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My mom brainwashed me to be confident. She told me over and over that I was great and destined for great things. And it worked. To this day, when I lose or make a mistake, I get mad, but I always wind up where my mother left me: “You’re great. All you need is more practice.” And it turns out, more often than not, that’s true. If you practice, you get better and achieve what you couldn’t, which builds more confidence. It becomes a self-fulfilling prophecy. Think you’re great and you become so. When I graduated from college, I was brimming with confidence. I legitimately thought that I would make a billion dollars within a couple of years. That did not happen and it led to some of the darkest days of my entire life. Never mind a billion dollars, it took me 3 years to even get profitable. But if my mom hadn’t instilled that confidence I would’ve given up. When I failed, and I did often, I wouldn’t have a reason to try again, because instead of thinking that I just needed more practice, I’d reach the conclusion that I wasn’t destined to be great. In the end, I made it. I am successful. I am great. But this isn’t what this post is about. This post is about you and your kids. I was lucky to have a parent brainwash me. My dad took the opposite approach but my mom always used to say “he loves you so much and when you’re not around he always brags about you.” I don’t know if it’s true, but it worked. You need to give your kids confidence. The world is cruel and you won’t always be around to pick them up when they fall. Tell them they’re great. Tell them to tell themselves they’re great. Tell them that they can do anything they put their mind to. And it’ll be true. And you? If you don’t have that confidence yourself, start today. Tell yourself your great and then start acting like you are. Take more risks, learn new skills, and when you fall, pick yourself right back up because you’re great and you just stumbled on the way to the world recognizing that. And eventually, if you stick with it, you’ll discover it was true all along. You just needed to believe at the beginning. I believe in you, your kids, your dreams. Make it happen, all it takes is to try. I know from experience.
One of the main reasons for the decline in goods and services in the United States, and to a lesser extent, the world, is the financialization of our economies by excessive money printing. Let's break that down into simpler language. The quality of the things and services you buy has gotten worse because the people making those things and doing those services are worse today, generally, than the ones who were doing it 10-20 years ago. Why? Because there is no money in it. Why is there no money it? Because all the money is in creating assets, not in creating goods and services. Why is all money in creating assets? Because there is an enormous demand for assets because all the governments of the world are constantly creating new money and people want to protect their savings. Their savings are not protected in cash. They will become worth less and less every year. So, they invest in assets, because assets trade at a multiple of what they earn, which is constantly rising because new money is created and then prices change. So, concretely, a smart person who otherwise would have run a manufacturing business making glassware, instead buys a bunch of glassware manufacturing businesses using debt to take advantage of the new money creation which is constantly driving the prices of these businesses up. Instead of thinking about how to make better glassware, that person thinks about how to raise more money, how to sell these businesses in another party which is doing the same thing. The focus goes from making a good product, to making an asset which is traded. Why? Because you can make so much more money buying a 5 million dollar glassware company and selling it for 10 million dollars than you can actually selling glassware. Further, since 2008, there has been no downside to this trade because every time there is an economic weakness on the horizon, governments, fearing loss of power, chaos, or hardship, just print more money so that there isn't any specter of job loss. So the only reason why you would make goods and services instead of assets is because you do it for the love of the game, because you get a much better reward and minimal risk from building assets because nothing is allowed to fail! There are a couple of reasons why this problem is particularly bad (yes it's bad that goods and services are in decline) in the United States: 1. It's tax advantaged. Selling glassware has a tax rate of about 35%. Selling assets has a tax rate of about 20%. 2. The United States has the "deepest capital markets", meaning its the easiest place to get the loans that are integral to this game 3. It's become part of the culture. While someone in France may say "absolutely not, I am not buying up bakeries, I am building baguettes", in the United States, we have a culture that celebrates this. We think it's the pinnacle of capitalism, when it's not even capitalism. The Federal Reserve is a unelected body of people who are nominated and then serve out a full term and decide how much new money to create. It's central planning, which is the opposite of capitalism. But, hey, look at that cool guy on wall street in the 1980s with his satellite phone, so cool, so capitalism. This is also why the new industrialization drive is 100% government driven. Whether it's the Chips Act or the venture-funded companies which will sell to the US government. There's no money in making this stuff unless the government comes in and pays a stupidly high price which is, once again, only possible because of excessive money printing. Unless they're just doing it for the love of the game, the only way you can get someone to make physical stuff instead of making assets (which they're kind of doing anyways) is by paying them the market rate, which has to compete with working in finance. This is why Zoomers have no motivation to work normal salaried jobs. Because, why would you work when you could trade crypto or stocks? The income potential is so much higher, which again comes from all the new money that is constantly printed. So when someone says "it's time to build!" and they're in the financial industry (I'm speaking generally, I have no personal issue with someone who does that), just laugh because it's not real. What they mean, is that it's time to build assets, not real goods and services, because that's a lot harder and, with the current system, from taxes to the way the government funds itself and saves the economy, it's a bad way to make a living (even if it's spiritually fulfilling).
