Weekend Food For Thought WFFT
On today's menu: History of Tech Revolutions, China's Recent 5-Year Plans, How Can US Sustain Competitive Advantage, Cyber Domain and Physical Domain, Lessons From The Swiss Watch Industry, and more..
Hello from LA,
I hope you had an interesting and productive week.
Donella Meadows stated that: “A system is not the sum of its parts — it is the product of their interactions.”
Start to connect the dots and then imagine the potential of their interactions below…
1 Getting Visual
2 If You Read One Thing Today - Make Sure it is This
3 Consequential Thinking about Consequential Matters
4 Big Ideas
5 Big thinking
6 Dream
1 Getting Visual
Spotlight - The Power of GPTs: “What the history of technology revolutions really teaches is how lopsided progress is. A small number of general purpose technologies quietly become cheap, ubiquitous inputs, and a small number of companies manage to harness them in a way that compounds for decades. Most of the noise in markets is everything else. For a serious, long‑horizon investor, the job is not to guess the next sci‑fi storyline, but to recognise which GPTs are already reshaping the present and own the businesses that are most deeply tethered to that curve. For over 200 years, the world did not get richer because we became slightly more efficient at doing the same things; the step‑changes came when a handful of technologies crossed the line into true General Purpose Technologies. Once steel, electricity, and later semiconductors became dirt cheap and ubiquitous, they stopped being “sectors” and turned into background infrastructure that every other activity could plug into. At that point the GDP curve bends, not because one company wins, but because the entire economic game is being played with different pieces – and forward‑looking investors who recognised that shift were effectively “long” the new techno‑economic paradigm, not just a single stock or theme. The skew in long‑term stock returns is not a quirky footnote; it is exactly what you would expect in a world organised around technology revolutions. Only about 2.4% of global stocks generated all the net wealth from 1990 to 2020, while nearly three‑fifths destroyed capital, because most incumbents either failed to adapt to new GPTs or were structurally constrained from doing so. That is why passively owning “the market” mostly gives you exposure to businesses on the wrong side of the revolution, and why we think the core of a serious long‑horizon portfolio should be built around the relatively small set of companies that are visibly harnessed to the dominant GPTs of their time – the firms for whom the revolution shows up as steadily compounding fundamentals rather than as a one‑off story.” - Rob Larity, Bespoke’s Chief Investment Officer.
Spotlight - Exponential Adoption: “4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026. While you blinked, AI consumed all of software development. We believe that Claude Code is the inflection point for AI “Agents” and is a glimpse into the future of how AI will function. It is set to drive exceptional revenue growth for Anthropic in 2026, enabling the lab to dramatically outgrow OpenAI.” - Semianalysis
Learn more:
Spotlight - Launch Cost Down. Record number of objects launched into space in 2025…
Key Trend - Solar Sovereignty (or shifting reliances/alliances?) “The underappreciated case for solar has to do with the sovereignty. Renewables localize power, as we wrote in our 2024 essay on the dawn of the distributed age; Pakistanis are increasingly responsible for their energy security. And it’s not just the sovereignty that matters here but its compounding effects. Our position is that solar as a technology isundergoing a supercycle, the declining cost of solar panels will drive the opening of new markets which means that every year that Pakistan continues to replace fossil fuels with solar, it is building a durable technology stack to participate in the new economy. 92% of countries would be more energy secure under a renewable paradigm than under a fossil one. Many countries used fossil fuels as a geopolitical weapon. From OPEC’s oil embargoes to Russia’s manipulation of natural gas, control over these resources gave them significant power. With renewables, this power dissipates. Once you have the solar panel, you have the energy – OPEC can’t block the sun. Pakistan has so far vindicated that argument. The solar transformation helped reduce their exposure to the price rises in fossil fuels this year by at least $6.3 billion, equivalent to 1.7% of the country’s GDP.” - Exponential View
Spotlight - China and Europe seen through the Electricity Lens: China’s electricity demand per person has overtaken Europe’s. Electricity is the least gamble economic indicator there is. It reads directly off industrial capacity, manufacturing scale, increasingly transportation, the real weight of an economy.
