Hey friends, my notes app is steaming with some absurd tales about my first four weeks as a postgrad from bizarre traditions in the oldest university in the English-speaking world, Oxford.

As I tie those thoughts together into something coherent, I thought I’d pop in and repost an example essay of what my creative writing MPhil in International Relations degree demands of anyone stupid enough to leverage it as a way to improve their writing and technical chops amidst LLMs obliterating every line your resume stands to offer the world.

I’m probably happily in denial. I write ~1,000 daily words to distill how I think about topics in international relations: hierarchies, treaties, empires, freedom, sovereignty—whatever this crusty curriculum will not stop force-feeding me. I love the process though. MORE!

For something more modern, I just published in a big SF tech magazine, Palladium. Check it out to get smart on how the AI model market is undermining US economic power! I’ll deliver a separate post (and live lecture soon!) on that. More to come there.

I think this is all still valuable: deeply reading, writing, and debating these topics does not waste my time. Probably. I think it’s what I want. Even if I don’t intend to push the world’s understanding of the topics themselves by pursuing a PhD, they improve my thinking, writing, and life better when I abstract the principles into personal questions: What “treaties” do I make with the world? Does my government ask for a tradeoff and subjugate me? How much anarchy do I tolerate in my daily life? Our group asked: are women genuinely ever equal in a heterosexual relationship?

These provocative questions are worthwhile— for we are pigs in the playpen getting muddy… I can never stay in the Ivory Tower too long.

Anyways, I have to go coach rowing. Below is some work no one will read. People barely look at each other’s in our course. Or they just don’t give feedback? That’s a critique of the lack of critique for another day.

Keep reaching for all that you want in life, with love,

Max

This essay that you don’t care about talks about “big bangs” in world history that create concepts. When we nuked Nagasaki, “nuclear deterrence” emerged. The Holocaust defined the word “genocide”… and of course, Oxford being a bagillion years old took up the case of “sovereignty” from 1648 and the Peace of Westphalia! Oh boy! How refreshing! Anyways, what is gained and what is lost when relying too heavily on those moments?

Prompt: Should the concept of ‘sovereignty’ be central to the study of international relations?

Echoes of a Big Bang: How Westphalia Calls the Centrality of Sovereignty into Question

Max Bessler | Nov 3 – MPhil in International Relations | <2,000 Words

Are there really “big bangs”? Creation begins somewhere, sometime. These creations evolve through space and time. Then, concepts emerge to explain them. In the study of international relations, strong concepts emerge from events that often shock the world. After Nagasaki, nuclear deterrence taught the Great Powers to avert wars, not win them. The Holocaust thrust the word “genocide” into conventions and international law. When every crescendo roars through the halls of academia, it leads fans of the music to roll back the tapes and listen for what happened before…

When examining the “when, what, and how” behind the emergence of a concept, scholars weigh the importance of those moments: how do the “big bangs” characterize a concept and establish its centrality in any study of international relations? The millions of Japanese and Jews who were bombed and gassed in World War II maintain the central importance of those concepts, nuclear deterrence and genocide, that fuel papers and policies to this day. But focusing too much on these historical events can also undermine the concept’s power to inform other similar papers and policies across space and time for the study and practice of international relations. States have been mutually deterred by the calamitous prospects of their comparable weaponry long before nuclear weapons, as with poison gas in World War II. And Raphael Lemkin, who coined “genocide” in 1944, himself pointed to the Armenian case of 1915–16 as the crime before it had a name.

Scholars of concepts in international relations can take on different approaches to explaining them today: presentist, genealogical, and historicist (Latham, 494–98). From the outside looking in, the debate between camps appears endless and may lead to an unsatisfying conclusion: no one can agree on whether a central big bang exists, nor even whether one should be conceptualized, to create a common foundation for debate. Still, historical events do happen and begin crystallizing concepts, which advances the field. Events are observed, the words and frameworks are debated, and a contested concept emerges.

There lies the heartbeat of this essay: for any concept in international relations, understanding the debate behind its historical origins helps explain its positioning in the field. That “big bang” may be a central tool for many and a misdiagnosis to others. All the same, tracking the emergence of a concept through the presentist, genealogical, and historicist approaches can show its centrality, its explanatory value, but also expose its marginality for seeing what historical events it seeks to conceptualize.

Focusing on today’s question, the concept of sovereignty certainly assists the study of international relations. No one benefits if the field outright disregards such a popular concept that seeks to explain how states organize themselves. By observing its emergence through the presentist, genealogical, and historicist approaches, with what’s lost, the unsatisfying conclusion emerges: the concept of sovereignty’s centrality should be questioned without abandoning it. Scholars of international relations need the concept—the question is how central it is for them.

This essay shows how the three approaches converge in treating the Peace of Westphalia as a “big bang” that is distinctly European; anchored by Westphalia, the concept of sovereignty is European and struggles to explain the history of states organizing themselves outside the continent—thereby undermining its centrality in the field.

Here’s the structure: first, the essay begins with Westphalia and takes it up as the big bang which marked the study of sovereignty as a concept. Entering the debate with a centralizing landmark offers a familiar starting point to introduce the different approaches that assess its emergence. Each approach—presentist, genealogical, and historicist—offers different answers to how Westphalia should be thought of in the strength of its centralizing force for sovereignty in the study of international relations. Then, its limits in conceptualizing sovereignty for China and Africa are explored in turn. An uneasy tension emerges: all three approaches weight Westphalia to explain its centrality for Europeans, but its explanatory limits lie with the continent, struggling to provide the same conceptual value for China and Africa. Regardless, it’s been adopted as an inadequate anchor all the same. Globally, the concept of sovereignty’s centrality to scholars may vary, but its strength lies in its staying power; the concept will survive because every scholar must confront it.

What does it mean to ask about the centrality of sovereignty? More specifically, the question asks: how does the concept of sovereignty shape relations in and among states and thus has emerged as a necessary principle for scholars to understand? And what does a concept of sovereignty mean? It’s necessary to spend a few minutes defining it today for common understanding, but it’s an undertaking that demands a lifetime of scholarship. Maybe that’s Grovogui? He ambitiously notes, “there has never been a uniform international system of sovereignty across space and time” (316).^[1] Beyond Grovogui, and for scholars everywhere who don’t want to pour words into a “Forum” debating its emergence, Westphalia serves as an effective founding myth to share a story and move on.

Krasner offers one way to define the concept of sovereignty, but his attempt quickly shows its inconsistencies when tested against history. Krasner says the concept of sovereignty is composed of four elements: territoriality, autonomy, mutual recognition, and control (18). Satisfying all four completes a full concept of sovereignty, but “there has never been some golden age for sovereignty” and thus states violate the model all the time (17). Krasner is not the only scholar to rely upon historical observations to note sovereignty’s flexibility.^[2]

Observing historical events guides how central any concept is to its field. Beyond Krasner, few would deny that the corpus of Week 4’s Core Readings, at the very least, comprises an attack on the ostensible fortress that “sovereignty” emerged from the Peace of Westphalia in 1648. This speaks to its fluid nature in the study of international relations, neither central nor to be discarded. Costa Lopez et al. host a forum^[3] to rescue sovereignty’s historical emergence from the “Westphalian straightjacket” (490), which helps answer the big question today about sovereignty’s centrality. Recent scholarship is “seeking to abandon the ‘big bang’ account of Westphalia” (491). Questions of its evolution have been “curtailed by the all-encompassing myth of the Peace of Westphalia—a myth that IR scholars have swallowed hook, line, and sinker” (490). Removing the Westphalian anchor, but understanding its significance, allows each approach to take up the question of how central the concept of sovereignty ought to be.

Latham offers three main ways scholars critique Westphalia’s centrality in articulating the emergence of a concept of sovereignty. His case rests upon whether notions of sovereignty apply to the medieval European world, even before the word formally emerged.

The presentist approach largely abandons the Peace of Westphalia to centralize the concept of sovereignty in their field today. Their approach treats sovereignty as the distinctly modern mode of differentiating states in the international world order and resembles the closest form of organizing supreme authorities over a territory after 1648 (495). While presentists “disagree profoundly in all sorts of ways,” they share the view that “a radical rupture separated the medieval and modern eras—a rupture both registered and induced by the invention of the institution or constitutive of sovereignty sometime between the sixteenth and nineteenth centuries” (496). The idea may have existed before, but the institution and norms are an artifact of Westphalia (495).

The genealogical approach will not go as far as invoking the Peace of Westphalia as a presentist big-bang “radical rupture” truth. This approach traces the concept’s emergence as a smoother continuation from a longer medieval political-theological tradition. By discounting the value of Westphalia as the definitive historical starting point, the historical weights that mark its centrality distribute evenly. Still, the concept’s centrality suffers because it remains distinctly European, needing to trace evidence to Westphalia.

The historicist approach still weights unique moments in history but sees their notions across orders. In the case of Westphalia, they view sovereignty emerging as an institution arising in early modern Europe but concede that its norms of supreme authority may have existed earlier (496). Among the three, a historicist centralizes the concept of sovereignty in international relations by showing, over time and regardless of whether they are European or not, the concept of sovereignty will “bear a strong family resemblance” (497).

All three approaches confront Westphalia but acknowledge its centrality to conceptualize sovereignty. As a result, the concept maintains its European flavor and marginalizes its ability to stay central to the study of international relations when other continents and scholars exist. For brevity today, consider how the concept of sovereignty—having emerged differently around Westphalia—struggles all the same in organizing China and Africa.

Why did Westphalia happen? Understanding why matters when comparing the following failures to assess its centrality. Can the concept explain how China and Africa organize? On why it happened, Krasner explains: the Peace ended the Thirty Years’ War by dividing territory, settling the practice of religion, and reworking the constitution of the Holy Roman Empire. The war wrecked central Europe (35).^[4] Westphalia needed the Holy Roman Empire to satisfy France and Sweden and deal with future religious disorders undermining regimes across the continent. The Peace reflected the short-term interests of those involved and not the shock to the international system that scholars have come to view it as (38).

China has pursued a “quest for sovereignty” in the international system, but it looks markedly different from a Westphalian transition that marked kingdoms organizing themselves into states. Carrai characterizes China’s claim to sovereignty as likewise pragmatic, but evolving from its own “haunted” imperial and colonial past, and complicated by Western colonial history (1, 9).

Africa similarly pursues sovereignty, deeply complicated by its own history of imperial invasion. Grovogui attacks the “Westphalian commonsense” (315): deviations from its concepts, as in the case of Africa, are treated as failures of the state, not the concept itself. In the case of Africa, the concept of sovereignty is practically a weapon, allowing for the transfer of power and wealth from the Congo to collaborating Great and Middle powers in Europe, including Belgium and Switzerland (317). As a result, these notions of sovereignty, deeply violated, cannot be central to a study of international relations that incorporates understanding how African entities organize themselves—for even calling them “states” invokes a Westphalian starting point that muddies debate.

Big bangs in history create new centers of gravity—new concepts to a field. But as time passes, those concepts end up explaining new events to maintain the explanatory value that powers their centrality. The concepts of nuclear deterrence and genocide look a lot different than they did in the 1950s—and so does sovereignty since Bodin turned it into a political term in the 1576 Les six livres de la République (Latham, 496; de Carvalho, 503). Following Westphalia, the two quick cases of China and Africa demonstrate that its centrality cannot explain every organizing goal it seeks to achieve for entities. Krasner addresses the theoretical failures but finds an optimistic escape that the Forum addresses. Sovereignty as a word will never leave the study of international relations—nor should it.

^[1] However, in the context of African states, it loses its global importance...

^[2] Krasner seeks to expose the shaky historical consistency underlying the concept of sovereignty. He also addresses the Peace of Westphalia directly, contending sovereignty “had almost nothing to do with what has come to be termed the Westphalian system although I use the term here in deference to common usage” (17). Sovereignty as “organized hypocrisy,” more broadly, ends up constructed as a “cognitive script” that decouples norms from actions (19).

^[4] Krasner: “The Thirty Years War, fuelled in part by religious antipathies, resulted in more than two million battle deaths, a larger carnage than any conflict except for the First and Second World Wars. It had been preceded by the religious wars in France during the latter part of the sixteenth century. The Civil Wars in England rent the English monarchy through the middle part of the seventeenth century.”

Entering The Slipstream seems simple—it only asks you to breathe.

But breathing is never simple. Not in the beginning. Not when the start of every alpine swim sucks all air. At the start of each Odyssey through these mountain lakes—Redfish, Alturas, Titus—there is no privilege to think.

It’s a different type of wild world from the backcountry. Open water offers different order. Merging into The Slipstream requires practiced, autonomic acceleration. I’ve learned to let my body embrace those frigid first seconds through breathing. remembering to breath. Cold silences all.

Like merging onto a highway, just gun it and just throw the elbows. Redfish’s clean crystalline blues may resemble the diamond luminescence of long swims in Costa Rica and the Adriatic—but it sure as hell doesn’t feel like it.

Temperature warps time: the first seconds are the longest, the minutes tick away faster, then the hours begin blinking by. I have been lucky to find The Slipstream around the world.

Once in The Slipstream, I reach for the beyond, pull through what I was before, and kick away the rest that no longer serves me.

Soon awareness seeps in.

The sun rises higher with each breath. Each shoulder glides through the perfect lake mirror.

Vision is great—until you’re left seeing nothing below.

The physical shock has left. Now, The Slipstream pulls me into a constant negotiation of instinctual anxiety. Should I be out here? We are built for the land. So why embrace every unique trial of each Odyssey? I don’t have an answer.

That shock calms me, but it claims lives. The Slipstream can kill. Especially in races. To bring order to the chaos, I’ve prepared in the pool, lifted, visualized, and planned. I’ve abandoned plenty. Safety is calculating a range of likely consequences I’m willing to suffer. Every breath, I feel safer.

And at the end, when I do step back onto my feet to walk the opposite shores of Redfish: the world—my world—is as calm as can be. The mind makes amends with the body. Still chilled. So chilled. Residual goosebumps are the sign of a job well done.

And now that I’ve left The Slipstream, I can still remember to just breathe.

Happy October my good friend. I moved to Oxford University last Sunday to start the “Masters in Philosophy of International Relations”. Here’s a quick strip. A naked update if you will. A little tease of what’s to come. I’ll stop with that, but I do think my experience may interest you.

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Welcome to a short one covering the first week of whatever the hell will follow… in the dreary backwaters of England, my arc as an author and athlete will be headquartered here… for the next two years….. If you know how often I’ve come to enjoy new communities, that two year commitment terrifies me the most. Do it. Diagnose me.

Summer CV Hardo Update: I’m happy with September. I’m in review for Bay Area Abroad, submitted two other works, swam the alpine lakes of the Sawtooth’s in Idaho, PR’d a 70.3 like A BIG DAWG, and smoked a half marathon mountain race— but most importantly, I just took care of myself: slept and ate well, didn’t overtrain, spent time with loved ones, camped under the stars with good friends, and rested when I needed to. I am so lucky.

Max is doing well. Well he was. It’s three in the morning. Again. I’ve been jet-lagged for 4 days. I also didn’t bring the right power converters so I lay in bed typing my phone into death to help me fall back asleep. Dude get your life together. Max will nap this afternoon.

Classrooms, dining halls, labs, gyms, apartments are shelled within buildings that easily date back centuries— the institution was older than the Aztec Empire. My American peabrain—that conceives of national history in a short term—short circuits thinking of the daily lives that have lived through literal ages of time. How many have said “I love you” in my resident park that’s a thousand years old?

It’s all so trippy today too. With this degree, the readings start very theoretical with some absurd coursework. I must embrace some inescapable elitism when my future job could lie, in part, to how well I pass a class about the “formation of international thought”. Like seriously. This research can end up so faraway from what ideas the economy rewards today. This sure doesn’t sound like comparing the impact of AI on anything for a hedge fund.

I do feel separated from the outside world. The intense intellectualism of academia takes up more mindshare. I can’t obsess over the daily news in tech and global affairs, nor do I have to as much. Either way, obsessing over nebulous things can remove us from the grounding world that actually changes life. Is this Oxford’s fault? I don’t think so; I just need to remember to touch grass, read, visit my friends and family in the workforce.

I will find more of my people outside the Department too through triathlon, rowing, and some technology and entrepreneurship programs. And compared to Sun Valley, San Fransisco, New York, and Washington DC, the fitness culture is hilariously lazy here. There’s this weird “cool” brag about not exercising(???). Whatever, I’ll take an emptier gym.

So, this campus is so convenient, but it cannot connect me my life outside of it that I’ve built, and don’t plan to leave behind.

I can tell most students do not share my own professional struggles in my early twenties, where I leapfrogged around like a white collar vagabond. I do not know their own struggles, but they have shared they do not share mine: walking into jobs that don’t fit them, being pumped full of cortisol in some factory, or been fired/hired/quit constantly. Here is where I admittedly feel some humbled advantage. Things will be okay. Dear god, stop asking about how long the final is 1 year from now.

Oh, and I wonder if I enter every room the least interesting in my cohort. I will share the intense experiences that’ve shaped me in due time… But for now, envision me in business casual everyday, looming over everyone uncomfortably in the back (+1 for the tall white American in the back). I miss my tall people lol.

I may be loud online, but I’ve been relatively quiet in person since arriving. I retreat to my slipstream by finding the familiar flow of training and writing alone by ducking out of these exhausting mixers where you can’t even hear anyone. It’s been nice, comforting even, extending my summer work and keeping in touch with friends across time zones.

I want this series on Oxford to stay casual. It’s just a public token of gratitude to all those who support me to live, study, and work in some of the world’s most historic, hallowed halls. I’m talking about anyone who checks in, calls, offers advice; these are all resources I cannot do without. Thank you.