My company has sold $2.6 million on Faire over the past 4.5 years. As selling on Amazon has become tougher and tougher, we are thankful for the growing sales Faire has brought us. That said, it's a difficult, counterintuitive marketplace to operate on, and one that is getting, like Amazon, more difficult. What is Faire? It's a wholesale marketplace. They make it easy for brick-and-mortar stores to buy your products, at wholesale prices. So that $2.6 million in sales above, became something like $5 to $6 million in retail sales for our customers, the brick-and-mortar retailer, which is cool. Like Amazon, Faire has its own version of "prime" which gives the brick-and-mortar retailers free shipping, for a fee. And Faire, has done a great job of combining this with terms, to enable brick-and-mortar businesses to finance their inventory purchases. Who is Faire good for? Faire's customer base is largely independent brick-and-mortar retailers. These businesses are not competing on price like Walmart, Aldi, or Dollar General are. They are mainly destinations, either as gift-oriented tourist shops, or, for us, Ozzy's Ostrich Adventure which sells our ostrich plush animals (not a real store, but we have many customers like this). If you're selling a product that fits into that space, I highly recommend Faire, because, they're excellent about bringing lots of customers to your brand. Increasing fees and complexity Faire has not yet reached Amazon's level of complexity but it's getting there. When we first started selling on Faire, they took 15% of what you sold there and paid you your shipping costs and that was it. Today the charges work like this: - 15% for what they sell - 1.9% to $3.5% depending on how fast you want to be paid - $10/order for new customers who've never ordered from your brand - Advertising on the platform if you want your products to be seen starting at $200/month - Forced discounts to participate in their deal days - And some fees around shipping that aren't even worth getting into they're so complicated It could be worse, but the problem is that the way Faire works is very different from every other e-commerce marketplace in terms of pricing, so it ends up occupying a lot of your headspace as an operator. And sadly, they've, like Amazon, decided to enforce pricing off of Faire meaning that if they find you selling your products for less off-Faire, they'll punish you on Faire. Normally this wouldn't be such a big deal, but Faire fees are quite high, so it requires you to bring all your pricing up, or lose Faire as a channel. They're not Amazon when it comes to software and systems Faire's sister company is not AWS (Amazon Web Services). They do not have dedicated artificial intelligence division. Amazon isn't what it was when it comes to tech competence these days but for many years we were spoiled. Faire frequently has code errors that cause inventory discrepancies, or in one case, us to be shorted $100s of dollars on multiple orders because their shipping reimbursements were not working as advertised. Faire's payouts can sometimes be un-Faire and you need to watch them carefully to ensure you're being paid as you think you are. Faire alternatives While I've been selling to brick-and-mortar stores for well over a decade, we're much better as a company at e-commerce, so I'm not qualified to have a strong opinion on this topic. For us, Faire generates more revenue than alternatives like trade shows and our sales reps, for whom I am extremely grateful. As someone who worked store-to-store door-to-door sales I know how hard it is to win those orders and when a sales rep delivers an order, I know how hard it is. Sales reps, despite the greater workload per order vs. Faire's digital platform, have lower fees than Faire, but at least for us, have not yet been able to get us to the same levels of revenue. Trade shows are great for general marketing and are necessary to attracting large retail clients, but are costly both in overall cost and time. With Faire, you're only paying (unless you advertise on the platform) when you get a sale, so while it's a challenge to manage, it is, in a way, less risky than committing to a trade show. Conclusion If your brand's products are gifty or purchased in independent retail, you need to be on Faire. It's not an option. There is certainly money to be made, but you need to be careful and have good systems and operations in place to take advantage of it.
