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We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 04 July 2021:

1. RNAi is Setting a High Bar for Gene Editing – Maxx Chatsko

Although there are many therapeutic modalities in the field of genetic medicines, individual investors have been most excited about gene editing tools such as CRISPR-Cas9. The valuations of publicly-traded CRISPR companies suggest investors have very high expectations — perhaps unreasonably high considering the general lack of meaningful data.

In the second quarter of 2021, three different drug candidates or drug products based on RNA interference (RNAi) have demonstrated the ability to reverse three different diseases — all with convenient dosing…

…Intellia Therapeutics (NASDAQ: NTLA) is initially focused on developing in vivo drug candidates for gene silencing applications. The approach uses CRISPR-Cas9 to “knock out” a gene by disrupting the sequence responsible for its expression. At a high level, the clinical objective of reducing protein levels is identical to that of RNAi.

Not surprisingly, there’s plenty of overlap between the company’s knockout pipeline and those of RNAi drug developers. Intellia Therapeutics’ lead in vivo drug candidate is taking aim at hATTR, while the next most-advanced program is targeting hereditary angioedema (HAE), another Alnylam target. Discovery-stage programs that might use knockouts include PH1, A1AT liver disease, and others that promise to square off with RNAi drug candidates and drug products.

On the one hand, gene knockouts promise to drive deeper reductions in protein levels than current-generation RNAi. They would also represent a permanent, irreversible change to a patient’s genome. Although CRISPR gene editing compounds must be administered intravenously, a single dose is the most convenient dosing.

On the other hand, there are clinical and commercial challenges for investors to consider. First-generation CRISPR gene editing requires making a double-stranded break in the genome, which is repaired with mutagenic (“mutation-causing”) processes. Double-stranded breaks can result in random insertions and deletions of genetic material far from the cut site, while there’s evidence that sections of chromosomes can be rearranged. Each is a hallmark of cancer cells. (It’s important to note that these are on-target effects inherent to CRISPR gene editing, separate from the more familiar off-target effects discussed in the media, which are largely exaggerated.)

The long-tail safety risks from on-target effects might not become evident until years after clinical development is completed. Therefore, drug candidates utilizing CRISPR-mediated knockouts might generate promising safety and efficacy data in clinical trials, but regulators might balk at speedy approvals for knockouts or require long-term patient monitoring. This is especially true considering many indications being targeted by knockouts will likely have safe, effective, and convenient treatments provided by RNAi. In other words, although these indications are called “rare diseases,” regulators probably won’t be under pressure to approve knockout drug candidates for the sake of patients.

Even if knockouts earn regulatory approval, it could be difficult to dislodge RNAi treatments. For example, by the time Intellia’s lead drug candidate reaches the market (assuming it does), most global hATTR patients will be taking treatments from Alnylam. An estimated 3% of global patients are taking the relatively inconvenient Onpattro, although many more could be eligible for treatment with vutrisiran should it earn regulatory approval in 2021 or 2022. That could result in Intellia boasting an approved knockout drug product and frustratingly little opportunity to capture market share. It’s more likely that the market experiences cutthroat pricing competition between RNAi treatments and gene knockouts, which would be great for patients, but perhaps not so great for the drug developers arriving a little too late to the market.

2. The Devastating Decline of a Brilliant Young Coder – Sandra Upson 

In Cloudflare’s early years, Lee Holloway had been the resident genius, the guy who could focus for hours, code pouring from his fingertips while death metal blasted in his headphones. He was the master architect whose vision had guided what began as a literal sketch on a napkin into a tech giant with some 1,200 employees and 83,000 paying customers. He laid the groundwork for a system that now handles more than 10 percent of all internet requests and blocks billions of cyberthreats per day. Much of the architecture he dreamed up is still in place.

But some years before the IPO, his behavior began to change. He lost interest in his projects and coworkers. He stopped paying attention in meetings. His colleagues noticed he was growing increasingly rigid and belligerent, resisting others’ ideas, and ignoring their feedback.

Lee’s rudeness perplexed his old friends. He had built his life around Cloudflare, once vowing to not cut his hair until the startup’s web traffic surpassed that of Yahoo. (It took a few short months, or about 4 inches of hair.) He had always been easygoing, happy to mentor his colleagues or hang out over lunch. At a birthday party for Zatlyn, he enchanted some children, regaling them with stories about the joys of coding. The idea of Lee picking fights simply didn’t compute.

He was becoming erratic in other ways too. Some of his colleagues were surprised when Lee separated from his first wife and soon after paired up with a coworker. They figured his enormous success and wealth must have gone to his head. “All of us were just thinking he made a bunch of money, married his new girl,” Prince says. “He kind of reassessed his life and had just become a jerk.”…

…WHAT MAKES YOU you? The question cuts to the core of who we are, the things that make us special in this universe. The converse of the question raises another kind of philosophical dilemma: If a person isn’t himself, who is he?

Countless philosophers have taken a swing at this elusive piñata. In the 17th century, John Locke pinned selfhood on memory, using recollections as the thread connecting a person’s past with their present. That holds some intuitive appeal: Memory, after all, is how most of us register our continued existence. But memory is unreliable. Writing in the 1970s, renowned philosopher Derek Parfit recast Locke’s idea to argue that personhood emerges from a more complex view of psychological connectedness across time. He suggested that a host of mental phenomena—memories, intentions, beliefs, and so on—forge chains that bind us to our past selves. A person today has many of the same psychological states as that person a day ago. Yesterday’s human enjoys similar overlap with an individual of two days prior. Each memory or belief is a chain that stretches back through time, holding a person together in the face of inevitable flux.

The gist, then, is that someone is “himself” because countless mental artifacts stay firm from one day to the next, anchoring that person’s character over time. It’s a less crisp definition than the old idea of a soul, offering no firm threshold where selfhood breaks down. It doesn’t pinpoint, for example, how many psychological chains you can lose before you stop being yourself. Neuroscience also offers only a partial answer to the question of what makes you you.

Neural networks encode our mental artifacts, which together form the foundation of behavior. A stimulus enters the brain, and electrochemical signals swoosh through your neurons, culminating in an action: Hug a friend. Sit and brood. Tilt your head up at the sun and smile. Losing some brain cells here or there is no big deal; the networks are resilient enough to keep a person’s behaviors and sense of self consistent.

But not always. Mess with the biological Jell-O in just the right ways and the structure of the self reveals its fragility.

Lee’s personality had been consistent for decades—until it wasn’t…

…In mid-March of 2017, Kristin and Lee went to a neurologist to get the results of an MRI. To Kristin, it seemed that the neurologist had initially been skeptical of her concerns. Lee was young, healthy, and communicative.

The MRI told a different story: There was atrophy in the brain inconsistent with the age of the patient, the neurologist reported to them. When Kristin asked her what that meant, she said Lee had a neurodegenerative disease of some kind, but they’d need to do more tests to get a specific diagnosis. One of their doctors suggested they go to the Memory and Aging Center at UC San Francisco…

…The neurologists delivered their verdict: He appeared to have a textbook case of frontotemporal dementia—known by the shorthand FTD—specifically, the behavioral variant of that disease. It targets a network of brain regions sometimes described as underpinning one’s sense of self. As the pathological process advanced, it was carving a different person out of Lee’s raw substance.

The term frontotemporal dementia refers to a cluster of neurodegenerative diseases that affect a person’s behavior or speech while leaving memory largely intact, at least early on. Unlike Alzheimer’s disease, FTD isn’t well known. It is a rare disease, affecting roughly one in 5,000 people, though many of the neurologists who study it believe it is underdiagnosed. What is known is that for people under the age of 60, it is the most common form of dementia. Still, as a man in his thirties, Lee was unusually young to be afflicted. For some patients, one of several genetic mutations turns out to be the likely cause, and a subset of patients have a family history of neurodegenerative diseases. But nothing in the neurologists’ investigations turned up even a hint as to why Lee had been struck down.

Regardless of cause, the prognosis is grim. There’s no treatment. Lee’s doctors warned that his symptoms would grow worse, and that over time he would likely stop talking, become immobile, and struggle to swallow, until eventually an infection or injury would likely turn fatal. The best the doctors could recommend was eating a balanced diet and getting exercise.

The family sat stunned at the neurologist’s words. The brain scans were undeniable. On a wall-mounted screen the doctors showed a cross-section of the four lobes of Lee’s brain. In a healthy brain, the familiar, loopy folds of tissue appear white or gray and push up against the edges of the cranium, filling every available space. Lee’s brain looked nothing like that.

Black voids pocked his frontal lobe, areas where brain tissue had gone dead. Seeing it, Kristin gasped. “There were huge dark spots in his brain,” Alaric says. “That’s what … that made it concrete.”

3. Interview: Marc Andreessen, VC and tech pioneer – Noah Smith and Marc Andreessen

N.S.: One of the themes of my blog so far has been techno-optimism. I have to say that some of that attitude comes from talking to you over the years! Are you still optimistic about the near future of tech? And if so, which tech should we be most excited about?

M.A.: I am very optimistic about the future of tech, at least in the domains where software-driven innovation is allowed. It’s been a decade since I wrote my essay Software Eats The World, and the case I made in that essay is even more true today. Software continues to eat the world, and will for decades to come, and that’s a wonderful thing. Let me explain why.

First, a common criticism of software is that it’s not something that takes physical form in the real world. For example, software is not a house, or a school, or a hospital. This is of course true on the surface, but it misses a key point.

Software is a lever on the real world.

Someone writes code, and all of a sudden riders and drivers coordinate a completely new kind of real-world transportation system, and we call it Lyft. Someone writes code, and all of a sudden homeowners and guests coordinate a completely new kind of real-world real estate system, and we call it AirBNB. Someone writes code, etc., and we have cars that drive themselves, and planes that fly themselves, and wristwatches that tell us if we’re healthy or ill.

Software is our modern alchemy. Isaac Newton spent much of his life trying and failing to transmute a base element — lead — into a valuable material — gold. Software is alchemy that turns bytes into actions by and on atoms. It’s the closest thing we have to magic.

So instead of feeling like we are failing if we’re not building in atoms, we should lean as hard into software as we possibly can. Everywhere software touches the real world, the real world gets better, and less expensive, and more efficient, and more adaptable, and better for people. And this is especially true for the real world domains that have been least touched by software until now — such as housing, education, and health care…

…N.S.: Your most famous quote is probably “Software is eating the world”. How is that likely to manifest over the next decade or so? Will A.I. automate whole business models out of existence? Will old-line companies that try to patch software into their existing operations and business models get outcompeted by companies that start out as software companies and then branch into traditional markets, as my friend Roy Bahat believes? Or something else?

M.A.: My “software eats the world” thesis plays out in business in three stages:

1. A product is transformed from non-software to (entirely or mainly) software. Music compact discs become MP3’s and then streams. An alarm clock goes from a physical device on your bedside table to an app on your phone. A car goes from bent metal and glass, to software wrapped in bent metal and glass.

2. The producers of these products are transformed from manufacturing or media or financial services companies to (entirely or mainly) software companies. Their core capability becomes creating and running software. This is, of course, a very different discipline and culture from what they used to do.

3. As software redefines the product, and assuming a competitive market not protected by a monopoly position or regulatory capture, the nature of competition in the industry changes until the best software wins, which means the best software company wins. The best software company may be an incumbent or a startup, whoever makes the best software.

