well, I think flexibility is one of the key things. I mean I would buy companies that had unions. I would buy companies that were in the steel industry. I’d buy textile companies. I always thought there was good opportunities everywhere and, researched my stocks myself. I mean Taco Bell was one of my first stocks I bought. I mean the people wouldn’t look at a small restaurant company. So I think it was just looking at different companies and I always thought if you looked at ten companies, you’d find one that’s interesting, if you’d look at 20, you’d find two, or if you look at hundred you’ll find ten. The person that turns over the most rocks wins the game. And that’s always been my philosophy…
…Talk about the change in ’86-87.
Well, I remember in my career you’d say to somebody you worked in the investment business. They’d say, “That’s interesting. Do you sail? What do you think of the Celtics?” I mean it would just go right to the next subject. If you told them you were a prison guard, they would have been interested. They would have had some interest in that subject, but if you said you were in the investment business, they said, “Oh, terrific. Do your children go to school?” It just went right to the next subject. You could have been a leper, you know, and been much more interesting. So that was sort of the attitude in the ’60s and ’70s.
As the market started to heat up, you’d say you were an investor, “Oh, that’s interesting. Are there any stocks you’re buying?” And then people would listen not avidly. They’d think about it. But then as the ’80s piled on, they started writing things down. So I remember people would really take an interest if you were in the investment business, saying “What do you like?” And then it turned and I remember the final page of the chapter would be you’d be at a party and everybody would be talking about stocks. And then people would recommend stocks to me. And then I remember not only that, but the stocks would go up. I’d look in the paper and I’d notice they’d go up in the next three months. And then you’ve done the full cycle of the speculative cycle that people hate stocks, they despised, they don’t want to hear anything about ’em, now they’re buying everything and cab drivers are recommending stocks. So that was sort of the cycle I remember going through from the ’60s and early ’70s all the way to ’87.
Where were you when the Crash of ’87 came?
Well, I was very well prepared for the Crash of 1987. My wife and I took our first vacation in eight years and we left on Thursday in October and I think that day the market went down 55 points and we went to Ireland, the first trip we’d ever been there. And then on Friday, because of the time difference, we’d almost completed the day and I called and the market was down 115. I said to Carolyn, “If the market goes down on Monday, we’d better go home.” And “We’re already here for the weekend. So we’ll spend the weekend.” So it went down 508 on Monday, so I went home. So in two business days, I had lost a third of my fund. So I figured at that rate, the week would have been a rough week. So I went home. Like I could do something about it. I mean it’s like, you know, if there was something I could do.
I mean there I was – but I think if people called up and they said, “What’s Lynch doing,” and they said, “Well, he’s on the eighth hole and he’s every par so far, but he’s in a trap, this could be a triple bogey,” I mean I think that’s not what they wanted to hear. I think they wanted to hear I’d be there lookin’ over – I mean there’s not a lot you can do when the market’s in a cascade but I got home quick as I could.
Why did the Crash of ’87 happen?
Well, I think people had not analyzed ’87 very well. I think you really have to put it in perspective. 1982, the market’s 777. It’s all the way to ’86. You have the move to 1,700. In four years – the market moves from 777 to 1,700 in four years. Then in nine months, it puts on a thousand points. So it puts on a thousand points in four years, then puts on another thousand points in the next nine months. So in August of 1987, it’s 2,700. It’s gone up a thousand points in nine months. Then it falls a thousand points in two months, 500 points the last day. So if the market got sideways at 1,700, no one would have worried, but it went up a thousand in nine-ten months and then a thousand in two months, and half of it in one day, you would have said “The world’s over.” It was the same price.
So it was really a question of the market just kept going up and up and it just went to such an incredibly high price by historic, price-earnings multiple load, dividend yields, all the other statistics, but people forget that basically, it was unchanged in 12 months. If you looked at September 1986 to October ’87, the market was unchanged. It had a thousand points up and a thousand points down and they only remember the down. They thought, “Oh, my goodness, this is the crash. It’s all over. It’s going to go to 200 and I’m going to be selling apples and pencils,” you know. But it wasn’t. It was a very unique phenomenon because companies were doing fine. Just, you know, you’d call up a company and say, “We can’t figure it out. We’re doin’ well. Our orders are good. Our balance sheet’s good – we just announced we’re gonna buy some of our stock. We can’t figure out why it’s good down so much.”
Was that the most scared you ever were in your career?
