It is undeniable technology companies have found their most hospitable setting in the United States and while there are many reasons for the US dominance of technology, easier access to capital for young businesses has been a key ingredient. Venture capital in the US, in its institutional and organized form, can trace its roots back to the 1950s, and over the last few decades, it has generated its share of legendary investors. Vinod Khosla is one of those legends, and it is for that reason that I was surprised to see him tweet the following: I understand that utterances on social media, often in response to comments by others or made in anger, are often quickly regretted, and I believe (though I am not certain) that Mr. Khosla did not quite mean what he said here, confusing profitability with cash flows, and arguing that every business should put scaling ahead of profitability. That said, his view that scaling should be given priority over profitability is more the norm, than the exception, among many venture capitalists, and while it probably always has been the case, I believe the tilt towards scaling has become pronounced in the last two decades. In this post, I want to zero in on the scaling and profitability trade off, how the emphasis on the former over the latter plays out at start-ups and very young companies, and why we live with the consequences, whether they want to or not. Scaling versus Business Building     To put the choices you will face on scaling up versus business building into perspective, let's assume that you are a founder, and that your start-up has a tested product and that you believe there is a market for that product. You can stay with what you have built and build a business to take advantage of the immediate market, focusing on financial health and profitability. The fact that you will stay small, and perhaps unrecognized in markets other than your own, is a minus, but there are pluses. You will have little need for external capital, and you will own much or all of the business, facing little pressure from outside to change the way you do things. Alternatively, you can take a more ambitious route, where you seek out a bigger market, augmenting existing or adding new products, and while that path will deliver larger revenues, you may have to work harder to get it to deliver profits and cash flows, and perhaps have to give up more of your ownership and control of that business. The Scaling Choice     Before starting on the determinants of scaling, it make ssense to begin with the metric being scaled. For most businesses, it is revenues that is the chosen metric, with scale capturing how big revenues can become over time. With some earlier-stage businesses, many of which are pre-revenue, the metric can become a variable that these businesses hope to convert to revenues; with tech intermediaries and social media companies, it can be users or subscribers.      Focusing on scale, though, there are factors that come into play that allow scaling to have a higher likelihood of success in some businesses than others: Market size: It is easier to scale up a company, if it is small player in a big market, than if if the market is small, and scaling up will quickly give you a dominant market share. That said, the way you describe your business, and then run it, can play a role in how big a market you will have for your products. In my posts on valuing Uber, for instance, I noted that describing it as a logistics company (car service, moving, delivery) rather than just a car service company could triple its potential market.  Market growth: It is also easier to scale up a company if the overall market that it is targeting is also growing, since growth does not require going after competitors' customers. A smartphone company (Apple or Samsung, for instance) in 2010 had a growing market to work with, as customers switched from flip phones and smartphones made inroads into large emerging markets.  In 2026, that advantage had largely dissipated, as the smartphone market has matured. Industry Structure: There is a natural structure to industries, driven by economics and business type, with some industries splintered across many players, and some concentrated in a few big players or even in a winner-take-all. You can scale up more in the latter, but you will have to confront the odds favoring you being one of the winners in the industry. Capital intensity: It is easier to scale up a business that does not require large capital investments to be able to generate more in revenues. Using Uber as an example again, scaling up was made easier in the early years, since it did not own the cars or hire the drivers that comprised its car service, and growth came quickly and with little added investment. Customer inertia: Businesses can grow faster and get bigger if there is less inertia among customers and more willingness to try out new products or services. At the risk of generalizing, this may explain why scaling up can happen more quickly in younger industries (like technology) than in older ones (health care, education). Key person(s): There are some businesses that are built around the specific skill sets of a person (usually a founder or business owner) and these skill sets are not easily transferred or taught to others. A master craftsperson, say a furniture-maker, will have a more difficult time scaling up that business, because without being able to pass his skills on to his or her apprentices (which can take time and require intense oversight), he or she is constrained in how much new business he can take on. If that craftsperson has a recognizable name, it is possible that you could build a scalable franchise model, as has been tried by some master chefs (Wolfgang Puck, Gordon Ramsey etc.) The graph below captures the scaling choices that companies make as a function of these factors: As you can see, some businesses can scale up quickly, some take more time to scale up and some never scale up, and the businesses that scale up quickly often scale down just as fast. Thus, the decision of whether to scale and how quickly to do so is as much driven by the nature of the business (capital intensity, industry structure, competition) and the characteristics of the market that it is targeting (size and growth, customer inertia).  Business Building     While having access to a big, growing market can allow you to scale up more quickly, your capacity to generate profits and build a business will ultimately come from other forces: Unit economics: Unit economics measures the profitability of the marginal unit sold by a business, and is thus determined by the price charged for that unit and what it costs the business to produce that unit. Businesses like software, where the marginal unit costs very little to produce and can still be priced highly, have superior unit economics and will find it easier to convert growing revenues into profits, since much of the increase in revenue will flow into profits.  Conversely, businesses like electric cars, where each additional car sold costs money to make, will struggle to convert scaled up revenues to profits. Economies of scale: Businesses with large fixed costs, whether they be associated with maintaining platforms and infrastructure, or sales and marketing, face obstacles to profitability. While growing can provide scaling benefits, that works only if the fixed costs don't grow with revenues and if they are not so onerous, that you still have losses after scaling up.  Competition: & Competitive Edges (moats): Large and growing markets provide businesses with opportunities to grow, but for that growth to translate into sustainable profits, these businesses will need pricing power and that power comes from barriers to entry that keeps new entrants out and gives existing players advantages.  It is true that the operating choices that businesses make play out on both the scaling and profit dimensions, sometimes pitting them against each other. A decision to lower product prices may increase revenues at the expense of unit economic profits, and a decision to spend more on advertising and promotion may expand markets, but the higher marketing costs will impose a drag on profitability.     One way to illustrate the combination of forces that go into business building is to to go back to basics, and to look at what lies under each one: As you can see, scaling up is not a mantra that automatically translates in profitability, and the pathway to profits will be determined by variables that are often out of the control of a business.  Scale & Profitability Mixes     With the multitude of factors determining both scaling potential and business model viability, it should come as no surprise that the outcomes that we observe can range the spectrum, starting with extraordinary companies that scale up quickly, while delivering huge profits, to companies that never scale up, either by choice or because they could not, and some of which never make money. Lightning in a Bottle: Are scaling and profitability mutually exclusive? Put differently, can a company scale up, while delivering profits and perhaps positive cash flows as it grows? The answer is yes, but it does require a fairly unusual combination of circumstances - a big and growing market, being an early entrant into the market with few competitors, low capital intensity and excellent unit economics.  There are a few companies that meet these conditions, and we will call them "Lightning in a Bottle" firms, partly because they are rare, and partly because success can come from being at the right place at the right time. Google and Facebook, in their early years, were good examples, with revenues growing exponentially and profitability in place. Field of Dreams  (Shoeless Joe Jackson version): As a baseball fan, I have always had a soft spot for the movie, Field of Dreams, where a farmer (Kevin Costner) builds a baseball field in the cornfields, and when asked why, responds with "if you build it, they will come". There are companies that seem to be built around this motto, where scaling up comes first, often accompanied by large losses, but with the promise that "if they build (revenues), they (the profits) will come. During Amazon's first decade and a half of existence, I described their business model as a Field of Dreams model, and gave credit for Jeff Bezos for being steadfast in not only telling this story, but also acting consistently with it, and carrying investors along. (If you are wondering what Shoeless Joe is doing in this story, I am afraid you have to watch the movie all the way to the end.) Field of Nightmares: Amazon was not the first successful Field of Dreams company, but as one of its highest profile winners, it gave rise to a legion of young companies, all labeling themselves the "next Amazon". Needless to say, Amazon's success came from being a disruptor of a huge business (retail), which had atrophied and weakened over time, and many of the Amazon wannabes that tried to imitate it managed to do so on the growth dimension, with immense amounts of capital invested in scaling up, but never turned the corner on profitability, partly because they had neither the unit economics nor the economies of scale to pull it off. Niche Star: Scaling is not always the optimal choice, and there are some companies that recognize this reality early, choosing to stay small and focusing on a portion of the market where they have decided advantages. To that extent that they can convert those advantages into premium pricing and niche market dominance, they can have values that are disproportionately large relative to their operating metrics, i.e., trade at high multiples of revenues and earnings. Ferrari, for instance, sells only a few thousand cars every year, but with an operating profit margin in excess of 20%, it trades at a market capitalization comparable to that of auto companies that sell hundreds of thousands of cars each year. Big and Broken: It is no secret that there are some businesses that start with business models with a fatal flaw, i.e,, a broken business model, and rather than being shut down, they are fed increasing amounts of capital and allowed to scale up. A real-estate based business that leases properties long term, and then sub-leases them short term, has a duration mismatch born in hell, and expanding it geographically and allowing it to lease hundreds of properties, as WeWork did, just makes it a really big, bad business. If you are puzzled as to why investors would supply capital to these businesses, you may want to read on. Small winner & Small losers: If you look at all businesses, private and public, most remain small, some due to business and industry structure and some because of owner constraints on capital and control. These small businesses, though, over time, bifurcate into good small businesses, earning more than their cost of capital and delivering value, and bad ones, earning less than the cost of capital, but still worth more as going concerns, than liquidated. Cut your losses: Finally, there are businesses that start up with dreams aplenty, and over time discover that they can neither scale up, nor make money. In the absence of capital infusions, these businesses fail early, but if capital providers keep funneling resources into these companies, they still fail, but do so later and with a much higher price tag. In the matrix below, with scaling on one axis and profitability on the other, I plot all eight of my scale/profit combinations: Any investor or founder who blindly follows the pathway of scaling first and profiting later for every business is using a cookbook approach to business building, and runs the risk of making small failures into big ones.  The Tradeoff between Scaling and Profitability: Determinants     As you review the factors that govern the trade off between scaling and profitability, it is clear that the right choice (on how much to scale) will depend on the firm, and that not every small firm is destined to become or be more valuable as a larger firm, and that not all large firms have the same profitability characteristics, once scaled up. That said, is it possible for firms to adopt scaling pathways that look, at least from a business standpoint, to be suboptimal? Of course! There are small firms that have viable pathways to scaling up that choose to stay small, and at the same time, there are small firms that are designed to be small, niche businesses embark on scaling that is value destructive, and the reasons are a mix of human frailties on the part of founders, system constraints (from governments and regulators), access to capital (too little or too much) and exit options (sell, liquidate or go public). 1. Founder Characteristics     The founder or founders of a business not only play a key role in guiding the business through its early days, when most start-ups fail, but they also make key choices that can determine in its end game. In making these choices, they may be guided by the fundamentals we outlined in the last section, that affect scalability, but they are also a function of their personal make-up, on at least a couple of dimensions: Control versus Ambition: There is a natural tension between wanting to control the levers of decision-making in a business and scaling that business, since the latter almost always requires raising capital from providers who will either constrain your choices (if borrowed money is used) or demand a share of ownership rights (if equity). With the latter, founders will find their control diluted over time, and with enough scaling up, it is possible that founders end up with less than controlling stakes. For some founders, that fear of dilution and losing power over their business creations runs deep enough to stop them from embarking on growth plans, even though these plans make economic and financial sense.The flip side of control is ambition, and for some founders, the desire to build big businesses that are not restricted geographically or in product offerings can drive the decision to scale up, even though the fundamentals may not support that expansion. This works only if they can convince investors that their ambitions In fact, this tension between a founder’s need to be in control and that same founder’s desire to build big plays out in what Noam Wasserman called the Founder’s Dilemma, where to make a business bigger, its founder has to step down or at least compromise on control. Longevity versus Scale: There is an argument to be made that if your intent as a founder is to build a business that is long-lived, your odds of success improve if you keep your business smaller and more focused on what it does well. While there are many exceptions to this generalized rule, it is worth noting that some of the longest lived firms in the world are family owned small businesses, that serve a niche market, and are passed down generation to generation in the same family. It is also true that firms that see a sudden surge in revenues, usually as the result of an external factors or happenstance, often live to regret their good fortune, as they scale up overnight. In the aftermath of the Covid shutdown, for instance, firms like Moderna and Peloton boomed, but they also overreached, and did long-term damage to their business models. In summary, the choice between scaling and profitability will play out differently across businesses, depending upon what founders value most, thought it is healthy for an economy to a have a mix of founders, since it creates a mix of businesses. II. Access to capital     It is true that businesses need access to capital, to varying degrees, to scale up, and the easier it is to raise that capital, the easier it is to make a business bigger. Capital can come from different sources, ranging from family wealth to venture capital to public equity, with each one carrying its pluses and minuses. Family (or friend) wealth:  Every business, through human history, having lived through its early days (when failure risk is high and its products and services are still untested) has faced a choice of whether to stay small, serving a market that it knows and understands, or whether to get bigger, going after a bigger market. For much of that history, though, with businesses funded with family funds and access to capital was limited, most businesses chose the first path and remained small businesses, focusing on building business models that delivered profits, with wide differences in success rates. For a few, owned by wealthier families, access to a much larger pool of capital (from family savings and bankers willing to lend to these families) created family groups that dominated economies, and continue to do so in some parts of the world.  