A famous newspaper asked me to write an opinion article. But every time I submitted a draft, they'd edit it, changing the message of the piece, even though the article was meant to be my opinion. Most people would have consented to the edits to have the honor of being in the newspaper. I decided not to be published and turned down the opportunity. Here's the last draft of the article: Chinese Labor Isn't Just Cheaper; It’s Better. We Need to Fix That. Why is everything made in China? Yes, the labor is cheaper, but that’s not really why. The real why is hard to read. America’s workers are in a sorry state. Robots and AI won’t save us. China is installing more industrial robots per capita than we are. Even so, the flexible adaptable human will be working in manufacturing (alongside machines) for decades to come. Manufacturing is about people, and ours need an upgrade. For 15 years, I’ve been manufacturing in China, Southeast Asia, and the Americas. I have great respect for the people I’ve worked with and I want to see them and all Americans thrive, but to do that, we must first be honest with ourselves about the state of US manufacturing labor. We are too fat to work in factories. Manufacturing is not a desk job. You’re on your feet all day, walking miles in the factory. To make quality products at reasonable prices, your workers need to be efficient. The obese suffer from chronic pain, move too slowly, are prone to work-ending to injury, and cannot perform the movements necessary to make physical products. We eat garbage. Manufacturing is intellectually demanding work. With apologies to the makers of spreadsheets, legal pleadings, software, and newspaper columns, making physical things is harder than you think. The American manufacturing worker starts their day with processed food from a drive-through, while their competitor in China eats rice congee and brain-building fish. Who do you think is more likely to improve their manufacturing process? We graduate but can’t do math. “The 9’s always get me!” exclaimed a sincere but math-challenged new potential hire. Too many American workers cannot do their times tables without a calculator, slowing down and degrading their work. Despite our world-beating GDP, American PISA math scores are not only below average, but in decline. Last time China took the same test, they scored 24% better than the USA. We don’t speak one language. 5,000 characters, every sound has four tones, and every sound-tone combination can have multiple meanings. Chinese is hard, but at least China has a single working language. In the US, English-speaking management struggles to communicate with the teams doing the hard work because they speak Spanish or other foreign languages. We are on drugs. In the US, not only will your team show up high, but it won’t show up at all, especially the day after it gets paid. If it’s not hard drugs, it’s industrial strength marijuana causing cognitive decline. When caught, employees lose their driver’s license and can’t get to work. Chinese workers walk to work, use safe public transport, or live in dormitories at the factory. We come from broken homes. In China, children are significantly more likely to grow up in 2 parent households, reducing the chance that an employee has to choose between their child’s needs and their job. Child support can cut an American parent’s wage by 60%, driving them to leave gainful manufacturing employment and turn to under-the-table cash odd jobs or dealing drugs. We have too many HR problems to improve operations. Before Americans can optimize our manufacturing processes, we must first navigate a human resource minefield of drug-addiction, violent felonies, and trouble at home to assemble a team, all while avoiding lawsuits. Making improvements on the factory floor is not easy while running what many in the industry call “adult daycare”. Our social media is toxic to worker