My partner Alex Rampell says that competition between an incumbent and a software-driven startup is “a race, where the startup is trying to get distribution before the incumbent gets innovation”. The incumbent starts with a giant advantage, which is the existing customer base, the existing brand. But the software startup also starts with a giant advantage, which is a culture built to create software from the start, with no need to adapt an older culture designed to bend metal, shuffle paper, or answer phones.

As time passes, I am increasingly skeptical that most incumbents can adapt. The culture shift is just too hard. Great software people tend to not want to work at an incumbent where the culture is not optimized to them, where they are not in charge. It is proving easier in many cases to just start a new company than try to retrofit an incumbent. I used to think time would ameliorate this, as the world adapts to software, but the pattern seems to be intensifying. A good test for how seriously an incumbent is taking software is the percent of the top 100 executives and managers with computer science degrees. For a typical tech startup, the answer might be 50-70%. For a typical incumbent, the answer may be more like 5-7%. This is a huge gap in software knowledge and skill, and you see it play out every day across many industries.

As for Artificial Intelligence, as an engineer myself, it’s hard to be quite as romantic as a lot of observers tend to be. AI — or, to use the more prosaic term, Machine Learning — is an incredibly powerful technology, and the last decade has seen explosive AI/ML innovation that’s increasingly showing up in the real world. But it’s still just software, math, numbers; the machines aren’t becoming self aware, Skynet is not here, computers still do exactly what we tell them. So AI/ML continues to be a tool used by people, more than a replacement for people.

A famous story from the birth of computer science has Alan Turing, father of the computer, lunching with Claude Shannon, father of information theory, in the AT&T executive dining room near Bell Labs in the early 1940s. Turing and Shannon engage in an increasingly heated discussion about the future of thinking machines when Turing stands up, pushes his chair back, and says loudly, “No, I’m not interested in developing a powerful brain! All I’m after is a mediocre brain, something like the President of AT&T.'”

I think about AI like that — although, for the record, the President of AT&T is a friend of mine, and he’s actually quite bright. I suspect “Artificial Intelligence” is the wrong framing for the technology; Doug Engelbart was probably more correct with what he called “Augmentation”, so think “Augmented Intelligence”. Augmented Intelligence makes machines better thought partners for people. This concept is clearer for considering both the technological and economic consequences. What we should see in a world of rapidly proliferating Augmented Intelligence is the opposite of a jobless dystopia — productivity growth, economic growth, new job growth, and wage growth.

And I think this is exactly what we are seeing. It’s worth remembering that before COVID, only 18 months ago, we were experiencing the best economy in 70 years — rising wages, low and falling unemployment, and essentially zero inflation. The economy was even improving more for lower skill and lower income people than it was for people like us, despite computers everywhere. Unemployment among the most disadvantaged in our society — people without even high school degrees — was as low as it’s ever been. This is far from an automation-driven dystopia; in fact, it’s the payoff from three centuries of increasing mechanization and computerization. As the economy recovers from COVID, I expect these positive trends to continue.

4. Individuals or Teams: Who’s the Better Customer for SaaS Products? – David Sacks

There are three main reasons for the superior economics of Team products:

1. Deal Sizes

Team products have larger initial contract values as a result of the ability to sell multiple seats. By contrast, the small deal sizes of Individual products may be insufficient to justify the cost of a sales team. Unless the Individual product is highly viral, it will be easier to build a distribution strategy for a Team product.

2. Retention

Team products are stickier than Individual products. To use a gaming analogy, multiplayer mode is more engaging than single-player mode. Users can do more interesting things when coworkers are part of the experience; value creation is higher.

Once a team is collaborating in a product, no single user can easily make the decision to leave. The decision to migrate to another tool requires coordination (aka a “rip and replace”). By contrast, a solo user can leave an individual product at any time.

Finally, collaboration provides constant opportunities for reactivation. A subscriber who stops using an Individual product is likely churned whereas an inactive user on a Team product is just one notification away from being reengaged. As long as the team maintains some minimum threshold of engaged users, it will avoid churn at the account level.

For all of these reasons, account-level churn rates for Individual plans are commonly around 5% per month, but only 1-2% per month for Team plans. This translates into much higher revenue retention for Team plans.

3. Seat Expansion 

Team plans have the ability to add new seats as the product spreads within a company, creating revenue expansion. As a result, successful Team products have “net negative churn,” meaning that expansion from retained accounts exceeds revenue lost from churned accounts. 

5. It’s Official: US Government Says Electric Vehicles Cost 40% Less To Maintain – Steve Hanley

In its latest study, the Office of Energy Efficiency and Renewable Energy says,

“The estimated scheduled maintenance cost for a light-duty battery-electric vehicle (BEV) totals 6.1 cents per mile, while a conventional internal combustion engine vehicle (ICEV) totals 10.1 cents per mile. A BEV lacks an ICEV’s engine oil, timing belt, oxygen sensor, spark plugs and more, and the maintenance costs associated with them.”…

…Big deal, you say? Who cares about a difference of a measly 4 cents? Consider this. The light duty vehicles — sedans, SUVs, passenger vans and the like — owned and operated by the federal government traveled nearly 2 billion miles in 2019, according to the General Services Administration. That difference of 4 little cents translates into savings of about $78 million a year, according to Motor Trend.

The one thing that the EERE study doesn’t show is the reduction in fuel costs for those government owned vehicles, which allows us to do a little speculating. Let’s assume the average fuel economy for all of them is 20 miles per gallon. That means it would take about 100 million gallons of gasoline to drive 2 billion miles.  Now lets assume that gas costs an average of $3.00 a gallon (I am math challenged so I like to use round numbers). 100 million gallons at 3 bucks a gallon equals $300 million, does it not?

Now let’s assume further that the cost of electricity is roughly half the cost of gasoline. The end result is that a fleet of electric vehicles would save Uncle Sam about $150 million in fuel costs every year. Add in the $78 million in lower maintenance costs and the total annual savings from switching the entire US government fleet to electric vehicles could be $228 million every year from here to eternity or $2.28 billion over the next decade.

6. Casualties of Perfection – Morgan Housel

So many people strive for efficient lives, where no hour is wasted. But an overlooked skill that doesn’t get enough attention is the idea that wasting time can be a great thing.

Psychologist Amos Tversky once said “the secret to doing good research is always to be a little underemployed. You waste years by not being able to waste hours.”

A successful person purposely leaving gaps of free time on their schedule to do nothing in particular can feel inefficient. And it is, so not many people do it.

But Tversky’s point is that if your job is to be creative and think through a tough problem, then time spent wandering around a park or aimlessly lounging on a couch might be your most valuable hours. A little inefficiency is wonderful.

The New York Times once wrote of former Secretary of State George Shultz:

His hour of solitude was the only way he could find time to think about the strategic aspects of his job. Otherwise, he would be constantly pulled into moment-to-moment tactical issues, never able to focus on larger questions of the national interest.

Albert Einstein put it this way:

I take time to go for long walks on the beach so that I can listen to what is going on inside my head. If my work isn’t going well, I lie down in the middle of a workday and gaze at the ceiling while I listen and visualize what goes on in my imagination.

Mozart felt the same way:

When I am traveling in a carriage or walking after a good meal or during the night when I cannot sleep–it is on such occasions that my ideas flow best and most abundantly.

Someone once asked Charlie Munger what Warren Buffett’s secret was. “I would say half of all the time he spends is sitting on his ass and reading. He has a lot of time to think.”

This is the opposite of “hustle porn,” where people want to look busy at all times because they think it’s noble.

7. Tobi Lütke – Sriram Krishnan and Tobi Lütke

This is a very natural segue to my next question. One of the theories behind this whole set of interviews is diving into the atomic bits of how we spend our time in meetings. This time compounds over the long term and has a massive effect. What does a good meeting with Tobi look like? Alternatively, what does a bad meeting with you look like?

So actually, agendas are not terribly successful with me. I admire how other CEOs I’ve spoken with always have a strict agenda where everyone has a speaking slot. I find that absolutely fascinating. Even if I really set myself to an agenda and say, “Okay, great, this is going to happen,” I can’t get through half of a meeting like this. Partly because a good meeting is, for me personally, when I learn something.

I started a company because I love learning. I went into programming because I found it fascinating. During meetings, I just love to hear the things that teams have discovered. When you’re discussing an idea or a decision, I want to know what has been considered. To be honest, I find myself more interested in the inputs of an idea than the actual decision. I say this because when I have my own ideas, the first thing I tend to do is just try to falsify them, to figure out why what I’m thinking about is probably incorrect. This is actually something that I have to explain to people that I work with. If I like someone’s idea, I tend to do the same thing: I try to poke holes in it.

I usually say, “Well, the implication of this choice means you’ve made the following assumptions. What inputs did you use to make these foundational assumptions?” Effectively, I’m trying to figure out if an idea is built on solid fundamentals. I find that shaky fundamentals tend to be where things often go wrong. The decision being discussed could be the perfect decision according to the various assumptions that everyone came into the room with. But if those assumptions are faulty, the seemingly perfect decision is faulty too. Interestingly, assumptions are rarely mentioned in the briefing docs or in the slide deck. Usually, I’m trying to make sure those are rock solid. Through this process, I invariably end up learning something completely new about a field. That gives me great confidence and comfort both in the decision and the direction…

…You try and design how your company spends time and attention. One particular incident came up recently which I found really fascinating. You wrote a script to delete every recurring meeting at Shopify. Talk about why you did that, and what you ended up learning from it.

[Laughs] So, going back a little bit further there—you know what, I should talk about books. One thing that is interesting is how people have accused Shopify of being a book club thinly veiled as a public company.

We tend to read a lot and talk about a lot of books. We read Nassim Taleb’s books and one person on my team began talking about Antifragile and gave an outline. He said, “I think Nassim is putting a word to the thing that you keep talking about…”

Now, I come from an engineering perspective. One of my biggest beefs with engineers, in general, is that they love determinism. I think there’s very little determinism in engineering left that’s of value. An individual computer is deterministic; once you introduce even just a network connection into the mix, everything becomes unpredictable and you have to write code that’s resilient to the unknown. Most interesting things come from non-deterministic behaviors. People have a love for the predictable, but there is value in being able to build systems that can absorb whatever is being thrown at them and still have good outcomes.

So, I love Antifragile, and I make everyone read it. It finally put a name to an important concept that we practiced. Before this, I would just log in and shut down various servers to teach the team what’s now called chaos engineering.

But we’ve done this for a long, long time. We’ve designed Shopify very well because resilience and uptime are so important for building trust. These lessons were there in the building of our architecture. And then I had to take over as CEO.

When that happened, I made two decisions: one, I’m going to try to learn as much about business as possible. But, if business is very different from software architecture, I’m going to be no good no matter what I do. And so, I ran an experiment to treat engineering principles, software architecture, complex system design, and company building as the same thing. Effectively, we looked for the business equivalent of just turning off servers to see if the system has resiliency. For instance, we used to ask people to use their mouse on their non-dominant hand for a day. We introduced these little nudges to ensure that people didn’t become complacent.

There are a bunch of really fun stories around this. I had a conversation with one of my co-founders, and we were discussing our unique problem: namely, Shopify was a company initially for American customers, built by German founders, in Canada.

[Both laugh]

It’s a very complex thing.

