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How did these individuals become vitamin D deficient in the first place? According to Bredesen, it’s a combination of lifestyle habits and nutritional choices: “They’re living indoors, they’re not getting out enough, they’re not taking vitamin D, or they’re not absorbing the vitamin D they are taking.”
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Ray Dalio has been saying for a while that the dollar is in trouble. Not right now, not tomorrow, but rather at a structural level. His theory on the rise and fall of empires points to an intriguing pattern: roughly every 100 years, the world’s reserve currency gets replaced.
Not because someone decides to replace it. But because change is unavoidable – and the underlying force that gave power to that currency shifts into something else.
We’re about 100 years into dollar dominance. We’re getting closer.
Reserve currencies don’t just happen out of thin air. They’re backed by whatever the dominant economic force of the era is.
Before the dollar it was the British pound, backed by the largest navy in the world and control over global trade routes. Before that, the Dutch guilder, backed by the most sophisticated merchant fleet of the time. Each transition happened because a new empire became dominant in the thing that mattered most for commerce.
For the dollar, that thing was oil.
After Bretton Woods collapsed in 1971, the dollar survived, and even consolidated, because oil was priced in dollars. You want oil, you need dollars. Every country needs oil, so every country needs dollars. Simple, unavoidable, effective.
The dollar wasn’t backed only by abstract American values or military trust. It was backed by the one commodity the entire world had to buy, every single day.
Let’s try an exercise of imagination, and no, I’m not talking about electric cars. I’m talking about something way deeper.
AI is already beginning to do what oil did for manufacturing — becoming the input for almost everything. It’s already at the foundation of drug discovery, legal work, financial modeling, logistics, content, code. The list grows every month.
And there’s a wilder version of this argument. AI is even accelerating energy research. Fusion, which has been “20 years away” my entire lifetime, is suddenly getting real traction. Solar and battery optimization is increasingly AI-driven. If AI helps us get cheap, abundant energy, the physical scarcity of oil — the very thing that made it a geopolitical weapon — starts to dissolve.
You could make energy at home. Not today, maybe not in five years. But it may happen soon.
When that becomes a reality, the petrodollar loses its foundation.
Unlike oil, which you had to drill for in specific places controlled by specific people, inference can be run anywhere you can build compute.
It has all the properties that made oil work as a backing. It’s scarce — quality compute isn’t free, and good models need tons of energy to train. It’s universally needed — every sector of the economy is becoming dependent on it. And it’s measurable. We already have a unit: the token.
Which is where PPT — price per token — becomes interesting. Not as a currency someone declares tomorrow, but as an index. The way price per barrel was the pulse of the oil economy, price per token might become the pulse of the inference economy.
Every six months, the frontier moves. What was cutting-edge a year ago is now available for almost nothing. The gap between the best proprietary model and a capable open source alternative keeps narrowing, and the compression has real consequences.
The US currently leads on proprietary models. OpenAI, Anthropic, Google DeepMind — the frontier is American, backed by an overheated investment market pouring money into compute, talent, and infrastructure.
China is doing something different. Instead of competing dollar for dollar on proprietary development, they’re doing what they’ve always done — taking the open layer and making it theirs. DeepSeek wasn’t a surprise. It was the result of a deliberate strategy: work within the open source ecosystem, optimize hard, and ship something affordable and at least as capable.
The result is that you don’t need a billion-dollar data center to run useful inference anymore. You need a decent GPU, the right model, and electricity. We’re moving toward a world where someone can have serious compute in the back of their garage and use it to generate daily income — running local models, offering inference services, solving real problems for real people.
This gives everyone a place at the table. A small place, yes, but still a place.
But having a place at the table doesn’t mean you get to eat. The concentration of power we’re describing isn’t new — it echoes patterns from history. I’ve written before about how showing up is not enough anymore. The world is increasingly run by a handful of corporations, much like the Mongolian Empire consolidated power across continents. Those who were conquered had a choice: swear allegiance and deliver real value, or be erased. In an inference economy, the math is similar. To survive, you need to generate at least 5x your current value — enough to justify your seat. To thrive, you need 100x. The table is open, but the entry fee keeps rising.
I’ve been thinking a lot about this during the last few years. We’re at a point where the nation-state framing starts to break down.