motivation and culture. Open the apps to watch videos celebrating arriving to work late, 30 minute bathroom breaks, sky-high OnlyFans incomes, and step-by-step guides to filing discrimination lawsuits against your employer. Chinese social media is less demotivating and it shows. Chinese workers don’t storm off mid-shift and or hide in the corner to swipe their phone. We taught our people to commit fraud instead of work. The most efficient day laborer we ever had was acrobatic and on disability. During Covid, unemployment benefits exceeded employed worker incomes. These bad incentives have permanently damaged the psyche and spirit of our people. And we don’t believe in the system, because it betrayed us. Between 2015 and 2025 US manufacturing wages rose 40%, while the cost of purchasing a home rose 93%. Meanwhile, in China, manufacturing wages increased 110% while housing prices were flat. No wonder Chinese workers work harder. From houses to cars and washing machines, Chinese workers are more motivated to work because what they want keeps getting cheaper (and better) in terms of their wages. In America, electrical engineers and computer science graduates, who otherwise might work in manufacturing, improving products and processes to make US products more competitive and by consequence increasing US manufacturing wages, instead, went into finance. The incentives in the United States do not support a vibrant manufacturing economy and we’re kidding ourselves if we think otherwise. The Chinese system is not holistically better. Unions are banned and employees do harder work for longer hours. But, if you look at our country vs. theirs in terms of speed, quality, and cost, we’re not just bad, America is getting worse. The problem is fixable, but it will take decades. It’s not as simple as slapping some tariffs on Chinese goods and repeating nostalgic slogans of American greatness. America needs an educational and cultural transformation to compete with China and reverse the decline in living standards that Americans have suffered over decades. We need to start with open-mindedness. We need to be copying the best policies from other countries regardless of whether they are our allies, share our democratic values, or have “communist” in their name. We need to play to our strengths. China will have world-beating semiconductor chips before they score a goal in soccer’s World Cup. But manufacturing and product development are like soccer, creative team-oriented problem solving. That and greenfield innovation are skills at which the United States thrives. And risk-taking, we have that in spades, especially when it comes to novel products and processes. And our people, we still have high expectations for product quality while China is still plagued by their “good-enough” chabuduo mentality. Teddy Roosevelt said “complaining about a problem without proposing a solution is called whining”. Reforming the prison system to teach manufacturing instead of recidivism, strengthening English second language requirements at US schools, reducing English and history classes to increase math and science, longer school hours and less vacations, visas for manufacturing because America’s forgotten how it’s made, special economic lawsuit-free zones, worker dormitories, increasing teacher pay, zero income tax for manufacturing workers, managers, and owners (not tips!), cutting student loans for non-STEM fields, and making universities responsible for unpaid student debt. You may hate these ideas and you might be right to, but it’s time to open up the conversation, because it’s becoming clearer every day that what we’re doing isn’t working. And this isn’t about beating China. It’s about doing the right thing for our country and our people, who do the hard, important work on which our cushy modern life relies. Chinese labor may be cheaper, but ours can be better. Let’s make it happen.