Venture capital:  The growth of public equity markets in the late 1800s and much of the last century did little to change the family control dynamic, since investors in those markets were primarily interested in funding larger companies with established business models. Recognizing this gap between capital need and capital access at younger businesses, and the opportunities that the gap presented, allowed for the rise of venture capital in the 1950s, primarily in the United States. These venture capitalists provided seed capital for start-ups, using winners to cover their failures, and got the bulk of their winnings when they exited these investments, either by going public or selling to another entity. Over the last few decades, venture capital has grown, and in the last 12 years, that growth has not let up:  Source: NCVA 2026 Yearbook In this century, venture capital has also become more global, growing in Asia and Europe, but it is still true that it is easier for a small business to raise capital to scale up in the United States than it is in much of the rest of the world. Public equity: There are some growth businesses that bypass venture capital and go after public equity, a much bigger pool of capital and one that may give founders better terms. In some cases, this access to capital might be enabled by going public, even with unformed business models and little to show in terms of existing operations (revenues or earnings), but in most others, it takes the form of capital invested by larger, more mature public companies in return for a share of ownership. These investments may be labeled as strategic, but the motives for making these investments vary across companies. Some invest to get access to a promising technology or product. some to pre-empt competitors and some for the same reason that venture capitalists do. The bottom line is that businesses that seek out capital, whether from family, venture capital or public equity, have to accept that the capital providers will demand and usually get a say in business decisions, and the more capital you seek, the more sway they will have. III. Investor Preferences     Businesses get their cues on whether to scale up or build business models from the investors who fund them, and much as founders want to map their own path, investor preferences matter, as do their end games. Put simply, a family that invests in a business with no plans for exit will choose a very different path for that business than a VC that invests in the same business with the intent of exiting that investment by selling it to another investor or company, or taking it public.         Venture capitalists are often viewed as the sherpas who guided young businesses to success, both operationally and in markets, the mythology about venture capitalists and what they do has also built up. Since that mythology extends to almost every aspect of venture capitalist activity, perhaps the best way to dispel myths and bring in reality checks is to look at what venture capitalists are "assumed" to do in each phase, and contrast it with what they actually do:     If you are reading this as a critique of venture capitalists, you are misreading it. My intent is not to paint a picture of venture capitalists as lazy and greedy, but to bring home the reality that given how venture capitalists invest, act and are judged, it is unrealistic to expect them to do the heavy lifting of building businesses for the long term and to even make business sense, when they talk about companies.     There are two parts of the venture capital rulebook that you should focus on, to understand why many VCs prioritize scale over profitability. The first is that they price companies, rather than value them, and in a post from a few years ago, I made the argument in more depth. VC pricing based on what other venture capitalists are paying for similar businesses, often scaled to simplistic metrics, users and subscribers for pre-revenue companies and forward revenues or earnings in what passes for VC valuation: The second is that VC success is measured based on price at entry and price at exit on an investment, rather than the quality of the business built, and using that metric, the median venture capitalist has not been much better at harvesting alpha than the median mutual fund manager or PE investor: Cambridge Associates There are, of course, standouts in each of these categories, fund managers who have delivered well above the market, but in mutual funds and to an increasing extent, hedge funds, that success is fleeting. There are two aspects on delivering returns where venture capital stands out, relative to other active investing classes.  The first is that failure, always a concern in investing, is much more a part and parcel of investing in venture capital than in other investing grouping. Put simply, not only are there more VC funds that go out of existence every year, but even the most successful VC funds lose on many or even most of the investments that they make, especially in angel financing deals.  The second is that venture capital investing, when it works, can generate outsized returns on winners that (hopefully) cover the cost of failures.  You can see both of these at play in the graph below, which looks at returns that VCs book when they exit investments: CF Private Equity, from Pitchbook data As you can see, across all the time periods, it is the top 10% of VC investments that deliver the bulk of returns to VC investors, and over time, that concentration has increased: in the 2023-2026 period, 80% of all returns to VC investors came from their top 1% of investments. The combination of these two forces (losses on most investments and outsized winners), i.e., the power law in venture capital, has two consequences. The first is that only about a quarter of venture capitalists in each year deliver above-average returns, making the average VC returns in the table above more palatable. The second is that success in venture capital, unlike in other areas of active investing (including mutual funds, hedge funds and even private equity), has been more enduring. The power law characteristic also feeds into VC incentives, leading venture capitalists to direct their capital more into chasing the biggest winners than in building businesses. In fact, the more top-heavy VC returns become, i.e., dependent on big payoffs, the more pressure venture capitalists feel (and pass on to their portfolio companies) to find the next big winner, pushing the ecosystem dangerously close to gambling. A Changing Game     With the discussion of the scale versus profitability at the business level leading in, and the assessment of the incentives of capital providers following, I think that we are well positioned to examine how changes in public and private markets have increased business incentives to scale, as opposed to building business models. There are two developments, in particular, that have taken the tilt towards scaling in venture capital and made it even more pronounced - the entry of public equity into the funding of private businesses and the fading of reversal, as an antidote to momentum, in public markets. The Gray Market Effect     For much of the last half of the last century, after venture capital established a presence in the United States, it remained the only or primary source of capital for young firms. That has changed especially int the last decade, as public equity investors have increased their investments in young, private businesses, supplementing venture capital in some and even displacing it in others. An early measure of this trend is captured in the charts below: Kwon, Lowry and Yiming (2020) While this graph looks at only the number of mutual funds investing in private businesses, and stops in 2016, there was a corresponding surge in capital invested by mutual funds in young, growth companies, with T.Rowe Price and Fidelity investing billions in high profile tech companies like Uber.  They were joined by sovereign funds, who invested heavily in these companies either directly or indirectly, through stakes in entities like Softbank's Vision fund.     We can debate the reasons for why we saw this surge, with fear over missing out (FOMO) and wanting to partake in tech playing roles, but whatever the reasons, capital access surged for young companies, especially in tech, during the period. In effect, rather than two mostly separated markets - one for young, smaller, private business dominated by VCS and one for larger companies more advanced in the life cycle, where public equity suppled the funds, a gray market was created where VC and public equity fund access allowed private businesses to stay private for longer. Public Markets: Momentum, Fundamentals and Reversals     Public equity markets have always been momentum-driven, allowing traders who ride that momentum to prosperity, before bringing them down when the momentum shifts. At the same time, fundamentals act as an anchor, operating as a counter to momentum, leading to reversals and allowing investors to hold their own over time. While the congruence is not always perfect, scaling feeds into momentum and profitability is the most critical fundamental, and in markets with balance, when one gets out of sync, the other restores harmony.  Over the history of stock markets, value investors have often claimed dominance, and pointed to the returns you could have earned by buying companies that look cheap on a value basis (low price earnings or low price to book) and waiting for price reversals. Traders push back by noting that over the same history, momentum has had a decisive effect on returns, especially over shorter time intervals.  While the momentum effect shows up across the decades, there is evidence that the reversal effect has weakened over time, leaving investors who bet on mean reversion and a return to fundamentals in the lurch: The reasons given for this shift vary, and are often reflective of the biases of the investors giving the reasons.  The Fed did it: For those who view central banks as all-powerful, and believe that the low interest rates of the last decade were their doing, those low rates have also become the proximate reason for market pricing behavior and reckless risk taking. Their argument is that interest rates that are close to zero induce investors to shift from bonds to stocks, and within stocks, to move from low growth, high earnings stocks to high-growth companies with little or negative earnings. The rise of passive investing: In the battle between active investing and passive investing, with ETFs supplementing index funds, the latter has had a decisive edge in terms of returns over the last two decades, and its share of the market now stands are well above 50%. There are some who argue that the flow of funds to passive investing vehicles has contributed to the increased power of momentum, since more new funds flow to the largest market cap companies than to the smaller ones. In addition, it is argued as the number of active investing declines, there are fewer investors looking at business models and profitability, reducing the pull of fundamentals on price. Public market composition: It is noteworthy that the reversal effect started weakening in the 1990s, a decade when young dot.com companies with unformed business models flooded the market, bypassing the more traditional route of using venture capital to grow. With these companies, where value is almost entirely driven by potential and not by operating metrics today, the catalysts needed for reversal may take longer to manifest. Information sources and access: It is undeniable that investors and traders get information from a wider ranges of sources now than two or three decades ago, with social media and online sources supplying information that used to come from newspapers and financial news channels. In additional to being less curated and controlled, that information is also instantaneously accessible to the public, and price reactions tend to follow.  While I take issue with parts of each of these arguments, there is some truth to all of them, and they have contributed to making pushing back against momentum a more hazardous exercise for investors. The Consequences     With larger amounts of capital being deployed by VCs at young, growth companies, substantial capital infusions from public equity funds into private capital markets, and public equity markets that are more used to and receptive to young company listings, it should not be surprising that it is changing how private companies behave. In the graph below, I look at the characteristics of companies going public in the United States, using the data that is generously made available by Jay Ritter; There are three clear changes over time that are visible in this graph: 1. Private businesses are waiting longer before going public: As you can see, the average age of a company going public has risen over time, with the median age rising about 11 years in the last 15 years. 2. Private businesses are scaling up (revenues) more, while waiting: While private businesses wait longer to go public, they are spending that time scaling up more than they used to. The inflation-adjusted revenues at the median IPO have tripled or even quadrupled, relative to IPOs in the 1980s. 3. Private businesses are deferring building business models & profitability: The most striking feature of the data, to me, is that while private businesses are waiting longer and scaling up more before going public, they also seem to be deferring business building for much longer as well. While it was routine for companies going public in the 1980s to be profitable (>80% were), less that a quarter of the companies that have gone public in the last decade have been profitable. While companies that are going public are bigger (in revenue terms) and less likely to be profitable, markets are attaching large market capitalizations to these newly minted companies, as you can see in this graph which zeros in on tech IPOs: You will also notice that companies going public are issuing smaller portions of their shares to the public, at least in the initial offering, suggesting that the need for capital that drove companies to go public has become less pressing over time, perhaps because of more capital access as private businesses. While the median market cap of a company going public in the last six years has exceeded a billion, the largest IPOs command market capitalizations that would have been unimaginable a few decades ago. From Facebook, with a pricing of $104 billion, in 2012 to SpaceX, going public in June 2026 at $1.8 trillion, the trend lines are pointing upwards, especially if Anthropic and OpenAI deliver on their trillion-dollar plus pricing promise.  Implications     By itself, the trend towards private companies scaling up more, while public, and going public at eye-popping market capitalizations may be understandable and explainable, but there are implications that we need to consider both from an investing and governance standpoint. Corporate governance: One of the reasons that private companies often delay going public is because governance requirements, from board composition to top management compensation, are more stringent at public than private businesses. While Sarbanes-Oxley, which wrote into law many of the current governance rules for public companies, is often toothless and ineffective, it still forces disclosures about governance (on conflicts of interest and board member relationships) at public companies. In addition, public market investors can pressure public companies to change governance practices or top management, if companies underperform in the market place. One of the perils of letting companies scale up more before these governance questions get raised is that the top management in these companies may have few checks on their actions. It is true that venture capitalists could operate as a disciplinary mechanism, but in an age of founder worship and where VCs can be divided and conquered, you can have companies with market pricing of a billion, hundreds of billions or even trillions run by people who are ill-suited for the task. Delayed business model building: If the first imperative for a private business is to scale up, because scaling pushed up pricing both in private and public markets, the challenge of business building will get deferred to a later stage. The problem with scaling up first, and building a business model later, is that it may be too late, since the choices made to allow for scaling up may impede the pathway to profitability. Again, if your response is that VCs will work on fixing this problem, they have little incentive to do so, since they benefit from scaling up and exiting these businesses, before the business problems become too big to ignore.  Scaling stories: If you believe, as I do, that valuation is a bridge between stories and numbers, and that the balance between the two shifts over the life cycle, with stories dominating early in the life cycle and the numbers taking center stage in the later stages, it is understandable that VCs and founders, when marketing their companies are primarily story tellers. I don't have a problem with that, but as I noted in my last post on AI as a business, the stories that are being told for these companies are often incomplete, and almost entirely focused on the scaling question. Thus, in the Anthropic sales pitch it is the growth in the annualized revenue run rate (ARR) and the size of the AI market (huge, but with no specifics) that comprises the bulk of the story, with little or no mention of business models or profitability. Disruption without replacement: Disruption has been a key component of the stories that underlie many of the largest companies that have gone public in this century. Accepting the premise that a healthy economy needs a shaking up of the status quo, and that disruption can lead to economic growth and better practices, it is still legitimate to look at disruption's debris. One of the perils of supplying capital in almost endless quantities to private businesses that aim to disrupt, without challenging them on business models, is that you may succeed at disrupting the status quo (driving existing players out of business) but your disruptor may not be able to build a business that can be self-sustaining in the long term. Conclusion     I am sure that you are already aware of the core message of this post, which is that notwithstanding the current emphasis on scaling up businesses, not all businesses are meant to scale up, and that scaling up comes with challenges that founders may be ill-equipped to meet. That said, ambitious founders will feel the urge to make their businesses bigger, and if they raise capital (from venture capitalists) to make this happen, the incentives to scale up will increase, even if it makes little or no business sense to do so, with all parties hoping to exit by selling to others (public or private) who will price based on scale. While this has always been the case, changes in private and public capital markets have tilted the scale even further in favor of scaling, and it is possible that companies, both public and private, with sky-high pricing have been built on bad business models that are irredeemable. YouTube Video Blog posts on Venture Capital and Scaling Blood in the Shark Tank: Pre-money, Post-money and Play-money Valuations (February 2015) Billion-dollar Tech Babies: A Blessing of Unicorns or a Parcel of Hogs (June 2015) Venture Capital: It is a pricing, not a value game! (October 2016) Risk Capital in Markets: A Temporary Retreat or a Long-term Pullback (July 2022)