Key Input - Copper Kingdom: Since 1999, US refined copper production is down 50%, while China’s is up 1200%…
Tech Perspective: It’s Good to be the Platform: “I was wrong about Apple and AI. I was in the camp that dismissed Apple on this. Siri hadn’t improved in a decade. Capex was flat while Microsoft and Google were spending hundreds of billions. No research breakthroughs, no frontier models. I agreed with the analysts calling their WWDC demos “concept videos.” But what I missed was visible in my own behaviour. Every day I was running Claude or ChatGPT or switching between a dozen models and I was doing all of it on an Apple device. The model changed constantly. The device never did. Then I put an AI agent on my Mac Mini at home. Within a week it was consuming everything the machine had. The audio system and CCTV cameras had stopped working reliably. I bought a second Mac Mini specifically for the agent. That machine, I call it R Mini Arnold, now runs full-time. By the time I ordered it, delivery had stretched from three days to seven or eight weeks. The 64GB RAM config was running that long everywhere. Best Buy shelves empty. This is a demand story. There is a structural reason. Apple’s Neural Engine runs nearly 40 trillion operations per second and is optimised for matrix multiplication which is, precisely, what every transformer model actually does. Unified memory shared across CPU, GPU and Neural Engine gives it bandwidth consumer devices almost never have. The stack was built for something else entirely. It turns out to be almost perfectly suited for running AI locally. But the silicon is only one layer. Apple also controls the OS, the App Store and a privacy architecture. It is embedded within the enclaves, the software and the operating system. And because of that, they have something rare – genuine consumer trust. Think about everything you own, from your socks to your wallet. What do you touch the most? Your wedding band if you have one, your glasses if you have them and then an Apple device. That is the degree of consumer intimacy Apple has built. Apple didn’t plan to be the AI inference hardware of choice. But it’s winning right now.” - Azeem Azhar
Spotlight: Private Markets - PE Investors Stuck in ‘Hotel California’ has no appetite for further “room service”… “There’s no compelling reason to believe that investors are losing faith in private equity. An overwhelming majority of LPs surveyed by Preqin indicate that they plan to either maintain or increase their allocations both in 2026 and over the long term. There is ample evidence, however, that LPs are stretched to their limit. Simple math dictates that the amount of capital they can commit to private equity today is constrained by the amount they get back from previous investments. By the end of 2025, 53% of LPs in a Private Equity International survey indicated they are limited in making new commitments to private equity because past commitments have yet to be drawn down. That’s an increase of 15 percentage points from year-end 2024. LPs are already on the hook for the massive commitments they made in the record 2021–22 fund-raising boom period, and without cash flowing back from aging fund vintages, funding those commitments becomes problematic. Until balance is restored, LPs will have to continue to juggle supply and demand very carefully.” - Bain Capital
2 If You Read One Thing Today - Make Sure it is This
Kyle Chan of the insightful High Capacity Substack reviews China’s recent Five-Year Plans to see what it reveals about its evolving tech strategy- and its plans for the industries of the future. Go explore it here in full…
Some Takeaways
Technology is a central focus of China’s new 15th Five-Year Plan. China is aiming to develop “strategic emerging industries” (战略性新兴产业) such as robotics and smart EVs as well as “future industries” (未来产业) such as quantum, fusion, brain-computer interfaces, 6G, and embodied AI. With the end of catch-up economic growth and the real estate boom, China is searching for new engines of future growth—so-called “new quality productive forces” (新质生产力)—that will allow China to attain the per capita income of a “moderately developed country” (中等发达国家) by 2035.
But a focus on technology is not new for China. And China’s obsession with science and technology did not start with Xi Jinping. Hu Jintao, Jiang Zemin, and Deng Xiaoping all viewed technology as key to China’s development. In 1978, Deng Xiaoping gave a famous speech at China’s National Science Conference where he said: “The key to the Four Modernizations is the modernization of science and technology. Without modern science and technology, it is impossible to build modern agriculture, modern industry, and modern national defense. Without the rapid development of science and technology, there can be no rapid development of the national economy.”