For instance, we talk a lot about how different cultures interact because we couldn’t have built Shopify without the Canadian optimism. These things were not necessarily things that we would recognize, at least when it comes to optimism, coming from Germany. That said, there are also challenges between cultures. For instance, Canadians are unbelievably nice. Like, no one wants to ever say anything to upset anyone. This is why we need to emphasize the importance of feedback. In this way, the uphill battle is more real for us than it would be for a Silicon Valley company.

There’s so much on the theme of how Shopify is not a Silicon Valley company. I think you pointed out one of these themes right here.

Exactly.

For instance, if we had built the company in Israel, this would not have been a challenge. It’s really important to understand that culture is real and multi-layered. The “host” city’s effect on the employees in that local office is very real. To do something world class, you have to show up with a lot of world class skills, and not a lot of downsides.

In this way, pushing people to give feedback is something very important for us.

That was a tangent, but to get back to the question you asked, we found that standing meetings were a real issue. They were extremely easy to create, and no one wanted to cancel them because someone was responsible for its creation. The person requesting to cancel would rather stick it out than have a very tough conversation saying, “Hey, this thing that you started is no longer valuable.” It’s just really difficult. So, we ran some analysis and we found out that half of all standing meetings were viewed as not valuable. It was an enormous amount of time being wasted. So we asked, “Why don’t we just delete all meetings?” And so we did. It was pretty rough, but we now operate on a schedule.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Shopify. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 27 June 2021:

1. Little Stories – Morgan Housel

After years of tests, Lockheed engineers finally built a stealth plane. They could fly their prototype without radar picking it up. It was a miracle.

Then one day, it just stopped working.

“You lit up the radar like a goddamn Christmas tree” an engineer tells a test pilot in the book Skunkworks. “They saw him coming from 50 miles away.”

No one could figure it out. They hadn’t made any changes to the plane’s design.

The cause, they eventually discovered, highlighted the complexity of their work.

A screw hadn’t been secured tightly enough during maintenance, its head extending a few millimeters above the plane’s surface. That was maybe half a drill spin less than ideal. It was more than tight enough for the plane to operate. But on radar, it “appeared as big as a barn door.”

There’s a lot of hidden leverage in the world – tiny things that seem inconsequential but operate in a tightly wound system where one flaw can bring everything down.

It also makes me wonder: How much incredible technology has been abandoned in frustration when we were half a drill spin away from success?…

…Skateboarder Tony Hawk landed a 900 – two and a half spins – at the 1999 X Games. It was the biggest achievement the sport had ever seen, the equivalent of the four-minute mile.

It catapulted Hawk into legend status. His video game came out a year later and sold 30 million copies. Six Flags named a rollercoaster after him.

But here’s the craziest part of this story: fifteen years later, an eight-year-old landed a 900.

Hawk was also the first person to land a 720 (two spins) – a feat later accomplished by a second-grader.

A lot of sports work like that. One person raises the bar over what previously seemed impossible, and that becomes the baseline for a new generation to build upon.

Just qualifying for the Boston Marathon requires a time that, 100 years ago, would put you within nine minutes of a world record.

A gold-medal gymnast 70 years ago would not make the cut in a local competition today.

Same with technology, business, and investment knowledge. One generation builds on the impossible feats of the previous one. It’s like compound interest.

A fifth-grader recently landed a 1080 – three spins, unthinkable in Hawk’s day. Asked what he thought of the achievement, Hawk replied: “It represents everything I love about skateboarding: constant evolution.”

Which is a statement you can apply to just about any field.

2. Tech Companies Discover Hidden Costs of Remote Work – Sarah Krouse

As companies prepare to implement new remote-work policies, they are finding those policies come with a host of unexpected costs. What’s racking up the bills: new time off and financial benefits to boost morale and help with challenges like child care, immigration fees and paperwork for workers who hold visas, and reimbursing employees for home office equipment. Plus there are potential tax costs associated with employees moving to a state where the company doesn’t already have a presence and business registration.

Intuit’s consumer finance app, Credit Karma, incurred an additional 8% to 10% of expenses for new benefits to support remote workers during the pandemic, said Colleen McCreary, the division’s chief people officer. The company added additional mental health benefits such as remote therapy and agreed to cover remote doctor visits that were outside its health plan’s coverage last year—perks that will remain in place as the company reopens its office. It plans to do so fully by September and expects workers to report in person some of the time, but it will not dictate how often or when they must do so.

To limit costs last year, Credit Karma told its 1,300-employee workforce they could only work remotely from certain states like California and North Carolina where the company already has business operations, she said.

A year ago, CEOs or chief financial officers believed their overall costs could fall dramatically if they relied less on real estate and went remote, said John Bremen, a managing director at Willis Towers Watson who advises companies on their work arrangements. But many corporate leaders have come around to a hybrid approach that allows employees to work part time in the office and part time remotely. That means companies aren’t giving up all of their office space as expected…

…More than a year into the pandemic, some tech companies say remote work has improved productivity and morale, in addition to allowing them to hire talent regardless of where workers live. Those benefits, remote work advocates say, surpass any additional financial costs associated with remote and hybrid work.

3. Howard Marks – Embracing the Psychology of Investing – Patrick O’Shaughnessy and Howard Marks

Patrick: [00:09:11] Living through 2020 and now into 2021 has surely been one of the most interesting markets that anyone’s ever seen. You’ve seen a lot of fascinating markets in your career. And I think your memo output in 2020 was prolific. You wrote a lot about the market. How does this 18-month period stack up to your own experience with market history in terms of its uniqueness and the fact that we had a vicious bear market very quickly and then a pretty similarly vicious bull market? It just strikes me as unusual relative to history, and I’m curious your read on it.

Howard: [00:09:43] Mark Twain said, “History does not repeat, but it does rhyme.” And if you look at the cycle of 2020, it doesn’t rhyme with very much. The main reason is because in every other crisis that I lived through, the upcycle, down cycle, let’s say, the cause was endemic. The cause came from within. And most cycles, I think, occur because people become over optimistic and everything departs from the secular trend line in the direction of excess. And as I mentioned, people become excited and enthusiastic and eventually their excitement and enthusiasm take things to an excess. And in the long run, that access is not sustainable. And so you get a correction back toward the trend line. You get a downward correction. But, of course, it goes through the trend line to an excess on the downside, which ultimately turns out to be unsustainable. So you get a correction back up toward the trend line. So I think cycles are best understood not as ups and downs, which sounds kind of random, but as excesses and corrections.

The point is that what happened in 2020 was obviously not the result of excess optimism. It happened because, for an exogenous reason, that is we were hit by a meteor from outer space in the form of a pandemic. That’s what caused the downturn, along with the fact that in order to fight the pandemic the authorities closed business to keep people from infecting each other. So you had, I would say, a manmade recession prompted by an exogenous event. And then you had an upturn which was engineered by the Fed and the Treasury, not because the upturn did not occur because things got so bad that they were unsustainable and there was a natural regression back toward the trend line of the economy. The recovery occurred because the Fed and Treasury did things that caused it. There’s no similarity to past cycles in terms of cause, speed, amplitude, and impact. You had to learn a whole new game plan.

Patrick: [00:11:59] Do you think that that entire new game plan affects all investors going forward? Because you’ve written a lot in the past about the role of liquidity in markets, famously in the Great Depression monetary supply contracted. The toolkit seems to be fight every battle by flooding liquidity into the system, and so how do we adjust our model of the world going forward?

Howard: [00:12:21] I think that there’s every possibility that people will look at the last two experiences, which are 2020 and 2008, the global financial crisis, and say, the Fed obviously has the firepower to prevent every downturn in the economy and they should do so when people think that way. I’m not confident on this subject because I’m not a professional economist or Fed watcher. And you know, you should beware of analogies. But in the forestry business, if there’s a small fire they let it occur and sometimes they even cause some small fires to burn up the fuel that lies on the forest floor. And if you don’t permit any small forest fires, when you finally have one that you can’t put out right away, you’re going to have a doozy because of all the accumulated fuel on the forest floor. I believe that if they prevent every recession, that will give rise to such excesses on the high side, it will be, as I say, unsustainable and will cause a recession and that’s going to be a doozy.

So it just seems to me that if I were running Fed, which I’m absolutely unqualified to do, I would opt for leaving it alone most of the time, the economy, and having it do what it does naturally. All of us in the investment business, I don’t think there are any socialists in the investment business. We’re all in the investment business because we believe in the efficacy of the free market as an allocator of resources. So if you do, then shouldn’t you leave the economy and the capital market alone as much as you can so that it can freely allocate resources? So I guess I would not be an activist.

Now having said that, what they did in 2020 they had to do. And if they hadn’t done it, we’d have a worldwide depression now. And I made the point in one of my memos that just because something has negative possible ramifications doesn’t mean you shouldn’t do it. But in this case, they had to do it. But it did have, in my opinion, negative possible ramifications, so they should try to avoid doing it again anytime soon. And I’m a visual person, so I come up with visual images. And my visual image for the economy is its kind of like a ball at the top of a water spout. And as long as the water spout is strong, the ball stays up in the air, it stays out of the water. So the Fed levitates the economy through the water stock, which consists of liquidity. But it only stays up as long as the Fed is injecting liquidity. And is it appropriate for the Fed to inject incremental liquidity on a permanent basis?

4. What Makes Quantum Computing So Hard to Explain? – Scott Aaronson

The trouble is that quantum computers will not revolutionize everything.

Yes, they might someday solve a few specific problems in minutes that (we think) would take longer than the age of the universe on classical computers. But there are many other important problems for which most experts think quantum computers will help only modestly, if at all. Also, while Google and others recently made credible claims that they had achieved contrived quantum speedups, this was only for specific, esoteric benchmarks (ones that I helped develop). A quantum computer that’s big and reliable enough to outperform classical computers at practical applications like breaking cryptographic codes and simulating chemistry is likely still a long way off.

But how could a programmable computer be faster for only some problems? Do we know which ones? And what does a “big and reliable” quantum computer even mean in this context? To answer these questions we have to get into the deep stuff.

Let’s start with quantum mechanics. (What could be deeper?) The concept of superposition is infamously hard to render in everyday words. So, not surprisingly, many writers opt for an easy way out: They say that superposition means “both at once,” so that a quantum bit, or qubit, is just a bit that can be “both 0 and 1 at the same time,” while a classical bit can be only one or the other. They go on to say that a quantum computer would achieve its speed by using qubits to try all possible solutions in superposition — that is, at the same time, or in parallel.

This is what I’ve come to think of as the fundamental misstep of quantum computing popularization, the one that leads to all the rest. From here it’s just a short hop to quantum computers quickly solving something like the traveling salesperson problem by trying all possible answers at once — something almost all experts believe they won’t be able to do.

The thing is, for a computer to be useful, at some point you need to look at it and read an output. But if you look at an equal superposition of all possible answers, the rules of quantum mechanics say you’ll just see and read a random answer. And if that’s all you wanted, you could’ve picked one yourself.

What superposition really means is “complex linear combination.” Here, we mean “complex” not in the sense of “complicated” but in the sense of a real plus an imaginary number, while “linear combination” means we add together different multiples of states. So a qubit is a bit that has a complex number called an amplitude attached to the possibility that it’s 0, and a different amplitude attached to the possibility that it’s 1. These amplitudes are closely related to probabilities, in that the further some outcome’s amplitude is from zero, the larger the chance of seeing that outcome; more precisely, the probability equals the distance squared.