I’ll button this up into a miserable LinkedIn blurb, but Substack is a selfish pleasure. They’re a long text to no one, and perhaps everyone. So I miss you all.

For better or worse, I’m an open book. And then I remember I shouldn’t share some chapters. So reach out anytime.

Max

Thanks for being here. You’re kind enough to put up with me— and my tendency to reject the “typical” way to use social media.

Today’s short chapter concludes our time with “Bay Area Abroad: Innovation through Fragmentation”. It’s just 7 paragraphs and a few snappy tables that tries to tie together like 20,000 words total—and way many more deleted— devoted to understanding how Bay Area technology companies navigate geopolitics.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

Thank you for reading, claiming to, and providing feedback. Who knows where this writing will lead. I have a gazillion ideas, but this is its first showing ahead of showing up at BACEI. Any feedback is welcome.

Assessing the Engine and Exposure

Bay Area technology flows risk fragmenting. At home, the domestic engine remains strong, attracting outsized investment and astounding profit. However, the pipeline of talent risks cracking. The bar to immigrate, study, and work is rising; that undermines retaining a healthy base of high-skilled foreign talent to research and work across Bay Area universities and companies.

Overseas, companies appear to be hedging their commercial activity depending on their core business lines. More profits are being reported at home by the median firm, in part due to new incentives that reward companies for reporting in the United States the foreign sales of U.S.-held intellectual property. Consumer-facing, digital-born companies see demand remain widely distributed. New physical projects appear to be shifting away from rival-bloc destinations, such as China, and toward allied markets like India.

Future research should compare fragmentation metrics against each other. Start with two pairings: profit share against FPTP, and talent inflows against new project announcements. Even as global profit share has stayed above half since 2019, the reported foreign profit share on 10-Ks has fallen, likely in part due to incentives that lure businesses to report foreign income at home. Perhaps most apparent is Meta, which reports just 6.1% of foreign profit abroad in FY2024—likely as a result of generating sales not from customers but from advertisers and other digital sources not tied to a specific geographic location1—yet the digital platform giant scores a DOI of 0.707 and reports 3.6 billion daily active people around the world across its family of apps.

Companies which manage to operate with light assets carry a double-edged dagger when competing in overseas markets. These consumer-facing, digital-born companies lack assets—e.g., subsidiaries, employees, and physical projects—that entrench them in host countries.2 That makes it easier for fragmentation to arise. A government could block access. So, they might be less exposed operationally to geopolitics, but they are also more vulnerable to losing their customer base of users.

Additionally, comparing talent inflows and greenfield announcements for India shows a conundrum for policymakers of competition and cooperation. Student visas issued to India, the largest sender of students, fell 60.5% in 2025, even as India’s share of new greenfield projects rose from 4.3% (2010–14) to 11.3% (2020–25). By contrast, China is consistent across talent and projects. Student visas issued to China fell by 30.3% and its share of new projects shrank from 7.2% to 2.4%. On one hand, the influx of high-skilled labor can debase the national pipeline to upskill homegrown talent; on the other hand, restricting talent inflows hurts the brain circulation3 that may produce advantageous overseas investments.

The History of Bay Area Tech Flows Fragmenting

Five distinct geopolitical eras shed light on how geopolitics influence the behavior of Bay Area technology companies. Whether they face direct foreign competition or not, Washington always plays a role. When threats to national security arise, restrictions on flows follow. This appeared during the Cold War against the Soviet Union with CoCom and remains true today with export controls on semiconductors to keep China behind the frontier. As with Japan and later China, competition was once two economies full of firms cooperating: trade divided production to mutually benefit firms spread along the value chain. The Bay Area played a supportive role in helping grow rival economies of Japan and China, fragmenting its own market position abroad. Chasing cheaper margins leads to technology transfer. In the rare moments of no economic or military competition, Washington steps out of the way by easing the restrictions that fragment. Today, the world risks Washington playing a heavier hand as flashpoints around the world risk fragmenting technology flows.

Bay Area technology firms are hedging against a future that further fragments trade along geopolitical tensions. Flashpoints could escalate into provoking Washington to play a heavier hand in guiding trade flows like prior eras of competition with the Soviet Union and Japan. The remnants of aggressive globalization remain, preventing Washington from insulating the Bay Area engine’s ability to reach markets worldwide. Through every era, a pattern has held: the Bay Area engine has produced waves of innovation; great companies that must navigate geopolitics will continue to rise and fall.

Thanks for reading friends.

I leave for the United Kingdom Saturday.

I’m drafting completely different pieces. No tech to follow!

Max

Financial history can chart the lives of businesses. Want to know how the world’s largest technology companies weather their geopolitical lives? Sail around and explore the stories their dollars and numbers tell us about today.

Welcome to the heart of “Bay Area Abroad: Innovation through Fragmentation”, two special chapters, posted together that explore how various commercial metrics can help understand whether Bay Area technology flows are fragmenting along geopolitical lines.

The first chapter assesses if the Bay Area Engine—of talent, investment, and commercialization—is being disrupted by geopolitics. The second chapter observes exposure: how much of Bay Area technology business rides on markets around the world?

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

Since I explore funky ways to figure out if geopolitics impacts tech business.... it might get a little weird... please, pray, tell me if you think about things differently. We’re on schedule for publishing with BACEI.

I always push for purity. This is my writing. It would be disrespectful to have you read something that wasn’t. I’ve left an AI disclaimer at the end.

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The Firms to Survey for Fragmentation

Are Bay Area technology flows fragmenting along geopolitical blocs today? Answering this requires a reproducible dataset of Bay Area technology firms with a worldwide presence. This section outlines how those companies were selected. Beginning with more than 2,000 public and private companies—drawn from the 2025 edition of the Forbes Global 2000 for public firms, and from announced valuations and raised capital for private ones—the list passes through three cuts: headquarters, sector, and scale. This distills the pool to 47 Bay Area-based technology companies, which the rest of this report surveys.

List of Analyzed Bay Area Technology Companies

Lyft is not in the 2025 edition of the Forbes Global 2000 that standardizes FY2024s. It last appeared in the 2019 edition and is retained on the roster after meeting the borderline floor for scale.

The remainder of this section briefly outlines each of the three selection cuts before turning to the metrics analyzed.

How to define a “Bay Area” Company

Whether a company qualifies as a “Bay Area” company is first based on its legal incorporation. Of the nine Bay Area counties, four are represented across 43 of the 47 companies studied: 24 are based in Santa Clara, 13 in San Francisco, three in Alameda, three in San Mateo. On a second pass, four additional technology companies were included because of their historical grounding in the region. A firm qualifies if it maintains at least 5,000 employees in the nine-county region or operates a central R&D facility there. By this standard, Amazon, Microsoft, Tesla, and Oracle are included despite being headquartered elsewhere.

How to define a Technology Company

Varying definitions of technology companies exist; this report anchors its definition in how companies navigate the changing world order. To qualify, a firm must derive its core commercial activity from at least one of six layers of the information-technology stack (“IT Stack”) as defined by Baums & Butts in Tech Cold War: 1) semiconductors, 2) telecom infrastructure, 3) cloud infrastructure, 4) endpoint devices, 5) artificial intelligence, and 6) digital platforms and applications.

A company that relies on the IT Stack as a tool, but without deriving its core commercial activity from it, does not qualify. This excludes Wells Fargo, a bank headquartered in the Bay Area whose core business is financial services rather than technology, while still including Visa, whose core business is a digital payments platform (6). Companies that innovate technology for a specific vertical sector are likewise excluded, such as major Bay Area biotechnology companies like Genentech, Gilead, and AbbVie. Though significant drivers of regional innovation and employment, these firms are excluded because their advances do not diffuse across other sectors, and including them would invite scope creep toward any other company that uses information technology to innovate within a vertical sector, such as “agritech”, “biotech”, “edtech”, and more.

How to define size

The third cut sets a floor on company size. Not every Bay Area company within the IT stack possesses the scale where its presence in the world economy makes for geopolitical relevance. Startups are numerous but often small, and data availability is limited; this cut therefore filters firms through the 2025 edition of the Forbes Global 2000 (FY2024 financials), which ranks public companies on a blend of four measures: revenue, profit, assets, and market value. Private firms are held to a parallel standard, since they do not report revenue the way public firms do: they must either exceed a $10 billion valuation or have raised more than $2 billion in capital.

With this dataset established, the following chapter reassess the engine today by asking: does the Bay Area’s cluster of technology firms still show the same capacity for reinvention that carried it through the Cold War, Japan, and China’s rise, or is fragmentation now visibly underway?

Chapter 8: Assessing the Engine

To understand how geopolitics are affecting the Bay Area technology companies, this section tests the strength of its engine globally today. This section measures the global share of talent, investment, and ability for these firms to commercialize their technology, i.e. turn a profit.

Little Sign of Talent Fragmenting

At the foundation of the Bay Area innovation engine is its high-skilled talent base. If geopolitics are fragmenting the engine’s talent, then the flow of immigration would be disrupted. This section observes whether that’s true based on census and H-1B data.

High-skilled immigrant talent has continued to grow in the Bay Area. From 2000 to 2024, the share of foreign-born scientists and engineers employed in Santa Clara County rose from 52.6% to 71.0%, while the share of native born fell from 47.4% to 29.0%. The share of Asian born scientists and engineers, and all employed workers for that matter, has steadily climbed for over two decades since 2000. But since 2010, it has slowed by about half among scientists and engineers, from 1.2 to 0.6 percentage points a year. The 2025 Silicon Valley Index corroborates this independent census analysis, finding that “Forty-one percent of Silicon Valley’s population is foreign-born (a historic high); among employed residents, 48 percent are foreign-born. This figure jumps to 66 percent in tech, where 70 percent of tech workers are Indian or Chinese and 73 percent of female tech workers are foreign-born.”1

Observing the list of Bay Area technology companies, 47% (22 of the 47) companies have at least one immigrant founder. Many have lived in America their entire life, having benefitted from open immigration policies. The list of Bay Area founders’ nationality tracks census data: Asia comprises the largest group—Jensen Huang of Taiwan at NVIDIA, Ken Xie of China at Fortinet, David Lam of China at Lam Research, Charles Liang of Taiwan at Super Micro Computer and Tony Xu of China at DoorDash. Europe follows, with Sergey Brin of Russia at Alphabet, Aart de Geus of the Netherlands at Synopsys and the Collison brothers of Ireland at Stripe. The Middle East, Latin America and Africa supply the rest: Nir Zuk of Israel at Palo Alto Networks, Eduardo Saverin of Brazil at Meta and Elon Musk of South Africa at Tesla, xAI, and OpenAI.

But recent worries of an eroding domestic engineering base have sparked Washington to restrict the flow of high-skilled immigration for several reasons, including national competitiveness. In 2025, the Trump administration sought to restrict the approval of H-1B visas—typically the practical way for a high-skilled foreign national to work long-term in the United States. The proclamation required new H-1B workers’ entry to be accompanied by a $100,000 payment, but a federal court vacated it in June 2026, and an appeals court refused to reinstate it in July.2

Have H-1B approvals fallen as a result of these policies? Marginally. According to the National Foundation for American Policy, “the denial rate for H-1B petitions for initial employment rose to 2.8% in FY 2025 from 2.5% in FY 2024.”3 In FY 2025, the top spots for approvals of new H-1B petitions were all held by Bay Area technology companies on the list: Amazon (4,644), Meta Platforms (1,555), Microsoft (1,394) and Google (1,050). California employers approved the most overall (21,559).4

Though H-1B rates have barely moved, the number of international students arriving to the United States has plummeted. The Department of State reported that 23% fewer student visas were issued in 2025 compared to the previous year.5 The two largest countries that send the most students, India and China, fell 60.5% and 30.3% respectively.6 For China, the White House and Department of State justify restrictions out of concerns that Chinese students and researchers act as “non-traditional collectors” to acquire sensitive technologies and intellectual properties.7 No direct proclamation that suggests India poses a security concern exists. The biggest dip was Iran; compared to 2024, over 90% fewer student visas were issued to Iranian nationals.

H-1B lottery swings are important to note but require more time to understand whether Washington’s policies are fragmenting the Bay Area’s access to top-tier foreign talent, a critical part of the engine for decades. Policymakers appear to be pursuing a dual mandate: combatting fraud, including multi-registrants, and also counteracting demand for foreign talent to restore a homegrown base that competes. That second reason, Washington asserts, is to address how companies have “deliberately exploited” the program “to replace, rather than supplement, American workers with lower-paid, lower-skilled labor.”8 Though student and lottery entrants may be shrinking, both are US policy choices currently applied to everyone, not exclusively applied along geopolitical blocs. Over the next decade, these policy tools could turn into levers to further enhance economic security.

These immigration metrics suggest the Bay Area’s foreign talent base remains intact, but policies are arising that threaten to fragment flows. At every census point between 2000 and 2024, the foreign-born share of scientists and engineers in Santa Clara County rose, from 52.6% to 71.0%. At the top, the roster’s leadership is international; 22 of the 47 companies carry a founder born in Asia, Europe, the Middle East, Latin America, or Africa. But the bar to arrive is rising: student visas fell 23% in 2025. Registrations for the H-1B lottery fell by more than half in two years, from 470,342 to 211,600. Since 2026, the lottery gives higher-wage job offers a better chance for visas.9 These metrics suggest the requirements to study and work in the Bay Area are rising.

Investment Continues to Concentrate

The Bay Area remains a strong source in attracting high-technology investment to its companies. Market capitalization tracks where investors park their money in public markets, and reflects investor confidence in a company’s future growth prospects.10 If investment were to be affected by fragmentation, we would expect to see various indicators of investor confidence fall, including market capitalization. The strong share of global technology investment directed toward the Bay Area suggests investors remain confident in the cluster’s perceived technological advantage, entrepreneurial culture, and future returns.

Observing changes in market capitalization reveals how investors feel about the future macroeconomic environment. Investors in companies more exposed to geopolitics will naturally weight flashpoints as higher risk factors. These companies operate in the best capital market in the world. As Vagle and Brooks note, relative to other financial hubs like China, where capital controls depress reported figures, “the openness of US capital markets”11 makes the US market itself a safe haven for investment, regardless of the company’s positioning. It’s easier to invest in the United States—which means the stock itself is the product, rather than the technology. Financialization and easing the flow of investment helps prevent fragmentation, rather than the fundamental trade of technology. As Sean Kenji Starrs said in an interview,12 “market value is probably a more important metric for investors, but investors are looking at the future.” This is one metric to complement others; the price sometimes reflecting broader investor mood as much as the company’s underlying performance.

On a three-year average across 2023-2025, this Bay Area cluster commands $17.15 trillion in market capitalization—64% of the entire world’s high-tech sector’s market capitalization, and about 20% of the market value of all Forbes Global 2000 companies worldwide.

Since 2004, Bay Area technology firms have grown dramatically in scale and captured a larger share of the global high-tech market. In 2004, 15 of today’s 38 public firms were in the Forbes Global 2000; by 2025, the roster’s combined market capitalization had multiplied 22-fold, from $0.91 trillion to $20.1 trillion. Its share of the global high-tech market climbed over the same span, from about 36% to roughly 65%, as a result of new firms replacing old ones13. Three dips in the cluster’s share of world high-tech market capitalization occurred over the last two decades due to tech equities shifting during the 2008 Great Financial Crisis, the 2019 trade war, and the 2021 pandemic, but each was largely reversed within a year. In fact, during none of the three episodes did Bay Area market capitalization actually fall—the rest of the world’s market capitalization just grew faster; the dips are relative, not absolute.

Which layers of the IT-Stack receive the highest share in high-technology investment? Break down the $20.1T cluster, whose tech-classified firms hold 64.7% of the entire world high-tech market capitalization. Digital platforms & applications 28.9% ($5.8T) and cloud infrastructure 28.0% ($5.6T) capture the most investment. Semiconductors 21.1% ($4.2T) and endpoint devices 20.4% ($4.1T) follow closely behind. Telecom 1.6% ($0.3T) nears the bottom. As of September 2026, no Bay Area frontier AI lab, e.g. Anthropic or OpenAI, has IPO’d, but both are targeting over $1 trillion market valuations14.

Investors remain resilient. Market capitalization data suggests geopolitics are not eroding confidence in the relative command of Bay Area technology flows. From 2004 to 2025, the roster’s share in the world’s high-tech global market capitalization rose from 36.3% to 64.7%. Capital has continued concentrating to the cluster even through geopolitical and economic tests: the great financial crisis, the trade war, the pandemic, and even after the recent rise in export controls, 65.6% in 2024. This concentration arises from the reinventive dynamism of the engine; the original 15 2004 firms fell from 36.3% to 17.8% as new entrants carried the rise. Each dip proved to be a blip where the cluster’s value still managed to grow.

Profit Power Remains Strong

With talent and investment established, how well the Bay Area can continue to commercialize its technologies abroad deserves deeper analysis. Commercialization in this report is defined as the ability to turn technology into profit. If Bay Area technology companies were struggling to commercialize their technology—to convert innovation into profit—global profit-share data would show it.

Strong profits suggest Bay Area technology companies remain among the world’s best at commercializing their technology. One of every two dollars in global high-tech profit is earned by the 38 Bay Area technology companies in the Forbes Global 2000.1516 Their centrality to the world trade of frontier technologies testifies to the ubiquity of their current economic activity. Unlike revenue, higher profits indicate a company's ability to perform above its costs—signaling the capacity to continually invest in research and development and enter new markets.17

If this cluster of Bay Area companies were its own country, it would generate more profit than every other nation’s high-tech sector combined, excluding the rest of the United States. The $611.1 billion in FY2024 is more than five times China’s total ($111.0 billion) and more than ten times Taiwan’s ($57.5 billion).