Here are the key trends I found:
Persistence: China has been relentlessly persistent at tackling the same core technologies over decades (see chart at very top). These are well-known technologies or industries with broad applications and positive spillovers: automotive, energy, semiconductors, shipbuilding, aviation, space, biotech, and so on. Many have long been the target of industrial policy around the world, especially in Japan and South Korea. Their recurring presence across China’s Five-Year Plans underscores their strategic importance to Chinese policymakers and, in some cases, the difficulty China faces in trying to catch up, particularly in semiconductors where the global frontier is a rapidly moving target.
Evolution: Some target technologies have appeared across Five-Year Plans but in new forms. Biotech was originally more focused on agricultural biotech and is now more focused on pharmaceuticals, genomics, and biomanufacturing. Automotive began as conventional internal combustion engine vehicles but branched into “new-type fuel vehicles” (新型燃料汽车) in the 11th Five-Year Plan and then eventually became “new energy vehicles” (新能源汽车). Information technology (信息技术) partly shifted focus to the “digital economy” (数字经济) and then eventually to AI (人工智能), which was first mentioned in the 13th Five-Year Plan (2016-2020) and is a core focus of the new 15th Five-Year Plan.
Global trends: China’s target technologies mirror some of the global tech trends of the times. China’s obsession with the information revolution and “informatization” (信息化) in the 2000s mirrored America’s 1990s dot-com boom. And this presaged in many ways China’s current obsession with AI where developments in the US, such as AlphaGo’s defeat of the top human Go player or the launch of ChatGPT, were like “Sputnik moments” for China on AI.
Energy security. China has been heavily focused on energy-saving technologies and alternative energy sources for decades, driven by long-standing anxieties over energy security. In earlier Five-Year Plans, China was more focused on energy-saving technology, such as energy-efficient industrial machinery and fuel-efficient combustion engines for cars. Over time, you can see China shifting more towards a massive push in clean technology, including solar, wind, batteries, hydropower, hydrogen, and electric vehicles. The seeds for China’s clean tech boom were already planted as far back as the 6th Five-Year Plan (1981-1985).
From catch-up to innovation. In earlier Five-Year Plans, China was focused on technological catch-up by “introducing and absorbing” (引进，吸收) foreign technology. 2006 marked a shift toward “indigenous innovation” (自主创新) with the launch of China’s Medium-and Long-Term Plan for the Development of Science & Technology (2006-2020). Rather than merely import foreign technology, Chinese leaders believed that China must be able to able to truly create and own the technology itself through innovation. It’s important to note that this push for “indigenous innovation” began under Hu Jintao, long before Xi’s rise to power in 2012. China’s focus on innovation has only grown since (see chart above), becoming a key strategic factor and driver for future economic growth.
From opportunity to threat. During the first decades of the Reform era, China saw technology as an opportunity to catch up and modernize quickly. The language in those earlier Five-Year Plans sounded more optimistic with hopes that China might even do “leapfrog development” (跨越式发展) to skip over technological stages and leverage its “latecomer advantage” (后发优势). China’s attitude starts to shift with its 2010 plan on Strategic Emerging Industries (战略性新兴产业) where it sees itself as not merely catching up but competing on the international stage in a race for the next round of key technologies. Finally, the 14th Five-Year Plan (2021-2025) marks a pivotal shift following the first Trump administration’s near-crippling of Huawei and ZTE in 2018-19. China sees itself as painfully vulnerable to technological “chokepoints” (卡脖子技术) and begins an urgent race to develop “key core technologies” (关键核心技术), such as advanced semiconductors, high-end manufacturing equipment, and industrial software. This sense of urgency is especially strong in the new 15th Five-Year Plan, which calls for “extraordinary measures” (超常规措施) to achieve decisive breakthroughs in key core technologies.”
Conclusion
What makes China’s tech-industrial policy remarkable is not some hundred-year master plan for technological supremacy or meticulously engineered blueprint for success. It’s China’s sustained focus on a set of obviously critical technologies over years and even decades.
While the strategies and tactics—and even the technologies themselves—may change, China’s overarching persistence has yielded steady gains that have allowed it to catch up and even achieve global leadership in key technologies.
China’s new 15th Five-Year Plan is but the latest chapter in a much longer technology story.”