The old model — one country controls the dominant resource, prices it in their currency, projects power through that control — made sense when the resource was physical. You can blockade oil, invade a country, take their president, problem solved. You can’t blockade a model weight file. You can’t invade it.
If inference becomes the primary economic force, power won’t necessarily concentrate in Washington or Beijing. It will concentrate around whoever controls the compute layer, the data pipelines, and the distribution networks. That might be a country. Or it might be a corporation. Or it might be something we don’t have a word for yet.
Neal Stephenson imagined something like this in Snow Crash, back in 1992. In that world, nation-states have fragmented into franchulates — corporate-run micro-nations, floating enclaves, sovereign territories defined not by geography but by who you pay allegiance to and what network you’re on. That famous novel reads less and less like fiction with every year.
Language barriers disappear when AI makes communication frictionless. Cultural friction softens when every interaction is mediated and translated in real time. The things that historically kept people inside national containers start to matter less. What matters is access to compute, and who sets the rules of the network you’re on.
Whoever controls the inference layer controls the economy that runs on top of it. That might look like a country. It might look like a platform. Dalio was right that the dollar is running out of road — he just observed the cycle, showing it on the map. What he didn’t map is that the next dominant force might not belong to any nation at all. The petrodollar logic was built for a world that is quietly becoming something else.
These things move slowly, and then all at once.
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dragos@dragosroua.com (Dragos Roua)
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Most entrepreneurs don’t fail because of strategy — they fail because of the lies they tell themselves. In this conversation, I unpack the hidden self-deceptions that keep ambitious people stuck, from negotiating with yourself to surrounding yourself with the wrong rooms and wrong influences. We talk about why difficult conversations are the true price of freedom, how discipline can quietly destroy your quality of life, and why betting on yourself is the ultimate turning point.
I also break down the “11 out of 10” attitude that allows elite entrepreneurs to persist with gratitude—even when everything feels uncertain. If you want to grow your income, work fewer hours, and build a business that thrives in any season, this episode will rewire how you handle pressure forever.
I share the exact mindset shifts that helped founders go from overwhelmed and underpaid to scaling multimillion-dollar businesses while working fewer hours. If you’re ready to stop negotiating with your potential and finally build real freedom, this episode will challenge you in the best possible way.
Let me know what you think of today’s episode! Did you learn something new? Am I missing something? Is there something that has or hasn’t worked for you in your path to success? Send me an IG DM or email and let me know how I can help you level up in life.
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Craig Ballantyne
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Robinhood’s co-founder reveals the brutal reality of surviving an 80% market crash, going “founder mode” to cut corporate bloat, and what actually happened during GameStop.
Vlad Tenev is the co-founder and CEO of Robinhood. Not only did he navigate the unprecedented GameStop crisis , but he completely re-engineered the fintech giant to thrive.
He breaks down the brutal transition from bloated hyper-growth to a lean machine, why a “juicy falsehood is more powerful than a boring truth”, and the 3 distinct phases of AI integration separating the winners from the dead.
Believe it or not, GameStop was not his hardest moment.
Coming Soon: YouTube | Spotify | Apple Podcasts | Transcript
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Vicky
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Looking for a new family favorite? This light and lemony, chock-full of flavor, color, vitamins, and minerals dish is for you. It’s so good that even Katie Couric loves it and loves talking about it. Added bonus: It’s perfectly balanced with carbs, protein, healthy fats, and veggies.
Reprinted with permission from Crave, Cook, Nourish: 80+ Recipes and Expert Guidance for Healthy, Happy Nutrition .Text copyright © 2026 by GrassoFed, LLC. Photographs copyright © 2026 by Erin Scot. Published by Ten Speed Press, an imprint of the Crown Publishing Group, a division of Penguin Random House LLC, New York.
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When I really started to amplify my work with AI, the most annoying thing was the message: “you have hit your quota, usage reset at 3:00 AM”. That was Claude telling me I have exhausted all my tokens and I cannot work anymore. I had to stop. Go out and take a break. It felt incredibly frustrating but I had no choice, I had to wait until my quota was replenished.