But amplitudes are not probabilities. They follow different rules. For example, if some contributions to an amplitude are positive and others are negative, then the contributions can interfere destructively and cancel each other out, so that the amplitude is zero and the corresponding outcome is never observed; likewise, they can interfere constructively and increase the likelihood of a given outcome. The goal in devising an algorithm for a quantum computer is to choreograph a pattern of constructive and destructive interference so that for each wrong answer the contributions to its amplitude cancel each other out, whereas for the right answer the contributions reinforce each other. If, and only if, you can arrange that, you’ll see the right answer with a large probability when you look. The tricky part is to do this without knowing the answer in advance, and faster than you could do it with a classical computer.

Twenty-seven years ago, Shor showed how to do all this for the problem of factoring integers, which breaks the widely used cryptographic codes underlying much of online commerce. We now know how to do it for some other problems, too, but only by exploiting the special mathematical structures in those problems. It’s not just a matter of trying all possible answers at once.

5. Twitter thread on the “fighter mentality” of Mark Zuckerberg – Dan Rose

In my experience the best founders develop a fighter mentality. Mark Zuckerberg was a fighter, and without that mentality Facebook would never have achieved its full potential. Here’s what I saw over 13 years working for Zuck:

One of Mark’s first big fights was with his own board + exec team. They tried to convince him to sell the company to Yahoo for $1B in ’06. At the time FB had 5M users (all college) and was 2 yrs old. At the age of 22, Mark stood to gain $300M personally. How could he say no?

Everyone told Mark to sell. Friends said he’d be crazy to pass up $1B. His management team wanted an exit. His board put pressure on him. But Mark knew something they didn’t – FB was on the cusp of launching new products that would completely change the trajectory of the company.

I joined FB in mid-2006, right after Mark made the decision not to sell (I’m glad he did!). He had the courage to go against everyone around him, and he was promptly vindicated the following year when we raised our Series C from Microsoft at $15B.

Within a couple of years after the Yahoo near miss, Mark replaced his entire management team and reconstituted the board. He needed people around him who believed in his vision, people he could trust to fight alongside him. I was one of them…

…The Social Network came out in 2010. Mark had been warned it would portray him in a negative light, and he was appropriately concerned about its impact on team morale, FB’s brand and his personal reputation. His advisors told him to ignore it, keep his head down, stay focused.

In one of the greatest jiu jitsu moves of all time, Mark rented out the Shoreline cinema complex and bussed in the entire company to see the premier of the movie. His first (and probably only) viewing of The Social Network was in a giant cinema with the rest of his employees.

Adding to the surrealness of this scene, Mark’s admin asked me to sit next to him – she thought my positivity would be a calming influence. When the character portraying him was being seduced by a girl, he leaned over and whispered “now this is awkward.” We both laughed out loud!

6. How Software Is Eating the Car – Robert N. Charette

“Once, software was a part of the car. Now, software determines the value of a car,” notes Manfred Broy, emeritus professor of informatics at Technical University, Munich and a leading expert on software in automobiles. “The success of a car depends on its software much more than the mechanical side.” Nearly all vehicle innovations by auto manufacturers, or original equipment manufacturers (OEMs) as they are called by industry insiders, are now tied to software, he says.

Ten years ago, only premium cars contained 100 microprocessor-based electronic control units (ECUs) networked throughout the body of a car, executing 100 million lines of code or more. Today, high-end cars like the BMW 7-series with advanced technology like advanced driver-assist systems (ADAS) may contain 150 ECUs or more, while pick-up trucks like Ford’s F-150 top 150 million lines of code. Even low-end vehicles are quickly approaching 100 ECUs and 100 million of lines of code as more features that were once considered luxury options, such as adaptive cruise control and automatic emergency braking, are becoming standard.

Additional safety features that have been mandated since 2010 like electronic stability control, backup cameras, and automatic emergency calling (eCall) in the EU, as well as more stringent emission standards that ICE vehicles can only meet using yet more innovative electronics and software, have further driven ECU and software proliferation.

Consulting firm Deloitte Touche Tohmatsu Limited estimates that as of 2017, some 40% of the cost of a new car can be attributed to semiconductor-based electronic systems, a cost doubling since 2007. It estimates this total will approach 50% by 2030. The company further predicts that each new car today has about $600 worth of semiconductors packed into it, consisting of up to 3,000 chips of all types…

…How little software is developed by car makers is illustrated by comments made in 2020 by Herbert Diess, then CEO Volkswagen Group and now its Chairman, when he admitted that “hardly a line of software code comes from us.” VW estimates that only 10% of the software in its vehicles is developed in-house. The other 90%  is contributed by tens of suppliers, and at some OEMs, this number reportedly reaches more than 50. 

So many software suppliers, each with their own development approach, using their own operating systems and languages obviously adds another level of complication, especially in performing verification and validation. This is highlighted by a recent Strategy Analytics and Aurora Labs survey of software developers across the automotive supply chain asking how difficult it was to know when a code change in one ECU affects another. Some 37% of those surveyed indicated it was difficult, 31% indicated it was very difficult, 7% indicated that it was pretty darn close to impossible, while 16% indicated that it was not possible.

Car companies and their suppliers are realizing that they must collaborate more to keep tighter control of data configuration management to keep unintended consequences from occurring due to unanticipated ECU code changes. But both admit that there is still a way to go. 

7. Twitter thread on the rise of intangibles and what it means for investors – Eugene Ng

Sharing my key takeaways from @mjmauboussin’s latest piece on “The Impact of Intangibles on Base Rates” and how it should affect us as investors. A must read! https://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdf?1624494283562

1️⃣ Thinking Casually White heavy check mark: Taking the inside view, gathering lots of information of what is of interest, combining with your own input & experience & project into the future and coming up with a narrative trumps…

2️⃣ Thinking statistically Cross mark: Taking the outside view, relying on the past & base rates. Not relying of own experience, but others experience. Outcomes tend to be average, outliers rare, best for bell-shaped distributions, not in stocks where power laws and tails exist.

3️⃣ Intangibles & Growth. Two key characteristics: (1) Grow Faster Chart with upwards trend: Enjoy strong economies of growth, cheap to reproduce and share Rightwards arrow companies can grow much faster & more persistent; (2) Decline Faster Chart with downwards trend: Obsolescence and sunkeness Rightwards arrow companies can decline much faster

4️⃣ Intangibles & Access: The distinction between tangible is access. Only one can use a tangible asset at one time, whereas many can use an intangible asset at the same time. Marginal cost of sharing can be very low. E.g. Software.

5️⃣ Intangibles & Scalability: Because intangibles are much more scalable, companies that rely on intangibles can grow much faster than those built on tangibles. Chart with upwards trendRocket

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Facebook and Microsoft. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 20 June 2021:

1. Blink – Michael Batnick

I can’t believe it’s been ten years since my mother passed away. The passage of time felt like the blink of an eye.

I was only 26 when my mother died. She only had 26 years with me. My fingers are shaking while I type because this is the most painful part. It’s not that I didn’t have enough time with her. It’s that she didn’t have enough time with me. She didn’t see me get married. She never got to meet her grandkids. She was robbed of some of the most joyful parts of life.

Even though my mother was the center of my universe, I don’t spend every second of every day thinking about her. It comes in waves. Tidal waves…

…I’m sad that my mother isn’t here, but I’m a better person for it. I would undo this in a second if I could, but losing her gave me a perspective on life that would have been impossible otherwise.

Ten years ago, I was a child in a man’s body. I had no prospects for a bright future. Death was staring me in the face, both metaphorically and literally. Now I’m a successful adult. I don’t mean that in the traditional sense of people equating success with money.

I’m successful because I don’t yearn for more. I have my wife and my boys and my freedom. I’m good. I have a unique appreciation of what I have because I already lost everything when my mother died. Now I have everything I need and everything I want.

Health is the only thing that matters. We all know this. But some people know it more than others. Losing my mother hurt like hell, but I’m grateful for what came of it. It taught me not to take anything in life for granted, especially life itself. Years aren’t promised, so I try to enjoy every day.

2. Technology Saves the World – Marc Andreessen

Only 15 months ago — March 13, 2020 — COVID-19 became a national emergency in the United States. My assumption at the time was that COVID lockdowns could extend as long as five years, the previous speed record for modern vaccine development, with many millions of deaths — a generational cataclysm.

While COVID certainly has been plenty devastating in the U.S. and around the world, with 600,000 Americans dead of and with COVID, and with shockingly broad destruction of American small businesses, it has not been nearly as destructive as it could have been. We are coming out of COVID years early, with many livelihoods and businesses preserved, compared to what we had any right to expect. And overwhelming credit goes to our spectacular technology industry.

The most amazing COVID technology story has to be the vaccines. Moderna, a product of the American venture capital system, created the first mRNA COVID vaccine within two days of receiving the genetic code for COVID by email. It’s hard to overstate the tremendous advance in both speed and effectiveness of this new technological platform — and now that we know how well mRNA vaccines work, we can look forward to decades of new vaccines both for potential COVID variants and for many other health threats. We now have the technological tools to quite literally code nature, and the payoff to human flourishing will be profound…

…Finally, possibly the most profound technology-driven change of all — geography, and its bearing on how we live and work. For thousands of years, until the time of COVID, the dominant fact of every productive economy has been that people need to live where we work. The best jobs have always been in the bigger cities, where quality of life is inevitably impaired by the practical constraints of colocation and density. This has also meant that governance of bigger cities can be truly terrible, since people have no choice but to live there if they want the good jobs.

What we have learned — what we were forced to learn — during the COVID lockdowns has permanently shattered these assumptions. It turns out many of the best jobs really can be performed from anywhere, through screens and the internet. It turns out people really can live in a smaller city or a small town or in rural nowhere and still be just as productive as if they lived in a tiny one-room walk-up in a big city. It turns out companies really are capable of organizing and sustaining remote work even — perhaps especially — in the most sophisticated and complex fields.

This is, I believe, a permanent civilizational shift. It is perhaps the most important thing that’s happened in my lifetime, a consequence of the internet that’s maybe even more important than the internet. Permanently divorcing physical location from economic opportunity gives us a real shot at radically expanding the number of good jobs in the world while also dramatically improving quality of life for millions, or billions, of people. We may, at long last, shatter the geographic lottery, opening up opportunity to countless people who weren’t lucky enough to be born in the right place. And people are leaping at the opportunities this shift is already creating, moving both homes and jobs at furious rates. It will take years to understand where this leads, but I am extremely optimistic.

3. Stripe: Thinking Like a Civilization – The Generalist (Mario)

The Roman poet Ovid coined that phrase, roughly translatable as “the end justifies the mean.” With that deft turn, Ovid summarized a school of moral philosophy referred to as consequentialism. 

If Silicon Valley’s ethics can be distilled into a coherent ethics, this is it: do what is necessary to change the world, no matter how many toes are trampled, privacy rights violated, or human norms deranged. The method does not matter, consequentialism tells us, the result is what counts. 

This is the ethos of Kalanick and Zuckerberg, and many tribute acts. It could not be further from the morality of the Collisons. 

Though perhaps they would disagree, and could certainly put a finer point on their particular weltanschauung, Patrick and John seem to adhere to a deontological ethics. This school, best articulated by glorious weirdo Immanuel Kant, suggests that the morality of an action is determined independently of its outcome. Though much too simple, deontologists argue that things like intent matter. 