Earlier this year, I was asked what I thought about Leopold Aschenbrenner and I admitted that I knew little about him other than what I had read about him, more in social media, than in the press - that he was a 25-year-old wunderkind who had started at OpenAI but had left to start a hedge fund. That hedge fund, built entirely around a bet that AI would pay off big time and near term, buying companies in the AI orbit and selling short on the businesses (especially software) that AI would disrupt, had been able to raise billions of dollars from well-heeled and presumably sophisticated investors, and had  posted eye-popping returns, up almost 450% through late June. Success of that magnitude needs no nitpicking, but it is worth remembering that there is nothing that markets enjoy more than cutting inflated egos and reputations down to size. In this case, the fall from grace was precipitous, and over the course of four weeks, the fund's public equity holdings lost more than two thirds of its value, but was also forced to liquidate, with Citadel buying almost all of its public equity holdings.     The reads on the swift rise and fall of Leo have been fascinating, a Rorschach test of investing priors. For older investors, the lesson was that you can be blessed with intelligence, but that wisdom required experience, which, at least in their saying, conveniently comes with age. For value investors, many of whom chafed at Leo being hailed as the next Buffett, there was vindication that there will never be another Buffett. For AI skeptics, who have long been on the lookout for catalysts that will break AI fever, there was at least a brief moment of hope that this was the catalyst. There is some truth and some overreach in each of these responses, and I don't plan to rehash them. Instead, I would like to use this story to talk about investing conviction, words used mostly in a favorable way, when people talk about success in markets. I am not as convinced that investing conviction is a net plus, but to get to that conclusion, I think we need to look at what it is, where it comes from and what it leads investors to do.  The Story of Situational Awareness     The Situational Awareness story is inextricably tied to the story of Leopold (Leo) Aschenbrenner. The short version of his life story is that he was born in Germany in 2001, and enrolled at Columbia University when he was 15. After graduating with a degree in economics in 2021, doing research briefly at Oxford University and working at Sam Bankman-Fried's FTX fund, Leo joined OpenAI as part of the team working on AI safety. He was fired in 2024 for leaking data on the firm, though his motivations for doing so are murky and he contests the allegation, and he published a long (167 page) paper titled "Situational Awareness: The Decade Ahead", which was not only widely circulated, but also became the blueprint for the fund that he created.     The Situational Awareness fund, founded in July 2024, and initially funded by tech luminaries, quickly took off as its bets on AI chips and infrastructure and against AI-damaged sectors paid off. Its early success allowed it to attract more money, with Jane Street being one of the more prominent names involved., and with the additional capital in play, it expanded its presence. While most of the companies that made the fund's list were publicly traded, it also had a stake that Leo had acquired in Anthropic, still a private business. The numbers posted by the fund made investors notice, as can be seen by its rise From August 7, 2025, to June 23, 2026, its highest mark day: Source: Portfolios Lab Measuring returns from August 7, 2025, Situational Awareness was up about 367% through June 19, 2026 and its returns since founding are even more stratospheric. Even at its peak, there were three caveats that any investor with experience in the market would (or should) have brought up. First, in market time, where decades of over performance are needed to separate luck than skill, a fund that has been successful for a little more than two years qualifies more as a shooting star than as a beacon of light. Second, to deliver returns of this magnitude, you not only have to be right in your guesses, but those guesses must be super-charged by adding substantial leverage to your strategy, either explicitly (by borrowing) or implicitly (by using options). Third, the fund followed the classic 2% (of funds under management) and 20 (% of specified upside) fee structure, an abomination that not only creates an almost insurmountable handicap, in the long term, for investors in the fund, but also encourages reckless risk taking on the part of management.     If the rise of the fund was breathtaking, its fall was even more so, and you can see the meltdown in the four weeks of July in the graph below, which looks at the fund performance from June 19, 2026 to July 29, 2026, the last day of trading for the day, before the fund was liquidated: Source: Portfolios Lab Note that the loss of principal (of more than 43%), with the Anthropic holding value retaining mostly intact, as a private holding, but with the public investment portion of the portfolio down by almost 67%. I am sure that there will be case studies and forensic analysis of what happened in these weeks, but for me, the lesson is one of market symmetry. What the market gives easily, it also takes away just as easily, and if you put into place strategies that are designed to deliver outsized returns, you have to live with the reality that you can have outsized losses. The surprise, though, for many is not that the fund lost money in July, but that it did not survive the month, and was forced to sell much of its public investment portfolio to Citadel, at prices, that at least in hindsight, look like bargain basement levels.  Conviction: What is it and where does it come from?     How do I get from the Situational Awareness story to a discussion of investment convictions? Simple! Leo's core belief that AI would win the battle with the status quo in most businesses, and that the win would be decisive and quick, was not unique, and not only are there other investors who shared that view, but there are also companies that are investing in AI cap ex, driven by that view. That said, to get from that view to a hedge fund built entirely around buying AI winners and selling AI losers requires that the belief to be deeply set and using debt to magnify those returns suggests strong conviction. What is investment conviction?     Before we embark on a discussion of investment conviction, it is worthwhile to start with an understanding of what it means. While there a myriad of definitions out there, the general consensus is that investment conviction measures the belief that an investment opportunity will generate significant returns, relative its risks, and with that definition, you can see that conviction is a continuum, rather than an absolute.  At one end of the spectrum, you have absolute conviction, where you know (or think you know) with certainty that an investment will pay off. At the other end of the spectrum is investment mush, where your feelings about an investment paying off are so weak that you are unwilling to even voice that opinion, let alone put money behind it. With most investments, you fall in the middle, with the variations being in the degree of confidence that you have in being right.     As you can see, the elevation of conviction as something to be sought after in investing is because in the complete absence of conviction, you will not act and that paralysis can result in portfolios entirely or almost entirely held as cash. I don't think, though, that even the strongest proponents of conviction as a good quality in investing  would make the argument that you should feel certain about the outcome of investments, when uncertainty is part and parcel of investing.  Where does conviction come from?     So, what is it that determines investment conviction or the lack of it? To generate a basis for that discussion, let's go back to basics, and start with an assessment of what has to happen for an investment to be viewed as a money maker. No matter what your investment philosophy, the process starts with a market price for an investment, and an assessment of what you believe is a "fair price" for that same investment. I am being agnostic about how you arrive at the fair price, leaving the door open for chartists, who may find it by looking at past price patterns, fundamentalists, who believe that you can assess fair price, only by looking at the fundamentals of the investment and traders, who may be in possession of information that leads them to believe that the current price is wrong. For the process to deliver winnings, though, there is a second part to the process that often gets less attention, which is that the market has to correct, with the market price moving towards or even to your fair price.  To have conviction in an investment, you therefore need to believe strongly in three aspects of this process: That your assessment of "fair" price is right (or at least more right than the market consensus)  That the market will correct, i.e., that the market price will move to, or towards, your fair price That this correction will happen during the time you plan to hold the investment (your time horizon), either because the investment has an expiration date (maturity) or because you feel that there will be a catalyst that causes the correction. With this description in place, you can see that investment conviction will depend on the investment in question, the market that it is priced in and on the investor making the judgment. a. Investment Mispricing     If the investment process starts with an assessment of a fair price that is different from the market price, there are at least four reasons why you may be more confident in your assessment of the price of an investment, relative to the market consensus: Private information: At the risk of treading on or crossing the line between the legal and the illegal, you may be in possession of information about an investment that is not available (or at least widely enough available to the public to be priced in) that you believe will change its price. Information processing: To the extent that private information is rarely available to investors, and even if available, difficult to act on legally, much of active investing is built around collecting and processing information that is available to the market. That private information can range from past prices and trading volume (used by technical analysts) to public filings (the financial data that the company provides, often the basis for fundamental investors) to quasi-public information (analyst forecasts and revisions, hedge fund and mutual fund holdings). If you are using this information to assess a fair price, it is because you believe that you have found patterns in the data that others have not. Business understanding: In some cases, your fair price will derive from your belief that you understand the business economics for a company better than other public investors do, with your superior understanding coming either from working in the business or from technical training. This is especially true in complex businesses (like bio pharma) and complicated assets, and likely to be  more the case with young companies, where financial history can stand in for business understanding. Pricing mistake: There are some investment theses that start with a market mistake, whether it be in pricing an individual asset or a pair of assets. With a pair of assets, often with similar fundamentals, the mispricing manifests with one of the assets being mispriced against the other, and the correction take place when the mispricing disappears. It is at the heart of derivatives trading, where options or futures on a traded asset can be mispriced enough that you can lock in the profits from the pricing mistake, with the guarantee of correction, when the option or futures expire. In sum, you can see that the degree of investment conviction that an investor has can vary across different asset markets (real estate, equities, fixed income, derivatives), geographies (developed versus emerging markets) and within equities, across industry groups and sectors (less for technology and more for utilities, for example). b. Market correction     Investment conviction may start with the spotting of a market pricing mistake, but for conviction to build, you need to get a measure of when, why and how the market will correct its mistaket. Here are some of the forces that can cause variations on the market correction dimension:     Finite maturity versus indeterminate end game: An investment with a finite maturity date comes with a greater likelihood that prices will correct than one without. A bond that is mispriced, by itself, or against other bonds of equal maturity, comes with a greater chance of correction than a stock that is mispriced against its own fundamentals or a paired stock. For the same reasons, if you can lock in a mispriced option against its underlying asset (or stock) or against other options of equal maturity, you are moving the odds in favor of correction. It should come as no surprise that true arbitrage, i.e., positions that can lock in guaranteed profits that exceed the riskfree rate are almost always in the fixed income or derivatives markets and that much of what passes for arbitrage in equities is quasi or pseudo arbitrage, where risk remains in the position. Market frictions: Market mispricing can sometimes reflect market inattention or irrational trading, but they more often are the consequence of market frictions, including restrictions on selling short and exerting control over an investment (such as buying and liquidating a company). If that is the case, it is possible that market mistakes, while visible and seeming obvious to everyone involved, may never get corrected, or at least not get corrected until the friction is removed. Market liquidity and depth: In equity markets, where there is no date by which mispricing has to disappear, corrections often require catalysts, i.e., events that lead market participants to reassess a market price, and to correct it. Those catalysts can come from corporate disclosures (earnings reports, for instance) by the mispriced company, corporate restructuring (divestitures and spin offs) or high profile investors (activists taking a stake in a under priced company or selling short an overpriced one). All of these catalysts are more likely to be present in liquid and deep markets, where information flows are more frequent and varied. Investment time horizon: No matter what the market mistake, it can be argued that  having time as an ally, and being able to wait for longer periods, for market corrections, should not only give you a greater chance of gaining from a market correction, but also give you more conviction in your investment, other things being equal. The bottom line is that you can feel (relatively) certain that an investment is mispriced, but have no conviction in that investment, if you have no sense or faith that the market will correct in your time frame for investing.  c. Investor characteristics     Is it possible for two investors to find the same market mistake, with the same underlying rationale for the mispricing, and have different degrees of conviction in following through? Absolutely, and while part of the reason is differing time horizons, there are other investor-specific forces that also come into play: Intelligence and educational background: This may be a generalization, and if you disagree, you should take exception, but the smarter an investor is, and the more exceptional his or her educational background (the right schools, credentials and certification), the greater the conviction that investor is likely to bring to investments. One reason is that it becomes easier to attribute perceived market mistakes to the lack of intelligence of other market participants than it is to take a closer look at real reasons why they may not be mistakes in the first place. Personality: Like conviction, self confidence falls on a spectrum with wide differences across human beings. Some investors measure low on the self confidence scale, and look to others for big decisions. Others measure higher  on the self-confidence scale and are willing to make decisions with incomplete information and in the face of uncertainty and disagreement. Still others have so much self confidence and so little self doubt that they risk having convictions that are out of sync with reality.  Over five decades of research in behavioral finance has highlighted overconfidence as one of the key drivers of irrational investor behavior, and underscored the reality that not only does this trait vary widely among individuals, but also that the most overconfident players often rise to the top of the investment and corporate world. In the conviction discussion, overconfidence enters the game early and is perhaps the best explainer of why some investors, looking at what they think is a market mistake, feel so much more convinced that they are right than other investors looking at exactly the same mistake. Track record: When you invest, you receive almost instantaneous and continuous feedback on whether your investments are paying off, and while investment success is always preferable to failure, it is undeniable that some of the worst investment lessons are learned from that success. Much as Wall Street likes its adages of "not mistaking dumb luck for skill", investors are quick to forget them when an investment bet that they make pays off, especially when their success leads to iconic and admiring profiles ("the next Buffett") and investor capital pouring in. You will notice that I don't list age as an additional characteristic, but that is because I don't equate aging with wisdom or temperance. It is true that aging usually muddies your investment track record, and that there is no better bound on over confidence than losing lots of money on what you thought was a sure bet.  The Consequences of Conviction     At this point in the post, I don't blame you for wondering why conviction is such a big deal, since buying Palantir or SpaceX with low conviction counts just as much buying shares in these companies with high conviction. Conviction matters in investing because it affects two choices that investors make - the sizing of positions (with more conviction leading to larger positions in the same investment) and the use of financial leverage (with more conviction often translating into a willingness to borrow more money to fund the investment).  Concentration     One of the fundamental questions in investing, and one that evokes strong disagreement, is how much, if at all, investors should spread their bets. The debate is an old one and there are many views that fall between two extremes. At one end is the advice that you get from a believer in efficient markets: be maximally diversified, across asset classes, and within each asset class, across as many assets you can hold. The proverbial “market portfolio” includes every traded asset in the market, held in proportion to its market value. At the other is the “go all in” investor, who believes that if you find a significantly undervalued company, you should put all or most of your money in that company, rather than dilute your upside potential by spreading your bets. The discussion of investment conviction ties into the answer to this question.  I am not an absolutist on this front, because what you do as an investor should reflect your circumstances.  At one limit, if you are certain about your assessment of value for an asset and that the market price will adjust to that value within your time horizon, you should put all of your money in that investment.  This may seem like an impossible dream, but it it is what you hope to pull off if you find mispricing in the bond or derivatives markets (true arbitrage), where you can lock in the mispricing, with a guaranteed price correction at maturity (of the bond or options).  At the other limit, if you have doubts aplenty and no conviction in your investment choices, you should be as diversified as you can get, given transactions costs. If you have no transactions costs, you should own a little piece of everything, a very real choice in a world of index funds and ETFs. After all, you gain nothing by holding back on diversification and your portfolio will be deliver less return per unit of risk taken. If you are active investor who is constantly in this position (of having no conviction), it is best to retire the "active" part of your investment profile and go all in on index funds.      