3 Consequential Thinking about Consequential Matters
McKinsey Global Institute takes a deep into how the US can sustain it’s competitive advantage in this report…Go ponder it her in full…
https://www.mckinsey.com/mgi/our-research/At-250-sustaining-Americas-competitive-edge
Some Takeaways
“America’s history of reinvention holds compelling lessons as the nation confronts a future of immense if uncertain opportunity”
At a glance
At 250 years old, the United States is the world’s most competitive economy. It generates 26 percent of global GDP and is home to 59 of the world’s top 100 firms. In the past several years, accelerating US productivity growth and announced foreign direct investment inflows have sharpened its edge over other advanced economies.
It’s a new world. AI is unveiling an ever-expanding realm of possibilities, just as geopolitical contention is growing and fertility rates are falling. The United States is a global technology leader today and spends 27 percent of the world’s research and development dollars—but will that be enough to sustain its current 59 percent share of top firms?
Some US historical competitive advantages are becoming liabilities. Current generations owe it to future ones to address deteriorating fiscal health, eroding infrastructure, declining educational achievement, fading manufacturing know-how, and sustained disparities in income and wealth.
Safeguarding an economic edge requires evolving, as America has before. The United States has repeatedly adapted its economic model to meet, and then shape, new technologies and geopolitical realities. Since the country’s founding, American competitiveness has shifted but sustained across four historical chapters: agricultural, industrial, scientific, and digital. A new one is coming.
A culture of innovation and natural abundance are abiding strengths on which to draw. By our count, Americans created or supported 76 of the 100 most important inventions since 1776, from steamboats to smartphones, from the electrical grid to generative AI. Over its history, the country has profited from twice as much agricultural land per capita as any other large economy, and it was largely self-sufficient in energy for 200 years, including since 2019. These are just a few examples of its resource wealth.
We the people will write the coming chapter. Collective effort from American individuals, business, and government can ensure energy abundance, an infrastructure backbone, education that builds minds and skills to match new technology, and the financial strength to pay for it all. The prize is continued growth, national economic security, and economic opportunity for everyone.
Competition in critical technologies is heating up
Past success does not guarantee future results, of course, and the US lead in technology is narrowing as China becomes more competitive. Some are now warning of a second “China shock,” should China displace American leadership in critical technologies.
Beyond simply focusing on the gaps of the past, the United States needs to prepare for leadership in the industries that will be most important in the coming decades. Future competitiveness increasingly hinges on leadership in critical technologies, such as AI, robotics, biotechnology, quantum computing, high-performance batteries, and space-based technology.
Economically, these technologies promise great gains for profits and wages. Geopolitically, they will be critical for protecting national security; their dual-use (military and civilian) nature means firms that develop them will be on both frontiers. In all these areas, China has made rapid progress and, in some cases, has taken the lead.
In remarkably short order, China has moved from producing low-cost goods to leading the world in complex, capital-intensive industries such as electric vehicles and photovoltaics. This shift is now extending beyond manufacturing into research-intensive domains once dominated by advanced economies. In biotechnology, for example, China’s output in drug discovery has grown more than tenfold since 2013.
As of 2024, China surpassed the United States in number of clinical trials and in the count of clinical-stage molecules. Altogether, China’s life sciences industry is no longer confined to generic biologics or follow-on products, and it is now playing a leading role in generating sophisticated novel biologics.
In the domain of AI, while America still has the most sophisticated AI models, China has more robots than the rest of the world combined. The United States has approached AI as a product unto itself, focusing on screen-based text and images. China’s approach, however, has emphasized AI’s deployment in the physical world, with intelligent machines that can see, decide, and act in real time. For example, Chinese firms are integrating AI into industrial robots that learn from their environments, drones that analyze visual data onboard while in flight, and autonomous vehicles whose core intelligence runs directly inside the vehicle rather than in the cloud.
Recently, China has also established a strong presence in the realm of fundamental scientific research, advancing the frontiers of knowledge. From 2017 to 2023, China overtook the United States in most cited research in fields including machine learning, quantum sensors, advanced integrated circuit design and fabrication, adversarial AI, natural language processing, and high-performance computing (it already led in other fields, including electric batteries and advanced magnets). In some instances, China is deploying this research in practical uses with tangible output; for example, China developed the world’s first quantum satellite. Although most cities with dense populations of highly cited researchers are American, Beijing saw the largest absolute inflow from 2019 to 2023.