Observing profit capture over time, the pattern holds. This reflects a long-running trend of capturing commercial value: Bay Area technology firms have increased their profits over time by splitting their value chains into low-value assembly and high-value branding, research, and development. Since 2019, the Bay Area cluster’s share of global profits in the Forbes 2000 list has never dropped below half.18

This chart reflects how corporations continue to divide labor internationally in what many characterize as a “merchant” model: companies like Cisco and NVIDIA handle design and quality control in the Bay Area while outsourcing production and assembly elsewhere.19 Firms treat this assembly work as interchangeable, low-cost input, while retaining the bulk of the profits for themselves. For example, a 2023 teardown revealed the Apple iPhone 15 Pro Max retails for $1,199, but costs only $523 to produce across several countries, of which less than $13 goes to firms in China for assembly and components.20

Which layer in the IT stack captures the highest share of profits?21 The companies whose core product is digital platforms & applications capture the most, 20.4% of world high-tech profits and 39.2% of the cluster. Cloud infrastructure follows (14.6% of world and 27.9% of cluster). When excluding the major non-headquartered Bay Area operators, cloud companies, including Microsoft and Amazon, dry up the category almost entirely. Endpoint devices (9.0% of world and 17.3% of cluster) and semiconductors (7.1% of world and 13.6% of cluster) follow.22 The Artificial Intelligence layer remains empty as frontier labs are private so they do not appear in the Forbes Global 2000.

Recognizable names emerge when these business lines are examined at the company level. The six largest companies alone account for 80.9% of the cluster’s profits: Alphabet ($111.0B), Apple ($96.2B), Microsoft ($92.8B), NVIDIA ($72.9B), Meta ($62.4B), and Amazon ($59.2B), on a Forbes Global 2000 basis.

Excluding the four firms that are not headquartered but have major operations in the Bay Area—Amazon, Microsoft, Tesla, and Oracle—the cluster’s share of global high-technology profit falls from roughly half (52.2%) to about a third (37.6%). A steep drop-off follows the remaining top five, with the list consolidating quickly until Visa closes out the top tier at $19.7 billion.

Drawbacks. Several limitations exist in relying on profit-share to assess whether technology flows are fragmenting. First, firms are not required to standardize where in the world they report earning profit—metrics like customer location, billing entity, or shipping destination would be more informative but are not consistently disclosed. Second, profits fluctuate year to year, which complicates any read on which firms hold durable power; some companies go unprofitable for years while prioritizing growth.23 Third, aggregate profit share obscures the rise and fall of individual firms within the Forbes Global 2000 list over time, which argues for examining several time series rather than a single snapshot. Finally, the metric is highly sensitive to a small number of firms: the top five companies represent 71.2% of total Bay Area high-tech profits, and NVIDIA alone accounts for nearly 12% of the cluster’s total—meaning a shock to NVIDIA’s addressable market could meaningfully move the cluster-wide statistic on its own.

These profit metrics suggest little fragmentation at the level of commercializing their products. Roughly half of the world’s high-tech profit is earned by Bay Area technology companies. Its top six firms earn 81% of the entire cluster’s profit and NVIDIA alone earns 12% of the roster’s profit. This suggests that while the dominance is apparent, a handful of firms carry the cluster’s profitability. Were geopolitics to disrupt any of these firms’ core business lines, the impact to the Bay Area’s profit power would immediately show, reverberating back on the region’s dynamism to research, develop, and invest in successive waves of innovation.24

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Chapter 9: Assessing Exposure

Having tested the strength of the Bay Area’s engine, this section turns to testing exposure: is this engine exposed to fragmentation? To test commercial activity, one basket of metrics observes a firm’s level of “transnationality”, the degree to which a firm’s commercial activity is earned at home versus overseas. Traditional performance-based measures include foreign sales to total sales (FSTS) and foreign profits as a share of total profit (FPTP).25 Fragmentation would appear in foreign profit share falling (FPTP), as the share in commercial activity would shift towards home.

Profits Come Home, at Least on Paper

Global profit-share speaks to the Bay Area’s continued prowess to commercialize the frontier; the Bay Area earns more high technology profit than other clusters around the world, but this does not reveal how exposed their earnings are. The United States boasts one of the largest and most-profitable economies in the world. The commercial strength of its companies could rest upon the ability to generate profits at home and not abroad.

This section offers a basic metric that splits whether profits are earned in the United States or abroad. By focusing on FPTP, it extends the earlier profit analysis and works within the data available in 10-K filings.26 Most in the dataset report a domestic-versus-foreign split in their SEC 10-Ks. Of the 47 roster firms, 31 reported a usable ratio. According to their FY2024 10-Ks, 22.9% of total pretax income was earned abroad, $133.5 billion of $584.2 billion. The median firm’s share is higher than the average, 37.4%, as the largest earners book the smallest share abroad: Alphabet, Meta, NVIDIA, Amazon and Microsoft earn 77.2% of the 31 firms’ pretax income and report 16.5% of it as foreign.27 The more transnational a firm’s activity, the more exposed it is to geopolitical risks.

Observing FPTP over time suggests businesses are increasingly earning—or at least reporting—more of their profit in the United States. Even as Bay Area firms have captured a growing share of global profit overall, the share they report earning overseas has fallen: the median foreign profit share roughly halved since its FY2017 peak of 63.2%, falling to 30.3%.

Which companies book more profit abroad? Breaking foreign profit share down by the IT-Layer reveals endpoint device companies report the majority of their profits abroad (59.3%). Analyzing the semiconductor layer requires further discussion into how each company books profits in their 10-Ks. For example, Lam Research reports the highest FPTP of any firm in the dataset, at 95.8%; the company’s own annual report stresses wide-ranging geopolitical risks: “tariffs, export controls, additional taxes, trade barriers, sanctions” and “certain materials … primarily available in a limited number of countries, including rare earth elements, minerals, and metals.”28

Digital platforms report low exposure, at 26.7%, and it’s worth mentioning that figure likely reflects a limitation in the underlying data because of how some digital-born firms can opt to report profits at home. Intuit’s low FPTP is straightforward to explain: its core product, tax software, primarily serves the United States. Meta’s is not: the company reports its own low FPTP in its 10-K,29 especially notable given how extensively Meta’s genuinely global user base has already been documented in this report.

This measure runs into several obstacles worth noting. Seven companies—Intel, Broadcom, AMD, DoorDash, Workday, Lyft, and Western Digital—were excluded from the median calculation because they reported losses in one or both geographies, placing their FPTP outside the interpretable 0-100% range.30 Breaking the analysis down by company also exposes a deeper issue: transfer pricing. Firms book profit in ways that optimize for tax treatment, which may not align with where their actual business or users are located.31 By three-year average FPTP (FY2023–2025), the most foreign-oriented Bay Area-headquartered firms in the list are Lam Research (95.8%), Applied Materials (91.6%), and HP (85.4%); the most domestic-slanted firms are Intuit (3.7%), Netflix (6.9%), and Meta Platforms (7.1%).

Observing foreign profit share can paint a mixed picture of fragmentation. The trend that foreign profit share is down by half—the median firm earned 63.2% overseas in FY2017 versus 30.3% in FY2025—suggests business came home. Peaking in FY2017, the fall afterwards deserves some attribution to new incentives that reward companies for reporting in the United States the foreign sales of U.S.-held intellectual property, including the profit earned overseas.32 Most exposed are those firms unable to bring profits home: Lam Research, Applied Materials, and HP make equipment that could be owned by legal entities abroad with US parents. For the profits that do return home, they help fuel the Bay Area innovation engine, allowing these incumbents to deploy more capital towards researching, developing, and investing in successive waves of technology.

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Digital Demand Is Not Fragmenting

For technology companies that sell physical products and infrastructure, financial reporting reflects a real operational and physical footprint overseas—profit earned abroad reflects genuine activity and exposure there. But as Meta’s case shows, a 6.1% FPTP in FY2024 suggests a category of companies escapes these traditional metrics by being “born-digital”: digital multinational enterprises that achieve rapid international growth through digital business models rather than physical expansion.33

“Born-digital” firms reach markets worldwide just like their physical counterparts, but their digital nature lets them scale rapidly, carry fewer physical assets on their books, and often report revenue in locations that don’t match where their customers actually are.34 This discrepancy invites the need for another metric to survey commercial exposure to geopolitics.

This section offers Google Trends as a novel research source to measure transnationality differently from firm-reported accounting data like profit. Google Trends captures search volume for key terms related to Bay Area technology companies, serving as a proxy for demand. This works because of Google’s dominance in global search: as of June 2026, Google held a 91.27% share of worldwide search, making its data a reasonable proxy for the digital behavior of billions of individual users.3536

Harald Puhr, the study’s lead author, and his co-authors Müllner and Trentini (2023) use Google Trends to construct a “Degree of Internationalization” (DOI) score, which measures how evenly search interest in a firm’s product is distributed across countries.37 DOI is scaled from 0 to 1: a score of 0 means search interest is concentrated in a single country, while a score of 1 means interest is spread across all countries measured.38 Where FPTP captures how a company books profit overseas versus at home, DOI captures how its user demand is distributed across borders.

If digital demand for Bay Area technology were to be fragmenting, DOI would fall because it would reflect search interest concentrating into the US market or another allied market. A higher DOI can suggest a lack of fragmenting digital demand.

Meta is the clearest illustration of why this second lens matters. The company reports an FPTP of just 6.1% in FY2024—by that measure alone, one of the most domestically anchored firms in this entire dataset. But by creating a basket DOI of its three consumer apps—taking the terms Instagram, Facebook and WhatsApp—the resulting figure is 0.707, suggesting a widely distributed digital demand.39 In June 2026, Meta’s family of apps averaged 3.60 billion daily active people worldwide—a genuinely global footprint that the FPTP figure alone would never reveal. The gap between these two numbers, for the same company, is the entire point of adding Google Trends to this analysis: a firm’s commercial exposure to the world can be far larger than its accounting statements suggest, particularly for firms that monetize global attention rather than global assembly lines. Further discussion between DOI and FPTP will follow in the concluding chapter that offers cross-metric comparisons.

Extending Puhr, Müllner, and Trentini’s methodology to Bay Area technology companies requires further scrutiny of the roster: only 15 firms have been selected of all 47 possible firms due to their consumer-facing, digital-born nature, as defined by Claudia Trentini and her UNCTAD co-authors.40 As Puhr, Müllner, and Trentini note, “Ideally, researchers also include an additional control for B2B versus B2C to capture systematic biases.”41

To draw conclusions about digital fragmentation with DOI and Google Trends, this section shrinks the list to measure a basket of terms under flagship consumer brands.42 Two limits must be noted. China blocks Google and other digital firms. Instances of digital decoupling in the observed periods are missing. And three artificial intelligence labs—OpenAI, Anthropic, and xAI—launched their products inside the window. Their significant rise in DOI reflects the worldwide spread in their product; that does not reflect a change in established demand.

The analysis suggests that digital firms managed to relatively diffuse their products across borders more, or maintain their spread. DOI does not speak to absolute growth. Outside the newly launched products, none of the 12 established firms became more concentrated. Search usage remained widely distributed. In fact, the US share of search interest fell for all 12 established companies, suggesting companies saw an increase in overseas search demand.

Extending Puhr, Müllner, and Trentini’s methodology to Bay Area technology companies in this way reveals which firms are more thinly spread across the world than traditional profit-based metrics alone would suggest—a gap in exposure that matters precisely because it is invisible to the accounting-based measures policymakers and analysts typically rely on.

Hedging New Future Projects

History shows that Bay Area technology companies have long earned money in markets around the world. This section asks whether they are still investing in building out that presence today via a metric called “foreign direct investment” (FDI). As Matt Sheehan writes in The Transpacific Experiment, “FDI refers to a foreign company either acquiring a large stake in a U.S. firm or setting up its own operation on American soil.” Bay Area technology “greenfield” projects are the latter where the firms in the roster announce a new project on foreign soil.43

This section examines newly announced overseas greenfields tracked from January 2010 to May 2026 by the Financial Times’ fDi Markets database, which aggregates data from media, newswires, and investment-agency sources.44

This analysis relies upon a dataset limited to headquartered California firms. This excludes Amazon and Microsoft. Due to limitations in the dataset, their outbound FDI data falls outside the scope of this report; though both are headquartered in Washington State, the rest of the report incorporates them as part of the broader Bay Area cluster thanks to their major operational presence. Conclusions thus trend towards the lower bound as both companies invest heavily worldwide.

If fragmenting were to be occurring, announced projects would be shoring away from rival-bloc destinations and toward allied markets.

Why do companies invest overseas? Drawing on background interviews with leading firms and experts, this report proposes three motivations: revenue (e.g. setting up sales and marketing offices), resources (e.g. R&D and manufacturing), and infrastructure (e.g. broadband, data centers, disaster recovery, and wireless communications projects).

Mapping these motivations onto business activities reveals how companies pursue each goal. From January 2010 to May 2026, of 2,018 total announced projects, revenue and resource motivations were roughly evenly split (42.2% and 38.5%, respectively), with infrastructure trailing at 19.3%. 45

Where do these projects go? Looking back across the full dataset since 2010, the Asia-Pacific region leads with 712 projects (35.3%), followed closely by Western Europe with 664 (32.9%), and, farther behind, Latin America and the Caribbean with 210 (10.4%). Europe (including both Western and emerging markets) and Asia-Pacific together account for 74% of all projects.

At the country level, China’s share of new projects is declining, from 7.2% in 2010–14 to 2.4% in 2020–25. India is rising, from 4.3% to 11.3%. Since 2020, the dataset indicates no new infrastructure project has been announced in China. China requires that this type of infrastructure project be capped at 50% foreign shareholder ownership, so foreign firms like AWS and Apple run data centers through Chinese partners.46 In addition, a data center built with majority Chinese ownership may be recorded under the partner’s name, not the Bay Area firm. This falls in line with its larger Great Firewall strategy intended to retain technological sovereignty. Out of all projects since 2020, the shift is small but worth noting in how firms are responding by moving new projects away from a rival market and toward an allied one.

As with other sections, the greenfield data carries limitations. Counting projects captures frequency but not magnitude—the dataset does not consistently report the size of each investment. Of 2,018 total projects announced, 583 (28.9%) projects carry either jobs or capital invested, 1,435 (71.1%) carry neither, and only 83 (4.1%) carry both. As a result, project counts are used throughout this analysis on the understanding that a modest “Sales, Marketing & Support” office is counted identically to a major infrastructure project like a data center.

Tracking new greenfield announcements suggests Bay Area tech firms are hedging. Outbound FDI efforts remain strong, only slightly re-routing away from China and towards India. Western Europe held relatively constant throughout. In absolute terms, the cumulative footprint abroad keeps growing amidst a minor hedge. However, this dataset only tracks announcements of new projects; making conclusions about future fragmentation based on it is limited because it does not accurately cover how many are completed, the jobs they create, or the money invested.

Wow, you are special. Last to come will be a concluding chapter, synthesizing conclusions from the numbers today (Volume II) and historical stories told thus far (Volume I).

Thank you,

Max

AI Disclaimer: Claude serves as my research assistant with a strict ~20 rule markdown that I continue to iterate on where I think it reduces the friction of research, without ceding cognitive sovereignty over my ability to form original thoughts and learn. It built and ran data pipelines → rendered charts → verified sources → and formatted citations. | The line is drawn at arguments and prose. Where Claude writes a note, it says so. I am not perfect and will continue to improve. I want the stakes to be higher. |

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Every device and app takes a dual-use today. They all help us with everyday life, but the tools, infrastructure, and companies also defend world peace in Washington’s vision. I think about “upholding peace” as the act of preventing war. So what role do I—as user and voter—play? For centuries, governments work with private institutions to secure life for their people. From bowyers and blacksmiths to oil companies today, governments must control technologies with violent ends…1 in practice, doing so requires cooperating with—not commanding—actors motivated to grow, profit, and change the status quo.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

Thank you all for the continued support and feedback ahead of formal publication for the Bay Area Council Economic Institute. Let me know what you’d like to learn more about. Idea-market fit baby!

Flashpoints can fragment technology flows. When states inevitably clash, Bay Area companies are thrust into the middle of conflicts thanks to controlling the infrastructure, platforms, and products across borders and sectors. This chapter discusses four flashpoints entangling Bay Area technology companies today:

Flashpoints Could Spiral World Trade

Flashpoints like wars and economic competition lead world leaders into worrying about independent survival. When protecting industries, raising import barriers can self-fulfill fears into eroding peace. Governments that pursue these policies of “autarky”—self-sufficiency, often at the cost of integration—isolate themselves, do not grow together, can end up directly competing, and even increase the chances of war. Look to the 1930s; after the world backslid into depression, tariff barriers rose, protectionism and reindustrialization rose—all making it easier for Europe to rearm itself leading up to World War II.

Today, leaders allude to flashpoints fragmenting world trade into a similar spiral. IMF Managing Director Kristalina Georgieva warned in January 2023, “we are facing the specter of a new Cold War that could see the world fragment into rival economic blocs.”2

But allowing economic competition prevents harsher military conflict. In an interview this summer at Stanford University, Edward Fishman, a former U.S. sanctions official and author of Chokepoints, reflected on the current moment of economic competition as a necessary pressure valve to avoid worse hot conflict.

Fishman’s time in the Treasury Department led him to navigate various cases of conflict with private companies, including Iran and the JCPOA, Putin’s modern imperialism, and China’s desire to lead the technological frontier. From these experiences, he concludes in Chokepoints, “during the Cold War, geopolitical competition reigned supreme. Each bloc enjoyed a degree of economic security because it renounced interdependence with the enemy.” Today, the picture looks a lot different, “without the ability to channel geopolitical conflict into the economic arena, great powers could once again find themselves fighting on the actual battlefield.”3

Flashpoints Entangle Technology Companies

Embedded into life worldwide, technology companies cannot avoid playing geopolitics. Executives need to grasp foreign policy just as the statesmen they sit across from need to understand markets.