For most active investors then, the question of how much to diversify will depend in large part on how strong or weak their investment conviction is, and that, in turn, depends on what investments these investors are focused upon. In this context, I would argue that the right amount of conviction and by extension concentration (or diversification) will depend upon the types of companies you invest in (with more diversification needed when you invest in younger companies) and your time horizon (with concentration increasing with time horizon)  Leverage     Financial leverage is an instrument that investors can use to enhance returns, but its use in investing has always been controversial. While borrowing money to fund an investment will increase upside, if you are right, it will also magnify downside, and in some cases, precipitate collapse, if you are wrong. In the early year of investing, financial leverage generally took the form of borrowing money to buy riskier investments (stocks), but the wave of default and distress triggered for investors by the great depression led to restrictions on the use of margin in stock markets. However, those restrictions varied across investor groups (with individuals facing more restrictions than institutions) and across asset classes (with more leverage in real estate than in stocks). The growth of derivatives markets opened the door to bypassing these borrowing restrictions, since buying a (naked) call option is equivalent to borrowing the underlying asset with debt, with leverage increasing with how out of the money the call option is.     Since leverage magnifies both upside and downside, it stands to reason that investors with more conviction in their investment, i.e., that it is under priced and that correction is imminent or very likely to happen, will borrow more money than investors with less conviction: When you are certain that an investment will pay off, you can use maximal leverage, and in true arbitrage, this leverage can be used to convert small mispricing into pure profits. In fact, when options and futures are mispriced relative to their underlying assets, you can borrow 100% of your investment needs, and since the pricing error will disappear at maturity, make a pure profit.     In sum, financial leverage magnifies your core investment judgments. If they are good, leverage will make them look better over time, and if they are bad, they will make them worse. That said, there is a component to the use of leverage that needs to be brought into the picture. Even if you are a good investor, with solid conviction in your investment ideas, using debt to turbocharge your returns can sometimes shrink your time horizon by forcing you to liquidate your mispriced investments before the market corrects its mistakes. That truncation risk eliminates the possibility that you can come back from your losses, and perhaps even have your investment thesis vindicated. A Corporate Life Cycle Perspective on Conviction, Concentration and Leverage     I use the corporate life cycle construct in almost every aspect of finance, because it not only helps understand corporate and investor behavior, but also provides perspective on why one size (or proposal) does not fit all. The corporate life cycle maps out a firm's evolution from a start-up to a growth company to maturity and eventual decline, and traces out changes in revenues, earnings and risk over the aging process: There is no deep intellectual insight here, but as companies age, the challenges that investors face in pricing them shifts. With young firms, where there is little history, the business model is still in flux and the value lies almost entirely in the future, the pricing will be less precise than for more mature firms, where there is an established business model and more financial history, and more of the value comes from investments already made. For declining firms, where liquidation looms as a viable option, the pricing exercise becomes one of estimating liquidation value, i.e., what others will pay for the individual assets owned by the firm. The higher pricing uncertainty that investors face when valuing younger companies is accompanied by a second problem, which is that pricing mistakes, if they exist, need catalysts for market correction. Those catalysts are less frequent and decisive with younger companies, where earnings reports have little of substance to report and operating targets are diffuse, creating more open questions about whether a market mistake will be corrected, and if so, when that will happen.     Using this framework, you can see that you can be more tolerant of concentrated portfolios, with debt added on, when you invest in mature companies than you should be when investing in younger companies. By the same token, investors who find pricing mistakes in younger companies, but are daunted by the noisiness of their estimates or uncertainty about markets correcting, and thus are low on the conviction scale, can overcome their reluctance to act by spreading their bets across many such companies. As some of you may be aware, I did value SpaceX at the time of its IPO at about $100 a share, and as the price has drifted down towards that price, I may very well be faced with an underpriced stock (where the market price drops below $100). Given the uncertainty that is associated with my estimate, and you can see it in the simulation that I reported in my post, it is unlikely that I would ever have sufficient conviction to make SpaceX the biggest or only investment in my portfolio, but I stand ready to buy the stock as part of a portfolio, where it is one of many bets that I make on markets. Lessons from Leo I started this post with the story of Situational Awareness and Leo Aschenbrenner, but I spent most of it talking about investment conviction, what it is, its sources and consequences. I want to end the post by returning to Leo’s story and what we can learn from it as investors. Lesson 1: Investment actions that are inconsistent with investment conviction risk ruin     I have no issues with Leo's story of AI winning big in the near-term and buying the winners and selling the losers that will result. It is macro story investing, and it has worked for some in the past and failed for others, but if timed right, it can deliver significant returns.  In fact, I will concede that Leo knows far more about AI than I ever will and is using that knowledge in constructing his AI story. I also have no bone to pick with investors using financial leverage to supercharge their returns,  with low-risk investments, though I remain concerned that the (2 & 20) fee structure may lead them to use too much debt. My concern with Situational Awareness, as a fund, and this would have been true on June 19, even at it peak, is that combining a macro story about AI winning with maximal leverage creates a time bomb. The AI story, no matter how well told, has multiple obstacles to overcome, some related to business economics and some to politics and regulation, and is a risky bet, and it makes sense to fund it with significant amounts of debt. I know that there are defenders who will point to the fact that the fund, even after its markdown, was up substantially from its inception date, but the fact that leverage cut the fund's life short only strengthens the case that if it had been run with less debt, it would have had a bad month in July, but lived to tell the tale and perhaps even deliver on its AI promise. Lesson 2: Momentum is a wild card in every investment strategy, and you ignore it at your own peril. It is a well-established finding in equity markets that momentum is one of the strongest forces moving markets and that it can overwhelm the best planned strategies of most investors. If you look at the composition of Situation Awareness portfolio through much of its rise and fall., the long positions were primarily in companies that benefit from the build-up of Ai architecture, selling their products and services to the hyper scalers and LLM companies, and the short positions were in software and other businesses that would be disrupted by the rise of AI. With both groups, Situational Awareness was taking bets that were in line with what the market was pricing in already, albeit in a more concentrated and leveraged form. While market observers were quick to link both the rise and fall of Situational Awareness to the AI story, you can make just as strong a case that much of that happened at the fund over its brief existence can be explained by momentum, with leverage acting as a super charger; continued momentum generated the outsized return though June 19, and the market reversal in July caused the correction. Lesson 3: Humble money beats smart money     The legend of smart money persists in markets, where investors who are smarter than the rest of us, with access to information and capital that others do not possess, deliver supersize returns for themselves and those that they invite into their inner circle. That legend serves everyone's interests, since the smart money uses its reputation to attract more capital and the not-so-smart money has someone else (hedge funds, insiders, activists) to blame for investment setbacks. While many money managers aspire to be part of the smart money group, most never make it into that rarefied circle, and those that do often have to pay their dues over long periods. Leo Aschenbrenner, in contrast, broke into the group in just a few months, perhaps helped by his pedigree as an AI insider and with an assist from his post on the coming AI revolution. The problem with smart money is that  its self-regard makes its susceptible to attributing more precision to its own convictions, than merited by the circumstances, and that, in turn,  results in over reach (portfolios that are much too concentrated or levered). Situational Awareness clearly overused leverage, and while some will attribute that to the youth and inexperience of its lead manager, it is worth remembering Long Term Capital Management, where John Merriweather, after a long and distinguished trading tenure at Salomon Brothers, aided by two Nobel Prize winners in economics, brought the fund to its knees by borrowing too much on risky trades. In a post from years ago, I drew a contrast between smart money and humble money, with the former including investors who attribute every basis point of excess return earned to their investing brilliance, and the latter open about the fact that their performance, no matter how stellar, has as much to do with being in the right place at the right time (being lucky) as it has to do with skill. Investors looking for someone to manage their money are likely to do much better with the latter than the former.        I hope that you don't view this as a hit piece on Leo or AI, since that was not my intent. In fact, I hope that Leo persists and perhaps even comes back as a fund manager, since he strikes me as an original thinker who is willing to take a stand, both scarce qualities among active fund managers.  I also hope that he has learned some lessons, especially on humility and restraint, for his next go around, and that he adopts a fee structure that gives his investors a chance of beating the market in the long term. YouTube Video Links to the Leo Aschenbrenner story Situational Awareness: The Decade Ahead (Leo's post on AI) The 24-year old AI Wiz who counts Jane Street as an investor (The Wall Street Journal in early June, prior to blow-up) Inside the Meltdown of a Wunderkind's AI Hedge Fund (New York Times) His Wedding Guests were arriving - Just as his $45 billion fund was falling apart (The Wall Street Journal) What does the humbling of Leopold Aschenbrenner mean for the AI bubble? (The NewYorker)

I am a creature of habit in my personal and professional life, and in the context of the content that I post online, there is a ritual that I follow with my data updates. I start the year with my general data update online, and follow up with a series of posts where I examine the implications of this data for investing and corporate finance.  Since 2008, I have also done annual update papers on equity risk premiums in March of each year, with the link to the 2026 update here, and country risk in July of each year, where I look at the topics in more details, trying as best as I can to integrate the data, research and my own thinking. This year's country risk update paper is now available, and as in prior years, I will spend this post looking what causes risk to vary across countries, how to measure those risk variations and the implications for businesses and investors. Country Risk: Relevance   In my years as a business school student, country risk was given short shrift and I don't remember spending much time talking or thinking about it. Part of the reason was that business school education  was dollar-centric and built on the presumption that most graduates would go to work in New York, London or Tokyo, and have little need to confront country risk on a day-to-day basis. For those who raised country risk as an issue, the response was that you could, as a company or investor with global exposure, diversify it away. Both presumptions were wrong even then, and have become even more flawed over time as we have sold both companies and investors on the benefits of globalization.     For businesses, the exposure to country risk comes from both the revenue side, as larger portions of every company's revenues come from foreign markets, and the cost side, as production gets outsourced to locales overseas. That exposure tends to increase as companies scale up, and is higher in some sectors than others; technology companies, for instance, get far more of their revenues from other non-domestic markets than manufacturing or service businesses. Outside of utilities (power, water), it is rare for a company to be entirely domestic-focused on both its revenue and cost sides. For investors, the initial draw of investing in foreign markets might have been diversification but the greater pull has come from greed, i.e., the belief that you can higher returns in the rest of the world. That process was accelerated by the creation of investment vehicles (index and mutual funds) that made investing overseas easier, the lowering of transactions costs across markets and a greater standardization of financial statements and disclosure across the globe. The home bias in portfolios, i.e., the skewing of portfolios towards domestic market investments, has not disappeared but it is lower than it was at the turn of the last century.    The notion that country risk is diversifiable, i.e., that if you are operating or investing across the world, the risks will average out across countries, has been undercut by the increased correlation across global equity markets, and especially so during market crises (which is when you care the most).  At the risk of being hyperbolic, there is no place to hide from country risk, for either businesses or investors, and ignoring or dismissing country risk is not an option. I discovered this truth in the 1990s, when I found myself in need of a mechanism to incorporate country risk into my corporate financial analysis and valuations, and the process that you see described in this post was born from that need. I would hasten to add that the process that I describe has very little intellectual firepower behind it, puts pragmatism ahead of theory and most importantly is a work-in-process. Country Risk: Drivers     I don't think that there would be much disagreement, if I assert that it is riskier to invest in some parts of the world than others, but there is likely to be plenty of disagreement on why there are risk differences and which parts of the world are riskiest. In the broadest sense, I argue that variation in business risk across countries can be traced to four factors - the political structure of the country (democracy vs authoritarian), the prevalence of corruption in the country (operating as a hidden tax and distorting business outcomes), the extent of violence in the country (from internal and external forces) and the strength of the legal system in enforcing property rights and contractual obligations.      On the political risk front, I looked at the EIU's Democracy Index, a composite score measuring both political freedom and protections of civil liberties, with the caveat that any index that tries to measure these will make subjective judgements that not everyone will agree with. In their most recent update, here is what the EIU scores looked like around the world: Source: Economist  Low (High) score: Least (Most) freedom Based on these scores, the tilt towards authoritarianism has increased over the last decade, with only 7.3% of the world's population living in democracies at the end of 2025. Note, though, that there is still an open question of whether businesses and economies do better under democratic than authoritarian regimes, and the answer in the research is at best a "maybe".  From a risk perspective, democratic regimes create more continuous risk for businesses, with elections bringing regulatory and rule changes to economies, than authoritarian regimes, where governments can promise more continuity in policy, but when change does come to the latter, it is more likely to be large and wrenching.          Corruption is a fact of life in much of the world, and businesses often have no choice but to pay the price to survive and grow. Transparency International, a global coalition against corruption, tries to capture the extent of corruption, comes up with corruption scores for countries, with lower scores indicating less corruption, and the most recent edition contains the following: Source: Transparency International Low (High) score: Most (Least) corruption Northern Europe has the lowest corruption scores, followed by Canada, United States and Australia, but large portions of Africa have high exposure to corruption, with Latin America and much of Asia falling in the middle.      Living in the midst of violence takes a toll, and that toll is extracted from businesses that try to operate in its presence. Vision of Humanity computes peace scores for countries, measuring exposure to both violence within the country as well as from wars and terrorism. The most recent peace scores are reported below: Source: Vision of Humanity Low (High) score: Most (Least) peaceful Canada, Australia, Japan and much of Europe score high on the peace dimension, and while Latin America and Africa score lower, there are portions of each continent that are more peaceful. The Russia-Ukraine war has created a huge area of violence across Eastern Europe and Russia, and exposure to gun violence creates a drag on the United States.     Businesses are dependent on the legal system  to enforce property rights as well as contractual obligations. Countries that have legal systems that are either capricious on these fronts, or hopelessly slow in acting, create challenges for businesses that operate in them, creating both costs and risks that they otherwise would not face. Property Rights Alliance is an entity that tracks international property rights across the world, and in their most recent update, their property rights scores by country are captured below: Source: International Property Rights Low (High) score: Least (Most) property rights There are wide differences across regions, when it comes to legal and property rights, with Latin America, Africa and Asia lagging and Europe, Australia and much of North America leading.      There is one final dimension that I have added to country risk in recent years that captures exposure to climate risk. While there are many different entities that measure this exposure, each one with its own skews, the map below which shows the climate risk exposure, by country, from GermanWatch: Source: GermanWatch Low (High) score: Least (Most) affected There are two reasons why climate risk has not become a bigger topic in country risk discussions. The first is that there is no part of the globe that is unaffected, making it less of a differentiator across countries on the risk dimension. The second is that climate risk, by itself, is an abstraction for businesses, until it starts affecting the bottom line, and while there are individual companies that are being impacted, the aggregate effects, at least at the moment, are not big enough to change the discussion.   