Since then, I started to experiment with on-device inference. Meaning using models on my own machine, and not via APIs, capped by my current subscription. At the moment of writing, this is still prohibitive. My Mac M1 has 16GB of RAM, which makes it barely usable for coding tasks. The best I can do is to use some 3B (3 billion parameters) model, like Qwen, which is roughly usable for task classification, and impossible for real hardcore coding tasks, the kind that I’m using every day.
So running inference on my machine basically means 2 things: first, I have to wait until models are becoming more performant (and it seems this is happening now every 6 months or so) and I have to get a better machine, one with at least 64GB of RAM.
But while I was researching all these AI configurations, I accidentally stumbled upon something called Apple Intelligence. It’s a collection of optimized models which are running on device, and can do decent text and image manipulation. They cannot generate code, or high resolution photos, but they are good enough for low res tasks.
Now, if only I can imagine a use case for those…
And here’s how Just 5 Words was born.
So, it works like this: the user picks 5 random words from a pre-made list, we feed these words to the on-device text model and instruct it to make a short story out of them – don’t ask me about what prompt(s) I’m using, it took me a lot of time to get them right. Once the story is done, feed the story to the image generation model and build an image for that story. Everything stays on device, no API calls, nothing.
Looks simple.
Well, in the beginning it was. But the more I worked on it, the deeper I went down the rabbit hole. Sometimes I was hitting some model limitations, like the fact that the text model cannot generate output if a person is involved. I don’t know why, but it’s just how it is. And then I realized the image generation could be further optimized by using different styles and perspectives. So I made a few presets for both styles and perspective.
And then there was the UX angle: how much of this is free, and how much is ad-gated?
After a couple of days of back and forth I came up with something not only working decently, but significantly… addictive. I know, I’m the builder, I’m supposed to like what I’m building, but still. There is something really addictive about watching how words are becoming short stories, almost like haikus, and then on top of them ephemeral, gentle images are being generated. It’s… beautiful.
Apple Intelligence is not available on all Apple devices. You need to be on iOS 18.4 or higher, and have an iPhone 15 Pro or newer, and to enable it in Settings. That’s a significant limitation and it was the biggest source of friction during the AppStore review process. Initially, the App Review team tested on simulators and it instantly rejected the app. I had to actually send them a message with instructions: test on devices, guys, Apple Intelligence doesn’t work in simulators.
On top of that, I had to do significant work in the sharing feature. Because what’s a beautiful image on my phone, if no one else can see it? Does it even exist? Joke aside, I built 3 different share sheets, for Twitter, Instagram and TikTok, trying to bank on the short form content that these platforms are prioritizing.
The app is finally live in AppStore, so you can try it out. Remember, you’ll need an Apple Intelligence ready device AND need to have Apple Intelligence enabled on that device.
Download Just 5 Words for free from here: https://apps.apple.com/us/app/just-5-words/id6753934664 – and let me know what you build. Just share on Twitter, Instagram and TikTok and use the hash tag #5Words, I’ll keep an eye on that one.
All in all, this was one of the most fun experiments I did recently.
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dragos@dragosroua.com (Dragos Roua)
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“In the wholeheartedness of concentration,” the poet Jane Hirshfield wrote in her beautiful inquiry into the effortless effort of creativity, “world and self begin to cohere. With that state comes an enlarging: of what may be known, what may be felt, what may be done.” But concentration is indeed a difficult art, art’s art, and its difficulty lies in the constant conciliation of the dissonance between self and world — a difficulty hardly singular to the particular conditions of our time. Two hundred years before social media, the great French artist Eugène Delacroix lamented the necessary torment of avoiding social distractions in creative work; a century and a half later, Agnes Martin admonished aspiring artists to exercise discernment in the interruptions they allow, or else corrupt the mental, emotional, and spiritual privacy where inspiration arises.
But just as self-criticism is the most merciless kind of criticism and self-compassion the most elusive kind of compassion, self-distraction is the most hazardous kind of distraction, and the most difficult to protect creative work against.
How to hedge against that hazard is what beloved poet Mary Oliver (September 10, 1935–January 17, 2019) explores in a wonderful piece titled “Of Power and Time,” found in the altogether enchanting Upstream: Selected Essays (public library).