Cooperating and Competing in China

China’s rise created a tightrope for Bay Area technology companies to walk. The Bay Area cluster cooperates and competes with various sectors overseas. China boasts several clusters that Bay Area technology companies outsource parts of their lower-profit manufacturing to. But rising up the value-chain has also stoked flames of direct competition.

Washington views China’s civilian market—which produces consumer goods like the iPhone—and its military markets—that create advanced weapons systems—as inseparable thanks to the Chinese Communist Party’s Military-Civil Fusion Policy.4 This doctrine gives Beijing sweeping authority to direct its domestic industries toward advancing the People’s Liberation Army’s capabilities.

China’s largest competitive strength arises from leveraging commoditized layers at scale into creating champions in high-technology sectors. For example, China’s EV industry is the best in the world and grew out of its battery and electrification efforts. Today it produces the bulk of the world’s EVs, including more than half of all Teslas, built in Shanghai.56 Founded in San Carlos, the company retains a heavy operational presence in the Bay Area despite moving its headquarters to Austin.7 China’s own homegrown champions command the world’s market outside the US.8 In the first eight months of 2025, the top five Chinese automakers made up 43% of all global electric vehicle deliveries.9

EV competitiveness rests on driving the cost of batteries down. Chinese firms produce about 80% of the world’s batteries; the Carnegie Endowment projects that by 2030 China “alone could produce the entire global demand for batteries… and has begun to weaponize its strength across battery supply chains.”10

As tensions rise, headlines suggest device companies are diversifying their factories into neighboring hubs like India. Supply chain watchers point to Apple’s recent factory buildout in Chennai as “physical proof” that India is on its way to becoming a credible manufacturing rival to China for the iPhone.11

Most pressing of all today lies the AI competition in the chip and model layers. According to historian Chris Miller in Chip War, “the rivalry between the United States and China may well be determined by computing power.”12

The competition for leading chip design disrupts Bay Area chipmakers and the hardware companies too. As compliance checks work to prevent products from reaching sanctioned buyers, governments have moved to curb illegal transshipment of critical technologies. In July 2026, NVIDIA excluded more than half of its previously authorized Asian customers from purchasing AI chips after creating a new “whitelist” system.13 Concerns of chip smuggling continue to rise.

Striking Iran

Bay Area technology continues to be used by US defense operations today. In February 2026, Bay Area technology companies helped strike Iranian targets at the outset of the war. Advances in AI-enabled data ingestion reportedly played a role in American strikes on Iran, with one account crediting Anthropic’s Claude model with supporting the identification of over 1,000 targets within 24 hours for “intelligence assessments, target identification and simulating battle scenarios.”1415

Project Maven is a defense innovation that compresses operational planning. It relies on frontier AI models to process billions of collected data points—human reporting, digital communications, satellite imagery, and open-source streams—to speed up kinetic decisions.

In March 2026, Iran’s Islamic Revolutionary Guard Corps responded and threatened 18 companies operating in the Middle East, including American tech and defense companies Apple, Boeing, Cisco, Dell, Google, HP, IBM, Intel, Meta, Microsoft, Nvidia, Oracle, Palantir, and Tesla.16 Hyperscaler data centers have become combat targets. Since March 2026, Iranian Shahed drones have reportedly struck or damaged data centers owned by Amazon and Oracle in the UAE and Bahrain.17

Underpinning Ukraine

In Ukraine, several Bay Area technology companies support the resistance today because they were drawn into the conflict due to their presence prior to invasion. More than 305,000 IT specialists and 2,200 active companies operate in Ukraine— many of which partner with Bay Area technology companies across the IT stack.18

For example, Alphabet had built its first research and development center in Kyiv in January 2020.19 Since the war’s outbreak, Russia escalated its dispute with Alphabet, throttling services like YouTube and imposing a fine on the company—one that, through weekly compounding, has grown to a figure notionally exceeding world GDP—for blocking pro-Kremlin and state-aligned media.20

And Cisco reportedly collaborated with the US government to modify a hardened wired network switch that helped Ukrainian infrastructure maintain accurate time synchronization despite Russian GPS-jamming.21

Navigating European Regulation

Several European initiatives are seeking to regain technological sovereignty as the great powers of the United States and China compete ahead of them on the frontier. Supporting emerging technology leadership is a constant talking point at Davos, G20, G7, and industry summits.22 The underlying reality is troubling: Europe’s share of global AI infrastructure is projected to barely exceed 5% by 2031.23 Founders are frustrated with the regulatory environment and pursue clusters more friendly to innovation, including the Bay Area.

In response, this August, the newly established Rhine Group, a consortium of European leaders from “government, academia, and business,” convened to “discuss possible answers to these challenges for the future of Europe.” This group’s own assessment is blunt: of the fifty largest technology companies in the world, only four are European, and “in every emerging technology that will shape the coming decades, Europe is weak.”24

Future Fragmentation in Chips, Telecom, and AI

Several future technologies could fragment along rival economic blocs: the entire chip layer, telecom infrastructure, and artificial intelligence are but a few. Today, export controls on semiconductors produced on Western supply chains continue to keep China behind the frontier, but does this spur indigenization? Time suggests so.25

And as the next mobile internet standard, 6G, emerges, doubts exist over whether Western and Chinese vendors—increasingly competing for high-tech market share—can converge on a single joint standard.26 In such a future, an iPhone sold in the United States might be unable to connect to network infrastructure built by Huawei. The mobile internet may very well split into two and premium dual-connectivity devices could arise.

Finally, the AI race between open-source Chinese and closed-source American models has raised new policy questions over whether AI models can be chokepoints to control like prior frontier technologies. Attempts to restrict models—preventing American businesses from running on Chinese models—are fickle.27 AI usage is fragmenting into a dual market split between the premium leading labs of the United States and the “Hundred Model War” of open-source rivalry in China.28 In July, a CNBC report found that the share of enterprise tokens used on Chinese models through OpenRouter, which lets developers access different models, has sat above 30% since February and risen to as high as 46%.29 Those chokepoints cannot exist in a commoditizing market that China is driving; the easy access to open models—good enough with plenty of alternatives— denies Washington a new tool for coercion.

A Coming Tech Cold War?

Geopolitics disrupting global trade affects where and how high-technology flows. Cybersecurity experts and executives Ansgar Baums and Nicholas Butts consider a future where the global IT stack separates into Western and Chinese stacks over the next decade. This would heighten the risk of brinkmanship, lock entire industries from collaborating, and could even divide the global internet into two. Baums and Butts lay out this coming struggle in detail but spend comparatively little time surveying the current economic state of the companies caught in the middle—a gap the quantitative analysis in this report aims to fill.30

The next chapter questions measures the impact of this fragmentation on the commercial activity of Bay Area technology companies.

See you tomorrow,

Max

Obviously, I’m talking about today’s chapter in “Bay Area Abroad: Innovation through Fragmentation”. Over the last two decades, China managed to rise into the world’s second most powerful economy and now fragments technology flows. Today’s post traces when the new Bay Area technology failed to integrate into China.

Telling this story can cut a million different ways. What lessons arise from this reading?

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

If the United States and China end up at war, history will highlight a speech from President Clinton that’s forgotten today.1 On March 9, 2000, President Clinton may have delivered a case of fleeting optimism.

We know how much the Internet has changed America, and we are already an open society. Imagine how much it could change China. Now, there’s no question China has been trying to crack down on the Internet — good luck. That’s sort of like trying to nail Jello to the wall. — President Clinton, March 8, 20002

Clinton’s words were emblematic of a wider belief at the time. The trade of technology could liberalize China’s economy and politics. That failed.

A Wave of Liberal Innovations

Over the past two decades, Bay Area innovations arrived in the world that extended liberal values.3 Personal computers, smartphones, and social media leveraged the open internet to empower users. To web a new digital world with the real economy, computing power revolutionized: cloud hosting lowered the cost of running tasks online at scale; transistor design went nanoscopic, making mobile devices that matched the power of old supercomputers; and machine learning algorithms began guiding decisions in real time.

A sense of common optimism united these Bay Area technologists with policymakers in Washington. Innovators in California believed they were creating a future “digital utopia,” where the benefits of new innovations would decentralize power away from these institutions built for the Cold War.45 Globalists in Washington worked to ease American companies’ access to foreign economies through bodies like the World Trade Organization (WTO), whose trade rounds increased imports and exports through mutually lowering trade restrictions.

A Shared Optimism for China

That shared sense of optimism extended into reforming China. Policymakers hoped trade would bring economic and political changes to the rising power. Since 1978 reforms, China’s economy grew by more than 9% a year on average, lifting almost 800 million people out of extreme poverty.6 Decades of protectionist policies and subsidies aided its centrally planned growth. The CCP was long criticized for rejecting democratic norms. Washington wanted China to deepen its trade ties worldwide and become a so-called “responsible stakeholder” of the global world order.7

Bay Area technology companies saw a cheap labor base to grow their margins and over a billion users coming online. The ambition was clear: could a huge economy—with a tremendous potential base for manufacturing and users—integrate in the world’s technology stack and world order moreover… when its government did not uphold the same values of a system built by the democratic West?

That’s what the Clinton administration thought:

“When China joins the WTO, by 2005, it will eliminate tariffs on information technology products, making the tools of communication even cheaper, better, and more widely available.” — President Clinton, March 8, 20008

Bringing Technology Trade to China

When China agreed to join the WTO in 2001, it took on a commitment to lower the barriers of technology trade through a series of longstanding agreements known as the Information Technology Agreement (ITA).9

Beginning in 1996, the ITA lowered tariffs over computers, telecommunication equipment, semiconductors, including its manufacturing and testing equipment, software, scientific instruments, as well as most of the parts and accessories of these products.10 The ITA made it easier for Bay Area technology to be manufactured in China, then exported out of it. 11

China is commonly called “the workshop of the world”. It might more sharply be called “the foreign-owned workshop of the world”. China’s rise has benefited US [transnational corporations] by keeping their production costs lower while also being an increasingly important consumer market as China’s middle class has expanded. — Sean Kenji Starrs and Robert Hunter Wade, “No End in Sight for Global Capitalism,” May 202612

Bay Area firms lowered production costs by shifting supply chains along the Chinese coastline and into the mainland, reinforcing their ties across the Pacific as a key linkage in lowering the cost of physical exports.13

China Started as a Supplier, Not a Buyer

Over the 2000s, China presented a regional opportunity as a factory for Bay Area technology companies. The strategy was to capture more profit by retaining high-value work like design while outsourcing the lower-value work to China. Ties grew even as consumer demand for connectivity remained low.

Cisco Systems provides an example of this mutually beneficial relationship. Beginning in the 1990s and into the new millennium, the networking company out of San Jose built routers, switches, and software to ease information sharing.14

Cisco’s sales stayed low in the Asia Pacific region; they did not follow the shift in supply chains to China. In October 1998, Cisco announced that China Telecom selected it as the “strategic supplier of the countrywide backbones for ChinaNet and the China Multimedia Service Network.”15 The contract was small—$11 million, just 13% of ChinaNet’s revenue—because China’s entire user base was also small, at roughly 600,000 users.16

In the ensuing decade, the internet did not diffuse into the Asia Pacific like it would in advanced Western economies; for in 2007, the Asia Pacific region, including the major markets of China, India, Korea, and Australia, composed only 10.2% of Cisco’s net sales.17

Sales may have been small, but China played a significant role in Cisco connecting the rest of the world; the company would contract China-based manufacturers rather than owned factories for assembling and testing circuit boards and repairs.18

“In the past five years, Cisco has purchased more than USD $7 billion worth of China-sourced components and services, a critical part of the company's virtual manufacturing supply chain.” — Cisco Systems, November 1, 2007 19

Cisco is one example of a Bay Area technology company benefiting alongside Chinese manufacturing firms. More broadly, the ITA helped fuel this kind of bilateral growth. One study finds the ITA helped push world exports from $549 billion in 1996 to $1.65 trillion by 2015.20 By 2015, China had become the largest importer of ITA products, accounting for 22.5 percent of all global ITA imports.21 China absorbed components, equipment, and inputs that fed its growing role in the global electronics supply chain, rather than displacing Bay Area firms… for now.

China Plays by Different Rules

When foreign economies trade, the best practices of their companies naturally diffuse. The same occurred over technology flows between China and the Bay Area. By chasing cheaper margins, technology transfer inevitably happened.22 As Sean Starrs notes, China’s “world share of manufacturing” grew “from 8.6% in 2004 to 28.8% in 2023,” a shift that by the 2010s extended beyond “cheap manufactured goods” to “higher-value technologies such as electric vehicles, smartphones, social media and solar panels.”23

Over this period, China would grow into the United States’ largest trading partner, surpassing Japan in 2003, Mexico in 2006, and Canada in 2015.24 By 2013, China had overtaken Japan as the world’s second-largest IT sector—$179 billion in spending to Japan’s $173 billion—though it remained barely a third the size of the United States’ $686 billion.25

Was China playing by the rules? In 2006, the WTO Secretariat confirmed in a speech that “ITA tariff lines” were “zero rated.”26 But in practice, the picture looked different. Across multiple sectors, trade officials in the United States believed that much of China’s free-trade commitments were hollow, in large part because China continued its model of state-sponsored capitalism through subsidies rather than liberalizing its economy.27

In the case of integrated circuits, for example, a zero-rated tariff did not mean equal treatment between Chinese and foreign firms: China refunded domestic producers most of the 17% value-added tax on their sales, effectively subsidizing their own products. It took the first WTO complaint the United States ever levied against China, in March 2004, to end the practice.28

Holding the Line

And as physical infrastructure helped mature the open internet, a boom of software-based business models followed. Over the 2000s, “dot-com” companies were asset light, could scale quickly, and offered online ways to digitize information, solve problems, and conduct business, largely in e-commerce and digital services.29 From 1995 to 2002, optimistic investment fueled hundreds of internet-based companies.30

This “dot-com” boom built familiar Bay Area champions in social media and cloud computing. Venture capital flowed into ambitious product ideas, massive ad campaigns, ornate corporate offices, and handsome employee bonuses. And then, the bubble exploded.

Some software startups that survived the dotcom bubble managed to scale into global enterprises. Facebook is one example: the social media platform began in a 2004 Cambridge dorm before quickly moving to Palo Alto. It scaled its user base worldwide, and today Meta’s entire family of apps—including Facebook, WhatsApp, and Instagram—connects more than three and a half billion daily active people.31 Google is another: the company began in 1995 at Stanford University with the mission “to organize the world’s information and make it universally accessible and useful.”32

Alphabet, its parent company today, operates through two main business segments, Services and Cloud, reaching users nearly everywhere on the globe by disseminating ads, developing the Android operating system, hosting YouTube videos, cloud computing and storage infrastructure, and more.33 Today, roughly 90% of all online searches are made on Google.34

Meanwhile, China was scaling its IT sector at home to compete with Bay Area technology counterparts. The Chinese state built “the Great Firewall” to censor its digital ecosystem and clear the field of Bay Area firms:35 as Dan Wang observes in Breakneck, “the state drove out Google and Facebook to the benefit of local platforms like Baidu and Tencent.”36 Throughout the 2010s, China founded at-home alternatives to Bay Area companies: Alibaba for eBay and Amazon;3738 Didi for Uber;39 Meituan for food delivery;40 and Ant’s Alipay for PayPal.41

In networking equipment, the competition ran deeper still: Huawei, founded in 1987, spent decades growing from a domestic supplier into Cisco’s chief global rival, and by the 2010s had surpassed Bay Area and other Western firms in telecom infrastructure markets worldwide.42

Hopes Dashed

Like Japan, China embraced a techno-nationalist strategy by setting lofty development goals.43 To achieve this, the Chinese state picked state champions and offered competitive alternatives to American firms.44 But unlike Japan, China did so without liberalizing its economy or adopting democracy.

Today, many of China’s sectors surpass or directly compete with their American counterparts, dashing hopes of a unified liberal world order and digital utopia.45

This concludes Volume I that of historical chapters. Up next, Volume II begins: Today’s fragmented world.

Have a great weekend everyone,

Max

Today’s happy little chapter of “Bay Area Abroad: Innovation through Fragmentation” happens to cover a peaceful period of little fragmentation: in the 1990s and into the new millennium, the United States sat atop the global world order alone. Washington had no rivals to police technology flows and the Bay Area benefited. Manufacturing and talent globalized.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

Help is always appreciated—anyone here remember the 90s? What’s missing in this story?

When the Berlin Wall fell in 1989 and the Soviet Union dissolved in 1991, the United States stood alone atop the world order. Bay Area innovations could flow worldwide with unprecedented ease. New technology, immigrant talent, and investment faced little resistance in crossing borders. Manufacturing and talent spliced into regions where advantages lie—it all added up to globalization in the absence of fragmentation.

Washington Gets Out of the Way

When this Administration came into office, certain basic personal computers, such as IBM PCs and Apple McIntoshes [sic], were still being controlled. Last September, we took the first step to liberalize licensing requirements for over $30 billion worth of computer exports. — Office of the Press Secretary, President Clinton White House, March 30, 19941

Fragmenting technology flows along Cold War lines made little sense now that it was over. Washington got out of the way by easing restrictions on exports. This included the innovations at the time: personal computers, consumer electronics, and the commercial internet all rapidly globalized. Access to the frontier was less expensive. The customers of earlier waves were mostly governments and corporations; now ordinary people were exposed to what the frontier felt like.