To lead in critical technologies in the decades to come, the United States will need not only to establish an edge in today’s emerging technologies but also to make the discoveries that uncover tomorrow’s. The nation will need to support innovation ecosystems and continue to attract—and build—talent. Currently the United States graduates fewer engineers than China, both in absolute terms and relative to population size. Even more fundamentally, in K-12 education, the United States lags behind both its own historical record and other major economies. The 2024 National Assessment of Educational Progress showed a downward trajectory in math, science, and reading; only about a third of eighth-grade students were proficient.
The Programme for International Student Assessment found that American 15-year-olds score lower on average in math than their peers in all other G7 economies. A robust public education system rooted in general knowledge and problem solving has been a historical strength of the United States.
The question today is how to restore that advantage.”
“Today the United States may be entering a new chapter. Tech, especially AI, is advancing rapidly. Postpandemic macroeconomic disruptions persist, marked by a recent 40-year high in inflation. And heightened geopolitical tensions have produced a growing tide of protectionism reflected in both higher tariffs (the US average tariff rate is now 12.7 percent, the highest since World War II) and industrial policies such as the Inflation Reduction Act and the CHIPS and Science Act. Current trajectories suggest that these forces, along with persistently high capital costs and aging populations, are likely to set the competitive context for the United States and other major economies in coming years.
The opportunity is immense. Future-shaping industries including AI, biotechnology, and robotics are expected to have market sizes in the trillions in the coming decade. By one estimate, AI could add up to 0.6 percentage point to annual productivity growth through 2040.
To seize this opportunity, the United States must prepare to confront looming challenges, including rising demand for energy, infrastructure gaps, and growing national debt. Success also means business strategy, operations, and innovation systems transforming to embrace AI. In parallel, business and society need to proactively train US workers to share their jobs with AI. Should those challenges be met, the net effect would be an American economy that innovates and operates in faster, bigger, and better ways. All this needs to be done with an eye to national economic security amid growing geopolitical fractures.
The magic of US competitiveness to date is that it has not been the result of top-down planning but rather has developed organically from its foundations of natural abundance and entrepreneurialism (which in turn have been harnessed through infrastructure and institutions). Overly specific prescriptions for how to attain the next wave of competitiveness risk missing this important point.
Whatever steps US firms, governments, and institutions take, they should ideally be informed by what’s worked in the past: adapting US abundance and entrepreneurship into continued economic leadership on the global stage.”
4 Big Ideas
Big Ideas are becoming tangible solutions all around us currently - here are two articles exploring changes at the ‘tip of the spear’ of conflict: The first looks at the cyber domain and the second looks at the physical domain - both highlight how GPTs are driving real change across the board…Go explore it all here in full..
https://www.forbes.com/sites/thomasbrewster/2026/03/17/ai-beat-most-humans-in-elite-hacking-competitions/?utm_
https://www.reuters.com/graphics/IRAN-CRISIS/DRONES/dwpkyamxqpm/
Some Takeaways
“Every year, more than 100,000 seasoned cybersecurity pros compete in global hacking competitions, designed to show off their abilities at picking apart security systems to pilfer data. The games task hackers with challenges that escalate in difficulty, from bypassing logins to more complex cyberattacks requiring exploitation of hidden software weaknesses. Ultimately, they aim to break through all the security layers protecting a digital “flag,” just like real life capture the flag.”
“Now, Israeli startup Tenzai says that earlier this month its AI hacker performed better than 99% of the 125,000 human competitors who faced off in a series of six so-called capture the flag (CTF) competitions, which regularly update with new sets of tricky challenges.
Tenzai tailors models from both OpenAI and Anthropic for use in offensive cybersecurity. The firm proved itself in both old school competitions, where participants had to hack a web application, and newer ones, where the aim was to break into AI apps with prompts that manipulated the underlying large language models.”