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In a post at the end of August 2026, I talked about interest rates in 2026 and marveled at the capacity of equities to keep rising in the face of rising rates. I argued that the resilience of stocks during the year could be traced to higher-than-expected earnings being reported by companies in 2026, and a concurrent increase in expected earnings in 2027 and 2028. Now that September 2026 is one for the record books, it is time to take stock and dig a little deeper, especially since the month brought about one of the largest increase in treasury yield rates in recent memory, and stock prices still held their own. In particular, I want to examine the earnings at US companies, in the aggregate and by sector, trying to trace out where the earnings increase is coming from, and how that increased earnings is playing out on corporate balance sheets and cash flows. Stock Prices and Rates In my earlier post on interest rates, I had looked at treasury rates by day through the end of August, and I will begin this section by updating that chart to include a tumultuous September: I had described the rise in rates between January and August as gradual, but the rise in rates in September was anything but, as the ten-year rate rose from 4.75% at the start of the month to 5.29% at the end. In fact, to put the 54 basis point rise in the ten-year rate in context, take a look at the distribution of monthly rate changes in the ten-year treasury in the chart below: The September rise in rates would put in the top ten percent of 770 monthly rate changes that we have seen between 1962 and 2026. In the face of the mark up in rates, stocks held their own in September, at least in the aggregate, and you can see that in the chart below, where I look at aggregate market values, by month, and by sector: = The market added $2.5 trillion in market capitalization across all stocks in September 2026, but almost $1.5 trillion of that came from technology As you look across the entire year, broken down by quarters, here is what you see in the aggregate market caps: Only companies listed at the start of 2026 included I excluded firms that were not listed at the start of 2026 from the list since including them will give a misleading sense of returns to investors; adding SpaceX, for instance, which was listed in June 2026, will increase the value of communication service companies by more than $2 trillion, but it was listed at roughly that value. There are many who have pointed to the fact that US equities, while up for the year, have seen divergence in performance, and you can see that phenomenon play out in two statistics. The first is that three sectors - technology, energy and materials have carried the market, with technology being the biggest contributor to market gains. The second is that the percent of companies within each sector that are up for the year is about 50% across the market, and in the third quarter, about 65% of all listed stocks saw dropping stock prices. It is often difficult to make sense of what is moving stock prices because there are so many factors from growth to interest rates to cash payout that are pulling in different directions. It is to counter this confusion that I have resorted to estimating an implied equity risk premium, where I estimate the internal rate of return you can earn by buying equities, given how they are priced, and their expected earnings growth and cash flows, as well as interest rates. That calculation, which I have done at the start of each month since September 2008, yields an expected return of 8.99% for equities and an equity risk premium of 3.70% (3.92%) over the ten-year treasury rate (dollar riskfree rate) of 5.29% (5.07%) at the start of October 2026: Download spreadsheet Note that this estimation is model-agnostic and is an internal rate of return for investing in stocks, given expectations of the cash flows from investing in equities. If you are a market timer, and I am not one, you could use this implied equity risk premium as a barometer of market priciness, with a lower number indicating overpricing and a higher number indicating underpricing. Download spreadsheet The jump in US treasury rates in September 2026 has had an effect, with the equity risk premium dropping below 4% for the first time this year. In fact, even as the ten-year treasury rate has climbed this year from 4.18% to 5.29%, the expected return on stocks has also gone up from 8.41% at the start of 2026 to 8.99% on September 30, 2026. The AI Cap Ex Boom: Accounting and Corporate Finance Consequences The focus on stock prices and interest rates can sometimes distract us from paying attention to corporate investing, financing and cash return policies that drive value. It should not surprise you, given the times we live in, that AI is at the heart of the business story that is driving corporate behavior, and in the process, providing the fodder for market resistance to higher rates. I will begin with an assessment of how the trillions of dollars in AI cap ex will show up in financial statements: As you can see, the AI cap ex story is a complicated one, if you are looking at market aggregates, because the market includes both the companies that are spending the money building the AI architecture, which includes data centers and other infrastructure, as well as the companies that are supplying the ingredients for that infrastructure. The builders of the architecture are the hyperscalers (Meta, Alphabet, Amazon, Microsoft et al.), and the money they spend on cap ex will cause lower earnings, at least until the cap ex starts paying off, in the form of amortization of the AI cap ex, as well as a hit to their free cash flows, which are after cap ex. The money spent on AI cap ex though becomes revenues to the chip makers (Nvidia and TSMC leading the way), network equipment manufacturers (Broadcom, Micron and Marvel, to name just three), power plant builders (Constellation Energy et al.) and even real estate developers focused on data centers (Equinix, Digital Realty), and ultimately net profits (with net margins driving the bottom line). It is true that there are gray zones here, with some AI builders also benefiting from being suppliers (Amazon is spending money on AI cap ex but is also benefiting from the usage of its cloud space for data storage, and Nvidia, while selling the chips that go into the architecture, is also investing directly or indirectly into data centers). As we trace through the aggregated effects of the AI cap ex boom on accounting statements, there are two caveats that need to be stated up front. The first is that the data that is accessible to the public, and which I will be using, will be data from publicly traded companies. To the extent that some of AI's big players (builders and suppliers) are private, I will be missing the revenues, earnings, cash flows and invested capital at these large private players (which include at least two companies in Anthropic and OpenAI that are expected to command trillion dollar plus market caps. The second is that some of the AI cap ex is taking the form of joint ventures and off-balance sheet entities, and the accounting for these (especially on the debt side) may not fully reflect the consequences for firms. As a result, the numbers you see in the public company financials will understate the full effect across all businesses. With those caveats in place, the business story for US equities starts with massive capital expenditures in AI, with trillions being invested into data centers and AI architecture. It is true that this cap ex is top heavy, with the top ten hyper-scalers accounting for more than $2 trillion of the AI cap ex, but in the table below, I look at the aggregate cap ex reported in corporate financial statements at all publicly traded companies in the United States: Even with the caveats about understatement, but you can still see that cap ex in the second quarter of 2026, which is our last completed quarter of reported financials, was up $133.4 billion from the cap ex in the second quarter of 2025, an increase of almost 36%. Again, the surge in cap ex is concentrated, with technology, communication services and consumer discretionary all registering growth of more than 50% in the quarter-to-quarter comparison. Accounting incorporates capital expenditures into the balance sheet as assets, and reflects how this cap ex is funded (debt or equity) by increasing the book values of the funding used in the investment. A surge in cap ex, such as the one that we have seen in 2026, will show up as higher book values for equity, debt and invested capital, and we capture this effect, by sector, in the table below: Across all US stocks, the book equity has increased almost 13%, between the second quarter of 2025 and the second quarter of 2026, and total debt is up almost 8%. In dollar terms, the book equity at US companies increased by $1.8 trillion between the second quarter of 2025 and the second quarter of 2026, and book debt by $1.9 trillion, over the same period. Technology, being the most active player in AI cap ex, has seen much bigger increases in both numbers, with book equity rising almost 30% and total debt up about 18.8%. From an earnings perspective, the focus on cap ex and book values may seem misplaced, since the former can only decrease cash flows and the latter impacts accounting returns. In 2026, though, the increased capital expenditures on AI are affecting earnings for a simple reason. The money spent on cap ex by a company building AI architecture will become revenues (and earnings) for other companies that supply the building blocks for the architecture. There is a reason why Nvidia has been the biggest beneficiary from the AI cap ex boom so far, since its chips, marked up massively, power the data centers, and there others, from electrical equipment makers to power companies to real estate developers who have also reaped the benefits. It is true that there should be increased amortization expenses at the AI builders, but the longer amortization schedules being used by many of them is reducing the current hit to earnings at these companies. The earnings effect of the AI story can be seen in the table below, where I look at aggregate net income at US companies, broken down by sector: Note that in both the first and second quarters of 2026, US companies have seen earnings surge over the corresponding quarters in 2025, with aggregate earnings increasing from $511 billion to $692 billion (translating into an earnings growth rate of 35%, quarter-to-quarter) in the first quarter of 2026 and from $576 billion to $904 billion (translating into an earnings growth rate of 57%, quarter-to-quarter) in the second quarter of 2026. As with stock prices, the earnings benefits are not broad-based, with more than half of all companies in the market reporting declines in net income, and there are wide differences in earnings growth across