’87 wasn’t that scary because I concentrate on fundamentals. I call up companies. I look at their balance sheet. I look at their business. I look at the environment. The decline was kinda scary and you’d tell yourself, “Will this infect the basic consumer? Will this drop make people stop buying cars, stop buying houses, stop buying appliances, stop going to restaurants?” And you worried about that. The reality, the ’87 decline was nothing like 1990. Ninety, in my 30 years of watching stock very carefully, was by far the scariest period.
What was so scary about 1990?
Well, 1990 was a situation where I think it’s almost exactly six years ago approximately now. In the summer of 1990, the market was around 3,000, Economy’s doing okay, and Saddam Hussein decides to walk in and invade Kuwait. So we have an invasion of Kuwait and President Bush sends 500,000 troops to Saudi to protect Saudi Arabia. There’s a very big concern about, you know, “Are we going to have another Vietnam War?” A lot of serious military people said, “This is going to be a terrible war.” Iraq has the fourth-largest army in the world. They really fought very well against Iran. These people are tough. This is going to be a long, awful thing. So people were very concerned about that, but, in addition, we had a very major banking crisis.
All the major New York City banks, Bank of America, the real cornerstone of this country were really in trouble. And this is a lot different than if W.T. Grant went under or Penn Central went under. Banking is really tight. And you had to hope that the banking system would hold together and that the Federal Reserve understood that Citicorp, Chase, Chemical, Manufacturers Hanover, Bank of America were very important to this country and that they would survive. And then we had a recession.
Unlike ’87 you called companies, in 1990 you called companies and say, “Gee, our business is startin’ to slip. Inventories are startin’ to pile up. We’re not doing that well.” So you really at that point in time had to believe the whole thing would hold together, that we wouldn’t have a major war. You really had to have faith in the future of this country in 1990. In ’87, the fundamentals were terrific and it was – it was like one of those three for two sales at the K-Mart. Things were marked down. It was the same story…
…Tell the story about your wife stumbling on a big stock for you in the supermarket.
I had a great luck company called Hanes. They test-marketed a product called L’Eggs in Boston and I think in Columbus, Ohio, maybe three or four markets. And Carolyn, ah, brought this product home and she was buying and she said, “It’s great.” And she almost got a black belt in shopping. She’s a very good shopper. If we hadn’t had these three kids, she now – when Beth finally goes off to college, I think we’ll be able to resume her training.
But she’s a very good shopper and she would buy these things. She said, “They’re really great.” And I did a little bit of research. I found out the average woman goes to the supermarket or a drugstore once a week. And they go to a woman’s speciality store or department store once every six weeks. And all the good hosiery, all the good pantyhose is being sold in department stores. They were selling junk in the supermarkets. They were selling junk in the drugstores.
So this company came up with a product. They rack-jobbed it, they had all the sizes, all the fits, a down they never advertised price. They just advertised “This fits. You’ll enjoy it.” And it was a huge success and it became my biggest position and I always worried somebody’d come out with a competitive product, and about a year-and-a-half they were on the market another large company called Kaiser-Roth came out with a product called No Nonsense. They put it right next to L’eggs in the supermarket, right next to L’eggs in the drugstore. I said, “Wow, I gotta figure this one out.”
So I remember buying – I bought 48 different pairs at the supermarket, colours, shapes, and sizes. They must have wondered what kind of house I had at home when I got to the register. They just let me buy it. So I brought it into the office. I gave it to everybody. I said, “Try this out and come back and see what’s the story with No Nonsense.” And people came back to me in a couple of weeks and said, “It’s not as good.” That’s what fundamental research is. So I held onto Hanes and it was a huge stock and it was bought out by Consolidated Foods, which is now called Sara Lee, and it’s been a great division of that company. It might have been a thirty-bagger instead of a ten-bagger if it hadn’t been bought out.
The beginning of the bull market in 1982 and the environment. Were you surprised?
1982 was a very scary period for this country. We’ve had nine recessions since World War II. This was the worst. 14 percent inflation. We had a 20 percent prime rate, 15 percent long governments. It was ugly. And the economy was really much in a free-fall and people were really worried, “Is this it? Has the American economy had it? Are we going to be able to control inflation?” I mean there was a lot of very uncertain times.
You had to say to yourself, “I believe it in. I believe in stocks. I believe in companies. I believe they can control this. And this is an anomaly. Double-digit inflation is a rare thing. Doesn’t happen very often. And, in fact, one of my shareholders wrote me and said, “Do you realize that over half the companies in your portfolio are losing money right now?” I looked up, he was right, or she was right. But I was ready. I mean I said, “These companies are going to do well once the economy comes back. We’ve got out of every other recession. I don’t see why we won’t come out of this one.” And it came out and once we came back, the market went north.