The internet had defense origins that went global to civilian markets. In Menlo Park, the Stanford Research Institute (SRI), funded by the Pentagon, hosted the second computer on ARPANET, the network that would open up and become the internet.2

By the 1990s, ARPANET was discontinued and a network of open nodes emerged that would become the early internet. Private companies like AT&T and Cisco Systems led the buildout.3 Digital fiber-optic cabling and the networking equipment allowed communication to flow at the speed of light, eased global investing and lowered the barriers of trade friction.

The White House eased the restrictions on these civilian technologies, many of which had parts previously deemed strategically sensitive. On March 30, 1994, the Press Secretary announced the end of CoCom: “the end of the Cold War and the disintegration of the Soviet Union and the Warsaw Pact led us and our allies to the view that COCOM’s strategic rationale was no longer tenable.”4

Facing fewer restrictions, high-technology exports from the United States rose. U.S. exports of advanced technology products rose from $94.7 billion in 1990 to $227.4 billion in 2000, a 140 percent increase.5

Commerce Secretary Ron Brown testified to Congress in January 1995 on the Clinton administration’s liberalizing policies to promote innovation: “freeing $32 billion in exports by reducing controls on U.S. computer and telecommunications products.”6 Exports rose as high-technology manufacturing and talent spread across borders into new markets where regional advantages lie.7

Manufacturing Goes Global

Over the 1990s and 2000s, the manufacturing chains that exist today began to take shape. The triangle of economic relationships linking Taiwan, the People’s Republic of China (PRC), and Bay Area firms developed, giving rise to the value chains that ultimately built consumer electronics.8 Along coastal China, decades of small-scale investment, primarily from Hong Kong and Taiwan, had built up a manufacturing base for labor-intensive goods. That base let the region take on low-cost consumer electronics like laptops.

Hewlett-Packard’s laptops demonstrate the division of work in this triangle. Proprietary specifications for the notebooks arose out of the Palo Alto headquarters, but HP relied on Taiwanese manufacturers, like Quanta and Compal, to flesh out the mechanical, electrical, and software designs.9 Intel supplied the processors and chipsets in this era, mostly made in its own U.S. factories.10 China took over with final assembly, mostly by Taiwanese contract manufacturers.11

Into the latter half of the 2000s, supply chains would only grow in complexity. Apple began taking full advantage of supply chains going worldwide. In earlier iPhones, “Designed by Apple in California, Assembled in China” was etched in the back, but manufacturing involved many more countries even then.12 A 2009 iPhone 3G teardown revealed nine companies spread across China, South Korea, Japan, Germany, and the US, with all components sent to a Foxconn facility in Shenzhen for final assembly.13 Looking today, the trend has continued: a 2025 Financial Times teardown found iPhones have grown even more complex, drawing on 187 suppliers across 28 countries.14

Immigrants Arrive in the Bay Area

Supply chains were only part of the story; firms brought more overseas talent into the Bay Area than ever before. As companies globalized, an insatiable demand for the best minds grew that the American pipeline alone could not meet.

Educated Asian scientists and engineers moved to the Bay Area. By 2000, more foreign-born scientists and engineers lived in Santa Clara County than native-born. In 1990, Dr. AnnaLee Saxenian found that one-third of scientists and engineers working in Santa Clara were born overseas, almost two-thirds of whom were Asian.15 I extended the analysis below with the same census data, finding the foreign-born share of the region’s scientists and engineers rose significantly, from 29 percent in 1990 to 53 percent in 2000, overtaking native-born workers.16

Not only were more immigrants moving to work in tech companies, but they also began to run more of them. As the Brookings Institution reports, “By the end of the 1990s, Chinese and Indian engineers were running 29 percent of Silicon Valley’s technology businesses. By 2000, these companies collectively accounted for more than $19.5 billion in sales and 72,839 jobs.”17

Duke and UC Berkeley researchers found the pattern held for new companies too: over half (52.4%) of Silicon Valley startups founded between 1995 and 2005 had at least one immigrant as a key founder, well above the California average of 38.8%.1819 The trend largely holds today: one 2026 study estimates that “70% of the Bay Area’s unicorn companies have an immigrant founder.”20

Clusters Abroad Benefit

The increase in high-skilled technology talent that flowed into the Bay Area led to a “brain circulation” that increasingly benefited both sides, rather than draining one direction only. For example, engineering talent grew as some immigrants chose to stay in or return to China, India, and Taiwan.21

Taiwanese immigrant Miin Wu earned a PhD in electrical engineering from Stanford University in 1976, then worked for more than a decade across Bay Area semiconductor companies. Eventually the Taiwanese economy improved, and he started one of Taiwan’s first semiconductor companies in 1989, Macronix Co. Going public on the Taiwan stock exchange in 1995, the firm regularly recruited Bay Area managers and invested in startups by the early 2000s.22

These mutual flows planted new seeds of shared trust, ideas, people, and technology—unique clusters of innovation began emerging worldwide.23 To this day, local producers remain in their home countries but stay connected to immigrant entrepreneurs in the Bay Area. Both sides own companies that span the value chain for products used today.

Manufacturing and talent moved with newfound fluidity, but fragmentation would not be gone forever… China would soon emerge as a new competitor.

Thank you for being here,

Max

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Writing "Bay Area Abroad: Innovation through Fragmentation" in San Francisco made it easy to drink the Kool-Aid: the Bay was always the world's core for new tech—an assumption that explains its centrality in recent geopolitics. But, thinking this misses an important part of the economy's story: this chapter covers how Japan's miraculous growth spilled over into challenging the Bay Area's lead in chip innovation by the 1980s.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

Your feedback on these prior chapters has been so helpful. Ahead of formal print at BACEI, help me sound somewhat coherent. I’m one text message away.

As rivalry with the Soviet Union grew, the United States sought to help its allied economies across Europe and Asia recover. Among them, the Japanese government managed its economy’s recovery so well—thanks to generous aid, loans, and protectionist policies—that an ecosystem of corporations emerged by the 1970s capable of worldwide competition; the Bay Area was not immune and lost the lead on the frontier in new semiconductors.

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This chapter observes a different way of fragmentation arising. In the 1980s, foreign companies had benefitted from their own government’s assistance that it impeded Bay Area technology companies’ claim to the civilian market share of the frontier. Earlier, the Cold War prompted Washington to fuel fragmentation. Here, cooperation with Japan for decades inadvertently led to fostering competition. But Tokyo rebuilt its civilian-only economy in a way that lacked the same flexibility of the Bay Area engine.

Starting from a postwar pile of rubble in a nation almost devoid of raw materials, Japan’s businessmen have built an economic superpower. Today it is flooding markets from Manila to Milwaukee with shoes, ships and steel, cameras, cable, cloth and cars, transformers, TV sets, tape recorders and, of course, the ubiquitous transistor radios. To many admiring but fretful Westerners, Japan has become a corporate state, and is even referred to as “Japan, Inc.” - TIME, May 10, 1971, Business: Japan, Inc.: Winning the Most Important Battle1

Japan Manages a Miracle

Three decades of rapid growth characterized Japan’s “economic miracle” by exporting more and more valuable goods overseas. Japan began by building a manufacturing base of raw inputs into exporting more expensive goods. By the 1970s, Japanese goods were flooding markets worldwide. During the 1980s, the fear drew a response from leading Bay Area technology companies to counter Japan’s rise.

During the 1950s, Japan initially relied on protectionist policies and tariffs. Out of World War II, Japan depended on grant aid and favorable trade policies to help regrow its decimated economy.2 The government enacted democratic reforms but kept the reins over its economy; known as keisha seisan hōshik, “priority production policy” was a series of managed reforms that directed entire jobless communities and capital into coal and steel, and iron production. These reforms provided the base to moving into explosive growth in exporting shipbuilding and electric power.34

Demand for Japanese goods in recovering allied civilian markets—coupled with the US governments appetite for industrial exports out of Korean war—drove growth. By the early 1960s, the Japanese economy allowed more investment to fuel more capital-intensive industries in tools, motor vehicles, and electronic devices to fuel its economy. Tokyo’s exports grew 18.4% per year on average over the 1960s and its gross domestic product at an average of 10.5%.56

keiretsu: Japan Comes to Compete

How did Japan manage to build a mature economy capable of capturing valuable demand overseas? As industries matured, a dense network of corporations and private banks in a model known as keiretsu, “group” in Japanese, arose to produce complex products.

The earlier policies that concentrated talent and capital into heavy industry provided the conditions for these new groups; a new alliance of large, diversified corporate groups webbed supply chains across industries.78

Such incredible growth under keiretsu over the 1960s inevitably captured market share from competing companies. By 1970, trade ministers worldwide were feeling pressure from their own companies to raise import quotas.9 As Japanese textiles, shoes, autos, and electronics flooded American markets, Tokyo reported its first net US trade surplus in 1965.10 By 1971, Americans were importing 30% of all Japanese exports.11

Since [1964], the popularity of Sony TVs, Nikon cameras, Panasonic radios, Toyota and Datsun cars, and Honda and Yamaha motorbikes has turned the picture upside down. - Time Magazine, 197112

The Center Shifts

Japan didn’t out-innovate the Bay Area, but rather out-manufactured companies to capture market share. DRAM semiconductors were an innovation whose products would commoditize showing little differentiation, low prices and margins, high reliability, and easy replication.

Japan wielded the momentum of its managed economy of keiretsu into the semiconductor industry, even as the original chip designs arose in America. The Japanese government funded keiretsu groups NEC, Toshiba, and Hitachi with lab funding to kickstart their own R&D to improve manufacturing. This would come to lead the semiconductor market for production.13

The idea, first designs, and patents for DRAM originated out of New York’s IBM between 1966 to 1968.14 Silicon Valley stayed true to its name. Soon, Mountain View-based Intel partnered to commercialize the first DRAM chip in 1970.15 The designs would end up in the main memory of mainframe computers around the world.16

As global demand for DRAM increased over the 1970s, Japanese chipmakers were improving and managed to strike licensing deals with Bay Area firms, like Intel and Fairchild, to manufacture their designs.17 Labor was cheaper and reliability was good enough in a commodity market. Japan grew its DRAM chip industry originally thanks to American chip firms licensing frontier technology.18Though semiconductor manufacturing equipment was a small portion of Japan’s overall GDP, the country invested heavily in R&D to improve it, rising from two percent of the sector’s R&D spending at the start of the 1970s to 26 percent by 1977.19

That investment paid off: by one estimate, keiretsu fueled Japanese firms into successfully controlling 76 percent of the global DRAM market by sales. Per one US federal interagency estimate, the United States lost its lead to Japan in over 75 percent of critical semiconductor technology between 1980 to 1987.20 Soon, executives and policymakers in America were raising alarm bells.

The Japanese are still fighting the war, only now instead of a shooting war it is an economic war. Their immediate intention is to try to dominate the Pacific and then perhaps the world.” - Secretary of Commerce Maurice Stans, 197121

The Bay Area lost ground in the supply chains for critical technologies at the time. As Japan’s market share grew, firms invoked national security concerns to press their case in Washington. Bay Area chipmakers Fairchild, National Semiconductor, and Intel went to Washington and asked lobbyists to broker domestic and foreign policy responses.

The Semiconductor Industry Association produced both SEMATECH—a joint industry-government research consortium—and a Ministry of International Trade and Industry (MITI)-negotiated agreement that guaranteed US suppliers “20 percent of the Japanese market for semiconductors”.22 The United States invoked policies of its own, boosted domestic manufacturing, and sharing the lead in chip demand with 43% of new global semiconductor sales against Japan’s 40% by 1993.23

“’We’re at war with Japan,’ Sporck insisted. ‘Not with guns and ammunition, but an economic war with technology, productivity, and quality.’” — National Semiconductor CEO Charlie Sprock in interview with Chris Miller24

New Arenas Above Chips

In the battle over the global chip manufacturing markets, Japanese firms captured a leading sector, but their failure to originate the next wave of innovation suggests they won the battle without winning the longer war as the world’s cluster of innovation.

Technology flows can fragment when innovations turn into indistinguishable commodities. If products made by several firms are good enough, their competitiveness compounds under state-sponsored capitalism in global free markets.

But a confluence of factors left Japan struggling to remain the center of development in the coming technological wave. In many ways, the keiretsu system stood in contrast to the characteristics at the core of the Bay Area’s cluster; picking favorites undermines the dynamism needed to innovate the new frontier. Great companies rise and must be able to fall. Japan’s most talented youth pursued high-status roles in government and large corporations rather than entrepreneurship. Policies favoring those same corporations left smaller, less visible firms with little institutional support.25

As the hardware layer of semiconductor commoditized, Bay Area startups began innovating a new wave that uses them: personal computers, microprocessors, workstations, and networking all rested on DRAM.262728

Something new was swelling in Cupertino.

In 1976, computer hobbyist Steve Wozniak built a user-friendly desktop computer containing 4 kilobytes of DRAM. It attracted the interest of Wozniak’s friend, Steve Jobs, and inspired them to start Apple Computer. Within a year, Wozniak had created the Apple II, improving upon his initial design by adding a faster microprocessor and more DRAM. The Apple II was the first commercially successful desktop computer built with DRAM. By 1984, sales of the Apple II reached 2 million. — “DRAM” IBM Heritage29

Japan’s wider economic challenge to the United States was fading by the time the next frontier emerged. Japanese companies continued to dominate DRAM, but demand shifted towards a more differentiated market of personal computing and connectivity in the 1990s.

Up next, an unbridled Bay Area in the personal computing wave of the 1990s.

Have a great week,

Max

Today’s chapter of “Bay Area Abroad: Innovation through Fragmentation” pulls history from the Cold War to show how it fragmented the flow of Bay Area technology. After World War II, competition with Soviet Union fueled Washington into fragmenting technology research in the Bay Area— building companies to advance the space and defense industries while restricting where that technology could go around the world.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

This chapter steps into an ocean of work: generations of careers, millions of words, and entire institutions are devoted to understanding how nation states power R&D to protect themselves. Today touches the surface, briefly highlighting how Bay Area technology flowed during the tense decades after World War II. Let me know where I’m too thin.

These words live online ahead of formal print for BACEI. I need your feedback. What do you see?

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Cold War Fragmentation

Decades of competition with the Soviet Union fragmented Bay Area technology flows in two distinct ways: by funding the industry and controlling exports. The frontier waves of innovation during this period—microwave electronics, semiconductors, missiles, and satellites—would not have been possible without government funds, motivated by the drive to advance the space and defense industries. Exports in this wave were heavily controlled in an early export-control regime known as “CoCom.”

Over this period, the effect of those fragmenting pressures—funding and export controls—slowly eroded. The early Cold War pushed Washington into investing capital that catapulted the Bay Area into emerging as a leader in innovation. But wealthier civilian markets emerged. As communist nations unraveled and allied markets recovered, wealthier consumers drove a new wave of personal computing innovations, sustaining Bay Area innovation.

Federal Dollars Fragment R&D

After World War II, Washington’s relationship with Moscow soured from an alliance of convenience—rooted in defeating the mutual enemy of Hitler’s Germany and the Axis Powers—into open hostility. The United States sought to contain the spread of Soviet Communism by spying, fighting proxy wars, and building a nuclear arsenal—all of which caused Bay Area technology flows to fragment along rival blocs.

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Immediately following World War II, Bay Area technology labs and companies involved in national defense efforts were in their relative infancy, largely a loose network of professors, predocs, and graduate students.1 From 1945 to 1950, Bay Area research was “basic,” as characterized by entrepreneur and historian Steve Blank. Stanford’s Electronic Research Lab focused more on microwave tubes and circuits, and less on wider systems.2

Paranoia about Soviet capabilities always existed, but it consumed the national security state by the late 1940s. On September 9, 1949, CIA Director Roscoe Hillenkoetter handed President Truman a carefully-worded report on “an abnormal radio-active contamination”, hypothesized as “an atomic explosion on the continent of Asia”. Two weeks later, Truman announced to the world that Moscow built the bomb.3

Fears of the Soviet threat exploded and channeled industrial focus to advance the defense and space sectors. For decades, federal R&D funding would guide waves of innovation. During the 1950s, the U.S. government funded nearly two-thirds of American science for the national interest.4

Cold War geopolitics fragmented research labs for dual-use technologies: those capable of both civilian and military application. At Stanford University in early 1950, just months before the outbreak of the Korean War, the Office of Naval Research asked Stanford’s dean of engineering Fred Terman to build a separate “Applied” Electronics Lab, the funding for which roughly doubled the size of the electronics program.56

By 1955, over half of the staff working in the Applied Lab held security clearances.7 One half worked on less-sensitive microwave and electronics; the other experimented with military intelligence and electronic warfare systems, then built prototypes for military labs to evaluate. Working designs went to companies to build in volume.8

The government guided funds into advancing the space and defense industries. Military motivations pushed advances in rocketry in the First Space Race.9 The Soviet launch of Sputnik in October 1957 led Eisenhower to establish the National Aeronautics and Space Administration (NASA) and the Advanced Research Projects Agency (ARPA, later DARPA) the following year. 1011

These research networks spun out the first chip laboratories and companies of “Silicon Valley.” From Stanford’s Industrial Park, William Shockley, a key innovator of the transistor, founded Shockley Semiconductor Laboratory that helped pioneer the chip industry.1213 The semiconductor industry was born.