sectors. Technology, financials and communication services have seen the biggest increases in earnings, and health care, utilities and real estate have lagged. A cap-ex driven surge in aggregate earnings comes with an asterisk, since the higher earnings across firms will be partially or even fully offset by capital expenditures across firms, leading to free cashflows to firms often growing at much lower rates than earnings. Since these free cash flows are what fund dividend payments and stock buybacks, I looked at cash returned to shareholders in both forms in 2026: In the aggregate, dividends in the last twelve months are up about $43.3 billion (about 5%) from dividends in the 2025 calendar year, and stock buybacks are up about $106.7 billion (about 9%). In fact, if you net out stock issuances, which spiked in the second quarter of 2026, from buybacks, net buybacks have grown bout 7% between the last calendar year and now. Those numbers represent reasonable step ups from the last year's numbers, but they clearly have not kept up with the earnings growth in 2026. One way to see the disconnect that is occurring between earnings and cash flows is to look at the cash returned as a percent of earnings for the S&P 500 companies over time: For much of the last two decades, US companies have returned 80% or more, and sometimes more than 100% of their earnings, to shareholders in dividends and buybacks. Starting in about 2024, you can see a divergence with earnings rising much faster than cash returns, and in the last twelve months leading into 2026, the companies in the S&P 500 returned 63% of their earnings to shareholders, a low not seen since 2004. Many of those who were criticizing US companies for buying back too much stock and not investing enough back into businesses are now finding fault with those same companies scaling back buybacks and investing more into AI cap ex, leading to the conclusion that these critics will find fault no matter what companies do. The AI Business Resolution: Accounting and Market Consequences It is true that the massive investments in AI cap ex are being driven by expectations that AI as a business will enjoy not only a large market, but one that where the winners can sustain huge profits for the long term. As I noted in my post on AI as a business, this is a plausible path, but there are vast disagreements on whether this is the expected one, given uncertainties about all three layers of the business story - the size of the total addressable market, the unit economics/operating margins of companies in the business and the moats and competitive advantages that will allow for sustainability in profits. So, what will the accounting and market consequences be, if the AI pathway diverges from expectations? In the table below, I trace out the accounting and market consequences of the AI business working better than expected at delivering growth and profits, as well as if i does much worse than expected: In the best case scenarios for AI, the companies that have invested in AI, at least collectively, will be able to deliver not just earnings growth from the cap ex, but enough incremental earnings to generate returns on the AI cap ex that exceed their cost of capital for those investments. Their lenders will be made whole, with interest and principal payments, and the AI builders will see their cashflows become more positive, but the companies, while successful, will emerge as very different businesses than when they entered the space, more capital intensive than they used to be. In the worst case scenarios for AI, there will be both accounting and market carnage, as accountants write off large portions of the AI cap ex, because of its failure to deliver promised profits, and while cash flows may recover, markets will correct the pricing of these companies to reflect a lack of trust in management. For companies that were excessively dependent on debt for their AI cap ex, there will be defaults and increased distress, with lenders feeling the pain as well. There are also intermediate scenarios, ranging from AI being a moderate success, where the companies investing AI may be able to extract some earnings from their investment, but not enough to cover the cost of capital, to a moderate failure, where some companies may be able to justify their investments and most will not. Given that AI business surprises will have both market and accounting consequences, I will hazard a guess that the market will lead in this process and accounting will follow. In short, if AI is working better (worse) than expected, you should see stock prices at AI-centered businesses rise (fall) before you see accountants respond. Put simply, in the event that AI does not deliver on its promise, waiting to act until accountants write off AI cap ex to sell your AI company implies that you waited too long. An Investor Perspective: Taking Stock and Taking Action In my post on AI as a business, I zeroed in on the debate between AI optimists, pointing to huge (albeit unspecified) markets for AI products and services, and AI skeptics, drawing attention to the outsized capital expenditures. While that debate plays out, financial markets and businesses cannot afford to wait for resolution, and are acting now, with companies making investments in cap ex and markets building in their expectations of what that will mean for future earnings into stock prices. That has made not just the market but also the economy a giant bet on AI, with