“AI-driven offensive security is no longer theoretical, Gurvich says, but works at scale. That’s cause for both concern and optimism.
If artificial intelligence programs are able to exploit complex IT systems at speed, it lowers the barrier to entry for almost anyone wanting to launch potentially devastating cyberattacks.
At the same time, AI could also be tasked with finding and fixing a significant number of security weaknesses before they’re exploited. It will come down to which AI finds the problem first.
It’s also significantly cheaper. It cost just $5,000 to run Tenzai’s AI models across all the competitions. That’s chump change for government agencies, cybercrime gangs or surveillance companies wanting to use artificial intelligence for snooping. It’s downright affordable for anyone with some expendable income who wants to do damage. “This is rapidly getting out of the realm of nations and military intelligence organizations and into the hands of college kids who may have very different incentives,” Gurvich says.”
Cheap drones are reshaping the war in the sky
For decades, air superiority was largely the preserve of wealthy nations able to afford advanced aircraft and the training needed to fly them. Cheap attack drones are beginning to erode that advantage, giving smaller and less wealthy forces a greater ability to inflict damage. The US, by contrast, has long relied on its vast military budget to field some the world’s most expensive aircraft.”
“The technology of war has evolved rapidly in recent years, a shift starkly illustrated by Ukraine’s fight against Russia. What began as a conflict dominated by tanks and artillery has increasingly become a drone war. Outgunned in conventional armor and aircraft, Ukraine turned to inexpensive unmanned systems for reconnaissance and attack. Drones are estimated to account for about 70% of Russian casualties, enabling strikes to be carried out remotely and reducing the risk to pilots and aircrews.
America’s most powerful aircraft rely on highly trained crews. For example, a two-seater F-15 requires aviators to take years of training at significant cost. If one of those aircraft goes down, the United States loses not only the plane but possibly the crew aboard it too.
By contrast, low cost drones are piloted remotely. If the drone is destroyed, the operator is not killed and the replacement cost can be tens of thousands of dollars.
That imbalance has become a strategic problem.
Attacking has grown cheap while the relative cost of defending has sky-rocketed, with the United States and its allies sometimes firing interceptors worth millions of dollars to shoot down drones assembled from off‑the‑shelf components at a fraction of the price.”
“If we’re shooting down a $50,000 one‑way drone with a $3 million missile, that’s not a good cost equation,” Bill LaPlante, the Pentagon’s chief weapons buyer, told a Senate appropriations subcommittee in May 2024, warning that the economics of air defense are becoming unsustainable.
The imbalance is already visible at sea. Since late 2023, the U.S. Navy has expended around $1 billion or more in munitions defending ships in the Red Sea from low‑cost Houthi drones and missiles, according to U.S. officials and defense analysts.
The missile price is only part of the cost. Each interception also depends on the presence of warships and their escorts, fuel and maintenance, trained crews, intelligence and surveillance assets, and command‑and‑control networks needed to detect and defeat incoming threats.”
“The United States is scrambling to catch up. Washington moved to fast‑track small military drones, approving systems such as the Low‑Cost Uncrewed Combat Aerial System (LUCAS) more quickly than is typical.
In July 2025, Defense Secretary Pete Hegseth issued a directive titled “Unleashing U.S. Military Drone Dominance,” ordering the Pentagon to cut red tape and accelerate drone deployment across the force, warning that adversaries are producing millions of drones each year while U.S. efforts have been slowed by outdated procurement practices.”
“The FLM-136 LUCAS resembles Iran’s Shahed, a one‑way attack system that has been used extensively by Russia in Ukraine. The Shahed helped popularize a new class of weapon that functions much like a cruise missile, but at a fraction of the cost. As attack drones have proliferated and grown cheaper, defensive counter‑drone systems have lagged behind, exposing gaps in air defense.”
5 Big thinking
Paul Graham goes off on an exploration of lessons from the Swiss watch industry and why “Branding is centrifugal; design is centripetal.” He, as per usual, provides plenty to ponder for entrepreneurs and investors - Go Read it here in full..
https://paulgraham.com/brandage.html?utm_
Some Takeaways…
“Branding is centrifugal; design is centripetal.