These researchers commercialized frontier technology to sell to the strong defense industry. In 1957, eight of Shockley’s best engineers broke off to form Fairchild Semiconductor.14 The group would create the first batch of transistors used to build the computer on board the B-70 bomber.15

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The Cold War Fragment Flows

The Cold War also drew physical boundaries around where these innovations could be exported. President Truman’s policy of “containment” extended to policing all trade, especially dual-use goods. By around 1952, all exports to communist nations had nearly disappeared.16

Policymakers in Washington sought to curtail technology exports out of the Bay Area. In 1949, the same year the Soviets tested their nuclear bomb, Washington took steps towards forming an early export control regime: Congress passed the Export Control Act and the Truman administration began the Coordinating Committee for Multilateral Export Controls, shorthanded as “CoCom.”17

What was CoCom in practice? By the 1960s, the “coordinating committee” emerged as an informal gentlemen’s agreement of embargo policies, where fifteen member states mutually agreed to restrict exports. The roster included Japan and all NATO members, except Iceland— USA, Canada, Denmark, Norway, England, France, Belgium, Luxembourg, Holland, Italy, Greece, Turkey, Portugal, and Western Germany.18

Enforcement proved slippery; as a 1987 Heritage Foundation report concluded, “to be sure, Washington would not have to control the re-export of U.S. items from its allies if the allies actually were effectively controlling the re-exports. The problem is that they are not.”19

This early export control regime directed waves of innovation—semiconductors, the first computers and software, early telecommunication networks, metal working machinery, and power-generating equipment—into distinct markets.20

^{Civilian Dollars Replace Federal Dollars}

Trade helped decimated economies recover. As standards of living rose, more civilians could afford more expensive goods and cutting-edge consumer technology from the Bay Area. Over the 1970s, civilian demand began to outstrip government demand.

“By 1980, there was a big shift in where tech innovation was initiated. In the first few decades, US military demand drove innovation, and commercial applications were spun off. After that, commercial demand was the key and the military came to depend on the broad infrastructure of civilian technologies and innovations.”21 – Interview with Michael Mastanduno, Professor at Dartmouth College

One Bay Area firm beneficiary was Hewlett-Packard (HP). Founded in 1939 in a garage in Palo Alto, the hardware company grew to symbolize the region’s hardware roots.

The firm contributed to the World War II effort, employing 200 people and producing radio, radar, and microwave test instruments.22 Successive innovations in semiconductors made the firm a leader in high-technology contracting during the 1960s.

In 1972, HP introduced the world’s first handheld scientific electronic calculator.23 Sales began soaring. HP’s revenue doubled between 1976 and 1979, reaching $2 billion in annual sales.24

As the Cold War tempered in the late 1960s and early 1970s, HP serves as an example of how Bay Area technology firms successfully capitalized on shifting global demand. Civilian spending outgrew federal. That shift shaped the next wave of Bay Area innovation amidst a new rival, a rising Japan.

Up next, the rise of Japan.

Have a good weekend,

Max

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Today’s the second chapter in the “Bay Area Abroad: Innovation through Fragmentation”. It’s a side product emerging from work with the Bay Area Council Economic Institute that’s generously letting me republish ahead of its full release with them.

I try to briefly introduce how, from the ground up, the Bay Area creates technology companies capable of influencing geopolitics. People research new breakthroughs and then build companies that commercialize them worldwide.

Talent + Funding → Commercialization.

The more I interviewed researchers and investors (and read my way into a migraine), the more I felt compelled to write this framing chapter: grounding “theory” about how technology companies from the Bay Area manage to keep appearing in modern history’s grandest stories. If any of this interests you, please don’t hesitate to reach out; I discovered many branches that grow this.

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As always, I need your help. We’ve already found typos and tweaked the name of the report. Keep steering me towards better work. What’s missing? What needs clarifying? Is this all a headache? How about the charts?

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

An Engine of Innovation

The Bay Area economy can be thought of as an engine that powers waves of innovation. This cluster fuses skilled talent with flush funding to successfully commercialize new technology. Unlike other economies, the Bay Area’s unique in that it maintains world-class competitiveness through flexibility.

“The Bay Area has managed to move from semiconductors to operating systems, to smartphones, to social networks, to now space, and then AI, fairly seamlessly… where other hubs rarely are able to go beyond their initial technology.” —Interview with Mehran Gul, Author of The New Geography of Innovation1

Detroit once led in cars and Pittsburgh dominated steelmaking, but not anymore. The Bay Area avoids a similar fate by not resting on one particular technology; instead, it preserves the ability to innovate. As Mehran Gul notes, “Places where scientific breakthroughs are happening are not necessarily the places where those breakthroughs have also been monetized.”2 Global companies continue to emerge out of the Bay Area by successfully commercializing research.

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This engine powers an extraordinary economy. If it were its own country, the nine counties would make it the 18th largest economy in the world by GDP—roughly $1.3 trillion in 2024—on par with wealthy oil states in the Middle East and larger than many developed nations worldwide. Technology companies play a central role: Santa Clara County—home to Apple, Google, NVIDIA, and Meta—generated $506 billion in 2024.3 This strength lies in three key components.

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Talent + Funding → Commercialization

Innovation requires skilled talent. The Bay Area ranks among the best in the world in technology education and research. The University of California (UC) school system and Stanford University consistently land as leaders in global lists. In 2025, UC Berkeley was ranked the #1 Public Research University and #5 Global University per the 2025 Academic Ranking of World Universities. Stanford University has been in second place in global overall rankings for nearly two decades.

For technology research, the Bay Area region leads the United States in patents. In 2024, the region generated 20,761 patents, 14.1% of the US total, and more than the next four US cities combined.4

Funding

The leaps in research emerging from schools and companies would not be possible without flush funding for researchers in academia and investors from the private sector.

In academia, Stanford University in 2025 reported funding over 7,500 externally sponsored awards, with total support revenue of $2.3 billion during the fiscal year; 70% was funded by the federal government.5

Robust venture capital powers the Bay Area’s ability to innovate, but it wasn’t always this way. Since World War II, the Bay Area slowly grew its venture capital industry, overtaking the Cambridge-Boston area as the destination for global technology entrepreneurship.6 By 1995, Silicon Valley’s share of all VC investment was 22.6%, over twice New England’s 9.9% share.7

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A cultural advantage emerged in the Bay Area over east coast clusters. In contrast to the tradition of “the company man”—coupled with California not enforcing non-compete clauses—talent moves more fluidly around the region and sparks breakthroughs across domains. Technologists in the Bay are loyal to the act of innovating new technology rather than their companies.

“I knew people who worked for the minicomputer companies back east, and if you went from one company to another, you were considered a traitor, people shunned, they wouldn’t even talk to you.” —John L. Hennessy, Chairman of the board of directors of Alphabet, in The New Geography of Innovation 8

Skilled researchers innovate with funding— plentiful in the Bay Area. Its investors tolerate high risk and are willing to risk capital on moonshot bets. Today, California has received more than $366 billion in venture capital funding since the beginning of the year; that’s over three times more than the other 49 states combined. Two San Fransisco companies, OpenAI and Anthropic, comprise $217 billion of it.9

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Commercialization

Talent and funding alone do not create companies that play roles in geopolitics. To do so requires successful commercialization: turning a profit, performing above costs, continually researching and developing technology capable of diffusing into markets.

Which part of this engine powers the geopolitical strength of the United States? Answering that question falls outside the scope of this observational report. The debate is active today how innovation underpins geopolitical power. Is it the Bay Area’s ability to innovate first and preserve the edge in leading sectors? Or does US leadership emerge, in-part, from the strength of Bay Area companies thanks to successful diffusion of those inventions?10 Regardless, when the engine makes companies that sell new technologies worldwide, few contest their presence in world affairs.

The rest of this report lives at this level: examining how the Bay Area companies that successfully commercialized new technology shape, and are shaped by, world affairs since the Cold War.

Up next, the Cold War.

Thanks for being here,

Max

Today’s post launches a series into my professional studies that I’m so proud to begin sharing with you. If you’d prefer to jump in and skip the personal preface, scroll past the italics and begin the starting chapter that introduces many more to follow.

Over the coming weeks, I’ll be publishing here to help me cross the finish line of a larger forthcoming report: “The Bay Area Abroad: Innovation through Fragmentation”. This series will observe how the Bay Area’s innovative economy has consistently maintained global relevance since the start of the Cold War.

The more I spoke with insiders—executives, investors, reporters, academics, and technologists—that all see deeply into these companies, the more I learned that the fast headlines invoke hysteria; the speed of daily news forgoes the patience required to let the dust settle and truly evaluate impact: how do these innovations let us live out higher truths? How do these technology companies, likely more powerful than ever, shape our life? There are small, subtle effects with how notifications feed you and me our news—all the way up to Iran bombing the data centers that defend armies. Finishing this report leaves me humbled with more questions than answers.

Brief notes of gratitude. Nothing to follow would be possible without crucial editorial help: Lucy Montgomery’s keen eye, far sharper than mine, culled countless drafts into something hopefully legible; Sean Randolph set the record straight every day thanks to his deep experience living through waves of innovation as a Bay Area diplomat; and I’d like to thank the ears of Ben Vagle—they nearly fell off as he proved an invaluable sounding board to talk through much of the history to follow. A longer, and more professional, acknowledgments section will be written in the final draft.

If you do see whack errors, terrible phrasing, or typos, please tell me. Publishing online here comes with the added advantage to edit after. For better or worse, I am human and no artificial intelligence wrote any words to follow.

Table of Contents: Introduction | How the Bay Area Makes New Tech | The Cold War | Japan | Globalization of the 1990s | China into Today | Today’s Fragmenting Flashpoints | Assessing The Engine & The Exposure | Conclusion

The Bay Area Abroad

Technology companies founded in the Bay Area innovate technology that reaches around the world. Today, Meta hosts a gargantuan digital town square. Over three and a half billion daily active people use its family of apps: messaging on WhatsApp, sharing life updates on Facebook, and posting photos on Instagram.12 One layer deeper, the constant connection rests on a personal computing revolution that first started in Silicon Valley garages; over 2.5 billion Apple devices are now in active use around the world.3 And descending further into critical digital infrastructure, the networking and cloud innovations hosted by Alphabet, Cisco, and Equinix—to name a few—all weave the world together by sending information at the speed of light.4

So deeply embedded in daily life, Bay Area technology companies cannot escape playing various roles in world affairs. During elections, should a social media company police content or do nothing? Where good governance is not a given, what narratives arise online that could turn civil unrest into civil war?567 In the Ukraine war, cloud providers provide the spine for cyberdefense, but then that leaves their employees the target of Russian hackers.8 The supply chains controlled by hardware players uphold trade between the United States and China; as the computing power for AI now serves as the latest measuring stick for great power rivalry, Bay Area chipmakers are seen as chokepoints for policymakers in Washington to control and preserve the lead.910

Ingrained in daily life and thrust into geopolitics, Bay Area technology companies need to navigate their ties to those governments, their economies, and populations. Other reports by the Bay Area Council Economic Institute examine overseas trade, but those focus on direct commercial ties to one economy, including Hong Kong11, Ireland12, India13; this report compares multiple economies over time to uncover insights into how Bay Area companies wield technology to play various roles in geopolitical competition.

Innovation through Fragmentation

To tell this story, this report aligns the major waves of new technology with geopolitical periods.

Innovation: The Supply and Demand for New Technology

Supplying new technology for the world rests on a distinctive engine: a dense, networked cluster of talent—both homegrown and foreign—that researches and commercializes new technologies. Great companies rise and fall, but they keep emerging out of the Bay Area, an economy which doesn’t defend any single technology but manages to innovate new ones.

The demand to innovate rests on global markets: the United States’ large appetite for public spending and a global economy of consumers, institutions, and governments. Geopolitics influence the source. During the Cold War, defense budgets derisked big bets for developing weapons and rockets that drove new inventions. It wasn’t until the 1980s that market restrictions fell and civilian demand outstripped government demand to fund frontier competition in semiconductors with Japan. Since the 1990s, aggressive globalization has obstructed rising national security concerns from entirely fragmenting technology flows. Today’s restrictive trade policies on China still accept interdependence: the Bay Area relies on China for talent, investment, manufacturing, and a large customer base.

Fragmentation: How the Technology Flows

Innovating through different geopolitical periods, a concept naturally emerges of “fragmentation”: a way to evaluate the ease with which Bay Area technology flows throughout markets worldwide amidst governments competing.

At times of cooler tensions, Bay Area technology companies find it easier to trade with various economies. During the 1990s, major networking providers faced less resistance in accessing foreign markets and introduced the networking equipment for the eventual Internet.

But when geopolitical tempers rise, governments restrict trade in many sectors, the world economy risks fragmenting into blocs, and the flow of high-technology follows. The Cold War dried up trade. Today risks the same. China’s rise and sectoral competition in high-technology industries like artificial intelligence, semiconductors, and electric vehicles are all provoking protectionist policies in Washington for the sake of protecting the national interest.

The Report to Follow

This report splits into two volumes.

The Bay Area consistently innovates new waves of technology, builds successful companies off it, and diffuses these advances into daily life and overseas markets—all through various levels of geopolitical competition.

Volume One splits into four chapters of history to trace how the Bay Area’s technology cluster navigates geopolitics from the end of World War II to 2020.

1. First, the Cold War throughout the 1950s drove innovation in the Bay Area to fuel a lead in strategic capabilities for the defense and space sectors.

2. Second, as the Cold War subsided over the 1970s and postwar economies recovered with various protectionist models, Japan arose as a chief competitor with the Bay Area over semiconductors; the United States saw its Bay Area companies lose the crown by falling behind in the frontier “Dynamic Random Access Memory” (DRAM) market.

3. Third, by the late 1980s, the Bay Area found support in Washington to protect its semiconductor firms, re-emerging as the leader in high technology through personal computing, microprocessors, and networking. With the fall of the Berlin Wall in 1989 and the Soviet Union in 1991, the world economy entered a period of unbridled globalization. Bay Area firms faced little direct global competition; they fostered overseas sources of talent and supply chains abroad like never before.

4. Fourth, over the 2000s and 2010s, the optimism of globalization soured as China’s rise into the upper echelon of the world economy brought new sectoral competition through a wave of digital revolutions: maturing internet, social media, and cloud computing. China pursued the same techno-nationalist playbook as Japan in many ways, but it managed to engage in global capitalism without relinquishing domestic control over its economy or adopting democracy. The result dashed the hopes of Washington’s liberal world order and the Bay Area’s digital utopia.

Volume Two splits into two halves to evaluate the current decade. First, the narrative extends the story to today: Since 2020, leaders have been sounding alarms about geopolitics risking the fragmentation of technology flows. Bay Area technology finds itself entangled in unique conflicts: China, Iran, Ukraine, and Europe. The rest of the report tests the narrative with an economic analysis that aggregates metrics of 47 relevant Bay Area technology companies.

Thursday’s chapter will introduce the Bay Area’s Engine of Innovation (Talent, Investment, and Commercialization). This framework will explain the cluster’s staying power to innovate through so many different geopolitical moments.

Thank you for being here,

Max

The smartest people in my life all seem different. They don’t wear the same clothes (though everyone should shower). They don’t share the same fancy degree, nor have they cleared some magical number in their bank account. Well, many make bank, but plenty talk openly about debt… some thug it out paycheck-to-paycheck, vibing out unmotivated by money. Some are fat; others are fit. Many never want to leave Manhattan; a few reject every returning again and flocked to the mountains. They’re not found anywhere in particular. I don’t think they’re in one city nor found along any coast.

But they all share one trait: Intention. Smart people know what they want.

“Limited in his nature, infinite in his desire, man is a fallen god who remembers heaven.” - Alphonse de Lamartine

The smartest people intentionally strike a peaceful compromise in life’s uneasiest tension: they desire for more but find contentment with what’s in front of them. They don’t have everything, nor have they “figured it all out”, but all the same— a calming humility envelopes their hidden horsepower.

“Thus it can be seen that mental health is based on a certain degree of tension, the tension between what one has already achieved and what one still ought to accomplish, or the gap between what one is and what one should become. Such a tension is inherent in the human being and therefore is indispensable to mental well-being. We should not, then, be hesitant about challenging man with a potential meaning for him to fulfill.” - Viktor Frankl, Man’s Search for Meaning

The smartest people in my life wrestle with inescapable desire. That desire fuels a chase to our highest life possible. Maslow offers the framework: at the lowest level, desire begins with needing the basics—food, water, shelter, safety— before climbing to higher desires that demand more intentional thinking.

Being smart means wielding intention. It’s a luxury that I think you have. Not many people get to think first, then act with so much choice: what do I work on? where do I live? who do I love? And it’s all in such a short life. I’m 26 in 2026 and probably gonna die before 2100. I’m blessed to be born now with this much battery life remaining. You guys, we’re floating through space on a rock named "Dirt”, but it’s the comfiest it’s ever been. I’m free of all the stupidest obligations needed to survive in in the Serengeti. I think you’re able to think intentionally. Hey, you’re reading this. That means you inherited that luxurious intentional gene.

On Stupidity

I’m not claiming to be smart. I’m usually pretty stupid because I don’t know what I want.

Smart thinking is rooted in intentionality. When intention slips, stupidity arises. Stupidity emerges from not knowing what you want most. In an hour, day, or week, my stupidity runs wild, between too much restless desire to restful contentment.

The longer I take to decide, the stupider I am. I spiral in a grocery store when there’s a bazillion sticks of butter— genuinely. who. cares. If we eat out together, you’ll notice I don’t bother looking at a menu until it’s my turn to order. After I got accepted into colleges, I couldn’t sleep for weeks, even deliberating in my dreams. Coin flipping didn’t work.

AI makes me stupid. It’s is still in its infancy as a Promethean tool— fire for sure, but I’m the dumbass caveman constantly burning myself. I use it for charts, writing software, all sorts of logistics… but it becomes Minecraft: pure productivity entertainment. I’ll spend hours on Claude on a Saturday to create nothing as I lack intentionality.

Everyone faces constraints to higher living. All the same, dare to imagine.

I know my privileged subscribers: you’re rich, hot, and healthy. Yes, I’m talking to you ;) If intelligence is measured by how intentional we live this life, then I dare you to introspect, imagine, and create the world you want by leveraging whatever privilege it is you possess. That last sentence should not be so dirty and shameful to publish online.