All of which is to say that the Collisons seem to have forged an alternative for elite leadership that does not seek to excuse a noisome, polluting process with a favorable outcome. Just as Patrick notes that the “no jerks policy” companies sometimes apply to restrain themselves from hiring brilliant assholes is “too low a bar,” Stripe’s leadership seems to understand that success alone is not enough. You have to win with grace…

…Above all, Stripe is defined by its commitment (and espousal) of a multi-decade timeline. Leadership constantly reinforces the message that Stripe is in its early innings and that its most defining products are yet to come. 

This is a useful message for nearly every company to advance, but it carries extra weight given Patrick’s intellectual influences and extracurriculars, particularly his service as a Board Member for The Long Now Foundation. The organization, “established in 01996” exists to encourage thinking about humanity over the next 10,000 years. 

Stripe doesn’t have explicit plans for the next several millennia, but the company has succeeded in shifting employee mindset to think further ahead. In an interview with Ken Norton, Business Lead Michael Siliski articulated this trait: 

“We talk a lot about building multi-decade abstractions. I personally like to think 10 to 30 years to get out of the three- to five-year mode, but generally here people do say “multi-decade” a lot. Patrick and John and the entire leadership team are clear that this is a long-term bet and that we’re still very early. That long time horizon comes from the top, and it’s in the culture. And my sense is it’s been like that at Stripe since day one.”

Others make the same note. From Patio11:

“[M]y career success metric is making a large improvement in the lives of a large number of software people. I encourage anyone who isn’t already planning on a 45 year time scale to try taking a stab at this and reviewing the plan every year; the weeks are long but the years fly by sometimes. At present I’m at Stripe because I think it is probably the best option available in working against those long-term goals. 15 years down; 30+ to go; still early innings.”

Even in the visionary world of technology, this extremity of foresight is unusual; it’s even more uncommon to have it effectively distributed through an organization. 

This manifests in the company’s recruiting. Patrick notes that “the biggest thing we did differently…is just being ok to take a really long time to hire people.” 

It took the company six months to hire its first two employees. Describing their “painfully persistent” process of recruiting in his conversation with Lilly, Patrick noted that he could think of five employees that Stripe had taken three or more years to recruit. 

This approach makes sense when you think of it in a decades-long framework. As he notes in that discussion, employees — particularly managers — bring more employees with them over the years. Taking the time to find someone truly exceptional, though painful in the short term, compounds year after year. 

4. Are Inflation Worries Over-Inflated? – Chuin Ting Weber

What happens to markets when inflation becomes a problem? For the US, historically, the worst inflationary period in recent memory was from 1973-1981. CPI started to print consistently in low single digits from 1982 onwards, with the exception of 6.0% in 1990.  Many analysts point to OPEC and the oil crisis as the trigger for cost-push inflation starting in 1973. However, others have put the responsibility for the long drawn-out stagflation and economic slowdown on tightening by the Fed – the same concern being flagged by the worry camp today.

Let us take a look at the historical performance of the S&P500 during this time, for a one-time investment made at the start of each of these “bad” inflation years…

…For the two most unfortunate start points (1973 and 1974), it took 9-12 years for a lump sum investment to break even, net of inflation. This is consistent with MoneyOwl’s guidance for investors who wish to be in a 100% equities portfolio to have a time horizon of 10-15 years, based on the historical performance of markets. These are not magic numbers, but it gives the long-term investor some degree of comfort. In the example, we did not factor in dollar cost averaging, which is a more common way of investing and which could change the breakeven thresholds; nor adjustments to the investor’s personalised CPI or PCE based on his basket of goods.

However, what is counter-intuitive and remarkable, is that despite the inflationary environment, an investment took less than 5 years to break even on a real return basis in 7 out 9 years, or 78% of the time. In 6 out of 9 years, you break even within a year. More intriguing is that in as many as 4 years, investments started at the beginning of those years have not lost money since. This includes investments deployed at the beginning of the worst inflationary year of 1979.

Our little empirical study of US inflation vs. markets tells us that:

• There is no relationship between contemporaneous inflation and an investor’s long-term experience, or even in any single year. In fact, you can be handsomely rewarded by markets even during a period of very bad inflation.
• The odds of a positive return from being invested and staying invested are much higher than trying to time the market. Staying invested is valid even in inflationary and uncertain times.
• Having a line in the water to capture an outsized return if it comes along can cushion you against cumulative losses into the long term. We do not want to miss those years by timing the market, because it matters to our overall, cumulative return.
• There is a case for Dollar Cost Averaging during times of severe economic dislocation, because it means that your total return will not be the worst-case and you will also catch the good years. The regular saving plan (RSP) way of investing out of your monthly income, which is what we recommend for our mass market accumulation clients, has benefits beyond the formation of a good financial habit.

This walk down a “scary” memory lane supports what we already know about markets: that asset prices move quickly to incorporate all expectations and information about inflation and its potential impact on interest rates and equity prices. This is also indeed, a random walk. There is a randomness to year-on-year return and any investment approach built on trying to outguess markets repeatedly is quite futile.

5. He makes up to $3,900 a week racing cars on a blockchain game – Shihan Fang

If you haven’t heard of F1 Delta Time or its publisher, Hong Kong-based Animoca Brands, you’re not alone. It’s a game so new that it doesn’t even have its own Wikipedia page. F1 Delta Time is among a growing category of online games that are leading the “play-to-earn” movement. Built on blockchain technology, these games allow players to make money from in-game assets.

This offers gamers more opportunities to monetize their gaming efforts. Many games currently allow for virtual items to be traded for virtual currency. But unless they are built on blockchain technology, there’s no way to cash out either the virtual currency or items.

As such, gamers who want to turn their hobby into their line of work either have to climb their way up to a professional level or participate in peripheral activity like livestreaming or giving gaming tutorials. Another popular but tedious option is to build up an account and then sell it in an off-game transaction.

The play-to-earn movement has gained tremendous investor interest of late. Two unicorns were minted just last month, with Animoca Brands raising US$88.8 million and San Francisco-based Forte securing US$185 million at a valuation of $1 billion each. Neither of these companies are strictly in the gaming business; instead, they provide the blockchain platform to enable play-to-earn games…

…Besides Revv, F1 Delta Time issues digital assets tied to NFTs. It’s a process known as the “tokenization” of an asset and enables what Animoca calls “true digital ownership,” or having identifiable property rights to unique digital assets.

To race, each player needs a driver, a car, and a set of tires. These can be further customized by gear (suit, helmet, gloves, boots, trinket) and parts (front wing, rear wing, transmission, brakes, turbocharger, energy store, engine block, suspension) to create the best configuration for every race and type of weather.

Each of the aforementioned assets can be bought and sold on game-agnostic NFT marketplaces such as Opensea. Even the segments of each race track are tokenized, allowing owners to make money from entry fees.

Another novel application of NFTs is the in-game “staking” mechanism, a virtual event that allows players to temporarily lock up their cars in exchange for revv. According to its developers, “staking” was designed to increase the value and utility of in-game NFTs, and to allow owners to generate passive Revv income.

All tokenized items come in four levels of rarity: common, epic, legendary, and apex. The rarer the car, the lower the in-game supply, and the higher the earnings from staking.

NFT enthusiasts may want to note that a tokenized asset is made up of two parts: the NFT itself, which resides on blockchain, and the digital asset, which is stored off-chain, usually on a server run by Amazon Web Services. This means that the digital asset could potentially still be lost if its server is damaged or hacked, or if Amazon goes bust.

According to NFT insiders, this dependency is a weakness of the “centralized storage” model. While no one has the solution yet, there are some nascent efforts to create decentralized storage schemes for more “persistent” availability of assets.

“We have people in our team that are not good gamers at all. But they earn more because of other things like staking. If you’re purely investment and money-driven, there is money for you. If you are just a gamer, then there is something for you. If you like motorsports, there are collectibles. If you are across a few of those sectors, this is perfect,” says Brock.

6. Genetic Control of Aging and Life Span – Jill U. Adams, Ph.D

When studying life span, scientists tend to work with organisms that do not live very long; that way, they can observe the entire course of an organism’s existence and obtain relatively rapid experimental results. One organism that researchers frequently employ in their studies of life span is Caenorhabditis elegans, a microscopic roundworm that typically lives to a ripe old age of two to three weeks. Another advantage of using C. elegans is that these worms have a simple physiology and easily manipulated genes.

Over the last several decades, C. elegans has been the subject of many published studies, but perhaps the most famous of these appeared in 1993. In that paper, researcher Cynthia Kenyon and her associates showed that C. elegans with a specific single-gene mutation lived twice as long as members of the species that lacked this mutation (Kenyon et al., 1993). This finding was groundbreaking for a number of reasons. First, it challenged the prevailing concept that aging occurs as the body deteriorates over time. Second, it led to a shift in thinking, even among researchers who already believed that aging was subject to some sort of genetic control. Prior to this point, most such scientists figured that aging, age-related illnesses, and death were consequences of multiple cellular and physiological processes, and therefore under the regulation of a wide and diverse set of genes. Kenyon’s paper, however, suggested that a single gene could dramatically regulate how long an organism lived, thus opening the door to new hypotheses about modifying life span through genetic manipulation.

The responsible gene is called daf-2, and, in 1997, a research group led by Gary Ruvkun finally solved its DNA sequence (Kimura et al., 1997). Scientists were surprised to find that the protein coded for by this gene (designated DAF-2) looked much like the receptor protein within humans that responds to the hormone insulin. In other words, the worm protein is simply a primitive form of our own insulin receptors…

…So, how does a single gene cause such a dramatic effect? It turns out that daf-2 normally controls many other genes, which in turn regulate a variety of physiological processes at different stages in life. For example, in their studies of C. elegans, researchers have found a large set of genes that are either “turned on” or “turned off” in worms that carry two copies of the daf-2 mutation. The genes that show the most change fall into several different classes, some of which line up nicely with existing hypotheses about the mechanisms of aging in other organisms; this includes the belief that various genes encode for proteins that extend life by acting as antioxidants, regulating metabolism, and exerting an antibacterial effect.

One particular gene affected by daf-2 is daf-16; this gene encodes a transcription factor, or a protein that determines when and where hundreds of other genes are turned on. Normally, the DAF-2 protein (which is an insulin receptor) exerts a dampening effect on the DAF-16 protein through phosphorylation, or the addition of a phosphate group. In the mutant worms, however, DAF-16 is not phosphorylated, and it is thus active and present in cell nuclei. Experiments have determined that this activation of DAF-16 (caused by the absence of a phosphate group) is a necessary step toward life span extension (Figure 1).

7. Harder Than It Looks, Not As Fun as It Seems – Morgan Housel

Good advice that took me a while to learn is that everything is sales. Everything is sales. It’s usually framed as career advice – no matter what your role in a company is, your ultimate job is to help sales. But it applies to so many things.

Everything is sales also means that everyone is trying to craft an image of who they are. The image helps them sell themselves to others. Some are more aggressive than others, but everyone plays the image game, even if it’s subconscious. Since they’re crafting the image, it’s not a complete view. There’s a filter. Skills are advertised, flaws are hidden.

A friend recently complained about how inefficient his employer is. Processes are poor, communication is bad. He then said a competitor company had its act together. I asked him how he knew that – he’s never worked there and has never been inside the company. Fair, he said. It just seems that way from the outside.

But almost everything looks better from the outside. I guarantee workers at the competitor find flaws in the way their company operates, because they know about their company what my friend knows about his: how the sausage is made. All the messy personalities and difficult decisions that you only see when you’re inside, in the trenches. “All businesses are loosely functioning disasters” Brent Beshore says. But it’s like an iceberg, only a fraction is visible.