Nobody told you it was coming.
It’s lovely to know when there’s a recession. I don’t remember anybody predicting 1982 we’re going to have 14 percent inflation, 12 percent unemployment, a 20 percent prime rate, you know, the worst recession since the Depression. I don’t remember any of that being predicted. It just happened. It was there. It was ugly. And I don’t remember anybody telling me about it. So I don’t worry about any of that stuff. I’ve always said if you spend 13 minutes a year on economics, you’ve wasted 10 minutes.
So what should people think about?
Well, they should think about what’s happening. I’m talking about economics as forecasting the future. If you own auto stocks you ought to be very interested in used car prices. If you own aluminium companies you ought to be interested in what’s happened to inventories of aluminium. If your stock is hotels, you ought to be interested in how many people are building hotels. These are facts. People talk about what’s going to happen in the future, that the average recession lasts 2 years or who knows? There’s no reason why we can’t have an average economic expansion that lasts longer. I mean I deal in facts, not forecasting the future. That’s crystal ball stuff. That doesn’t work. Futile…
…Can the little guy play with the big guy in the stock market?
There’s always been this position that the small investor has no chance against the big institutions. And I always wonder whether that’s the person under four-foot-eight. I mean they always said the small investor doesn’t have a chance. And there’s two issues there. First of all, I think that he or she can do it, but, number two, the question is, people do it anyway. They invest anyway. And if they so believe this theory that the small investor has no chance, they invest in a different format.
They said, “This is a casino. I’ll buy stock this month. I’ll sell it a month later,” the same kind of performance that they do everywhere. When they look at a house, they’re very careful. They look at the school system. They look at the street. They look at the plumbing. When they buy a refrigerator, they do homework. If they’re so convinced that the small investor has no chance, the stock market’s a big game and they act accordingly, they hear a stock and they buy it before sunset, they’re going to get the kind of results that prove the small investor can do poorly.
Now if you buy a – you make a mistake on a car, you make a mistake on a house, you don’t blame the professional investors. But now if you do stupid research, you buy some company that has no sales, no earnings, a terrible financial position and it goes down, you say, “Well, it because of the programmed trading of those professionals,” that’s because you didn’t do your homework. So I – I’ve tried to convince people they can do a job, they can do very well, but they have to do certain things…
…Talk about market timing.
The market itself is very volatile. We’ve had 95 years completed this century. We’re in the middle of 1996 and we’re close to a 10 percent decline. In the 95 years so far, we’ve had 53 declines in the market of 10 percent or more. Not 53 down years. The market might have been up 26 finished the year up four, and had a 10 percent correction. So we’ve had 53 declines in 95 years. That’s once every two years. Of the 53, 15 of the 53 have been 25 percent or more. That’s a bear market. So 15 in 95 years, about once every six years you’re going to have a big decline. Now no one seems to know when there are gonna happen. At least if they know about ’em, they’re not telling anybody about ’em.
I don’t remember anybody predicting the market right more than once, and they predict a lot. So they’re gonna happen. If you’re in the market, you have to know there’s going to be declines. And they’re going to cap and every couple of years you’re going to get a 10 percent correction. That’s a euphemism for losing a lot of money rapidly. That’s what a “correction” is called. And a bear market is 20-25-30 percent decline. They’re gonna happen. When they’re gonna start, no one knows. If you’re not ready for that, you shouldn’t be in the stock market.
I mean stomach is the key organ here. It’s not the brain. Do you have the stomach for these kind of declines? And what’s your timing like? Is your horizon one year? Is your horizon ten years or 20 years? If you’ve been lucky enough to save up lots of money and you’re about to send one kid to college and your child’s starting a year from now, you decide to invest in stocks directly or with a mutual fund with a one-year horizon or a two-year horizon, that’s silly. That’s just like betting on red or black at the casino.
What the market’s going to do in one or two years, you don’t know. Time is on your side in the stock market. It’s on your side. And when stocks go down, if you’ve got the money, you don’t worry about it and you’re putting more in, you shouldn’t worry about it. You should worry about what are stocks going to be 10 years from now, 20 years from now, 30 years from now. I’m very confident.
If you had invested in ’66, it would have taken 15 years to make the money back.