There is some wiggle room here of course. Design doesn’t have as sharply defined right answers as math, especially design meant for a human audience. So it’s not necessarily bad design to do something distinctive if you have honest motives. But you can’t evade the fundamental conflict between branding and design, any more than you can evade gravity.
Indeed, the conflict between branding and design is so fundamental that it extends far beyond things we call design. We see it even in religion. If you want the adherents of a religion to have customs that set them apart from everyone else, you can’t make them do things that are convenient or reasonable, or other people would do them too. If you want to set your adherents apart, you have to make them do things that are inconvenient and unreasonable.
It’s the same if you want to set your designs apart. If you choose good options, other people will choose them too.
There are only two ways to combine branding and good design. You can do it when the space of possibilities is enormously large, as it is in painting for example. Leonardo could paint as well as he possibly could and yet also paint in a style that was distinctively his. If there had been a million painters as good as Bellini and Leonardo this would have been harder to do, but since there were more like ten they didn’t bump up against one another much.
The other situation when branding and good design can be combined is when the space of possibilities is comparatively unexplored. If you’re the first to arrive in some new territory, you can both find the right answer and claim it as uniquely yours. At least at first; if you’ve really found the right answer, everyone else’s designs will inevitably converge on yours, and your brand advantage will erode over time.
Since the space of watch design is neither unexplored nor enormously large, branding can only be achieved at the expense of good design. And in fact if you wanted one sentence to describe the current age of watchmaking, that one would do pretty well.”
“The most striking thing to me about the brand age is the sheer strangeness of it. The zombie watch brands that appear to be independent and even have their own retail stores, and yet are all owned by a few holding companies. The giant, awkwardly shaped watches that reverse 500 years of progress in making them smaller. The business model that requires a company to rebuy their own watches on the secondary market to catch rogue customers. The very concept of rogue customers. It’s all so strange. And the reason it’s strange is that there’s no function for form to follow.
Up to the end of the golden age, mechanical watches were necessary. You needed them to know the time.
And that constraint gave both the watches and the watchmaking industry a meaningful shape. There were certainly some strange-looking watches made during the golden age. They weren’t all beautifully minimal. But when golden age watchmakers made a strange-looking watch, they knew they were doing it. In fact they give the impression of having done it as a deliberate exercise, to avoid getting into a rut.
That’s not why brand age watches look strange. Brand age watches look strange because they have no practical function. Their function is to express brand, and while that is certainly a constraint, it’s not the clean kind of constraint that generates good things.
The constraints imposed by brand ultimately depend on some of the worst features of human psychology. So when you have a world defined only by brand, it’s going to be a weird, bad world.
Well that was dark. Is there some edifying lesson we can salvage from the wreckage?
One obvious lesson is to stay away from brand.
Indeed it’s probably a good idea not just to avoid buying brand, but to avoid selling it too.
Sure, you might be able to make money this way — though I bet it’s harder than it looks — but pushing people’s brand buttons is just not a good problem to work on, and it’s hard to do good work without a good problem.
The more subtle lesson is that fields have natural rhythms that are beyond the power of individuals to resist. Fields have golden ages and not so golden ages, and you’re much more likely to do good work in a field that’s on the way up.
Of course they don’t call them golden ages as they’re happening. “Golden age” is a term people use later, after they’re over. That doesn’t mean that golden ages aren’t real, but rather that their participants take them for granted at the time. They don’t know how good they have it. But while it’s usually a mistake to take one’s good fortune for granted, it’s not in this case. What a golden age feels like, at the time, is just that smart people are working hard on interesting problems and getting results. It would be overfitting to optimize for more than that.
In fact there’s a single principle that will both save you from working on things like brand, and also automatically find golden ages for you.
Follow the problems.
The way to find golden ages is not to go looking for them.
The way to find them — the way almost all their participants have found them historically — is by following interesting problems.
If you’re smart and ambitious and honest with yourself, there’s no better guide than your taste in problems.
Go where interesting problems are, and you’ll probably find that other smart and ambitious people have turned up there too. And later they’ll look back on what you did together and call it a golden age.”
6 Dream
Have a Great weekend when You get to that stage,
Sune