success vindicating the companies and investors who have bet on it, and failure manifesting in massive write offs at companies (feeding into losses) and stock price markdowns. As investors, there are four choices that you can make, and unfortunately, none of these choices give you the luxury of sitting out the AI debate: Go all in on the AI story winning (and doing it soon): The first betis that AI is an unstoppable force, destined to change the way we live and work, with AI businesses reaping the benefits of the disruption. It is a plausible story, albeit one that raises significant questions about the economic and social costs of disruption, with disagreements about the speed and extent of the disruption. It was the story that Leo Aschenbrenner built Situational Awareness around, and while excessive leverage, driven by hubris and over-conviction, brought him down, it is possible that you could mimic his strategy, of buying the AI disruptors and/or selling the AI disrupted, albeit with far less leverage, and win in the long term. Go with the market consensus: In an age where we worship at the altar of crowd wisdom in almost everything we do, you could examine what the market is pricing in, as its AI story, and go along. At the moment, at least, the market seems to be building in the expectation that AI will be a major disruption that will give rise to large and valuable businesses and it is picking its winners among the AI architecture companies (with Nvidia the biggest so far) and among the LLMs (SpaceX in the public markets and OpenAI and Anthropic in the private markets). For better or worse, you may have already chosen this path implicitly, if your pension funds and savings are invested passively, getting partial exposure to this story with an S&P 500 fund, and more complete exposure if you buy a total market fund for US equities. Be an AI skeptic: There are many reasons to be skeptical about the AI story, and for some, that skepticism may lead to the belief that AI will not make it as a viable business, or at least one large enough to sustain the pricing and investment you are seeing for it. While that belief may not be strong enough to lead you to act on it, you can steer your new investing away from the AI space, investing in businesses that are least likely to be altered by AI (food processing and leisure) and in geographies where AI is less likely to be a threat, such as the EU (perhaps because of regulation) and parts of Asia (because AI is too expensive to replace human labor in many buainwaawa). Crash out on the AI story: If your belief that AI will fail hardens into a conviction that failure is imminent, you can try to actively cash in on your story. You should, at the minimum, reduce your exposure to equities, especially in the US, by selling your holdings and putting that money into cash,. If you are more risk taking, you can sell short on the companies that have seen their pricing surge on the AI story and perhaps buy the companies that AI was meant to disrupt, flipping Leo Aschenbrenner's story. This has not been a winning strategy for many of the traders and investors who have tried it out for the last two years, and it is worth remembering the adage hat markets can stay irrational longer than you can stay solvent I am personally going with the "market consensus' choice for the bulk of my portfolio, since I do hold five of the Mag Seven (all except Tesla and Nvidia) and four of my holdings in this group (Amazon, Alphabet, Meta and Microsoft) are heavy investors in AI cap ex, but the new money added to my portfolio in the last year or two has gone mostly into cash (short term treasuries, yielding 4%) for much of the last year, leaving my portfolios more cash-laden than usual. I have left money on the table undoubtedly by doing so, but it has helped me sleep better at night, and my advice to you is that you find a pathway in the AI jungle that helps you pass the sleep test as well. There is one final piece of this puzzle that bears watching, and that is a portion of your portfolio that does not show up (yet) in your holdings. The income you will earn in your occupation, over the rest of your working life, is human capital, and to the extent that you believe that AI disruption is coming for your profession, it behooves you to direct your financial capital away from the businesses most exposed to AI disruption to balance your portfolio. I am old enough not to care much about this component, since I have fewer working years left, but if you are much younger than me, this could change your investment game. YouTube Video Blog Posts on AI AI's Bar Mitzvah Moment: From Hope and Hype to Business Questions! Spreadsheets Implied Equity Risk Premium on September 30, 2026
A look at how Four Seasons founder Isadore Sharp learnt to handle recessions in one of the most cyclical industries known to man.
Plus! IP; Gemini; Interfaces; The End Customer; Humans
October is here, the markets are coming off a pretty choppy September, and there’s a lot happening beneath the surface.
I’m excited to share this previously unreleased 2022 conversation between Charlie Munger and Todd Combs. Public Release: Oct 6th. Members have access now.Join us. As with any Munger talk, the subjects are both deep and wide. I’ve pulled out the ideas that most resonated with me. You’ll learn how Munger recognized people worth betting on, chose problems … The post [Outliers] Charlie Munger’s Interview with Todd Combs appeared first on Farnam Street.