Well, from ’66 to 1982, the market basically was flat. But you still had dividends in stocks. You still had a positive return. You made a few percent a year. That was the worst period other than the 1920s, in this century. So companies still pay dividends, even though if their stock goes sideways for ten years, they continue to pay you dividends, they continue to raise their dividends. So you have to say to yourself, “What are corporate profits going to do?” Historically, corporate profits have grown about eight percent a year. Eight percent a year. They double every nine years. They quadruple every 18. They go up six-fold every 25 years. So guess what? In the last 25 years corporate profits have gone up a little over six-fold, the stock market’s gone up a little bit over six-fold, and you’ve had a two or three percent dividend yield, you’ve made about 11 percent a year. There’s an incredible correlation over time.
So you have to say to yourself, “What’s gonna happen in the next 10-20-30 years? Do I think the General Electrics, the Sears, the Wal-Marts, the MicroSofts, the Mercks, the Johnson & Johnsons, the Gillettes, Anheiser-Busch, are they going to be making more money 10 years from now, 20 years from now? I think they will.” Will new companies come along like Federal Express that came along in the last 20 years? Will new companies come along like Amgen that make money? Will new companies come along like Compaq Computer? I think they will. There’ll be new companies coming along that make money. That’s what you’re investing in.
4. Roughly Right or Precisely Wrong – Ben Carlson
I have a love-hate relationship with historical market data.
On the one hand, since we can’t predict the future, calculating probabilities from the past in the context of the present situation is our only hope when it comes to setting expectations for financial markets. On the other hand, an overemphasis on historical data can lead to overconfidence if makes you believe that backtests can be treated as gospel.
In some ways markets are predictable in that human nature is the one constant across all environments. This is why the pendulum is constantly swinging from manias to panics. In other ways markets are unpredictable because stuff that has never happened before seems to happen all the time…
…Let’s say you put $5,000 into the initial S&P 500 ETF (SPY) right around when it started at the beginning of 1994. On top of that you also contribute $500/month into the fund. Simple right?
Here’s what this scenario looks like:
Not bad.
This is the summary:
- Initial investment (start of 1994): $5,000
- Monthly investment: $500
- Total investments: $181,000
- Ending balance (April 2023): $915,886
Plenty of volatility along the way but this simple dollar cost averaging strategy would have left you with a lot more money than you initially put into it.
Even though things worked out swimmingly by the end of this scenario there were some dark days along the way. You can see on the chart where the purple line dips below the blue line in 2009 by the end of the stock market crash from the Great Financial Crisis. By March of 2009 you would have made $96,000 in contributions with an ending market value of a little more than $94,000. So that’s more than a decade-and-a-half of investing where you ended up underwater.
It wasn’t prudent but I understand why so many investors threw in the towel in 2008 and 2009. Things were bleak. Everything worked out phenomenally if you stuck with it but investing in stocks can be painful at times…
…Just for fun, let’s reverse this scenario to see what would happen if you started out in 1994 with the same ending balance but now you’re taking portfolio distributions.
Like this:
- Initial balance (start of 1994): $915,886
- Annual portfolio withdrawal: 4% of portfolio value
An ending balance of more than $4 million while spending $1.7 million along the way from a starting point of a little less than $1 million is pretty, pretty good.
The usual caveats apply here — past performance says nothing about future performance, no one actually invests in a straight line like this, no one invests in a single fund like this, no one uses this type of withdrawal strategy in retirement nor do they invest 100% in stocks while doing so, etcetera, etcetera, etcetera.
5. ‘I can’t make products just for 41-year-old tech founders’: Airbnb CEO Brian Chesky is taking it back to basics – Nilay Patel and Brian Chesky
Lots of companies are bringing their people back to the office. The idea that, you know, people are going to be in a different house every time you see them on a Zoom call has somewhat faded. Is that still part of the bet for Airbnb? Or are you shifting to this other model?
Yeah. Let me tell you how I think it’s going to play out. And of course, we’re just all in the business of predicting the future, and the problem is it doesn’t always age well. I think that, like, pure work from home or pure remote is ending.
I generally think the future is flexibility. Here’s the calculation every CEO has to make: are you more productive having people physically in an office together and then constraining who you hire to a 30-mile or a 60-mile commuting radius to the office?
Or by allowing your team to be able to hire people from anywhere? And the truth is, it probably depends on the role. A lot of our software engineers or accountants, certain types of lawyers, we probably don’t need them physically in the office with everyone else. There’s certain creative functions or people on certain teams that we probably do want together physically quite a lot.
And then the question is, “Do we need them together 50 weeks a year?” And the answer for us is no. We actually go in spurts. We do these product releases, so we kind of need people together months at a time, and they can choose to live here, but if they want to go away for a couple months, if people want to go away for the summer, that’s possible.