Country Default Risk     While country risk is determined by multiple factors, the challenge that businesses is  in consolidating all of those risks into one number. The market that does this most directly is the debt market, where, when countries (sovereigns) seek to borrow money, lenders determine the interest rates to charge them, based upon perceived default risk. To understand why lenders worry about default with sovereign debt, you can start by looking at the history of sovereign defaults in the graph below: Source: BoC & BoE Sovereign Default Database Debt defaults, which soared in the 1980s and 1990s, have been lower in this century, with a shift away from loan defaults (where banks are usually the lenders) to defaults in the bond market. It is also worth noting that a non-trivial portion of sovereign defaults in each year are local currency defaults, indicating that for some borrowers, the costs of defaulting are viewed as smaller than the costs of inflation arising from printing more currency to pay off debt. Over time, Latin America has been the epicenter for sovereign default, but at the end of 2023, sovereign debt in default had a wide geographical spread: Source: BoC & BoE Sovereign Default Database The most widely accessible measures of sovereign default risk remain sovereign ratings, with ratings agencies operating as (imperfect) arbiters. At the start of July 2026, the graph below reports the sovereign ratings for all rated countries, from S&P, Moody's and Fitch: Source: Multiple public sources As you can see, the ratings agencies mostly agree on their assessments of default risk, and sovereign ratings are correlated with the risk drivers (politics, corruption, violence, legal system) that we outlined in the last section. I do believe that ratings agencies, notwithstanding the critiques of bias and mis-measurement leveled against them, do a reasonably good job in their ratings assessments, but they are often slow to act, when confronted with change.      The sovereign CDS market offers a market-based alternative for measuring sovereign default risk, with investors making assessments of how much they would demand to insure against sovereign default in the form of (annualized) spreads. In the graph below, I list 10-year sovereign CDS spreads as of July 1, 2026: Source: Bloomberg Note that sovereign CDS spreads are available for only 84 countries, and that there are swaths of the world (Central and North Africa, frontier markets) where they are not available.  Country Composite Risk     When you lend money to governments or buy government bonds, sovereign default risk is your key concern, and both sovereign ratings and CDS spreads try to measure that risk. When running a business in a country, you are exposed to a much wider range of risks, and measuring exposure to those risks may require different measures. One alternative is country risk scores, where services evaluate how  countries measure up on different risk drivers, and come up with composite scores for these countries. In the table below, I report the country risk scores from two services - Political Risk Services (PRS) and the Economist (EIU), at the start of July 2026: Sources: EIU (Economist) and PRS The table illustrates three problems that you face with political risk scores. The first is that the scoring is idiosyncratic, with the Economist going from low scores for the safest countries to high scores for the riskiest, and PRS doing the reverse. The second is that each service picks different factors to consider, and different weightings, leading to scoring divergences that sometimes confound; PRS, for instance, ranks the United States as riskier than Ghana, on a composite risk basis. The third is that the scores, by themselves, are difficult to convert into inputs in financial analysis, either in cash flow or discount rate adjustment.    It is to combat the third problem that I started estimating country equity risk premiums, and while the details of the process and the data that I use have changed over the last three decades, the basic structure has remained unchanged. I start with an estimate of the equity risk premium for a mature market, and build a country risk premium, if needed, for riskier countries. Until 2025, I estimated the mature market premium by computing an implied equity risk premium for the S&P 500, and using that as the base, arguing that the US, as a Aaa rated country (at least according to Moody's), represented a mature market. The Moody's downgrade for the US, from Aaa to Aa1, has thrown a wrench into that approach, requiring adaptation. In response, I now start with an estimate of the implied ERP for the S&P 500, but then adjust that estimate for the default spread (based on the Aa1 rating) for the US, with the resulting values at the start of July 2026 below: Spreadsheet: https://pages.stern.nyu.edu/~adamodar/pc/implprem/ERPJuly26.xlsx As you can see, with the S&P 500 at 7499.36 on July 1, 2026, the implied equity risk premium for the United States is 4.42%, and netting out the default spread of 0.22% for the Aa1 rating yields a mature market premium of 4.20%.     To estimate country risk premiums, I start with the sovereign ratings for rated countries and convert those ratings into default spreads. To adjust for the higher risk associated with equities, relative to government bonds, I estimate a composite measure of that relative risk, by scaling the volatility in an emerging market equity index to the volatility in a emerging market government bond ETF, and scale the default risk up with this relative risk measure (1.55 in July 2026) to get country risk premiums: For the two dozen countries that have no sovereign ratings, I adopt an even more makeshift approach, where I used political risk scores for these countries, and then looked for rated countries with similar scores. The table below has equity and country risk premiums, by country, for all of the countries that I evaluated in July 2026: Download data I did post an earlier version of this table a couple of weeks ago, but the numbers that I reported reflected in incomplete update of sovereign default spreads, and this table (and the data on my webpage) now reflect the corrected (and lower) spreads. (As a solo act, I am deeply grateful for the checking that those who use my data do, and thankful when they point out mistakes that I have made.) Company Exposure to Country Risk     If you buy into my argument that every company has a narrative, and it is the narrative that drives its value, it is worth considering where country risk fits into that narrative. The answer, I believe, comes from looking at where the country in question falls in the life cycle: The message from this life cycle view is a sobering one, especially for those analyzing companies that operate in very risky countries, since the narratives for these companies implicitly or explicitly incorporate a country risk component. You cannot value a Venezuelan company without taking a strong view about Venezuela, or even an Indian and Brazilian company without an India or Brazil country story underpinning value. In contrast, you may be able to value US and European companies, without explicitly considering the evolution of country risk in those parts of the world.     When looking at an individual company, I believe that country risk exposure comes less from where the company is incorporated and more from where it operates. It is undeniable that companies around the world have substantial exposure outside their domestic markets, and that exposure has increased over time. In the graph below, I look at the revenue breakdown of companies in four indices - the S&P 500 (US), the FTSE 100 (UK), the Nikkei 225 (Japan) and the Sensex (India):      In every single index, companies that comprise that index get a significant portion of their revenues from outside the domestic market. Looking across sectors, exposure to foreign markets varies widely with technology companies often generating more than half of their revenues outside their domestic settings. I believe that equity risk premiums for companies should reflect exposure to foreign markets, though it is worth debating how best to weight that exposure - revenues work well for consumer product and service companies, production works better for natural resource companies and a mix of revenues and production may be the right choice for manufacturing companies: With this framework, you can see why almost all analysts will confront country risk, sooner or later, no matter where they operate in the world and which companies they analyze.      For companies, country risk will also come into play when faced with capital budgeting decisions, where they need estimates of hurdle rates for individual projects, to decide where to invest. For a multinational operating in many businesses, the project cost of equity will have to then also reflect the business the project is in, in addition to country risk. Thus, the cost of equity for a Siemens Appliances for a project in India should reflect the beta for the appliance business, in addition to the country risk for India. In contrast, a Siemens power tool project in Hungary should be computed using the beta for an power tools project and the country risk for Hungary. It is also possible that country risk is not easy to isolate, if the production facilities are in one country but revenues are generated in another. If the Siemens appliance factory in India will be producing products that will be sold in Japan, should we be showing the country risk of India or Japan in the cost of equity calculation? The answer, as was the case in the earlier section on valuation, is that it depends on where the company sees risk coming from. If the risk is that production will be delayed or disrupted by political and economic risk in India, it is Indian country risk that should be looked at, but if the primary concern is that revenues in Japan will be volatile because of economic conditions there, it is Japanese country risk that matters more. If both risks are considerations, you should use a weighted average of Indian and Japanese country risk. Currency Questions     For some of you, it may seem odd that I have spent almost an entire post talking about country risk without bringing up currencies. The reason is simple. Currencies are measurement mechanisms, and while they may be affected by the same political and economic factors that drive country risk, they don't determine country risk and in my view, should not command risk premiums, on their own.      It is true that hurdle rates are affected by both the equity risk premiums that you estimate and the riskfree rate that you use, and that riskfree rates vary across currencies. In the figure below, I estimate riskfree rates in about 40 currencies, where a local-currency government bond rate is present, and I adjust that government bond rate for the default risk of the government in question: When estimating the cost of equity for a Turkish project or company in Turkish lira, we start with a riskfree rate in excess of 20% and build on it, by adding equity risk premiums to it, but the cost of equity for the same project or company in Euros will begin with a riskfree rate close to 3% (the German Euro bond rate) and arrive at a much lower number. While this may sound farfetched, the value that you derive for the project or company should be the same using either currency, if you are consistent about estimating your cash flows in the same currency: Since much or almost all of the differences in riskfree rates come from inflation differentials, matching the high Turkish lira discount rate with a high growth in cashflows in Turkish lira, and the low Euro discount rate with the low growth in cashflows estimated in Euros will yield results that are consistent.     If you do want to estimate riskfree rates in currencies where there is either no local currency government bond that is traded or where you mistrust the government bond rate, because of light trading or government intervention, the fact that riskfree rate differences across currencies can be tied to differential inflation can be used for estimation; the riskfree rate in any currency can be computed from a base currency (dollar or Euro) riskfree rate and the difference in expected inflation between the local and base currencies: Put simply, if the expected inflation rate and riskfree rate in US dollars are 2.5% and 4% respectively, and the expected inflation rate in Brazil is 10.5%, the riskfree rate in Brazilian reais should be roughly 12%. The implication of this approach is that currency pegs, when they do exist, will hold only if the inflation in the pegged currency matches or is close to the inflation in the index currency to which it is pegged. It is true that the estimates of riskfree rates will only be as good as the expected inflation rates that are embedded in the estimation, but the good news is that being wrong on expected inflation will be largely offsetting, since both your cashflows and your discount rates will be wrong in the same direction; if you underestimate expected inflation, you will underestimate (overestimate) your riskfree and hurdle rates, but you will also underestimate (overestimate) your expected growth rate in cash flows. Conclusion    One of the side effects of the rise of globalization is that there are fewer and fewer companies that are entirely local-country focused in both their revenues and production, and as a result, almost every business and investor is exposed to risk in other parts of the world. The problem with measuring country risk is that while its consequences are economic, it has its sources in history, politics and governance structures. The measures of country risk, whether they be entity-based like sovereign ratings, or market estimates like sovereign CDS spreads, reflect this interplay.     I confess that I have made simplistic assumptions and cut corners in my attempt to estimate equity risk premiums, by country, and there will be individual countries, perhaps even your own, where you might disagree with my assessments. As I noted earlier, my estimation approach remains a work-in-progress and I am always open to suggestions on how to estimate these premiums better, but keep in mind that whatever those improvements may be, they will have to work across 180 countries.  YouTube Video Papers on country risk and equity risk premiums Country Risk Premiums - The 2026 Edition (July 2026) Equity Risk Premiums - The 2026 Edition (March 2026) Data Equity Risk Premiums, by country - July 2026 Implied Equity Risk Premiums for the S&P 500 (Annual since 1960 & Monthly since Sept 08) Inflation-based riskfree rates, by currency - July 2026 Spreadsheet Implied ERP for S&P 500 (July 2026)

A few weeks ago, I assessed the value of SpaceX ahead of its initial public offering, with the admission that I was making my estimates with drabs of data, some of it coming from unofficial sources. I also promised to revisit my valuation, when the prospectus came out, and now that it has, I will examine how the information it contains has changed my view of the company and its valuation. I will also use this post to talk about the information gained by having access to a company's financials, and why the information you glean from those financials is different at younger companies, with growth potential, relative to mature companies. The Prospectus: Data versus Information     The requirement that companies that plan to go public in the United States have to register with the Securities Exchange Commission (SEC) and file a prospectus has been in place for decades, but the contents have changed over time, with disclosures added on partly by regulation and partly in response to investor demands. In a paper focusing on IPO disclosures from a couple of years ago, I noted that prospectuses have become more bloated over time, often running four to five times longer than those filed by companies that went public three or four decades ago, but not necessarily more informative. The SpaceX prospectus that we made public on May 20, 2026, is 277 pages long, with an addendum that runs another 100 pages, with dozens of pictures (mostly of spaceships going into orbit), a soaring story, but with weak links and multiple distractions. To get a measure of how the prospectus changes my pre-prospectus story and valuation, I will start with the easy part of the update, where I use the numbers from the financial statements in the prospectus to replace my pre-prospectus estimates, on operating metrics like revenues and earnings as well as on share count and IPO proceeds. I will then move on to the weightier part of the analysis, where I assess how the information in the prospectus has changed my story line and value for the company.  The Prospectus: Data update     In my pre-prospectus valuation, where I assessed the value of SpaceX at roughly $1.2 trillion, I relied on scraps of information, including leaked stories of estimated revenues ($15.5 billion) and EBITDA of $8 billion, since I did not have access to the company's full financial statements. With the release of the prospectus, that shortcoming has been remedied, and I started by updating the operating metrics that drive the intrinsic value of the company: SpaceX prospectus As you can see, my estimates for revenues for the launch and connectivity (Starlink) businesses were close to the actual numbers, but my xAI revenue estimates were much lower than reported. Overall, I had estimated an operating loss of $2 billion in 2025, and the prospectus yielded a larger loss of $2.57 billion. With almost $2 billion in interest expenses, unavailable prior to the prospectus, incorporated, the company reported a net loss of about $5 billion. A big factor in the operating losses reported by the company were its ballooning R&D expenses, and in keeping with my argument that these expenses should be capitalized, I estimated an earnings before interest, taxes and R&D of $4 billion.     On the financing front, the prospectus filled in details on cash and debt that were unavailable prior to the prospectus being made public: SpaceX prospectus My pre-prospectus estimate of book value of equity was a shot in the dark, at $20 billion, but the acquisition of xAI caused that number to jump to $41.3 billion, as did the total debt (inclusive of leases) to $22.9 billion. The former (book value of equity) played little role in my valuation, but ignoring debt of this magnitude may seem monumental, there are two offsetting factors that reduce the impact on my value estimate. The first is that I also ignored the presence of cash, and with $24.7 billion in cash, the company's net debt is −$1.9 billion (cash exceeds debt), making the impact on value minimal. The second is that with my estimate enterprise value of $1.21 trillion, the debt, even if considered in full, is small enough to represent rounding error.     The prospectus did contain information on share count and structure, as well as on the company's plans for the proceeds, and both were useful at the margin, with the former affecting my estimated value per share and the latter determining the treatment of the cash that will be raised from the offering: Share count: In my initial valuation, I used the private company pricing per share in conjunction with estimated market cap to back out a share count of 2467 million shares. With the prospectus, we get a clearer sense of shares outstanding, with a basic share count of 12,535 million shares reported in the prospectus (pages 246 & 247) in computing per share numbers. That share count does not include the new shares that will be issued in the offering, but that share count will be determined by the magnitude of the offering as well as the expected issuance price, and while the total share count includes options, warrants and rights that are exercisable before June 30, it does not include restricted stock units held by employees (see prospectus, page 18) and that information is still blanked out in the prospectus.  