It’s the same for people. Instagram is full of beach vacation photos, not flight delay photos. Resumes highlight career wins but are silent on doubt and worry. Investing gurus are easy to elevate to mythical status because you don’t know them well enough to witness times when their decision-making process was ordinary, if not awful…

…When you are keenly aware of your own struggles but blind to others’, it’s easy to assume you’re missing some skill or secret that others have. The more we describe successful people as having guru-like powers, the more everyone else looks at them and says, “I could never do that.” Which is unfortunate, because more people would be willing to try if they knew that those they admire are probably normal people who played the odds right.

When someone is viewed as more extraordinary than they are, you’re more likely to overvalue their opinion on things they have no special talent in. Like a successful hedge fund manager’s political views, or a politician’s investment advice. Only when you get to know someone well do you realize the best you can do in life is to become an expert at some things while remaining inept at others – and that’s if you’re good. There’s an important difference between someone whose specific talent should be celebrated vs. someone whose ideas should never be questioned. Eat the orange, throw away the peel.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have no vested interest in any of them. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 13 June 2021:

1. #023 – The A/B sides of the Internet – China Playbook

What’s the number 1 competitive element in an industry?

It’s the status quo, not the competition between competitors. The US has a long commercial history, so many industries and businesses have developed very well over several generations. If we call the last generation companies as the conservatives, then the conservative forces in the US are very strong. In China, the conservative forces are very weak. 

When I just started working on the food delivery business, I conducted some market research and found something that surprised me.

The largest delivery site in the US is called Grubhub, but they only had hundreds of thousands of orders a day. Domino’s Pizza had more orders than it did! Big chains like McDonald’s and KFC didn’t want to work with Grubhub either because they can offer delivery themselves. The delivery service has become a standard in established F&B chains. Additionally, the Americans eat pretty much the same things every day, unlike the Chinese, we have a lot of varieties.

This led to the last-gen solution being rather satisfactory, leaving very little room the the next-gen solution.

From the research that I did at the time, there were only three companies in China focusing on food delivery. In total, their orders were less than 100K a day. There’s no wide consumer awareness [of this product experience]. Their finances were not great either. If we see them as our last-gen, when we started, they were very weak.

What does this mean? It means when we started, we were not just bringing the Internet to the food delivery industry, we were building the food delivery industry itself. In fact, since we’re building the food delivery industry itself, our impact to the industry is much greater than just digitalizing the industry, our commercial value would also be greater.

This is a core difference between China and the US. This is a core difference between China and the US. Considering all these factors, we can understand why American investors can’t understand Meituan.

Lastly, a simple judgment – for the LBS [location-based services] category, China is a much better market than the US due to our population density, labour cost, population size and generational competition…

…Categorizing also has implications for which products can be made into one app and which can’t.

Taobao and Alipay have huge traffic, but putting Ele.me there didn’t do much.

WeChat and its Moments have such great traffic, but Weibo is still thriving.

It’s also why Meituan is able to consolidate so many things into one app, because most of them are in B2.

Douyin and Toutiao are separate apps. They didn’t incorporate Douyin into Toutiao despite Toutiao’s huge traffic.

All these have to do with categorizing. Categorizing correctly involves core competencies, resource allocation, consumer psychology, and organisational abilities.

2. How SEA Tech Giants Solved The “Cold Start” Problem – David Fallarme

If you’re introducing a radically new operating model to the industry, your primary constraint will be supply. You’ll use high-touch tactics to onboard sellers. You’ll need to go where they are or tap into existing networks, then manually onboard them to make sure they’re good representatives of your platform.

If you’re competing within well-understood industry dynamics, then you’ll be constrained by demand. You’ll use tactics with high scalability. This could take the form of owning digital marketing channels where you have an unfair advantage, riding the wave of a media narrative, or localizing wider and faster than anyone else.

A final lesson not explicitly mentioned here is that the solving Cold Start Problem is already hard, but even harder in a fragmented market in Southeast Asia.

Solving it in one country doesn’t necessarily give you a tailwind to set up in another country, even if those countries are neighbors or can speak the same language. And when you think you’ve got it nailed, your market can suddenly turn into a red ocean.

3. An interview with Patrick Collison – Elad Gil and Patrick Collison

Elad Gil:
Stripe has done an amazing job both in terms of scaling and in terms of attracting people with common values and a shared interest in building infrastructure for the internet economy. I’d like to hear some of your thoughts on how to build a culture, and how to let it evolve.

To start, how do you see culture evolving as an organization scales, and what you think is important early versus later in that evolution?

Patrick Collison:
When it comes to culture, I think the main mistakes that companies make are being too precious about it, being too apologetic about it, and not treating it as dynamic and subject to revision.

Generally speaking, and certainly if a company is working well to some degree— if you’re making progress in building the product you want to build and the service you want to create, and if the organization is growing and customers are adopting—there are empirically some things about your culture that are working well. And I often see companies making a mistake by being too abashed about simply being specific about those.

For example, you might believe firmly in the importance of working hard. Or you might believe firmly in the importance of minute attention to detail to the degree that you’re willing to redo something five times over. What often happens is that companies allude to these things, but in overly oblique fashions. They’ll say, “We believe in the importance of commitment,” but won’t be concrete enough to say that, well, we want people who really want to pour their hearts into this for several years, and we expect this to be the singular focus of your working life.

Similarly, on the attention-to-detail front, it’s easy to describe things in overly milquetoast terms without being really explicit, like: “If you work with us, you’re going to have to be okay with your work being repeatedly designated as inadequate, and okay with it being redone several times over.” These aren’t things that everyone is looking for. And you’re going to have to be okay with some people having that conversation with you and deciding that it’s not for them.

If you aren’t having these explicit conversations about what your culture is, the downsides are threefold: You don’t have the right people joining you, and you’re being unfair to those who do join you, in the sense that they end up being surprised by this emergent friction and tension in work styles. Thirdly, and I think this may be the non-obvious one, people’s disposition with regard to the company is actually a function of what they feel like they signed up for. If they feel like they signed up for an all-encompassing project, they’ll be much more willing to treat it that way than if they discovered it by surprise later on. And so you can actually change the outcome simply by being explicit at the outset…

…Elad:
How do you think about reinforcing or reminding employees about an organization’s cultural values? Do you incorporate it as part of performance reviews, incorporating it into weekly all-hands?

Patrick:
I think the macro thing to bear in mind with a lot of culture stuff is that a rapidly scaling human organization is an unnatural thing. The vast majority of human organizations that we have experience with, be it the school, the family, the university, the local community, the church, whatever, these are not organizations that scale really rapidly. And so the cues and the lessons and the habits you might learn from them are not necessarily going to be sufficient for the kind of human organization you’re building, which is perhaps doubling—or even more—in size, year over year.

As a consequence of that, you’ll often hear people talk about things like using explicit cultural values in performance reviews or in weekly all-hands. And you think, “Well, most of the other human organizations I see don’t do that,” and so it seems sort of contrived or whatever. But the difference is that you actually have a much more difficult challenge, which is to maintain a high degree of cohesion despite the really rapid evolution in the group of constituent participants.

So I’m a big fan of all the things you just mentioned. I think most companies start to explicitly encode and articulate their principles or values too late. I would try to produce a provisional revision literally when you’re just a handful of people. Then continue to update it on an ongoing basis, because assuredly there will be things you realize or come to appreciate are wrong over the course of the company.

But I would start with something right from the outset. And I would absolutely weave it into your product development, your collective communications with each other, your decision-making in general. For example, when you’re choosing the right series A investors, say, I think it would be ideal if the principles by which you ran the organization and the culture internally could help guide you to the right kind of investor for the company…

…Elad:
As you look across the Valley now, it seems like there have been some shifts that have created almost a culture of entitlement. People get enormous benefits, then start to complain about things that may not be that important, like the number of times they can get a free haircut on campus. How do you manage that? As people get bigger and bigger benefits, how do you make sure they don’t feel that they deserve everything?

Patrick:
I think that this is simply a challenge that we collectively have in the U.S. and in the Bay Area in this era of history. Such wealth has been created by our predecessors that we’re short-term benefiting from that it’s easy for that to have spillover effects in the culture and to distract from focus or lead to a loss of determination.

And again, if you just study and read a little about the early days, and ideally talk to people who were around, you see that at the first semiconductor companies and the early software companies and, up to Seattle, early Amazon and Microsoft, there was nothing to be entitled about. People thought that software companies were inconsequential add-ons to the hardware. They were dismissed, they were subject to brutal release cycles, companies were going out of business left, right, and center, there was a lot of concern over competition from Asia. It was a tough market to grow up in. Of course the survivors have done well. But while people are attuned to how successful a cradle for technology Silicon Valley is, they pay less attention to, and are I think less aware of, how densely populated a graveyard it is.

And so while I think that selective pressure was good for the surviving companies, it really kind of screws with our intuitive sense for what’s required to actually build one of these. You have some early success or you raise series A or gain some early traction, and it’s easy, even subconsciously, to start lining up the plots in your head: “Well, Facebook raised its series A in 2005, and went on to be worth $15 billion in 2008 or 2009 or whatever it was,” and so on. And I think the effects of that, in blunt terms, are really pernicious. In many ways it’s harder to create an organization with the kind of focused, determined, disciplined, non-complacent mindset that you need today than it was 20 or 30 years ago. That’s just a structural headwind that we all face.

There are many natural benefits and tailwinds that Silicon Valley enjoys, but I think this is one of the challenges we face. And if Silicon Valley is supplanted by another region, or even just more broadly by a general diffusion, I think this is one of the top contenders as to why that would be the case. It’s because we had too much wealth, we had too much early success, and it caused us to lose our hunger and our edge.

People who’ve spent any time with the great software companies in China— JD, Tencent, Alibaba, and now the next generation of startups—will tell you in no uncertain terms that there is a lack of entitlement, a lack of complacency, and a real determination to succeed that is at least not uniformly present here in Silicon Valley. And so I really think it’s something that should be top of mind for everyone.

4. Boxes, trucks and bikes – Ben Evans

The traditional way to think about ecommerce penetration is to look at share of total retail sales, and then deduct things like car repair, gasoline and restaurants – to get to ‘addressable retail’. On that basis, US ecommerce was at 16% penetration at the end of 2019 and increased to 20% or so in 2020, adding 12-18 months of growth in a year. 

The obvious problem with this analysis is that penetration of different retail categories varies a huge amount – penetration of makeup is different to books, which is different to shoes. This reflects how different the buying journey can be for different kinds of products – we sometimes talk about ‘high touch’ versus ‘low touch’ goods. The chart hides a lot of variation.

However, there’s also another way to split this, that I think is becoming increasingly important – instead of looking at the product category and the buying journey, look at the logistics model.

For Amazon, makeup, books and shoes are all just interchangeable SKUs with the same buying journey that can all be stored in the same fulfilment pod and all go into the same brown cardboard box, but a cucumber, a stove, a bag of cement or a bowl of soup do not fit this model at all – they might need a different buying journey, but they definitely need a different logistics model. So, as well as thinking in terms of hardline versus softline, or high touch versus low touch, we should also think of parcels versus collection or delivery versus bikes.