I think we’re going to start to live in a much more nuanced world where the companies aren’t going to have all the people in the office. They’re going to decide that some roles are most effective being on a small team in the office, but a giant sea of desks probably isn’t the most effective thing, and many roles will be much more effective when allowing flexibility so you can have a global talent pool.
I think there’s going to be a post-pandemic equilibrium that we haven’t seen yet that’s going to play out over the coming years…
…You have a lot of decisions to make. You’re obviously very thoughtful about how you make decisions and how you see the company going. How do you make decisions? What’s your framework?
Can I answer that question with a story? So, in 2011, I had my first crisis. We had our first crisis. A woman named EJ was a host in San Francisco. And one day, someone came, and they trashed her apartment. And I went on, and I wrote a letter. I published it on TechCrunch and I said, “We’ve resolved the issue.”
And then, of course, EJ said, “No, you didn’t resolve the issue.” And I was misinformed, and this crisis brewed. And then basically what happened was within days, every time I tried to communicate something, I kind of seemed to keep making it worse. And then I hired these crisis communications professionals, and I had these outside counsels, and they were giving me what seemed like good counsel.
They basically said, “Be careful about admitting fault. Be careful about this. Don’t say that. Do this, do that.” And every time I got advice and every time I tried to manage to an outcome, I seemed to make the situation worse because I think what people really wanted was authenticity. They really wanted me to, you know, just speak from the heart.
And at some point there was — this is in 2011—we were one of the first hashtags. There was #ransackgate and #ripAirbnb. I mean, people literally thought we weren’t going to recover from this because they thought we had no solution.
And at this point, I came to a conclusion that the most important decision I’m going to make would be based on principles, not on outcomes. In other words, I was going to make principle decisions, not business decisions. And the principle decision is: if I can’t figure out the outcome, how do I want to be remembered?
And I said, “Well, I don’t know how this is going to play out. Whatever I’m going to do is probably going to make the situation worse. But I’m just going to say wholeheartedly, ‘I’m sorry.’ I’m going to tell the story, and I’m going to do something crazy. I’m going to do more than what is expected of me.”
What was expected was we make it right for customers. So we ended up with this $50,000 guarantee. It started as a $5,000 guarantee. Marc Andreessen came by my office at midnight. He had just funded the company, and he said, “Add a zero.” And then suddenly we said we would provide $50,000 protection retroactively to everyone on the platform.
And it actually was one of the biggest moments in the company. And ever since then, I came to the conclusion that I’m going to try to make principle decisions, not business decisions. And then this led to another development, which is first principle thinking, which I’m sure you’re aware of. I think a lot of us think by analogy, but if you can understand the first principles of something, then you can really make a decision.
So I’ve been applying this ever since. And it all came back to us during the pandemic because, in January and February 2020, I noticed our business fell off a cliff. And within eight weeks, we lost 80 percent of our business. And on March 15th, the Ides of March, we called an emergency board meeting.
It was a Sunday, I’ll never forget it. And in this board meeting, I wrote out a series of principles about how to manage the crisis. And the first principle I set is we’re going to act decisively. The second is we’re going to preserve cash. The third is we’re going to act with shareholders in mind. And the fourth is we’re going to win the next travel season.
And I had even more detailed principles, and I said to the board, “I’m going to have to make like a thousand decisions a week, and so I can’t run every decision by you. So instead, let’s agree on the principles, and I’ll use those principles to make these decisions.” And I think a lot of people really struggle in a crisis or in times when they’re moving quickly because they don’t have data or the data’s changing.
But if you have a deep understanding of something, that’s better. My issue with A-B experimentation, for example, is that a lot of times, when people choose A or B, they don’t know why B worked. So let’s say, “Oh B works.” Well, why did B work? Because if you don’t know why B works, then you can never change it because you don’t actually have any intellectual property developed around B.
So experimentation’s fine if you know why the experiment worked and if it reinforced your understanding. So I try to make decisions based on first principles. And those first principles are based on whatever we believe in, and what we believe in might be right, might be wrong in the eyes of others, but that’s how we do it.
And you know, it really comes down to listening to people. I try to have qualitative and quantitative information, art and science. I try to balance being in the lab with being in the field. And I try to be as close as I can to decisions as possible. I try to get emotionally invested. A lot of people say if you do a layoff or fire people, don’t get emotionally invested.