Use of proceeds: It is estimated that SpaceX plans to raise $75 billion from the offering, and the prospectus specifies that the company plans to hold the proceeds to cover infrastructure investments in these businesses (see prospectus, page 66). That implies that any money raised in the offering will add to the company's cash balance, right after the offering, and will augment firm value (but not enterprise value).  The prospectus also lays bare the governance questions that will overhang the firm, with information that there will be two classes of shares- 6,932 million class A shares with one vote per share and 5,602 million class B shares with ten votes per share. The public offering will be class A shares, and with Elon Musk holding all of the class B shares, he will control more than 85% of the voting rights in the company. In summary, the prospectus is long and filled with distractions, but there is almost nothing in it that surprises me. SpaceX is a growing company that is money-losing and cash-burning, that will be a Elon Musk vehicle (with all the pluses and minuses that entails).  The Prospectus: Story update     In my original post, I noted that SpaceX is a company, where it is the story about how its businesses will evolve over time that drives value, rather than the base year numbers (on revenues, earnings and cash flows). That story, broadly speaking, has three key spokes to it and they are summarized below: The first of these spokes, target revenues, frame how big each business can grow over time, and is a function of the total market and market share. The second, the target operating margin, will capture how profitable each business can become, and is determined by unit economics and economies of scale. The third, reinvestment, measures how much each business has to invest to get to target revenues, and will vary with the capital intensity of the business. To frame how my valuation will change, as a result of what I learned from looking at the prospectus, I will start by presenting by pre-prospectus estimates on these key inputs, and then look at the impact of the prospectus on each input. Pre-prospectus inputs and value     My pre-prospectus valuation of SpaceX contains my storyline for the three businesses that the company is in, with an add-on for the expansion options embedded in each business: With these inputs in place, I estimated a value of $1.2 trillion the SpaceX enterprise, and since I ignored cash and debt, this yielded an equivalent market value. Driving these numbers are upbeat stories about each of the three businesses that SpaceX is in, with large revenues and high margins in stable growth. The Prospectus Effect     To the extent that the prospectus contains information that alters the storylines on any or all of these businesses, it will affect my estimate of value for SpaceX. 1. Revenue Growth (Target Revenues)     I will start with the growth (target revenues) input and use two parts of the prospectus to reexamine my story. The first is the historical growth reported by the company for each of its three business lines - launch, connectivity and AI. As you can see, the company saw its revenues grow by a third in 2025, relative to 2024, with divergence across businesses; the connectivity business led with revenues growing by almost 50%, the AI business saw an increase in revenues of about 22% but the space business reported only modest growth in the year (7.64%). In short, notwithstanding the star role played by AI and the appeal of the rockets in the space launch business, it is Starlink that carried the company in 2025. The prospectus mentions Colossus, xAI's compute center, which has been leased to Anthropic for an eye-popping $1.25 billion a month, which should kickstart revenues next year, with the potential of tension in future years if xAI plans to go head-to-head against Anthropic in the AI products market.     The other relevant section of the prospectus contained estimates of total addressable market (TAM) for the company, broken down by business: If the prospectus is to be believed, SpaceX has the largest TAM of any company in history, with a total TAM of $28 trillion, and AI accounts for $26 trillion of that market estimate. This estimate borders on fantasy, but I will cut the bankers who came up with these numbers some slack for two reasons. First, the estimation of TAM has been gamified by Silicon Valley, with bloated and patently unreachable numbers floated for companies, as I noted when I valued Uber (which was given a TAM of $5.7 trillion in its prospectus) for its IPO in 2019 and Airbnb (with a TAM of $3.4 trillion in its prospectus) in 2020.  Second, it is true that AI agents are usable across almost every business and geography, giving it much wider reach than most products and services, and while the details of how the TAM was estimated are not specified in the prospectus, my guess is that the $26 trillion estimate includes all or most of the operating expenses of all businesses.  Story takeaway: I will stick with my estimates for target markets for the space launch and connectivity businesses, since the TAMs in the prospectus are, in my view, over reaches, and I will slow growth in the near years, to reflect that these businesses will take time to mature. In the AI business, I disagree with the magnitude of the TAM in the prospectus, but the acquisition of Cursor and the indications in the prospectus suggest that xAI very much wants to be part of the enterprise solutions space, notwithstanding its immense capitalization needs, and I will double my target revenues for AI from $80 billion to $160 billion, reflecting my estimate of a TAM of about $3 trillion to $4 trillion for AI products and services from businesses. 2. Profitability      On the profitability front, the first part of the prospectus that I looked at was its breakdown of income statements, by business: With the caveat that we have only two years of detailed information, there are interesting findings that emerge from the historical data on each of the businesses.  The space business has the best unit economics of the three business, with a gross margin of about 67%, reflecting the cost advantages of its reusable rocket technology. While the space business reported an operating loss, that was entirely because of its weighty R&D expenses, and capitalizing those expenses results in a healthy operating margin for the business. The connectivity business does not have gross margins as high as the space business, but those gross margins are improving, with gross margins jumping from 37% in 2024 to 48% in 2025. This business had positive operating income in 2025, even before capitalizing R&D, and improves substantially with capitalization.  The AI business not only has the lowest gross margins of the three businesses, but saw deterioration of those margins in 2025, reflecting intense competition from other LLMs as well as the rising costs of delivering AI products and services. There are other parts of the prospectus that come into play in the profitability discussion, with each of the businesses: On the space launch business, the cost of launching payloads at SpaceX have been trending down, making its already large cost advantages in the business even larger.  On the connectivity businesses, there is bad news and good news on the per user front. The bad news is that the revenues, per month, per subscriber, declined from $99 in monthly revenues in 2024 to $66 in monthly revenues in the first quarter of 2026. The good news is that the number of subscribers has doubled from 5 million in the first quarter of 2025 to 10.3 million in the first quarter of 2026, with the bonus that the company has been able to improve its profitability (see gross margins in the table above) over time.  On the AI business, there is not much to go on, on the profitability front, since the focus in the prospectus is more on the increase in compute capacity (see nameplate compute draw on Page 90 of the prospectus) than it is on revenues, especially on the enterprise front. Here again, though, the Colossus lease with Anthropic should help with profitability in the near term. Story takeaway: The unit economics for the space businesses, in conjunction with the recognition that there are no other substantial operating expenses (outside of the misclassified R&D expense) in either business, lead me to increase my estimate of the target margin for the business to 45%, from 40%. I will leave intact the target margin of 60% for the connectivity business, because once the satellites that service this business are in space, this is the business that will benefit the most from scale. My biggest shift is in my estimated target margin is for the AI business, where the dynamics that are pushing gross margins down, i.e., increased competition and high costs of delivering AI services, will persist; my estimated operating margin drops from 45% to 25%. 3.  Reinvestment     In my post prior to accessing the prospectus, I did describe SpaceX as a capital intensive business, but the actual spending on capital expenditures and R&D in the prospectus is breathtaking in its magnitude: In 2025, the company spent almost $14 billion in capital expenditures and almost $9 billion in R&D, a doubling of its reinvestment from 2024. In particular, it is AI that is driving the bulk of this surge, accounting for more than $14 billion in total reinvestment in 2025, with $9.1 billion in capital expenditures and $5.1 billion in R&D. The positive twist that a SpaceX optimist would put on these numbers is that the spending on AI in particular is a positive, indicating that the company is not planning to settle on a niche market strategy, but instead will will go head-to-head with Anthropic, Google and OpenAI for the enterprise solutions markets. The negative spin is that this ambitious agenda will translate into tens of billions more in capital expenditures in the near years, creating a drag on the cash flows and value destruction if they lose the AI market competition. Story takeaway: Given that SpaceX is continuing to invest substantial amounts in its space launch and connectivity businesses, I will increase reinvestment in the near term (years 1-5) by lowering how much they will generate as additional revenues for every additional dollar of capital invested (lower sales to capital ratios). With AI, where I was already assuming that reinvestment would be large (with a low sales to capital ratio), the tripling of target revenues will result in a surge in reinvestment to generate the higher sales. Updating Story and Value     While the core story of SpaceX being a company with growth potential and strong competitive advantages that I framed prior to reading the prospectus remains intact, there are changes to that story that come from the information in the prospectus. The prospectus reinforces the notions that the company is best positioned in the connectivity business to generate both revenue growth and profits in the near term, that its cost advantages in the space launch business will persist and deliver profits, but that target market will be slower to develop, and that the AI business has both the largest target market and poses the biggest challenges, in terms of profitability and capital intensity, for SpaceX.      Bringing together my changes in target revenues, operating margins and reinvestment inputs allows for an update of the input table that I started this section with: Clearly, some of the changes in inputs (such as the higher margins for the space launch business and a bigger target market for AI) will push value higher, and some of the inputs (including a slowing of near term growth for all business, and the much lower margin for the AI business) will push in the opposite direction. Since US treasury rates have risen from 4.20% at the time of my earlier valuation to 4.56% at the start of June, I have increased the costs of capital that I use in the valuation accordingly (to 8.37% from 8.02% to start the valuation, and the steady state cost of capital to 8.25% from 8.00%; both numbers would put SpaceX at close to the median for all US companies). With these updated inputs, I reestimate the cash flows and the valuation for SpaceX, with the IPO proceeds (estimated at $75 billion) added to the mix: Download spreadsheet The enterprise value for SpaceX edges up from $1.21 trillion, in my pre-prospectus valuation, to $1.22 trillion with the post-prospectus numbers, and the overall equity value increases to $1.3 trillion, with almost all of the increase coming from the influx of $75 billion in cash from the IPO, albeit with a higher share count. The value per share of about $100 will need some revisiting as the IPO numbers firm up and more information is forthcoming on restricted stock units owned by employees, but just as I was finishing this post, a news story hit the wires that the offering price would be set at $135/share.    If I were to summarize the impact of the prospectus on my SpaceX story, it would be that it has made the story bigger, but also more volatile. There are a multitude of risks that SpaceX faces in each of its businesses, but the one that I would be concerned about the most is that it will overreach in the AI business, beginning with an overestimate of the target market for AI products and services and the strength of its own competitive position in that market, and following through with investments that reflect those misplaced assessments. Those concerns are heightened  by a voting share structure that locks in Elon Musk's control of the company, since there is little that shareholders can do to restrain the company, if SpaceX doubles down on capital expenditures and acquisitions in the AI space, even after it becomes clear that the AI market is much smaller than anticipated and/or that xAI's offerings are not as good as the competition. If you add to this mix the antipathy that exists between Musk and Sam Altman, you have the potential for a UFC match between two monstrous egos, funded by tens of billions of dollars shareholder money. Financial Statements and Value: The Life Cycle Effect     Financial analysis and valuation, going back to Ben Graham's Security Analysis, has always been centered on financial statements, and that focus has become more intense over the last few decades as access to data and analysis tools has expanded. In fact, much of what passes for valuation has become financial modeling, where line items in financial statements are forecast based upon the historical time series, with the proverbial bottom lines being earnings and cash flows. Along the way, ratios computed from financial statement numbers are used to screen companies for investment quality. Some of these ratios, such as accounting returns on capital and equity, have become the basis for assessing company quality and competitive moats in the hands of consultants and investors. The SpaceX prospectus is a case study in why this approach to investing is often myopic and misleading, and why the informational value of financial statements will change as companies grow and mature.      In valuing companies, you are always trying to forecast revenues, profits and cash flows in future, but they key questions you want answered and the drivers of value shift as you move through the life cycle: As you can see, for young companies, the key determinants of value include sizing the total market and assessing unit economics, and not the proverbial bottom lines in accounting statements including the magnitude of revenues and profitability. As companies move through the life cycle from start-up to mature to decline, you should expect to see financial statements evolve as well. Young and high growth companies will generally report small revenues (though they expect those revenues to ramp up over time) and losing money and having negative cash flows is a feature, not a bug. As companies mature, revenues will get larger (albeit with lower growth) and profits turn positive, as will free cash flows available to return to shareholders in dividends and buybacks. If you allow for the fact that all three of SpaceX's businesses are young, falling in the young to high growth categories, the big questions driving value are about market size and unit economics, since the former provides the basis for revenue growth and the latter determines profitability. That is why, when looking at the prospectus for SpaceX it was the data on total addressable markets, unit economics and capital intensity that had a bigger impact on value, and this information, for the most part, was in the footnotes to the financials, rather than in the financial statements themselves.     For those who are focused on value metrics/constraints (consistently money making, high profit margins and accounting returns)  and pricing multiples (low EV to EBITDA or low PE), the SpaceX prospectus is full of red flags. SpaceX is a company with small revenues and large losses, and paying a hundred times revenues for it (which is where a $1.8 trillion pricing would put it) seems foolhardy. I have no quarrels with this point of view, which animates old-time value investing, but this perspective comes with a cost in terms of investment choices. Investors who are wedded to never buying money losing companies or never paying more than twenty times earnings for a stock will end up with portfolios of mature (and declining) businesses. If that is their comfort zone, the strategy is perfectly defensible, but they should dispense with complaints about never being able to find high growth stocks to invest in or critiques of others who find these stocks attractive, notwithstanding the weak numbers.      There are many good arguments that can be made about why you should not invest in SpaceX, but basing that conclusion on the fact that they are money-losing or have negative cash flows or trade at a high multiple of revenues is both lazy and unconvincing. In contrast, making a case against investing in SpaceX because you believe that the target markets for its businesses will be far smaller than the company thinks they will be, or that cost and competitive pressures will drive margins down or even that you find its corporate governance structure and dependence on a personality (Elon Musk) off-putting is perfectly reasonable. If you do make that case, though, it is worth remembering that this is your point of view, and that disagreements about market size and profitability across investors, especially in young companies, are natural and healthy. In short, based on my inputs and story, I think that SpaceX is worth about $1.25-$1.3 trillion, but if you contend that it is worth $3 trillion or only half a trillion, it is neither my job nor my place to convince you that I am right and that you are wrong.  The IPO Pricing Game     In the coming weeks, you will undoubtedly be exposed to multiple perspectives on SpaceX, and that is healthy. That said, you will be better equipped to make sense of these perspectives, and perhaps incorporate some of the views into your own, and reject those that do not make sense, if you have an understanding of what an IPO process involves. In particular, understanding the motivations of the different players in the game (the investment bankers setting the offering price and managing the offering,  the issuing company, the investors and traders jockeying for shares at that offering price and the traders positioning themselves for the first day of trading) will help determine whether you should be playing this game or sitting it out, at least for the moment. The Bankers     Let's start with the sequencing that goes into a conventional initial public offering, though alternatives have emerged to it in recent years: As you look at the role played by bankers to the IPO process, allowing them to keep a  slice of the IPO proceeds, the SpaceX IPO is a testimonial to the dwindling value added by bankers on every dimension: Timing: It is urban (or market) legend that investment banks can time markets, and that this market timing can help determine the best time to go public. Just one look at the track record of market strategists at investment banks should dispense with this delusion, since banks (and most institutional investors) are (and have never been) good at gauging market momentum and shifts in mood.  