“Imagination is the beginning of creation. You imagine what you desire, you will what you imagine and at last you create what you will.” - George Bernard Shaw

Higher means oblige us to higher ends. What are those “higher ends”? The intentional person makes that decision for themselves. I see it in all the smarter people than me in my life. They have a why that fuels their intentionality. Both the banker on Wall Street, stimming out of their minds 100 hours a week, and the Peace Corps volunteer, sleeping on the floor in a village in the Congo teaching English, throw themselves into their lives. This isn’t happiness. This is misery a lot of the itme— BUT DO THEY LIVE. THEIR EYES LIVE ABALZE WITH VITALITY.

If we have our own why in life, we shall get along with almost any how. - Nietzsche, Twilight of the Idols

Sorry for yelling. In my life, an entrepreneurial ethos conditioned me to believe the best life is the one that offers the most control; intentionality is a prerequisite. I notice I opt for personal freedom to explore places, dive into ideas, and connect with the people in them. Consuming more than creating, I’ve done a disservice to the world in my life not writing more about these experiences.

America fetishizes bootstraps as a symbol of brilliance. By intentionally navigating life, individualism emboldened me with the idea that I, alone, should have the “smarts” to navigate any chaos. How do how I want my career to contribute to the world? I have tried, so many times, letting others make the call about job choices. Hasn’t worked yet. Then there’s the future questions we must confront: should I worry about AI killing us all? I can’t control that. Am I sitting across from my future wife? Well, that’s up to us. No arranged marriage for me, but I do see the logic.

Among all the places I’ve lived, I’ve noticed intentional intelligence is especially valued in the Bay Area, a bizarre culture that blends financial nihilism and techno-utopianism to create an economy of borderline-bullshitting companies that will supposedly change the world, while also letting you escape to the Euro-summer-aristocracy-F1-circuit before you turn 30.

If there are higher ends achieved by intentional thinking, there’s no single one. If it were, then there should be one yard stick of enlightenment: the most popular, the wealthiest, most beautiful, and healthiest? No, it’s not an absolute scale.

I still can’t stop thinking about Rawls’ original position. His political philosophies sought to structure society as “just” and “fair” regardless of where you started. But in this lens today, a Rawlsian “intentional” society would be tinted where everyone’s starting privilege—whether its wealth, beauty, health— can be intentionally leveraged for higher ends to get them what they want, in that tension between restless desire and grateful contentment.

Whether its friends, jobs, a family, I urge you to create worlds that make intentionality easier. Let the fashionable walk the runway. Give the passionate singer time in the studio. Sponsor our competitive athletes to train and win gold. If you want to make a gazillion dollars, let’s tee you up to do it and be a capitalistic savage. Or if you want to spend your life’s battery travelling the world, seeing your children, you probably could! But you won’t be living in the same tax bracket or zip code with whoever that was with 5 houses in the sentence before you. Balance those desires with contentment.

"Your blessing in life is when you find the torture you're comfortable with, and you'll do well." - Jerry Seinfield

The “smartest” manage to pick their poison, a Sisyphean pursuit that never stops torturing them.

Here’s to many more, thanks for being here, I’m going to keep trying, writing remains a big boulder, I love this, have a good weekend,

Max

Brief Update to the Newsletter

In that theme of being intentional, I am rebranding this newsletter to long form essays. Grand Technologies sunsets below the email banner and personal long form essays—hopefully titled ”Max Bessler”, like today— dawns in its place.

I’m trying to be smart here… This Substack provided a great platform to host earlier writing samples, but I now have better outlets to publish professional pieces, which will be republished here.

My writing soared this summer. I tried to hit 500-1000 words a day. They flowed into several streams: a personal life on iMessage; work has me in Word writing memos on industry and technology developments; an X account to push my voice and make sense of the news; entering grad school will soon torture professors and peers; and… I want this Substack to stay true to commentary.

Reach out if you want to collaborate and attach your name to something embarrassing.

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The Obligation to Beauty - A fantastic essay on the concept of how “higher means oblige us to higher ends”. I think more of us are aristocratic than we realize. I use that term loosely.

“Wealth consists not in having great possessions, but in having few wants.” - Epictetus

99% Derisible

There will only be four jobs

There are only four jobs…

Read more

7 months ago · 204 likes · 16 comments · Yoni Rechtman

“People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I’m actually as proud of the things we haven’t done as the things I have done. Innovation is saying no to 1,000 things.” - Steve Jobs

I don’t think the answer is being a neurotic, type-A, optimizer. In fact, the optimizers may maximize their time out of fear they don’t have enough of it— because they’re not being intentional with how they want to spend it.

Philosophers debate if reasoning can be measured by instrumental rationality: how we adapt our thinking to achieve real things.

Don’t use any devices or wear headphones. Put away that book. Just look around. The screens reflect digital souls with the NBA highlights, “get ready with me” morning videos, fringe conspiracy reddit threads, and breakup TikToks.

Content feeds our minds and dyes the souls of billions. Digital screens color our world: which words we read, conversations we have, and feeds we scroll; all pull us towards jobs, places, and people that write our personal history.

This Grand Technologies post today offers loose observations on algorithms: the technology that guides content which ultimately influences our life. Algorithms warp what information we receive and then it’s up to us to respond… we can either 1) drift, 2) withdraw, or 3) curate.

What are algorithms?

Algorithms have been around forever, long before today’s conception of them. as this digital beast we commonly think about warping our thoughts.

Algorithms are a set of procedures to solve a problem or accomplish one end. Between people, algorithms are social technology: tools that direct human behavior, beliefs, culture, and society. Another social technology is trust. It provides the foundation for relationships in business, friendship, and romance. Or, entire civilizations rest on constitutions that provide the foundation for freedom and fairness.

Algorithms are social technologies that guide what information we absorb. Over my upbringing, the most impactful ones weren’t all digital. The algorithms were my home life, how it was structured and the habits formed; my friends, the jokes shared, jobs worked, and hobbies and sports we played; my teachers, their effort and inspiration; and a greater Pacific Northwest community, that outdoors ethos— all this stimuli shape my behavior today.

In my most formative years, I was largely shielded from the social impact of digital algorithms. I don’t think I grew up when digital content streams were powerful enough then to truly redirect our behavior over traditional, physical ones in my community like family, friends, and teachers. The content streams were symptomatic of existing streams: 88.5 NPR radio, a podcast feed around it, awkward middle school Snapchat culture, software through modding and hacking, and endless YouTube.

Now, I’m not so sure. Digital algorithms seem to challenge physical ones.

What’s the influence of algorithms today?

It’s Father’s Day. His generation grew up through a much different time. Today, we wade through the effects waves of influential digital innovations— the internet, smartphones, social media, AI— that have hooked us to digital content streams and now grip society.

• In the U.S., more than half of people under 35 now consider social and video platforms their primary news source, surpassing TV and legacy news websites.

• Globally, about 44% of people aged 18 to 24 say social and video platforms are their main source of news.

• Recent data from Pew and the Reuters Institute also show that around 44% of U.S. adults aged 18 to 29 cite TikTok as their go-to news source.

• For example, Meta products alone service 3.5 billion daily active unique users worldwide.

The business model monetizes attention with ads but threatens division. How many times in the last year have you spoken about any sharp issues?

I vividly remember a late night walking through the West Village just off Bleecker. My college buddy and I were filling some lonely street with words to no conclusion, “I really only speak politics with you and one other friend of mine; no one is willing to engage. People seem too afraid, worn out, tired by everything already”.

I’m not trying to point the finger. The innovations, companies, and builders deserve respect. I just need to figure out how I can individually respond.

Drift? Withdraw? Curate?

My generation accepts algorithms everywhere. We respond to consuming digital content in three ways: “adrift” with no care (I), or they are “withdrawn” from the platforms (II), or “curating” their feed (III).

I. The adrift camp scrolls without resistance. Most rest here in resignation, passively allowing the disinformation, chaotic memes, and all the emotional, loud addictive content to wash over them. I don’t think the adrift are dumb nor brainwashed. When I’m adrift, I’m just exhausted. It’s after the long days and during the stretches of boredom. Let’s just waste wait for time to pass. Up against an army of psychologists, no one’s mind is immune.

Never ask a man his salary… or to see his “For You” page. Even my kindest and charitable friends will have the most bizarre threads infesting their feeds. Some algorithm could decide they’re into those propaganda films that Iran is pumping out to make fun of the Trump administration. “Dude, what is your algorithm? Is this what you genuinely think?” No, it’s what they let wash over them.

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II. The withdrawn camp deleted it all and never looked back. They reject anything with algorithms and commit to digital self-isolation. Perhaps they read study-after-study about how less time on the internet improves mental health. Or, they’re minimizing their digital footprint to avoid their own personal information from being harvested. This smaller crop sacrifices sharing internet culture and breaking news to their emotions in exchange for winning over their own sense of personal liberty.

Protected from polarization? Well, kind of. If everyone filters into a bubble of their own, their very defense of minimalism is a retreat in itself. The very purpose of algorithms, as digital social technology, loses their value.

III. The curation camp sculpts out their feeds with specific practice. The algorithm is a tool they try and wield themselves. If algorithms do carve the mind, this camp acknowledges that doomscrolling will happen anyways… and can be a force for good? So difficult. This runs the risk of thinking the curator is above it all.

I try to curate a feed on X that I think can improve my life. Maybe it’s commentary on technology to stay informed; Famous authors from any genre share writing tips so you might read this. Daily vignettes from history to make small talk. Whatever. The truth is, I forget it all within a day unless I use it. What good is any consumption without creation?

Polarization is not a question of left vs right, but really whether they are engaged vs checked out. We’re past the point of whether algorithms are driving history and now wonder how it will in the future.

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"If you don't tell your story, someone else will select your version of it." — Haruki Murakami (… or something?)

Good morning everyone, I’m sitting on two longer polished drafts for Grand Technologies on technology’s influence: one looks at algorithms and the other compares our digital life in small towns versus big cities… Can’t wait to share those, but it has been a while. If this newsletter is a pressure valve for creative analytical writing, then my lack of bothering your inbox suggests that my compulsions are flowing into other outlets. They are.

Amidst work that looks at Big Tech’s imprints on the world, journaling about the political economy of my own life, and spam- texting through daily mundanity, I’ve maintained the pursuit of daily writing. Much like someone resolves to get, and stay fit, I left this brain gym of a newsletter and now sweat out the words elsewhere.

Well baby, we’re back in this lab for a few hours this morning. Screw AI. Don’t critique me. Change the training plan. Rather than toil with another essay for weeks, I’d like to publish more, shorter vignettes that lean more into the personal data in front of me, my daily life.

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So let’s talk about our personal digital data.

I think there’s a problem with how much digital data we have access to. It takes strong will today to not let it warp our perception of ourselves: who we were in the past, today, and can be in the future. Most of us don’t know how to handle how much personal information our devices record about us.

Life’s good, but it hasn’t always been. Relying on any one digital data metric can mislead how I perceive life. I’m going to consider a few digital data points —its historical, current, and future— and where that could shape my personal identity, were I to let it.

This Newsletter: I’ve been asked “When’s the next Grand Technologies post?” That’s just an indefensible digital data point = “There have been zero words in my inbox for 6 weeks” Flattering in that you pretend to care, but also annoying because it is me dropping a commitment. But did I? Letting these essays rest online here require a difficult confidence today I know many lack. I need it in the future.

Fitness, Health, and Competition: My love for movement has evolved in the past decade: soccer, rowing, triathlon, lifting, and now open-water swimming. Fitness watches feed my Strava to convert specific metrics— e.g., GPS, time, heart rate— creating a virtual twin of digital performance that challenges me as an entire athlete in this true reality. This digital data steers the correct conversation away from “Am I healthy?”, “Am I competitive?”, and “Am I a good teammate?”. Instead, the data detours me, distilling my pursuits into answering wrong questions at the whims of the data itself.

For me, it’s “Am I fit?”— religiously chasing faster pace risks all types of injury. Torn labrums and bouts of depression later, I tell you it’s easy to make faster numbers; it’s harder to let those numbers work truly for you.

Camera Roll: My digital life is over a decade old now. Messages aside, my photos have condensed into iCloud. Thousands of pictures capture memories in the pixels and metadata behind then: when, where, how, and with who was the picture taken with. The software can collate this into some brutal reminders of better and worse times.

Apple be like: “Good morning Max, here’s a lovely photo album to make you crash out for the rest of the day.” How we frame those visceral memories in the present require the same mental fortitude with every other datapoint. In moments of trudging the valleys of despair today, being haunted by happier past memories can also be reminders of better times to come. Hopefully.

So I’ve been fat and happy. Fit and miserable. Single and satisfied. Dating and depressed. Writing a lot and whatever— you get it. On any one of these axes we need to write our own history first. Digital data underly the technologies that guide our history— but don’t write it. Keep pushing.

Thanks for being here,

Max

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What digital data do you track and value?

I didn’t even talk about the two most popular ones. 1) Money: We get paid, pay rent, and spend our way through the world almost entirely digitally. 2) Weight: is it just a digital number on a scale? what is it really a proxy for?

What’s outside today’s discussion: comparison with others and companies. Social technologies on digital platforms rely on data to foster a sense of competitiveness for engagement, for better or worse. And then it’s also worth discussing how the companies themselves wield data to surveil and sell what we “volunteer” on these platforms we seemingly can’t live without.

* Birthday Update: Summer in San Fran, Fall in the UK

* How Silicon Valley’s tech shaped the Iran War (I and II)

Do you want to lend your view about the power of tech in our daily lives? Outside of geopolitics, I’ve been thinking about whether tech empowers goals, keeps us single, and helps us try new things.

Writing is evolving like woodworking.

Authors can write with a chatbot like a contractor props up entire housing communities. The software are like power tools that craft entire arguments, but they risk making the big old house of an essay looking all the same.

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And now a schism exists. Like artisanal wood workers, an author that writes by hand holds the craft itself sacred. To the purists, it’s this way of expressing themselves through the work itself, even at the expense of productivity.

I write today an ode to the act of writing. LLMs fundamentally changed it. Creating words and arguments will never be the same. Since ChatGPT released in November 2022, AI has plagued the world of writing to many of its purist authors: warping each stage of drafting, improving, and publishing arguments.

Regardless of your views on the machines, we must all be careful— for the sake of how we express ourselves in work and the world.

AI has infested the written word:

• In February, OpenAI bragged that ChatGPT reached 900million weekly active users;1 some 40% of which use it for writing and editing2.

• In the workforce: 87% of marketers use it,3 around 70% of newsroom staffers4, 54% of legal professionals have AI help them draft correspondences.5

• An April 2025 study found 74.2% of new web pages had detectable AI content (900k+ websites scraped).6

• Students lean on AI from drafting all the way up to just letting them write entirely. College Board published a survey that reported 84% of high school students using GenAI. College faculty reported 74% of their students are using AI to write essays and papers.7

Walk down the street, read your favorite newsletter, the news— a fake brain probably helped write it. Poor detection and the nature of self-reporting likely underestimates these numbers.8

Scholars of tech history agree now that a new form of writing is here to stay. We will all be expected to write more in less time.9

Reading anything before ChatGPT’s release in November 2022 will be relatively more sterile than what has followed. The lazy authors since then make their readers suffer.

These LLMs write so obnoxiously similar. Yes, the most recent models use the M dash less—whose reputation is forever tarnished—but other patterns remain metastasized into plenty of different bodies of text. For starters, there’s that short staccato phrasing. Everything matters. It’s got this consistent cadence. And don’t forget about a forceful tone. Because it’s all so important. Then, the piece will arc into some stupid crescendo for a sweeping conclusion. Because that’s what LLMs do best— they dramatize.

Well, isn’t this just the latest way in which technology abstracts our physical world?

• Think of how we get places: we walked, then rode horses and carriages, and then drove cars.

• Or, software engineering used to punch binary code into cards on massive machines to run calculations overnight. Now software can be built from writing in plain English thanks to natural language processing.

So this time, it’s technology lowering the friction to communicate. We once carved hieroglyphs into caves; ChatGPT and I could write an entire 80,000 word novel in an afternoon. Why is that evolution so bad? What is lost?

You must express yourself.

Say I relied on every a tool trained on billions of written words from others, are the ones I create really mine? Were creative writing to disappear—in all its human flair and mistakes—it would limit the self-expression that shapes our work and personal lives. I should learn the M dash.

Losing ownership over creative writing hurts learning and owning the work.10 Analytical jobs expect GenAI for everything: draft quicker analyses, respond to emails faster, and automate sloppy routines like outreach.

Every workday “feels” more intense, but I still ask what is lost?11 The more we automate, the less my individual contributions uniquely matter. When I lose writing, I don’t read, nor learn, as as closely. When I punt the responsibility over the words, I delegate away dealing with the material and people behind it.

Frauds always get found out and there are no shortcuts to expertise. I fell victim to this in research. I listened to some tech bro online and experimented with drafting a whole AI research workflow. I let it write an entire report that allegedly rivaled “an army of McKinsey consultants”. Even though I spent time refining it, I didn’t write it nor understood the material. So when I strutted in with my fancy deliverable ahead of a deadline— I fell completely on my face. I could not explain anything “below the iceberg”. I apologized and said I was “way over my skis”. So I went “back to the drawing board”. plz fix. thx.

In our personal life, I beg that you remain creative wherever possible. Relying on a chatbot to write can quickly become a crutch. Delegating away voice strips me of my creative soul. I want typos. orrrr, maybe ur a lowercase texter at all times! as a tangent, i do take openai’s sam altman’s ardent commitment to writing everything lowercase as slightly too much. look here; he’s messaging leaders of trillion dollar companies as he gets kicked off his.

If we prioritize connection, then 80-95% of message conversation should probably be a call. Written words still matter, for their voice reflects tone, energy, interest, and mood.