I say that’s exactly what you want. You want to understand deeply all the costs. And then if you can still make the decision, then you know you’ve made the right decision. So I generally say be principled, be as close to the decision-making as possible, and get as emotionally invested in something as you can. And then explain your thinking. The exercise of having to explain your thinking clarifies your thinking. A lot of people, they feel something, but they can’t explain their thinking. It’s a good indication that their thinking is still cloudy.
So that’s kind of how we do it. It’s first-principle oriented. It’s clear, it’s hopefully compassionate. We get as close to the decision, and as connected to emotions, as possible. It’s the head and the heart.
The last time you were on, we talked a lot about the structure of the company.
You said that when the pandemic hit, the business had cratered 80 percent. A good quote you said, that I think about all time, is, “I stared into the abyss.” And then you restructured the company. You had a functional startup structure. Then you’d gone into a divisional structure, and you said, “You know what?
I’m pulling this back into a functional structure. We have one division. I’m going to run it all. I’m going to make sure I see everything.” You’re talking about going through customer service complaints now. Are you still in that structure? Has it worked?
Yeah. I mean, we are still in that structure. We decided, let’s go back to being a functional organization. And I actually drew inspiration from Apple around the same time that the pandemic hit is when I started talking to Jony Ive.
We brought him on board a little later. I also hired somebody who changed the trajectory of the company named Hiroki Asai. He was the creative director at Apple, and they really kind of brought me along on this methodology Steve Jobs had. Steve Jobs came back to Apple in 1997.
They were like 90 days from bankruptcy or maybe even fewer. And it was divisionalized. I think it had something like 80 products. And he did two things. He cut most of the products, and he went back to a functional organization, and that’s what we did.
And the other thing we did, which seemed crazy at the time, and it’s now totally intuitive, is we put the entire company on one road map. So for most tech companies, every executive has their own swim lanes. We said, “You have no swim lanes. Everyone works on everything together. Your only swim lane is your function.
We’re going to all collaborate.” I said, “I’m not going to push decision-making down. I’m going to pull decision-making in.” I’m the chief editor. I’m like an orchestra conductor, and I have to understand enough about each instrument to make sure it creates one sound. The other thing I said is, “We’re going to connect product and marketing together.”
Product at a company are like chefs, marketing are like waiters, and they never allow the waiters in the kitchen, or they get yelled at. And I thought, well, what if you actually have them collaborate on product? What if marketing, you know, challenges engineering and engineering inspires marketing? They could actually be connected.
And I think you can tell the health of the organization by how connected engineering and marketing are. And so we did this. We then started doing release cycles, which meant instead of doing this agile, bottoms-up AB testing, shipping continuously every minute of every day… Now we do some of that still. We said 70–80 percent of our product release is going to be done like hardware.
We’re going to ship stuff twice a year. And the reason we’re going to do that is we’re going to embrace constraints. When you ship stuff at the same time, everyone’s on a deadline. Then I meet with every single team every week, every two weeks, or every four weeks. I’m working and editing the work. I’m making sure it all fits together.
It ladders up to a cohesive product story. And then we have this function called product marketing. It’s actually outbound marketing plus product management in one role.
This is very much like Apple, by the way. Apple has product marketing at scale.
Yes, and we took that from them because they’re really good at talking about the product.
We don’t have senior product managers at Airbnb. If you’re a senior product manager, you also have to do outbound marketing. You’re not allowed to decouple the roles. We have no pure product marketers who don’t do product management.
We don’t allow that. And their job is to keep the entire company stitched together and make sure we understand the story we’re telling, who the product’s for, and make sure everything we deliver ships to that product. So we now do two releases a year. The reason we’re talking is because we just did our summer release for May, and what we found is this: when I told people, Nilay, about this development process, the first thing everyone said is, “This is going to be horrible. No one’s going to wanna work together. It’s going to stifle innovation. It’s going to be too top-down. You’re not going to have as many ideas. It’s going to be a bottleneck,” et cetera. “I can tell you all the reasons this is a bad idea.” What we found is we ship way faster. We have now shipped 340 upgrades. We shipped over 53 upgrades today.
It creates a drumbeat for the organization, a rhythm. There is very little bureaucracy. Now we do say no to more things. There are some downsides, like you can’t do as many divergent things because everything is cohesive and integrated. But anything on the road map ships. Almost never do we greenlight something and it doesn’t happen.
So the answer to your question is we’ve been able to ship significantly faster and the paradox is that people are actually happier. As I created more constraints, as the culture got a little more top-down, as it was more integrated… Everyone, if they could have, 99 percent of people would’ve voted against this idea [at the beginning] because it doesn’t intuitively sound like something fun to work in. Almost everyone, at least people still here, seem to be happier. Now, maybe there’s a bias of the people who like it decided to stay, and the people who don’t like it decided to leave. There might be that, too. I want to acknowledge that.