Filing and Offering details: It is true that there are technical details and logistical steps to filing a prospectus and setting offering details, but they are almost all mechanical. With SpaceX, I am not sure whether the prospectus, as filed, was the work of a team of bankers, but if it was, I wonder what an entirely Grok-written prospectus would have looked like, and whether we would have noticed the difference.  Pricing: In an IPO, the bankers' mission is to price companies for their offering, not value them, and while they usually draw on pricing multiples and peer groups to make that pricing judgment, they are guided by the pricing in the most recent private transactions, usually in the form on venture capital rounds. With SpaceX, that task is simplified by the reality that this company, while private, has had active trading in its private shares, and that it was priced at roughly $1.2 trillion prior to the IPO process commencing. Adding the $75 billion in offering proceeds, and incorporating the advantages of increased liquidity from being a public company and becoming part of the S&P 500, it is not surprising that there is a sense that the offering will be priced at between $1.5 trillion to $2 trillion, with or without the investment banking input. My guess is that we will end up somewhere in the middle, with some handwaving about revenue multiples and other AI companies used to justify that pricing. (After I finished this post, a news story popped up that the offer price would be set at $135/share, translating into about a $1.8 trillion pricing for the company.) Selling/Marketing: In an age where investment banks have lost credibility and social media is where marketing happens, SpaceX can generate its own marketing spin, and has an army of influencers behind it. In addition, almost every institutional investor has a point of view on whether to own SpaceX or not, it is unclear what exactly a roadyshow can do to augment the sales pitch. Price guarantee: The pricing guarantee that investment bankers offer in initial public offerings is a mostly empty promise, since they systematically set offering prices at below (by 15-20%) what they believe the market will pay. That is the reason that the offer price for SpaceX will be set below the upper end of the range, and while the discount may seem like a significant loss to funders and current owners, the fact that the offering is for less than a tenth of the shares in the company will soften the blow. Post-market support:  As a follow-up to the price guarantee, investment banks often offer after-market support for companies in the days after they go public, buying shares if the stock comes under selling pressure. With SpaceX, that option is off the table, since no investment bank has the capital to support the pricing of a two-trillion company, if investors turn negative on it. In fact, given that banks are perhaps getting more from the initial public offering, in terms of publicity and allotments for their preferred clientele, than SpaceX is getting from their services, you could argue that the bankers should be paying the company for reflected glory, rather than charging them fees. The only good reason that I can think of for SpaceX not going the direct listing route, where you dispense with the kabuki dance of offerings and let the market set the offering price, is that the company needs the cash from the offering, and that route is much more difficult to take in a direct listing. Issuer (Company, Founder and Investors)     Looking at the IPO from the SpaceX perspective, the public offering will provide benefits. For the investors in the company in its private form, including venture capitalists from early in its life to public investors in more recent years, the IPO will allow them to cash out, albeit after the lock-out period expires in a few months. For the company, the increased access to capital from being a public company will allow it to fund the capital expenditures and investment needs that emanate from the company's ambitions in the AI business. For Elon Musk, the public offering has the potential to make him the first trillionaire in history, in addition to unlocking new pathways to further enrichment for meeting specified targets (including getting a million people on Mars).    Since some of these benefits have been in existence for many years, the fact that company stayed private for that period is an indication that there are costs to going public that have held it back. The first is that, notwithstanding Musk's voting control of the company, become a public company will open SpaceX to market scrutiny, in the form of earnings reports every quarter and insider trading reports. The second is that the market is fickle, and while it is rewarding companies that invest in AI with high market prices today, it can change its mind and punish them for the same reason. The third is that while there is little that investors can do to trade and make money on overpriced private businesses, they can sell short on public companies. Investors and Traders     SpaceX is a company that has been in the public eye for a decade or more, even as a privately owned enterprise, partly because of its social media boosters and partly because its space launches make it a magnet for attention. There are many who are drawn to the company, but unable to invest in it as a private business, will now have a chance to do so, if it goes public. But should they try to partake in the initial offering? The answer to that question  depends on whether you are an investor, where you buy (sell) companies that you believe are trading under (over) their assessment of value and hope the gap closes or a trader, where you buy (sell) companies where you expect prices to go up (down) in the future, for a multitude of reasons, only some of which may relate to company fundamentals.     I am more investor than trader, and I say that without judgment, since the end game in markets is to make money, not score intellectual points. The truth is that I am not a very good trader, and I am better off staying in my preferred domain, which is valuation, albeit with no guarantees of a payoff.  My valuation of SpaceX was driven by my interest in the company and belief that it is in unique, cutting-edge businesses, and my decision on whether to buy into the offering is therefore driven by my assessment of its value. At the rumored pricing of $1.8 trillion for the company, it is too richly priced for my tastes, given my valuation of $1.25-$1.35 trillion for the equity in the company. That does not mean that I will never buy the stock, since the market does change its mind, and if the price does drop by enough, my decision would change accordingly. It is worth remembering that Facebook was selling at half its offering price a few months after its IPO, and that Uber lost more than 50% of its market cap in the year after its public offering, moving both companies from over to under valued.     If you are a trader, though, the game changes. Specifically, the intrinsic value of the company is not central to your decision, perhaps even irrelevant, and your judgment on whether you seek to partake in the SpaceX offering will depend on your reading of market mood and momentum. I would not be surprised in the least to see the offering priced at $1.8 trillion, and see a jump in the price on the day of or in the weeks after the offering, and if that is your most likely scenario, being able to get into the offering at the offer price or even in the first few hours or days of trading will be a winning strategy. The risk, of course, is that momentum can shift quickly, causing a significant price drop, effectively making  timing your trades right key to your trading strategy. The shifting and often unpredictable forces of mood and momentum are also the reason that as an investor, I would not sell short, notwithstanding my value assessment, even if the pricing for the company pushes from $1.8 trillion to $2 trillion or more.  A Loaded Bet on AI!     As the IPO process for SpaceX heats up in the coming weeks, you should prepare yourself for a flood of selling from the company and its bankers, with talk of possibilities and potential dominating the discussion, as well as arguments from the other side, where it will be framed as a vehicle for AI hype, destined to fail. If you are on the receiving end of these sales pitches, you should listen but check the numbers for plausibility and make your own judgments. For the bankers involved and the issuing company, the biggest danger to a successful offering is not that there will be near-term reality checks on their hype, but that the market mood will shift, either in the aggregate or specifically related to AI, in the weeks leading up to the offering.  No matter what your views are about the SpaceX IPO, positive or negative, there is no denying that this company is a loaded bet on the AI  and Elon Musk, and while that may concern some, there are others who will look at Musk's track record with Tesla and feel the odds are in their favor.  YouTube Attachments SpaceX prospectus Valuation of SpaceX, post-prospectus on 6/2/26 Blog posts on SpaceX To a Trillion(s) and Beyond: A SpaceX Odyssey!

Through time, we have glorified conquerors and empire builders in politics, civic life and business, from Alexander the Great and Genghis Khan to the tech titans of today. That is no surprise, since these individuals have oversized personas and often change the course of history, but it is also true that this glorification of empire building has shortcomings. The first is the deification of these heroes comes with whitewashing of the dark sides and the costs of empire building. The second is that we discount and undervalue those who make contributions to societal or business advances, but do so quietly and with little fanfare. It is in this context that I was drawn to the story of Tim Cook stepping down as Apple CEO, after a tenure of fifteen years atop a company that has been among the top market cap companies in the world for much of that period. While Steve Jobs, his predecessor as CEO at Apple, has now been deified in business circles, as an unparalleled visionary and business builder, and deservedly so, I think that Tim Cook, in many ways, has played just as significant a role in molding the company into its current day standing, with far less recognition. Apple's CEOs: From Scott to Jobs to Cook!     Unfair though this may seem, the Tim Cook story at Apple has to start with Steve Jobs. Jobs co-founded the company in 1976, with Steve Wozniak, and while the company went through a series of CEOs in the next two decades, Jobs was the face of the company in its early years. While it is easy, with the benefit of hindsight, to view these as good years for the company, those early years reflected both Job's strengths and weaknesses. His vision and force of personality gave rise to the personal computer in its current form, as a tool for everyone to use, not just tech geeks, and as someone who bought his first Mac (the 128K without a hard drive) in 1984, and has stayed a Mac user since, I am grateful. That said, the dark side of Jobs, manifested in impatience with underlings and an obstinate belief that he knew what customers needed better than they did, led to the Lisa, the only Mac I regretted buying almost immediately after my purchase, and a loss of business markets to Microsoft. Those failures led Apple to the brink of failure, and to Jobs being cast out of the company by its board in 1985, though the CEOs that followed had neither the strategic vision nor the business-building capacity to rescue the company.     In 1997, Apple looked like it was a company heading into oblivion, as Windows became the dominant operating system for personal computers, and it seemed like Apple had lost its purpose. The August 1997 return of Steve Jobs,, who had used his years in the wilderness to build Pixar, a company that revolutionized animated movie making, is now the stuff of legend, as he rebuilt Apple in the ensuing years into a powerhouse, around the iPod, the iPad and most of all the iPhone. While there are books and movies chronicling the Steve Jobs success story, it is worth asking what the difference was between the first iteration of Steve Jobs at Apple (from founding to leaving in 1985), where Apple lost ground to Microsoft, and the second iteration of Steve Jobs (from his return in late 1997 until his resignation in 2011). The first was that he was older, and to the extent that with age comes some wisdom, it helped, but it is unlikely to have been the change maker. The second was that in his period away from Apple, Jobs created and built up other companies, with Pixar being the biggest, where he learned to deal with people better and perhaps compromise a bit more than he used to. The third was that he benefited from the presence of Tim Cook, first as an executive in Apple sales and operations, and more importantly, as chief operating officer (COO) for Apple, starting in 2005. If Steve's skill was vision, where he showcased Apple's next "big innovation" at meetings in his trademark black turtleneck, Cook's skill was building manufacturing hubs and supply chains to convert the vision to products. That separation of vision from business building created the Apple juggernaut in the first decade of this century. While that division of labor clearly was in the company's best interests, Jobs deserves credit for being willing to set his ego aside and delegate the powers to make it happen.     Tim Cook has been CEO for fifteen years, and when he retires on September 1, 2026, he will have been the longest serving CEO at Apple. It cannot have been easy, especially in the early years, as the comparisons to Steve Jobs were front and center, and there was pressure on him to continue in the same path. To Cook's credit, he never tried to be Jobs, and he created a very different template for himself, one that fit him and the company well, and served as a testimonial to his self assurance. In one of my talks about a decade ago about Apple, I described Cook, perhaps harshly, as a man without a visionary bone in his body, but one who would make sure that the trains ran on time (or the iPhones were delivered as promised), and I think that he has used that strength to good effect during his years as CEO of the company. Apple's Finances in the Twenty First Century: The Steve Jobs and Tim Cook Years!     Steve Jobs handed over a company to Tim Cook in 2011, that was extraordinarily profitable, and at the time of his leaving, already the largest market cap company in the world. While that fact leads some to discount what Cook has done at Apple since, I think it is worth going back in history and looking at corporate handoffs of great companies, and how often they become tangled messes, as new CEOs overreach and overpromise.      The place to begin our comparison of the Jobs and Cook tenures is by charting Apple's market capitalization, with the delineation into the Jobs years (1998-2011) and the Cook years (2012-2026): Looking across the aggregated years across both CEOs, it has been an extraordinary time. Apple began the Jobs tenure as CEO with a market cap of $1.68 billion, and by the end of 2025, its market cap had risen to over $4 trillion, and its performance burnishes the reputations of both Jobs and Cook. Jobs provided the foundational boost for the company and the innovations he presided over delivered a compounded annual price appreciation of 47.19% between 1997 and 2011, a period when US equities were struggling and Apple reached the top of the market cap table in 2011. With Tim Cook at the helm, Apple added an astounding $3.64 trillion in market cap, but a strong equity market provided strong tailwinds, and the company's annual returns were more modest.  On a percentage return basis, the Jobs years were better, but in my view, the fact that the annual returns in the Cook years were just as impressive, because they had to be earned on a much larger firm.      The reasons for Apple's sustained increase in market capitalization were simple - solid revenue growth and a profit machine that delivered high margins, even as the company scaled up: As with the market capitalization comparisons, this chart yields metrics that are favorable to both Jobs and Cook. Under Jobs, the company scaled up its revenues significantly, with a compounded annual revenue growth rate of 23.67% between 1997 and 2011, and just as significantly, went from posting subpar margins and a net loss in 1997 to becoming one of the most profitable tech companies in the world, Under Cook, revenue growth rates came down (to a compounded annual average of 8.52% between 2012 and 2025), but on a much larger scale, and the company preserved and grew its profit margins.     There was one corporate finance dimension on which Cook deviated from Jobs, and that was on cash return or dividend policy. In the chart below, I look at the cash returned to shareholders by Apple during the tenures of the two CEOs: During Job's tenure at Apple, the company paid no dividends and initiated only modest cash buybacks, mostly to cover stock-based compensations. With Tim Cook as CEO, Apple was one of the greatest corporate cash success stories of all time, initiating dividends in 2012 and increasing them over time, and supplementing those dividends with cash buybacks that, in the aggregate, were the largest in corporate history. In sum, the company has bought back almost $800 billion between 2012 and 2025, and the most astonishing feature was that, while returning all of this cash, the company also accumulated one of the largest corporate cash balances in history.     To the question of how Apple was able to return this much cash, increase its cash balance and still grow itself, the answers are three fold. The first is that the iPhone, perhaps the most valuable single product in business history, continued to deliver for the company, with modest reinvestment needed on its upgrades.  