5. Getting the Goalpost to Stop Moving – Morgan Housel

Paul Graham wrote a few years ago about what happened to the U.S. economy after World War II:

“The effects of World War II were both economic and social. Economically, it decreased variation in income. Like all modern armed forces, America’s were socialist economically. From each according to his ability, to each according to his need. More or less. Higher ranking members of the military got more (as higher ranking members of socialist societies always do), but what they got was fixed according to their rank. And the flattening effect wasn’t limited to those under arms, because the US economy was conscripted too. Between 1942 and 1945 all wages were set by the National War Labor Board. Like the military, they defaulted to flatness.”

Indeed, a few years after the war historian Frederick Lewis Allan wrote:

“The enormous lead of the well-to-do in the economic race has been considerably reduced. It is the industrial workers who as a group have done best – people such as a steelworker’s family who used to live on $2,500 and now are getting $4,500, or the highly skilled machine-tool operator’s family who used to have $3,000 and now can spend an annual $5,500 or more. As for the top one percent, the really well-to-do and the rich, whom we might classify very roughly indeed as the $16,000-and-over group, their share of the total national income, after taxes, had come down by 1945 from 13 percent to 7 percent.”

This went beyond income – even the variation in consumer goods flattened out. Harper’s Magazine wrote something in 1957 that was so important to the era:

“The rich man smokes the same sort of cigarettes as the poor man, shaves with the same sort of razor, uses the same sort of telephone, vacuum cleaner, radio, and TV set, has the same sort of lighting and heating equipment in his house, and so on indefinitely. The differences between his automobile and the poor man’s are minor. Essentially they have similar engines, similar fittings. In the early years of the century there was a hierarchy of automobiles.”

If you look at the 1950s and ask what was different that made it feel so great?, this is your answer. The gap between you and most of the people around you wasn’t large. It created an era where it was easy to keep your expectations in check because few people lived dramatically better than you.

It’s the one thing – maybe the only thing – that distinguishes itself from other periods.

The lower wages felt great because they’re what everyone else earned.

The smaller homes felt nice because everyone else lived in one too.

The lack of healthcare was acceptable because your neighbors were in the same circumstances.

Hand-me-downs were acceptable clothes because everyone else wore them.

Camping was an adequate vacation because that’s what everyone else did.

It was the one modern era when there wasn’t much social pressure to increase your expectations beyond your income. Economic growth accrued straight to happiness. People weren’t just better off; they felt better off.

And it was short-lived, of course.

By the early 1980s the post-war togetherness that dominated the 1950s and 1960s gave way to more stratified growth where many people plodded along while a few grew exponentially. The glorious lifestyles of the few inflated the aspirations of the many.

Rockefeller never yearned for Advil because he didn’t know it existed. But modern inequality mixed with social media has made it so you do know that people drive Lamborghinis and fly in private jets and send their kids to expensive schools. The ability to say, “I want that, why don’t I have that? Why does he get it but I don’t?” is so much greater now than it was just a few generations ago.

Today’s economy is good at creating two things: wealth, and the ability to show off wealth. Part of that is great, because saying “I want that too” is such a powerful motivator of progress. Yet the point stands: We might have higher incomes, more wealth, and bigger homes – but it’s all so quickly smothered by inflated expectations.

That, in many ways, has been the defining characteristic of the last 40 years of economic growth. And Covid-19 pushed the trend into hyperdrive.

The point isn’t to say the 1950s were better or fairer or even that we should strive to rebuild the old system – that’s a different topic.

But nostalgia for the 1950s is one of the best examples of what happens when expectations grow faster than incomes.

And all of us, no matter how much we earn, should ask how we can avoid the same fate.

6. How Startup Founders in Southeast Asia Should Value Their Company – Monk’s Hill Ventures

One of the real challenges Series A founders face is identifying a reasonable valuation for their business before they engage with VCs. At MHV, Peng’s team looks for ‘win-win’ valuation scenarios where both founders and investors agree on valuations that reflect first principles.

Founders need to avoid making the mistake of calling out a company’s valuation upfront. As a founder, you’re typically focused on your own business – and rightly so. However, this means that walking in with a ready-to-go valuation is a mistake. Simply put, you’re going to be wrong when you propose a valuation because you’re not the experienced party. VC’s like MHV see 50 – or more – deals a year in your domain, and see valuations across the board.

Instead, Peng suggests there’s a good way to answer the question about what your company’s valuation is – and that’s to not reference yourself.

“For instance, you could say something like ‘I’ve seen another company get funded at this level and the revenues were X, and the valuation was in Y range’. Give two or three examples. That’s how you answer that question. It shows you’re smart enough not to put forward a number you’re not sure about.” Indicate that you’re fine with what the market offers.

Founders need to take onboard that the principle of a win-win is all about both parties bringing an educated view of a company’s valuation to the table. Being educated means doing your homework and knowing how similar companies in your sector, region, and stage of growth are valued. The idea is to settle somewhere in a range where both parties think it could have been better for them but come out saying ‘it’s reasonable’.

Later in the session, one founder asked Peng whether one approach founders may employ is to establish how much they need to raise based on their strategic goals.

“Absolutely. If I asked what the valuation is for your company, as a founder, that’s something you should avoid answering upfront.”

“But then if I asked how much you need to raise, which is a typical follow-on question, then you’d better have that answer and be able to back it up.”

7. What is Zero Trust? – Muji

Today’s enterprise networks are fractured, moving farther and farther away from a centralized location. Zero Trust is the next-gen security paradigm that is capable of helping to secure today’s scattered networks, but it’s becoming so heavily used a term that the definition is getting blurred.

Let’s look at what Zero Trust is solving, how the ecosystem has evolved, and look at the moves major players like CrowdStrike, Okta, Cloudflare and Zscaler are making within it.

Traditionally, the primary usage of an enterprise network is interconnecting infrastructure which runs services hosted internally, handling traffic from enterprise users who use some type of device to access the network. Remote workers had to use connection tools, like a VPN, in order to get onto the trusted company network to access internal services.

The old method of castle & moat security, where you maintained a trusted network across all of your enterprise infrastructure, apps, devices and users – with a secure perimeter around it all – is becoming a thing of the past, as all of those areas continue to sprawl outside of the perimeter (and IT’s grasp).

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Amazon, Facebook, Meituan, Okta, and Tencent (owner of WeChat). Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 06 June 2021:

1. The Cost of Cloud, a Trillion Dollar Paradox – Sarah Wang and Martin Casado

However, as industry experience with the cloud matures — and we see a more complete picture of cloud lifecycle on a company’s economics — it’s becoming evident that while cloud clearly delivers on its promise early on in a company’s journey, the pressure it puts on margins can start to outweigh the benefits, as a company scales and growth slows. Because this shift happens later in a company’s life, it is difficult to reverse as it’s a result of years of development focused on new features, and not infrastructure optimization. Hence a rewrite or the significant restructuring needed to dramatically improve efficiency can take years, and is often considered a non-starter.

Now, there is a growing awareness of the long-term cost implications of cloud. As the cost of cloud starts to contribute significantly to the total cost of revenue (COR) or cost of goods sold (COGS), some companies have taken the dramatic step of “repatriating” the majority of workloads (as in the example of Dropbox) or in other cases adopting a hybrid approach (as with CrowdStrike and Zscaler). Those who have done this have reported significant cost savings: In 2017, Dropbox detailed in its S-1 a whopping $75M in cumulative savings over the two years prior to IPO due to their infrastructure optimization overhaul, the majority of which entailed repatriating workloads from public cloud.

Yet most companies find it hard to justify moving workloads off the cloud given the sheer magnitude of such efforts, and quite frankly the dominant, somewhat singular, industry narrative that “cloud is great”. (It is, but we need to consider the broader impact, too.) Because when evaluated relative to the scale of potentially lost market capitalization — which we present in this post — the calculus changes. As growth (often) slows with scale, near term efficiency becomes an increasingly key determinant of value in public markets. The excess cost of cloud weighs heavily on market cap by driving lower profit margins.

2. Twitter thread that rebuts the “The Cost of Cloud, a Trillion Dollar Paradox” article – Zack Kanter

Excellent *financial* analysis of using *commoditized* cloud infrastructure (vanilla servers). It misses: i) the (long-term devastating) cultural cost of recruiting world-class engineers to do undifferentiated heavy lifting; ii) it’s unfeasible to recreate noncommodity infra. 1/n

On i: saving 50% on COGS sounds great – until you realize that it means recruiting & retaining engineers instead of paying an AWS/GCP invoice. Opportunities to buy technical competence with a credit card are extremely rare; you can’t buy core product competence per API call. 2/n

Every sufficiently-funded software CEO on earth will tell you that their constraining factor is hiring great engineering talent – repatriating commodity servers to save on COGS means increasing engineering headcount requirements, definitionally making the constraint worse. 3/n

It follows that the optimal strategy is to do *the exact opposite* of reducing third-party API COGS: fanatically review labor COGS and shift it to third-party API COGS wherever possible – regardless of cost! You’re effectively buying autoscaling, on-demand top talent. 4/n..

…Part ii [it’s unfeasible to recreate noncommodity infra]: if you look at what your cloud provider is doing for you & your takeaway is “we could do this cheaper ourselves,” then your problem is you’re using the cloud incorrectly by choosing lowest common denominator services. 8/n

Instead of saying “we can run servers ourselves for cheaper,” you should be asking: how can we use AWS/GCP in ways that we couldn’t possibly do better ourselves? This is called “servicefull” architecture – using your provider’s cloud-native services to replace server code. 9/n

If you’re using AWS/GCP to run vanilla servers, you’re building software to work the same way it did when companies ran servers in their office 15 yrs ago. That should be a wake up call about your technology choices – not a call to put servers back in your figurative office. 10/n

3. How the World Ran Out of Everything – Peter S. Goodman and Niraj Chokshi

The most prominent manifestation of too much reliance on Just In Time is found in the very industry that invented it: Automakers have been crippled by a shortage of computer chips — vital car components produced mostly in Asia. Without enough chips on hand, auto factories from India to the United States to Brazil have been forced to halt assembly lines.

But the breadth and persistence of the shortages reveal the extent to which the Just In Time idea has come to dominate commercial life. This helps explain why Nike and other apparel brands struggle to stock retail outlets with their wares. It’s one of the reasons construction companies are having trouble purchasing paints and sealants. It was a principal contributor to the tragic shortages of personal protective equipment early in the pandemic, which left frontline medical workers without adequate gear.

Just In Time has amounted to no less than a revolution in the business world. By keeping inventories thin, major retailers have been able to use more of their space to display a wider array of goods. Just In Time has enabled manufacturers to customize their wares. And lean production has significantly cut costs while allowing companies to pivot quickly to new products.

These virtues have added value to companies, spurred innovation and promoted trade, ensuring that Just In Time will retain its force long after the current crisis abates. The approach has also enriched shareholders by generating savings that companies have distributed in the form of dividends and share buybacks.

Still, the shortages raise questions about whether some companies have been too aggressive in harvesting savings by slashing inventory, leaving them unprepared for whatever trouble inevitably emerges.

“It’s the investments that they don’t make,” said William Lazonick, an economist at the University of Massachusetts.

Intel, the American chip-maker, has outlined plans to spend $20 billion to erect new plants in Arizona. But that is less than the $26 billion that Intel spent on share buybacks in 2018 and 2019 — money the company could have used to expand capacity, Mr. Lazonick said.