Oliver writes:
It is a silver morning like any other. I am at my desk. Then the phone rings, or someone raps at the door. I am deep in the machinery of my wits. Reluctantly I rise, I answer the phone or I open the door. And the thought which I had in hand, or almost in hand, is gone. Creative work needs solitude. It needs concentration, without interruptions. It needs the whole sky to fly in, and no eye watching until it comes to that certainty which it aspires to, but does not necessarily have at once. Privacy, then. A place apart — to pace, to chew pencils, to scribble and erase and scribble again.
But just as often, if not more often, the interruption comes not from another but from the self itself, or some other self within the self, that whistles and pounds upon the door panels and tosses itself, splashing, into the pond of meditation. And what does it have to say? That you must phone the dentist, that you are out of mustard, that your uncle Stanley’s birthday is two weeks hence. You react, of course. Then you return to your work, only to find that the imps of idea have fled back into the mist.
Oliver terms this the “intimate interrupter” and cautions that it is far more perilous to creative work than any external distraction, adding:
The world sheds, in the energetic way of an open and communal place, its many greetings, as a world should. What quarrel can there be with that? But that the self can interrupt the self — and does — is a darker and more curious matter.
Echoing Borges’s puzzlement over our divided personhood, Oliver sets out to excavate the building blocks of the self in order to understand its parallel capacities for focused creative flow and merciless interruption. She identifies three primary selves that she inhabits, and that inhabit her, as they do all of us: the childhood self, which we spend our lives trying to weave into the continuity of our personal identity (“The child I was,” she writes, “is with me in the present hour. It will be with me in the grave.”); the social self, “fettered to a thousand notions of obligation”; and a third self, a sort of otherworldly awareness.
The first two selves, she argues, inhabit the ordinary world and are present in all people; the third is of a different order and comes most easily alive in artists — it is where the wellspring of creative energy resides. She writes:
Certainly there is within each of us a self that is neither a child, nor a servant of the hours. It is a third self, occasional in some of us, tyrant in others. This self is out of love with the ordinary; it is out of love with time. It has a hunger for eternity.
Oliver contrasts the existential purpose of the two ordinary selves with that of the creative self:
Say you have bought a ticket on an airplane and you intend to fly from New York to San Francisco. What do you ask of the pilot when you climb aboard and take your seat next to the little window, which you cannot open but through which you see the dizzying heights to which you are lifted from the secure and friendly earth?
Most assuredly you want the pilot to be his regular and ordinary self. You want him to approach and undertake his work with no more than a calm pleasure. You want nothing fancy, nothing new. You ask him to do, routinely, what he knows how to do — fly an airplane. You hope he will not daydream. You hope he will not drift into some interesting meander of thought. You want this flight to be ordinary, not extraordinary. So, too, with the surgeon, and the ambulance driver, and the captain of the ship. Let all of them work, as ordinarily they do, in confident familiarity with whatever the work requires, and no more. Their ordinariness is the surety of the world. Their ordinariness makes the world go round.
[…]
In creative work — creative work of all kinds — those who are the world’s working artists are not trying to help the world go around, but forward. Which is something altogether different from the ordinary. Such work does not refute the ordinary. It is, simply, something else. Its labor requires a different outlook — a different set of priorities.
Part of this something-elseness, Oliver argues, is the uncommon integration of the creative self — the artist’s work cannot be separated from the artist’s whole life, nor can its wholeness be broken down into the mechanical bits-and-pieces of specific actions and habits. (Elsewhere, Oliver has written beautifully about how habit gives shape to but must not control our inner lives).
Echoing Keats’s notion of “negative capability,” Dani Shapiro’s insistence that the artist’s task is “to embrace uncertainty, to be sharpened and honed by it,” and Georgia O’Keeffe’s counsel that as an artist you ought to be “keeping the unknown always beyond you,” Oliver considers the central commitment of the creative life — that of making uncertainty and the unknown the raw material of art:
Intellectual work sometimes, spiritual work certainly, artistic work always — these are forces that fall within its grasp, forces that must travel beyond the realm of the hour and the restraint of the habit. Nor can the actual work be well separated from the entire life. Like the knights of the Middle Ages, there is little the creatively inclined person can do but to prepare himself, body and spirit, for the labor to come — for his adventures are all unknown. In truth, the work itself is the adventure. And no artist could go about this work, or would want to, with less than extraordinary energy and concentration. The extraordinary is what art is about.