But ultimately I do think the company’s much more productive, and it actually bears out financially. When we were doing this bottoms-up free for all approach, which is kind of my pejorative for it, we were basically losing $250 million in EBITDA a year. We were not profitable. Growth was slowing, cost was rising.
Last year, we did $3.5 billion in free cash flow and actually I believe, Nilay — this might be true now — for every dollar we earn, I think we earn more free cash flow than Apple, Google, or Microsoft. More than 40 percent of revenue becomes free cash flow. Now we’re not nearly the size of them.
That’s not the point. But the point is it’s extremely efficient. It helps to be a marketplace that’s capital-light, but it also helps to have one marketing department. It helps to not have a lot of waste. It helps to have one rhythm of the organization…
…There’s like an AI stack. The bottom of the AI stack is what you might call base models. And there’s like three to five base models. So Google has, like, maybe a couple of ‘em. OpenAI has one.
Anthropic has one. Microsoft Research kind of has one, though they seem to be mostly tied to OpenAI at this point. So those are the base models. Think of it like a highway. Those are infrastructure companies. They’re building the highway. We’re not going to be building base models ‘cause we’re not going to be building infrastructure.
The layer on top of that is now tuning the models. Tuning the models is going to be really important. If you and I go to ChatGPT and we ask it a question, we’re probably going to get something like the same answer. And that would be because ChatGPT doesn’t know your preferences and doesn’t know my preferences.
And for many queries getting the same answer is great. But what if you ask, like, “Hey, where should I go on vacation?” Or like, “Who’s a good person to, like, date?” Well, depends. Who are you? What do you want in your life? And so I think that there needs to be a personalization layer on top of AI, and that’s going to come from the data you have and the permission you get from customers.
Now, I think our vision is eventually one day, we’re going to be one of the most personalized AI layers on the internet.
We’re going to design, hopefully, some of the leading AI interfaces. We’re going to basically try to deeply understand you, learn about you, care about you, and be able to understand your preferences…
…Here’s one of the great things that AI does: think about it — 130 years ago, only probably a few people could use a camera, right? It was a highly technical thing. It was expensive. Most people take photos now.
Anyone in the world can basically use a camera. They’re ubiquitous, they’re on our phones. I kind of think software development’s going to be like that, that pretty soon, everyone will be able to develop software because software is just a language you have to learn. Now there’s always going to be development below the stack at the deeply technical level, but a lot of that front-end development is going to be replaced by natural language. As this happens, so many more people can develop software, and as so many more people can develop software, I think you’re going to see software in everything.
We’re going to have to create interface standards because we don’t want to ping-pong back and forth and just be totally confused. I don’t even think search is the right use case for every task. Sometimes it’s voice, sometimes it’s a conversation.
Ultimately, it would be great if interfaces understood you better, right? This is a problem with Airbnb. Every time you come back to Airbnb, we show you a whole bunch of categories. And if you’re a budget traveler, we show you lux.
And if you’re wealthy, we might show you Airbnb Rooms. We should know more about you. The way companies have tried to solve personalization is through data regression of clicks, right? So if I clicked on something in the past, then I’m going to show you that in the future. But that’s actually not a great way to understand somebody.
Like maybe I went on Amazon, I bought a bunch of alcohol, but I’m actually now a recovering alcoholic and I’m trying not to drink. And you don’t know that, and the mini bar has alcohol there because I order all the time, but I actually feel bad about it and I actually don’t want to drink.
And so I think companies developing a better understanding of you, having a sense of your personalized preferences, having that interface is going to be really important. And I actually think it allows many more people to participate in the economy because, in the past, the only people that could build software were engineers…
…You’ve given me so much time. Last question. We’ve talked a lot about Apple and how inspired you are by Apple structures, by their organization, by their processes, by Steve Jobs.
You do have this long-standing deal now with Jony Ive and his agency LoveFrom. Have they shipped anything with you? What does that relationship look like? What has it accomplished for you?
In 2014, we were designing our new logo, what people know now as our logo, and I knew Jony Ive, and I sent it to him, and he basically talked to me about how you shouldn’t have flat lines, you should have this continuous curvature.
And so he and the team spent some time, and he redesigned the spleens of the curb. And so the actual logo that you see on Airbnb, the final mark, was designed by Jony Ive. I kept in touch with him, and then when I read that he left Apple, I said, “We gotta work together.” And we started talking a lot in the beginning of 2020.