Some experts assume that the crisis will change the way companies operate, prompting some to stockpile more inventory and forge relationships with extra suppliers as a hedge against problems. But others are dubious, assuming that — same as after past crises — the pursuit of cost savings will again trump other considerations…

…Just In Time was itself an adaptation to turmoil, as Japan mobilized to recover from the devastation of World War II.

Densely populated and lacking in natural resources, Japan sought to conserve land and limit waste. Toyota eschewed warehousing, while choreographing production with suppliers to ensure that parts arrived when needed.

By the 1980s, companies around the globe were emulating Toyota’s production system. Management experts promoted Just In Time as a way to boost profits.

“Companies that run successful lean programs not only save money in warehouse operations but enjoy more flexibility,” declared a 2010 McKinsey presentation for the pharmaceutical industry. It promised savings of up to 50 percent on warehousing if clients embraced its “lean and mean” approach to supply chains.

Such claims have panned out. Still, one of the authors of that presentation, Knut Alicke, a McKinsey partner based in Germany, now says the corporate world exceeded prudence.

“We went way too far,” Mr. Alicke said in an interview. “The way that inventory is evaluated will change after the crisis.”

Many companies acted as if manufacturing and shipping were devoid of mishaps, Mr. Alicke added, while failing to account for trouble in their business plans.

“There’s no kind of disruption risk term in there,” he said.

4. Can Apple Change Ads – Ben Evans

Apple regards itself not just as a platform provider but as a system provider. Your iPhone is a system, and Apple decides how it works and what developers can do on it, and just as Apple controls security, wireless networking, power management or multi-tasking, it also controls privacy. This year Apple started requiring apps to get permission before sharing information to track users across different sites (‘ATT’), just as the EU and California’s cookie laws have required the same on the web. The main reason to do this tracking is to make advertising more relevant (and therefore more valuable for publishers), and ATT, cookie laws, and Apple and Google’s decision to block third party cookies on the web anyway, in Safari and Chrome, all mean that the foundation of a lot of online advertising has collided with privacy and shattered, with very little clarity on what comes next.

In parallel, Apple has built up its own ad system on the iPhone, which records, tracks and targets users and serves them ads, but does this on the device itself rather than on the cloud, and only its own apps and services. Apple tracks lots of different aspects of your behaviour and uses that data to put you into anonymised interest-based cohorts and serve you ads that are targeted to your interests, in the App Store, Stocks and News apps. You can read Apple’s description of that here – Apple is tracking a lot of user data, but nothing leaves your phone. Your phone is tracking you, but it doesn’t tell anyone anything.

This is conceptually pretty similar to Google’s proposed FLoC, in which your Chrome web browser uses the web pages you visit to put you into anonymised interest-based cohorts without your browsing history itself leaving your device. Publishers (and hence advertisers) can ask Chrome for a cohort and serve you an appropriate ad rather than tracking and targeting you yourself. Your browser is tracking you, but it doesn’t tell anyone anything -except for that anonymous cohort.

Google, obviously, wants FLoC to be a generalised system used by third-party publishers and advertisers. At the moment, Apple runs its own cohort tracking, publishing and advertising as a sealed system. It has begun selling targeted ads inside the App Store (at precisely the moment that it crippled third party app install ads with IDFA), but it isn’t offering this tracking and targeting to anyone else. Unlike FLoC, an advertiser, web page or app can’t ask what cohort your iPhone has put you in – only Apple’s apps can do that, including the app store.

So, the obvious, cynical theory is that Apple decided to cripple third-party app install ads just at the point that it was poised to launch its own, and to weaken the broader smartphone ad model so that companies would be driven towards in-app purchase instead. (The even more cynical theory would be that Apple expects to lose a big chunk of App Store commission as a result of lawsuits and so plans to replace this with app install ads. I don’t actually believe this – amongst other things I think Apple believes it will win its Epic and Spotify cases.)

Much more interesting, though, is what happens if Apple opens up its cohort tracking and targeting, and says that apps, or Safari, can now serve anonymous, targeted, private ads without the publisher or developer knowing the targeting data. It could create an API to serve those ads in Safari and in apps, without the publisher knowing what the cohort was or even without knowing what the ad was. What if Apple offered that, and described it as a truly ‘private, personalised’ ad model, on a platform with at least 60% of US mobile traffic, and over a billion global users?

5. Explained: Neural networks – Larry Hardesty

Deep learning is in fact a new name for an approach to artificial intelligence called neural networks, which have been going in and out of fashion for more than 70 years. Neural networks were first proposed in 1944 by Warren McCullough and Walter Pitts, two University of Chicago researchers who moved to MIT in 1952 as founding members of what’s sometimes called the first cognitive science department.

Neural nets were a major area of research in both neuroscience and computer science until 1969, when, according to computer science lore, they were killed off by the MIT mathematicians Marvin Minsky and Seymour Papert, who a year later would become co-directors of the new MIT Artificial Intelligence Laboratory.

The technique then enjoyed a resurgence in the 1980s, fell into eclipse again in the first decade of the new century, and has returned like gangbusters in the second, fueled largely by the increased processing power of graphics chips…

…Neural nets are a means of doing machine learning, in which a computer learns to perform some task by analyzing training examples. Usually, the examples have been hand-labeled in advance. An object recognition system, for instance, might be fed thousands of labeled images of cars, houses, coffee cups, and so on, and it would find visual patterns in the images that consistently correlate with particular labels.

Modeled loosely on the human brain, a neural net consists of thousands or even millions of simple processing nodes that are densely interconnected. Most of today’s neural nets are organized into layers of nodes, and they’re “feed-forward,” meaning that data moves through them in only one direction. An individual node might be connected to several nodes in the layer beneath it, from which it receives data, and several nodes in the layer above it, to which it sends data.

To each of its incoming connections, a node will assign a number known as a “weight.” When the network is active, the node receives a different data item — a different number — over each of its connections and multiplies it by the associated weight. It then adds the resulting products together, yielding a single number. If that number is below a threshold value, the node passes no data to the next layer. If the number exceeds the threshold value, the node “fires,” which in today’s neural nets generally means sending the number — the sum of the weighted inputs — along all its outgoing connections.

When a neural net is being trained, all of its weights and thresholds are initially set to random values. Training data is fed to the bottom layer — the input layer — and it passes through the succeeding layers, getting multiplied and added together in complex ways, until it finally arrives, radically transformed, at the output layer. During training, the weights and thresholds are continually adjusted until training data with the same labels consistently yield similar outputs.

6. Ant Group searches for direction in a new era of Chinese fintech – AJ Cortese

When Ant Group, then Ant Financial, launched its mobile payment service Alipay in 2004, it was meant to be a complementary function to improve shoppers’ checkout experience on e-commerce marketplace Taobao. Few could have predicted the main role it would go on to play in the development of mobile payments in China.

Ant Financial was spun off from Alibaba in 2014, with Alipay as its core business. The mobile payment platform generated the majority of the firm’s revenue until 2018. However, as Ant’s business strategy began to shift in 2019 to cultivate different growth engines based on new digital financial services, Alipay’s central role began to vanish, with the e-wallet generating only 36% of the firm’s total revenue in 2020. At the same time, the company’s credit services alone accounted for a whopping 40% of total revenues for Ant Group in the first half of 2020.

In July 2020, Ant Financial was rebranded as Ant Group to better reflect its role as “an innovative global technology provider” for businesses and financial institutions. Ant leveraged Alipay’s 900 million users to create a one-stop marketplace for financial products, including short and long-term credit loans, insurance products, and wealth management offerings. The restructuring and the new offerings were the special sauce that powered the company to within arm’s reach of the world’s largest IPO.

Leading up to the IPO in March 2020, Ant Group’s former CEO, Simon Hu, unveiled a new horizontal strategy for Alipay, looking to expand the range of services available on the platform, from food delivery to travel bookings. Alipay’s Chinese slogan was changed from the mundane but functional “Use Alipay to make payments” to the broader and catchier “Live well, Alipay.”

However, following the stalled IPO and new regulations severely limiting cash machine loan products like Huabei and Jiebei—which can no longer be offered as direct payment options—Alipay is back at the center of Ant Group’s thinking, also fueled by an announcement from the People’s Bank of China (PBOC) in December 2020, clearly instructing Ant Group to “return to its roots in payments.”

Despite the changes, Ant Group’s range of offerings will not be limited to just mobile payments. The company can still offer a wide range of services as long as it stays away from lending. In fact, the firm is actively onboarding service providers, aiming to reach 50,000 in total by 2023, up from 10,000 in mid-2020. This service-oriented approach represents the next logical development in Alipay’s maturation…

…Just this week, Alipay was incorporated in the PBOC’s digital yuan rollout pilot program, which expanded its scope to include private operators like Ant Group and Tencent. Alipay and WeChat Pay are likely to maintain a prominent position in the future when the digital yuan will be rolled out at scale.

“It is a misconception that the digital yuan is meant to be a direct competitor to Alipay and WeChat. In fact, the expanded rollout of the digital yuan will allow new industries, payment flows, and data to be digitized in areas like employee salaries,” Turrin explained.

Instead of routing worker’s wages through a bank’s system to then be transferred into a digital wallet like Alipay, salaries could be directly integrated into these wallets using the digital yuan, Turrin said. Going forward, the aim is to facilitate more use cases for the digital currency, which is reliant on consumer platforms like Alipay. “The digital yuan will fail without these types of consumer platforms,” Turrin said.

“It is not a zero-sum game where the central bank’s digital currency takes market share away from the payment platforms. Actually, the digital yuan will enlarge the overall size of the digital payment pie,” he added.

If China’s digital yuan isn’t meant to cut into Alipay and WeChat’s duopoly in mobile payments, the two payment platforms will likely retain and even reinforce their dominant positions, especially as other verticals of their businesses face regulatory challenges.

7. Own The Internet – Packy McCormick

What if I told you about a business with strong network effects and 200x YoY revenue growth that was preparing to offer a 25% dividend and implement a permanent share buyback program? Is that something you might be interested in?

That’s pretty much Ethereum. It’s one of the most fascinating and compelling assets in the world, but its story is obfuscated by complexity and the specter of crypto.

Ethereum is so many things at once, all of which feed off of each other. Ethereum, the blockchain, is a world computer, the backbone of a decentralized internet (web3), and the settlement layer for web3. Its cryptocurrency, Ether (ETH), is a bunch of things, too:

• Internet money.
• Ownership of the Ethereum network.
• The most commonly-used token in the Great Online Game.
• Yield-generating.
• A Store of Value (SoV).
• A bet on more on-chain activity, or the web3 future. 

Because Ethereum is so much at once, it’s hard to understand. This post is an attempt to help Ethereum be understood. To a group like us, people interested in technology businesses, finance, and strategy, it’s much more fascinating than bitcoin, but that comes with a tradeoff. It’s much harder to grok than bitcoin, and because of that, it hasn’t gotten the mainstream or institutional attention that bitcoin has…

…Ethereum is so much more than a cryptocurrency. It’s a “world computer,” and the “value layer” of the internet. It lets people build apps and products with money baked into the code. If you believe that web3 is going to continue to grow, then you likely believe that over time, Ethereum will become the settlement layer of a new internet. All sorts of transactions, whether they happen on Ethereum, another blockchain, or even Visa, will turn to Ethereum to exchange funds and keep secure, immutable records. A year ago, I wouldn’t have said that.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google), Apple, and Tencent (parent of TenPay). Holdings are subject to change at any time