In a sentiment that calls to mind Van Gogh’s spirited letter on risk-taking and how inspired mistakes move us forward, Oliver returns to the question of the conditions that coax the creative self into being:
No one yet has made a list of places where the extraordinary may happen and where it may not. Still, there are indications. Among crowds, in drawing rooms, among easements and comforts and pleasures, it is seldom seen. It likes the out-of-doors. It likes the concentrating mind. It likes solitude. It is more likely to stick to the risk-taker than the ticket-taker. It isn’t that it would disparage comforts, or the set routines of the world, but that its concern is directed to another place. Its concern is the edge, and the making of a form out of the formlessness that is beyond the edge.
Above all, Oliver observes from the “fortunate platform” of a long, purposeful, and creatively fertile life, the artist’s task is one of steadfast commitment to the art:
Of this there can be no question — creative work requires a loyalty as complete as the loyalty of water to the force of gravity. A person trudging through the wilderness of creation who does not know this — who does not swallow this — is lost. He who does not crave that roofless place eternity should stay at home. Such a person is perfectly worthy, and useful, and even beautiful, but is not an artist. Such a person had better live with timely ambitions and finished work formed for the sparkle of the moment only. Such a person had better go off and fly an airplane.
She returns to the problem of concentration, which for the artist is a form, perhaps the ultimate form, of consecration:
The working, concentrating artist is an adult who refuses interruption from himself, who remains absorbed and energized in and by the work — who is thus responsible to the work… Serious interruptions to work, therefore, are never the inopportune, cheerful, even loving interruptions which come to us from another.
[…]
It is six A.M., and I am working. I am absentminded, reckless, heedless of social obligations, etc. It is as it must be. The tire goes flat, the tooth falls out, there will be a hundred meals without mustard. The poem gets written. I have wrestled with the angel and I am stained with light and I have no shame. Neither do I have guilt. My responsibility is not to the ordinary, or the timely. It does not include mustard, or teeth. It does not extend to the lost button, or the beans in the pot. My loyalty is to the inner vision, whenever and howsoever it may arrive. If I have a meeting with you at three o’clock, rejoice if I am late. Rejoice even more if I do not arrive at all.
There is no other way work of artistic worth can be done. And the occasional success, to the striver, is worth everything. The most regretful people on earth are those who felt the call to creative work, who felt their own creative power restive and uprising, and gave to it neither power nor time.
Upstream is a tremendously vitalizing read in its totality, grounding and elevating at the same time. Complement it with Oliver on love and its necessary wildness, what attention really means, and the measure of a life well lived, then revisit Jane Hirshfield on the difficult art of concentration.
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Maria Popova
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Last month, I was at a dinner party in Barcelona.
Someone asked me why I moved to Europe, why I stepped back from the relentless pace of building Mindvalley, and why I’m taking one week off every month to learn photography and stand-up comedy instead of grinding.
I told them the story.
I saw flamenco dancers one night. Thought: Why am I fantasizing about living other lives when I could just live them?
Built Eliza AI. Realized 90% of my work could disappear. Made a choice: presence over productivity. Learning over legacy metrics.
The person nodded politely. And then said:
“But isn’t Europe kind of… declining? America’s still the richest, right?”
That question haunted me.
Because the assumption underneath it is one that almost everyone holds. And it’s about to become deeply, structurally wrong.
So I spent the last month analyzing something that surprised me: If you measure the right variables, Europe isn’t behind. It’s ahead. And in an AI-powered future, it’s going to be way ahead.
This isn’t ideology. It’s data. And it’s going to reshape how you think about work, wealth, time, and what you actually want from your life.
You’ve probably heard this:
America’s GDP per capita is roughly $86,600. Europe’s is about $62,660. That’s a 28% gap in favor of America.
Case closed. America wins. Go back to grinding.
Except… that number is the economic equivalent of measuring someone’s intelligence by how much they talk. It tells you volume. It tells you nothing about what actually matters.
So let me ask you the question they don’t ask: How does America make that money?
The answer: More hours. A lot more hours.