The worst words filter through a chatbot. The best ones emerge over a handwritten letter.

As chatbots improved, I relied on them less to write. That’s my choice. It’s tied to my goal of the words to hone my voice and amplify my insights. So do you care that I wrote this?

• How Silicon Valley is shaping the Iran War (I and II)

• The threat of LLMs on learning

I’m pleased to announce that around the New Year, I deleted LinkedIn and started this newsletter. Today I turn 26. Truly incredible accomplishments. Thank you.

Float the dam balloons.

To commemorate, we’re hijacking Grand Technologies to combine the worst of both. Welcome to an even longer self-aggrandizing LinkedIn post where the author gifts himself a birthday present by sharing what he’s done and doing amidst hiding all his failures and insecurities, and inevitably rambling without a word count.

There are moments in life where it’s healthy to step outside the box so you can think outside it. That’s been the last 6 months; this post reflects on that time. Since leaving the corporate rhythm of strategy consulting in Seattle, I’ve tolerated heaps of uncertainty to realign my ambition with how I want to spend the time I have left in the world.

I. Where I’ve Been

I have these coffee chats with old friends. Every single one eventually flows along some undercurrent of “where the hell have you been?” and “what the hell do you do?” The occasional vague Instagram post hasn’t helped either.

Since the fall, here’s some highlights:

Studied yoga— both postures and spiritual teachings—in Nosara, Costa Rica

Visited Israel - developing my own views with a historical & heritage trip

Hosted such motivating friends for skiing in Ketchum, Idaho

Moved to New York City thanks to the generous sublet of another friend.

All to say, none of my nomadic living would be possible without others. These experiences led to growth only possible from the help, insights, and pure generosity from others. Thank you.

For the past 5 months, the job on the main resume out of New York has been freelance. I sell myself as an economic analyst to write about the world of emerging technologies. That’s taken me to copywriting for creative agencies, publishing samples here, and supporting research for other scholars.

For the past 5 months, the work (the “what the hell do you do all day?”) has been to learn as much as possible. Amidst working for others, I maintain a daily schedule of reading, writing, and improving personal software projects.

New York has been good to me. It’s turned an ounce of ambition into a Marty-Supreme motion. Everyone’s so active. I won some hackathon for using marketing AI tools and collaborated in another to make open-source prison telecommunications software. I joined a dinner community of AI researchers and will be co-hosting an event at a16z tech week. I attend debate societies where my background in social sciences lends a fresh view.

The list will go on, but not here. All this motion cannot just be for the sake of motion.

I’m leaving thanks to what its taught me. I do not want to live in a place where wellbeing is an afterthought. The urban density that powers its unique energy restricts the natural benefits of healthy life: quality sleep, deeper relationships, varied fitness, the outdoors, quiet, and the space to think. Social life revolves around drinking and eating, neither of which delight me enough to stay.

I will miss my friends.

II. Where I’m Going

The script over coffee continues. The inevitable “what’s next?” pours in:

This April, I’m a rowing coach in Texas.

And for this summer, I’m finalizing being a research fellow in San Fransisco. The accepted proposal below.

This fall, I am slated to begin graduate school in the UK, swinging for Oxford’s MPhil in International Relations.

Do people change? I hope so. Still, our past guides the present. The student-athlete demons never left after college. I grapple with this daily compulsion to train the mind and body through reading, writing, and exercising in what really interests me. The daily work arises easily; the jobs that emerge into careers prove harder to find.

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But we must create, not consume. If I were a betting man, I’d tell you I’ll shake out as some teacher by trade. Whether it’s formal— as a professor and coach— or informal—as a journalist or advisor—is what the next decade will answer.

If you’re reading this, you’re important to me. Thanks for being an early investor in Grand Technologies and a life unfolding.

Book Updates

I read about a book a week right now. Here’s what I can remember that’s laying around. Suggest anything. I struggle with podcasts.

Careless People: A Cautionary Tale of Power, Greed, and Lost Idealism, Sarah Wynn-Williams

Great Founder Theory, Samo Burja

The Monk Who Sold His Ferrari, Robin Sharma

The Courage to Be Disliked, Ichiro Kishimi & Fumitake Koga,

Noise: A Flaw in Human Judgment, Daniel Kahneman, Olivier Sibony & Cass R. Sunstein

The New Geography of Innovation: The Global Contest for Breakthrough Technologies, Mehran Gul

The Genius Habit, Laura Garnett

Chokepoints: American Power in the Age of Economic Warfare, Edward Fishman,

The Bitcoin Standard: The Decentralized Alternative to Central Banking, Saifedean Ammous

Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI, Karen Hao,

The Deep Keel (Joy Covey profile), Kevin Gee

The Technological Republic: Hard Power, Soft Belief, and the Future of the West, Alexander C. Karp & Nicholas W. Zamiska

Zero to One: Notes on Startups, or How to Build the Future, Peter Thiel with Blake Masters

The Alchemist, Paulo Coelho

The Iran war teaches a bitter lesson in failing to win against a weaker adversary that has existed for decades: funding terrorism, seeking nuclear weapons, and building up an entire anti-American ideological regime.1 In response, our leaders relied on policies like the sticks of sanctions and carrots of nuclear agreements, but they’ve stopped short of such sweeping strikes that spark war.

Grand Technologies observes how hyped technology can impact our lives. Last post provided a perspective on how technology from Silicon Valley made a strike more appealing. Silicon Valley changed warfare by compressing operational planning and giving our leaders a god’s eye view. Today discusses Iran’s response in face of that digital advantage.

Even though the United States wields more digital power, Iran neutralized it by shifting the contest into the lower-tech analog domain where it matters less: decentralizing its domestic power to prevent insurgencies and controlling the Strait of Hormuz to wield global economic control.

I. Decentralizing Domestic Power

Iran politically structured itself to survive how the West could kill off its leadership to create a power vacuum; democracy distributes power to citizens and is a luxury not afforded to the daily Iranian.

Iranian Political Scientist Saeid Golkar is an expert on the authoritarian regime, “for years, Iranians have endured cycles of mass arrests, torture, executions, and deadly crackdowns on protests. Between January 8 and 9, the regime killed thousands of its own citizens for taking to the streets and demanding change. This is not an authoritarian state that sometimes oversteps, but a modern security autocracy that uses fear as a core tool of governance. And a regime that normalizes mass violence should not be treated as a legitimate political authority.”2

To retain its power, Iran governs its people on coercion, rooted in systematic repression in a tangled web of military commanders that run the state by force.

Iran’s foreign minister has described its leadership as structured by “Decentralized Mosaic Defense”: a doctrine that distributes its military into an estimated 31 regional commands, each capable of responding alone with full capabilities.3 Designed to retain military control without any single leader, Iran has negated a digital advantage that could enable any insurgency, short of the West invading with boots on the ground.

No internet prevents a revolution to rise in the digital world. Since the war broke out, Iran shutdown the wider internet for its 92 million citizens— roughly 1% of normal traffic remains accessible.4 The regime’s leaders maintain their own intranet, a digital iron curtain heavily monitored.

This all lowers the chance of a power vacuum arising even as drones circle the skies to kill leaders at a moment’s notice. The West’s decapitation strategy—the targeted killing of Iranian leadership— failed to force terms in Pakistan. No wonder the United States keeps ground invasion on the table. Iranian commanders remain in power and are under no hurry to surrender their arms to the very citizens they’ve shot, tortured, and silenced for decades.

II. Chokepoint Geography

The second analog advantage: Iran’s geographic fortune. The country doesn’t need to match the West’s technological capabilities when it controls a crucial bottleneck to the world’s gas and oil production: the Strait of Hormuz in the Persian Gulf.

Iran is the second-largest country in the region. Its regional power extends to controlling the Persian Gulf, home to 31% of global crude oil production. The Strait is two miles wide at its narrowest point and at peak flow, 20 million barrels a day of crude and refined oil flow through it. That’s roughly equivalent to both the United States and Canada’s combined daily production.5 All bypass pipelines in Saudia, UAE, to Gulf of Oman are within Iranian weapons and have been hit.

Iran’s proximity to the Strait means it doesn’t need the best digital technology. Sharing over 1,800km along the Persian Gulf, it only needs weapons that are good enough to threaten the oil that flows from the region.

Low-cost Shahed drones cost between $20,000 to $80,000, a tenth of the Western missiles that cost contractors like Lockheed Martin millions to make. And Iran built a reserve of an estimated 2,000-6,000 naval mines—the largest stockpile in the region—over decades from the various sources: Chinese, Soviet-era, Russian and their own makeshift ones.6 Less than $25,000, each mine can disable a billion-dollar warship.

The low-tech drones and mines prove good enough. Iran has attacked at least 21 ships and made transit uninsurable for underwriters.7 On March 11, Iran began laying mines. Within weeks, legitimate shipping dropped 95%. 140 vessels a day dropped to as few as five.

The consequences land on everyone. Thousands have died. The average price of gas has soared past $4 a gallon. 54% of Americans oppose the war.8 There’s been “no rally around the flag effect” that boosts a president’s favorability. And whatever comes from future negotiations, the war remains unfavorable.

We cannot live in a world where a nuclear power threatens to destroy entire civilization and wipe out its 90 million citizens— the regime is horrible, but its people are not.

Power asymmetry does not let our leaders ignore strategy; tools are only good as those who wield it. Rapid innovation has kept the United States ahead against its adversaries since WW2, but this latest war testifies that gap does not guarantee success.

New digital, godlike weapons influenced the Trump administration to strike Iran, but they appear little help in improving the judgment required to win the war.

The US & Israel's data ingestion capabilities gave leaders a false sense of confidence by providing asymmetric information that emboldened decision-making. But despite our digital advantage, Iran succeeded by equalizing the contest into its own analog advantages— now we all pay the price.

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Grand Technologies observes how technology affects our daily lives. Even the most removed from the war in America today will face the consequences of the ongoing conflict between the US, Israel, and Iran. The average price of gas in America now exceeds $4/gallon, the highest it’s been since 2020. Buyers of diesel, jet fuel, chemicals, and fertilizer all face inflated prices. From heating and electricity to flights, we are in for an expensive summer. Thousands of US troops are headed to Iran; the US death toll stands at 13 with 365 injured.1

Silicon Valley reinvented warfare— the conduct. In the digital domain, Iran cannot compete with the West’s overwhelming capabilities in cyberwarfare: jamming communications, hacking the entire networks of a city’s CCTV cameras, and relying on frontier models to coordinate the ensuing operations. New advances in data ingestion allowed for 2,000 targets to be struck in 4 days.

Source: The proliferation of AI-enabled military technology in the Middle East, Noor Hammad, IISS,

Programs that synthesize intelligence like Project Maven compress operational planning. Leveraging billions of collected data points, a smaller team of a dozen analysts rely on frontier models to orchestrate human reporting, digital communications, satellite imagery, and open-source streams to make kinetic decisions faster than larger teams can. The missions that took weeks in Iraq now take days against Iran.

Silicon Valley changed warfare, but not the fact that we’re at war: we’ve resorted to violence with Iran to achieve some policy objective. The same tools that reinvented warfare had sped up judgment and led to an unclear strategy, the policy plan necessary in every war (regardless of what warfare looks like).

AI doesn't just compress planning time, it also forces analysis into an act of signing off. When we prompt a chatbot to plan our commute or cook us dinner, the stakes of outsourcing that thinking is low. But when the technology powers a kill chain, judgment is paramount— necessary to improve by the process of weighing facts, arguing the merits to an action, and owning the conclusion.

To “win” a war requires defining a win. The tools prove attractive for warfare… but are they effective if winning is unclear? First it was to support protesters revolting? Then openly support a regime? Or destroying Iran’s nuclear program? and its ballistic missiles?2

As the goal-posts continue to shift, critics argue we’re headed towards a strategic defeat, but the White House boasts we’re winning. The tools of warfare evolve, but war’s domains remain relatively constant: physical, digital, and economic.

We learn from history that we learn nothing from history - George Bernard Shaw

Despite the growing influence of technology firms in geopolitics—such as the case of big tech “Building the digital front line” in Ukraine— leaders still set the strategy of foreign policy and which tools to win with. If we don’t know what victory looks like, no tool will get us there.

A new dynamite has entered the world. Large Language Models (LLMs) improve how we access and wield knowledge, but, like dynamite, it doesn’t improve knowing when to use it.

Grand Technologies discusses how sweeping tech impacts our daily lives. Today observes technology threatening learning. LLMs are a landmark upgrade to knowledge infrastructure: the systems which store information to educate us.

“From gold rushes to guerrilla wars, dynamite’s dual legacy is one of construction and destruction.” - Christopher Klein

For nearly a thousand years, the world relied on imprecise black powder until dynamite arrived. Introduced in the 1860s, dynamite-driven engineering quickly became indispensable for civil engineering, mining, but also weaponry.

Famous engineering projects, like the Hoover Dam, would not be possible without dynamite’s ability to blast through larger amounts of rock more accurately. Henry Petroski, a professor of civil engineering and history at Duke University tells Popular Mechanics that “its introduction coincided with a lot of the railroads being pushed through uncharted territory, and they needed to get through large mountains,” and argues that “it was much more efficient than going up and down, and the dynamite was essential in blasting tunnels.”1

Not only an instrument for engineering and mining, dynamite improved high explosives at war. Only three years after entering production, dynamite was used by fighters in the 1870 Franco-Prussian War and then anarchists wielded dynamite to destroy public monuments during the subsequent Paris Commune of 1871. Its stability and portability made it easier for attackers to breach defenses.

A New Dynamite to Knowledge

Dynamite built and destroyed physical things; LLMs stand to do the same with how we think. For generations, grasping new knowledge got easier. Over thousands of years, technological leaps upgraded knowledge infrastructure that improved our access to information: language improved, the printing press spread, libraries grew, and digital networks and databases went online.

Each advancement reduced the friction to manage information. Reducing that time managing the information naturally trades off working in that information: lines of text, code, and pixel. Spending less time in the information risks losing our grasp over concepts.

The Dual Legacy of LLMs begins

The innovations of dynamite and LLMs are both amoral, not inherently “good or bad”. How the use of this power and technology is judged determines that. So, a dual legacy originates soon after.

dynamis translates to power in Greek (δύναμις),

tekhnē (τέχνη) translates to “art, skill, craft in work; method, system, an art, a system or method of making or doing.”

Neither word carries moral charge.

Today, LLMs revolutionize knowledge infrastructure, marking the most dramatic reduction in the friction to learning— but also present the greatest risk to intellectual development.

Over the last two decades, the growing popularity of “data-driven insights” —first from AI/ML algorithms but especially since the advent of LLMs— marks an inflection point in knowledge infrastructure. Humans have been abstracted so far from consuming and producing content that these steps are collapsed into one single “check”.

The analyst once read, synthesized, and reasoned. Now the analyst prompts an LLM to read, synthesize, and reason— then check what it’s done.

Ceding that control bears risk.

In the good, dynamite revolutionized civil engineering. LLMs stand to engineer together disparate knowledge that humans cannot. For example, a tech entrepreneur reduced the cancer in his dog by 75% by sequencing its DNA for $3k and navigated the research pipeline on a $20/month ChatGPT subscription.2

I’m convinced a solo founder will come along and make a billion-dollar unicorn. Their creation will definitely command an army of agents, but it will not inherently create some good.

In the bad, many pacifists historicize Alfred Nobel as “the Merchant of Death” with how widely dynamite was used in war. Can LLMs kill cognition? The same tools that teach and destroy learning in schools, jobs, and in life.

Abstracting knowledge management risks losing control over our own ability to access information ourselves. When we outsource how we access thought, we risk losing access to those thoughts themselves.

When the Library of Alexandria burnt down, its value as a central repository was lost. What happens if LLMs vanish?

We offer no explanation as to why these architectures seem to work; we attribute their success, as all else, to divine benevolence. “GLU Variants Improve Transformer” -- Noam Shazeer

We once wrote papers, pushed code, and drove ourselves; now we can “one-shot” that same work by immediately producing deep research, hacking together a working demo, or asking for a Waymo to take us straight to the airport.

Automate only the skills you’re willing to lose. - Gurwinder

So I drafted this in an email exchange to force me to research, think, and write slower. I can defend the lack of citations this time around. Weird grammar, awkward syntax, and janky flow will soon be be features of artisanal research, not bugs. Intentionally creating a space away from algorithms prevents encroaching upon my own thinking.

That luxury of slowness —to think and process the world at a pace that matches our own cognition— is unaffordable in competitive environments like work and warfare. We will naturally use every tool that enhances our thinking, to maximize our gain and minimize our losses.

In work, the massive leaps in knowledge management stand to benefit the individuals who wield LLMs correctly: playing secretary, automating routines, or testing insights. In warfare, Project Maven is an innovation to the knowledge management of intelligence.3 It allowed the Western forces to start the War in Iran by striking over 900 targets in less than 24 hours.

Learning will look a whole lot different in a decade. But what about leadership?

A computer can never be held accountable, therefore a computer must never make a management decision. Thus, it’s important for those who wield its immense power to know what they use it for. - 1979 Internal IBM training Manual

Applying LLMs to our daily lives—removing us from the loop of our decisions—holds up a mirror to our own morality. Most of it is innocuous; some of it is for the good of others; and some of it for the acts of evil. The tool itself is at its core amoral, but it all boils down to how humans use it.

Once men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.” ― Frank Herbert, Dune

Today’s cognitive capabilities are unmatched thanks to advances in knowledge management. Our brains cannot keep up. The world requires more restraint from its leaders than ever. A new modern Marcus Aurelius needs to emerge as Trump exposed how powerful4 a unitary American presidency can be.

“Yeah,” Trump grunted inelegantly. “There is one thing. My own morality. My own mind. It’s the only thing that can stop me.” He continued, “I don’t need international law.”5