Again, it happened perfectly coincidentally, with a period of time when I felt like we had a crisis, almost the size of Apple’s crisis in the late ’90s. And I turned to him, and obviously, he gave me a lot of great advice. He told me a couple things.
The first thing is we used to talk about our mission as belonging. And the problem with using the word belonging is I noticed that employees were confusing belonging with inclusion. And then they were conflating inclusion with the lack of discrimination. And then they said, “Well, our mission is to not discriminate.”
And I said, “Well, that’s a really low bar.” Of course, you shouldn’t discriminate, but when we say belonging, it has to be more than just inclusion. It has to actually be the proactive manifestation of meeting people, creating connections in friendships. And Jony Ive said, “Well, you need to reframe it. It’s not just about belonging, it’s about human connection and belonging.”
And that was, I think, a really big unlock. The next thing Jony Ive said is he created this book for me, a book of his ideas, and the book was called “Beyond Where and When,” and he basically said that Airbnb should shift from beyond where and when to who and what?
Who are you and what do you want in your life? And that was a part of the inspiration behind Airbnb categories, that we wanted people to come to Airbnb without a destination in mind and that we could categorize properties not just by location but by what makes them unique, and that really influenced Airbnb categories and some of the stuff we’re doing now.
The third thing is he really helped me think through the sense that Airbnb is a community. You know, this is really interesting. Most people think of Jony Ive as like somebody who deals with atoms, like aluminum and glass.
But actually he said that he spent 30 years building tools. And what he realizes now is that we don’t just need more tools — we need more connections. And I thought that was a really profound thing and. He really helped us think of ourselves — this is a subtle word shift, Nilay — but going from a marketplace to a community because in a marketplace, everything’s a transaction, and in a community, everything should not be a transaction.
Otherwise, those aren’t real relationships or real connections. And so he has helped me think about how to shift from a marketplace to a community. I think some of that inspiration is what led to Airbnb Rooms, what led to the creation of the host passport. But he and the team are heads-down with me working on stuff that’s going to ship next May and next November.
One of the things Jony and I talked about is we need permission to do new things. So I’ll just use a rewind. It’s the year 2005, maybe 2006, and everyone was hoping that Apple would come out with an iPhone. And in January 2007, Steve Jobs announced it.
Now the reason we all wanted Steve Jobs to come out with an iPhone in 2006 and 2007 was because most of us loved our iPods. None of us were asking Gateway computer to come out with a phone because we didn’t love Gateway’s laptops. And so basically I think we need to have permission to do new, innovative things.
And we have permission when people love the core thing. And I came to the conclusion that we needed to focus much more on our core service. People were still complaining about pricing, cleaning fees, all sorts of things about Airbnb. And again, it comes from this disease that happens to a lot of founders or this thing that happens where we fall out of love with our core business.
And, as I told you a couple years ago, when we almost lost our business, we stared into the abyss. There’s something about almost losing something that makes you fall back in love with it. And I think maybe that happened to our core business, and we said, “Before we go on to new things, before we do whatever we’re going to do, we’re going to get back to the core, back to the basics, and really just focus on making this product something that people love.”
And so for the last few years, that’s what we’ve tried to do. We’ve tried to basically fix as many things as possible. That’s why we created a blueprint, something that Jony and others helped inspire, which is to say, “Let’s be systematic about the complaints. Let’s be systematic by how we address the feedback, and let’s tell a story to the community about all the things we’re fixing.”
And my hope is that by the end of this year, we’ll have addressed to some extent every single thing people are complaining about. They really do love the service. It feels truly delightful.
So our vision for this company is the following: that Airbnb is a marriage of art and science, that we’re a truly creatively-led company. Our two core values are basically design creativity married with technologies and then this idea of community and connection. A company with this real humanistic feel that you come to Airbnb, we ask you a series of questions.
We learn about you. We understand who you are, what you want. We design these incredibly simple interfaces, and then our job as a host is we develop these really robust matching algorithms, and then we can match you to whatever you want.
And so if we can build this incredibly robust identity system, if we can have the most robust profiles, almost like a physical social network where we can connect people together in this community, if we can use AI to augment customer service, to deeply understand and resolve your issues within seconds, not just minutes or hours, and we can then build these incredibly simple interfaces where we match you to whatever you want in your life, that’s basically the idea of where we’re trying to go. And Jony Ive and his team, they’re working on things just in that area.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Alphabet (parent of Google), Amazon, Apple, Meta, and Microsoft. Holdings are subject to change at any time.