While much of the credit for the iPhone is still given to Steve Jobs, and rightly so for fostering the innovation, credit is also due to Cook, who has taken the franchise handed to him, and grown it on steroids. The second is that the company borrowed $17 billion in 2013, a Cook departure from a Jobs practice of avoiding debt, and it has added to that debt load over time, though it remains a small slice of overall value: While much is made of Apple's debt foray, it is worth recognizing that Apple is still a very lightly indebted company on any debt metric, and that if you net the company's considerable cash balance out against its total debt, its net debt has always been negative (cash exceeds debt). In fact, Apple's use of debt is so light that the only rationale for its existence is creating a presence in the bond market, just in case it needs to use it more in the future. The third feature is that the company has been cautious in its forays into new products and markets, especially outside its domain, and this shows  up in two data series. The first is that while Apple has acquired more than a hundred companies, almost all of them are small, private technology companies with small price tags, with the intent being bringing their products and services into the Apple ecosystem after the acquisition. In fact, its largest acquisitions during this century are so small that they represent petty cash, relative to its cash balance as a company. Beats, for instance, which was one of Apple's biggest acquisitions cost the company about $3 billion, a number dwarfed by its cash balance that year, which was more than $100 billion. The second is that in the last five years, as big tech companies have gone on an AI capital expenditure binge, Apple has been the outlier, holding back on its AI investments, and this can be seen in the chart below, where I compare Apple's capital expenditures to those of the rest of the Mag Seven: As the rest of the group has ramped up its capital investments, with much of it going into AI, Apple has held back, and its share of the total cap ex at the companies has fallen from 8.04% to 3.02% over the period. In sum, looking at the changes at Apple over the last fifteen years, the company has changed from the growth engine, driven by disruptions, in the Jobs years to a mature, cash-returning and more cautious company under Cook. I have posted more about Apple than about any other company in the world (and I have a sampling of some of those posts at the end of this post) and have been a shareholder in the company for significant portions of both the Jobs and Cook tenures. I have not always agreed with either man, on choices that they have made at the company, but I respected both of them enough to view them as good stewards of my investment. In a world full of CEOs who are quick to herd to what the consensus view is, I admire both men for their willingness to stand on their beliefs. Vision or Restraint: A Life Cycle Perspective     If you were to create a profile of Tim Cook, the manager, based upon the choices that he has made at Apple during his tenure as CEO, two very divergent views emerge. To his admirers, his actions on some fronts (initiating dividends, massive stock buybacks, borrowing money) and inaction on other fronts (no big acquisitions, diffidence on AI investments), represent an exercise in discipline and restraint,  preserving the company's crown jewel (the iPhone) and fending off the bankers and consultants, with their false promises.  To his critics, and there are quite a few, Cook's caution has cost Apple its disruptor status, when it could have used its ample cash reserves to buy its way or invest in into almost every new business that has bloomed in the last fifteen years. In fact, they point to chances that Apple has had to buy some of the biggest stars in the market, from Tesla and Netflix more than a decade ago to Anthropic, Mistral and Perplexity in more recent years.          It is impossible to argue that one side is right and the other side wrong, but it is undeniable that both pathways (the restrained pathway that Apple adopted and the more aggressive pathway that it could have taken) include trade offs. It is true that Apple's restraint has led it to miss out on some of the biggest trends in technology over the last decade, but it has also avoided the overpayment that is so common with high profile acquisitions of big companies. The argument that Apple would be worth a lot more today if it had bought Netflix or Tesla a decade ago falls flat for two reasons. The first is the selection bias in picking two companies that, in hindsight, have emerged as winners, when in fact there were at least a dozen other worse-performing companies that were also on Apple's radar. The second is the presumption that companies like Tesla or Netflix would have been just as successful, owned by Apple, as they were as stand alone enterprises. The clash of corporate cultures that would have ensued if Apple had bought either Tesla, a company that reinvents its business narrative every few hours, or Netflix, an entity that makes content in quantity with the hope that some it sticks, would have been epic, with the risk that both Apple and its acquired target would have gone down in flames.     More generally, though, the question of whether you want a visionary or a disciplined business builder at the top of a firm is not one that has an easy answer, since it depends on the firm in question. In my work on corporate life cycles, I focus on the management skills that are needed most in a company, based upon where it is the life cycle, and that may help address the choice between vision and restraint: With young companies, vision dominates, as managers work to sway investors, employees and nascent customers that their product or service will find a market. As the vision takes hold, converting it into commercial products and services requires trading off some portions of vision for pragmatism, in the interest of getting the business going. As products and services find demand among customers, business building becomes a key difference-maker, with the grunt work of marketing, production facilities and supply chains coming into play. Assuming that you have made it through these three stages, the trade offs of scaling up come into focus, and as you hit market limits, success depends on being opportunistic in finding new products and markets, but only if they exist. In corporate middle age, pathways to easy growth, especially at scale, become difficult to find, and to the extent that value comes from moats and core products, playing defense against competitors takes priority. Finally, in decline, a phase that no company ever wants to enter, but is inevitable at some point, you need to be willing to shrink a firm, shutting down businesses that no longer deliver value and selling other assets to high bidders.     Given these very divergent management functions, it should come as no surprise that there is no prototype for the perfect CEO, McKinsey and Harvard Business School blueprints notwithstanding. Viewed in this framework, I would argue that Apple has been lucky with its last two CEOs, both in terms of persona and in terms of sequence. When Steve Jobs rejoined Apple in 1997, the company had hit rock bottom, and with little to offer in liquidation, his vision allowed for a reincarnation, with disruptions leading the way, and as we noted earlier in this post, having a strong chief operating officer in Tim Cook made the difference. The Apple that Tim Cook inherited, when he became CEO, was a very different entity, already the world's largest market cap company, with a superlative franchise in the iPhone. In corporate life cycle terms, Apple was a mature growth company, and what Cook lacked in opportunism , he made up for by defending Apple's biggest product line(iPhone) and augmenting value with increments like the app store and devices. That said, while each of these men created value for shareholders, I don't think that either would be regarded as highly, if you swapped their tenures in terms of timing. I don't think Tim Cook would have been able to bring Apple from its near-demise to being on top of the corporate universe, if he had become CEO in 1997, and I think Steve Jobs would have been ill-suited to the Apple that was in existence in 2011.  Aging, Management Mismatches and Corporate Governance     In a post from a few years ago, I used the connection between CEO type and corporate lifecycle to examine why management mismatches occur at firms, and the consequences of that mismatch. Specifically, there are three confounding factors that can make matching up CEO to company, given where it is in the life cycle, complicated: Like humans, companies age, but unlike humans, the rates at which different companies go through the life cycle can be wildly different. An infrastructure or manufacturing company can take decades to become operational, followed by extended phases of growth and maturity, before going into decline. In contrast, a tech company can have explosive growth early in its life, spend a brief period enjoying the fruits of its success as a mature company before declining precipitously. As a consequence, managers and investors who use chronological age as their corporate aging metric can misjudge where they are on the life cycle. While aging is inevitable for both humans and businesses, some mature or even declining businesses can find pathways, either through happenstance or management choices, to rediscover their youth. These businesses become the stuff of legend, and they are the subjects of books and business school case studies, and their CEOs are elevated to management deities.  The narratives built around companies that reincarnate and the CEOs atop these companies also feed into management incentives and behavior. The story of Steve Jobs at Apple has been told and retold, but it is worth remembering that for every story of reincarnation, there are a hundred stories you can tell about other CEOs who tried to follow the Apple playbook, spending billions on reinventing their companies, with little to show in terms of payoffs. (See my posts on Marissa Mayer at Yahoo! and on Blackberry.) In essence, the glorification of CEOs who bet big on turnarounds at mature or declining companies, and win, sets up CEOs facing similar circumstances to behave like riverboat gamblers, when making management choices at their firms. After all, if their bets pay off, they join the legend crowd, and if they do not, they contend that they did their best, and that circumstances conspired to bring them down. The bottom line is that there are a number of ways in which you can end up with CEO mismatches - a CEO who cannot adapt to the changing demands of an aging business, a hiring mistake or even changes in the macro environment, and when those mismatches occur, is is inevitable that there will be friction between the CEO and shareholders. In a sense, almost all corporate governance challenges can be traced back to management mismatches, and the power (or the absence of it) that shareholders have to fix those mismatches: While Tim Cook's time as CEO of Apple is now seen through rose-colored lens, it is worth remembering that Apple was targeted repeated early in his tenure by activist investors. While some of the changes that these activists were pushing for were warranted, some were not, and Cook deserves credit for not capitulating. Carl Icahn, for instance, wanted Apple to increase its debt substantially, borrowing hundreds of billions, but I took issue with his argument that Apple could borrow this money at the low rates that he was extrapolating. A couple of years later, David Einhorn made his play, arguing that Apple should issue preferred shares with a 4% dividend yield, and I noted that preferred stock could bring with it all of the cashflow commitments of debt, with none of the tax advantages. I have long argued that the best defense a management has against activist investors is delivering superior performance and returns, and Tim Cook delivered on both dimensions, and faced little more than sniping from disgruntled investors in his later years as CEO. In the last four years, the criticism has come primarily from analysts who fault his caution, and argue that Apple risks falling behind its more aggressive competitors in the AI race, but here again, Cook has stood his ground. Management Transitions, Past and Present - The Mag Seven     I don't envy John Ternus, who is Cook's heir apparent, because he is following two CEOs who were immensely successful, albeit in different ways. If there are lessons he can learn from both Jobs and Cook, they include the following: Find your own path: There will be pressure from some investors to be just like Jobs, and go for big disruptions, or from others to imitate Tim Cook, and leave Apple as a cash machine. While it may take time, Ternus has to find his own path as CEO, based on not only what he brings to the table, given his background in computer hardware, but on what Apple's strengths are as a company in 2026 and the markets it is facing right now. Adapt to the company you are managing: Just as the Apple that Jobs took over in 1997 was very different from the Apple that he handed over to Cook in 2011, the company that Ternus takes over is different from the ones handed over in either of the prior iterations. When you are at the helm of one of the largest market cap companies in the world, you have to start with the recognition that any new product or service that you introduce will have to be huge to make a dent in the operating metrics (revenues and profits) or market capitalization. In addition, the franchise that holds up the company's cash machine is the iPhone, and Ternus cannot afford to take his eyes of that prize.  Keep the feedback loop open: When you are a company worth trillions, with legions of shareholders, and hundreds of analysts, you will have advice meted to you constantly on what you should or should not do. Much of that advice will be bad, and should be dismissed, but some of it is worth listening to and perhaps converted into policy. In addition, as CEO, I hope that Ternus views the market price as a crowd judgment on Apple's actions rather than the product of speculation, and accepts that while that judgment can be wrong, it should be taken seriously.  I wish Mr. Ternus the best, for purely selfish reasons. As a Mac and Apple device user, I want the company to prosper and continue to make products that I can continue to use on a daily basis, and as a shareholder, I want my investment to do well.      The attention, in this post has been on the management transition at Apple, but management transitions are part and parcel of every company, with the changes sometimes forced on the company and sometimes voluntary. Expanding the discussion of management to the other companies in the Mag Seven can provide us with an opportunity to examine management transitions that have either already happened or that will happen in the future, and the ensuing frictions: At Microsoft, the only company in this group that traces its vintage back to Apple, there have been two CEO transitions, from Bill Gates to Steve Ballmer in 2000, and from Ballmer to Satya Nadella in 2014. While Gates built Office and Windows into cash cows, and Ballmer preserved them, Nadella created his own pathway to reincarnation by building up a cloud business that is now the dominant source of revenues for the company. By partnering early with OpenAI on LLMs, and investing massively in data centers, Nadella is now making a bet that AI can provide a further boost to the company's operations, perhaps setting the stage for a second rebirth. Amazon has seen a management transition, where a legendary founder (Bezos) left the firm in 2021, and his successor (Andy Jassy) has taken the reins, with remarkably little fanfare. Like Nadella, though, Jassy is betting big on AI being a growth and value driver, and the success or failure of that bet will largely determine how his stint as CEO gets judged. Alphabet offers a case study of a company that tried to split the difference, by separating its cash cow (Google advertising) from its other businesses, naming Sundar Pichai as the CEO for Google, while remaining atop the other Google businesses (the bets in Alphabet). That experiment has struggled to deliver, as the other businesses remained earth-bound and in 2019, and Pichai took over as CEO of Alphabet as well. Over its lifetime, Alphabet has been immensely successful in coming up with products and services that catch public attention, whether it be its development of the Android operating system or its work on Waymo or Gemini, but it has struggled to convert those successes into revenues and operating profits. In three of the companies (Tesla, Meta and Nvidia), founders remain CEOs, though they bring very different perspectives and personalities into their roles. As I noted in my last post on SpaceX, Musk has veered between genius and eccentricity in his stewardship, but shareholders at Tesla have largely benefited from the rollercoaster ride. At Meta, Zuckerberg has been a shrewd businessperson in his management of his social media holdings, with savvy acquisitions of Instagram and Whatsapp boosting his ad-driven ecosystem, but he has also been headstrong in his pursuit of ventures that he feels are the "next big thing".  His expensive failed bet on the Metaverse led some investors to question his governance, and many of these investors worry that his bet on AI will play out similarly. Finally, on Nvidia, the company's soaring market capitalization and huge success with AI chips has pushed Jensen Huang into the spotlight, but less than a decade ago, there were questions about his management as well. The fact that all six of these companies have invested heavily in AI is a lead-in to what could be the key test for management at all of them. If the AI investments pay off and deliver value, Nadella will cement his legend status, Jassy will have created his own legacy at Amazon, the Alphabet experiment will finally pay off, and the founder-run companies will have more room to run. If the AI investments fail, though, Nadella's reincarnation reputation will take a hit and Jassy's position atop Amazon will be at-risk. The AI failure will also raise doubts about Alphabet's capacity to grow beyond advertising and the rumblings about Zuckerberg's big bets will get louder, but at these two companies, it is unclear what investors, no matter how large their holdings are, can do, since they have acquiesced to a voting share structure at these two companies that has reduced them to bystander status. At Alphabet, Brin and Page control 51% of the voting rights, with less than 10% ownership, and at Meta, Zuckerberg controls 57% of the voting rights, with about 13% of share ownership.    An Ode to Restraint     While there are many who compare to Tim Cook to Steve Jobs and find him wanting on vision and flair, I am grateful, as an investor in Apple, for the restraint and discipline that he brought to the job. That gratitude will stay intact even if Apple's caution on AI turns out to be a mistake, since the restraint and rectitude that Cook brought to his job are management qualities that significantly undervalued. I don't teach from or write cases, but I would love to see more business school cases about CEOs like Cook who are not easily swayed by the temptation of more growth and ego-driven acquisitions. I loved the Steve Jobs movie, but I don't expect to see a Tim Cook movie anytime soon, and while that is understandable, it also explains why we will continue to have too many CEOs at companies viewing themselves as saviors, gambling shareholder money on turnarounds and rescues, when the better pathway would be acceptance and shrinkage. I believe that investors lose more money from companies trying to do too much rather than from them doing too little, and from overreaching than from underachieving. YouTube Video My posts on Apple Apple: Thoughts on Bias, Value, Excess Cash & Dividends (March 1, 2012) Apple: Know when to hold 'em, know when to fold 'em (April 3, 2012) Emotions, Intrinsic value and Dividend Clienteles: The Apple postscript (April 6, 2012) Apple's Crown Jewel: Valuing the iPhone Franchise (August 29, 2012) The Year in Review: Apple's Universe (December 2012) Are you a value investor? Take the Apple Test! (January 2013) Back to Apple: Thoughts on value, price and the confidence gap (February 7, 2013) Financial Alchemy: David Einhorn's value play for Apple (February 8, 2013) Apple: News, Noise and Value (April 30, 2013) Love the company! Love the product! Love the stock! (September 9, 2013) Watch the Gap: Apple's Long and Twisted Journey (April 2014) The Race to the Top: The Duel between Alphabet and Apple (February 2016) Icahn exits, Buffett enters: Whither Apple (June 2016) Apple: The Greatest Cash Machine in History (February 2017) Investor Whiplash: Looking for Closure with Apple and Alphabet (December 2018) My book on the corporate life cycle The Corporate Life Cycle