Here’s what the data actually shows when you stop looking at total GDP and start looking at productivity per hour:
US: $85/hour worked
Germany: $86/hour worked
Denmark: $95/hour worked
France: $83/hour worked
A German worker produces the same value per hour as an American worker. They just work 471 fewer hours per year. That’s almost three full months less.
The average German logs 1,340 hours per year. The average American logs 1,811 hours. They do the same amount of economic work in 9 fewer months per year.
The French work nearly two fewer months than Americans. The Danes produce more per hour than American workers while working 431 fewer hours annually.
These aren’t lazy economies. These are efficient economies that made a different choice about what to do with that efficiency.
This is where it gets interesting. EU citizens live 81.7 years on average. Americans live 79 years. That’s 2.7 years longer.
But here’s what I discovered when I dug into the data: that extra lifespan doesn’t translate into more economic output in Europe. Instead, it translates into more life.
Let me show you the lifetime calculation:
| Life Expectancy* US: 79* Germany: 81* France: 82.5* Denmark: 81.5 | Hours Worked/Year* US: 1,811* Germany: 1,340* France: 1,511* Denmark: 1,380 |
| Working Years* US: 43* Germany: 41* France: 39.5* Denmark: 42.5 | Lifetime Work Hours* US: 77,873* Germany: 54,940* France: 59,684* Denmark: 58,650 |
| Lifetime GDP Output* US: $6.6M* Germany: $4.7M* France: $5.0M* Denmark: $5.6M | Retirement Years* US: 14* Germany: 18* France: 21* Denmark: 17 |
An American worker produces $6.6 million in lifetime economic output. A German produces $4.7 million. A Frenchman produces $5 million.
America wins on total output. Europe converts the equivalent output into something different: time.
The American gets 14 years of retirement. The German gets 18. The Frenchman gets 21.
Not because Europeans are less productive. Because they made a deliberate civilizational choice: We will work efficiently, then we will live.
What you’re really looking at here aren’t just different economic policies.
There are two fundamentally different philosophies about what human life is for.
The American system is ruthlessly optimized for maximum economic production. Work more hours per year. Work more years per career. Retire later. Accept higher inequality as the price of dynamism. The result: world-leading GDP, extraordinary innovation, the most powerful technology sector on earth.
The cost: Shorter lifespans. Less leisure time. Healthcare tied to your job. Higher stress. A culture where your identity is your job title. The thing I noticed living here for six years: Americans are exhausted.
The European system produces the same or higher economic value per hour, then redirects the surplus into what it calls “quality of life”: more vacation, earlier retirement, universal healthcare, walkable cities, stronger communities, longer lives, and lower inequality.
The tradeoff is lower total GDP, fewer tech unicorns, and less entrepreneurial dynamism in the traditional sense.
But here’s the thing: For most of modern history, the American model was obviously superior. Bigger GDP meant more power, more innovation, more influence. GDP was the scoreboard, and America was winning.
Then AI arrived.
I’ve been thinking about this deeply because I’m living it in real time. I built an AI that eliminated 90% of my work. I could choose to build 10 new companies. Or I could choose to actually use that time to live.
And I realized: the European model has already solved what AI is about to force on everyone.
America’s GDP lead isn’t because Americans are more talented or hardworking per hour. It’s because Americans work more hours. You win by quantity.
But AI is about to automate exactly that: quantity.
When an AI agent can do 10 hours of analysis in 10 minutes, the country winning by grinding 1,811 hours per year loses its primary advantage.
Germany’s model, producing $86 per hour while working only 1,340 hours, already looks like a post-AI economy. They’ve solved for efficiency. America has been brute-forcing GDP through sheer labor volume, and that’s the first thing that becomes obsolete.
When AI displaces millions of workers, the data is clear that you will need systems that don’t collapse when employment drops.
Universal healthcare not tied to your job? Europe has it. America ties your health insurance to employment.
Robust safety nets? Europe has them. America has a threadbare system designed for full employment.
Pension systems that don’t collapse? Europe designed them for lower work hours. America’s Social Security is already under strain.
The American economic model requires full employment to function. Lose your job, you lose your healthcare. Lose your job, and your retirement contributions stop. Lose your job, often your housing.
The European model is built to absorb shocks. When 20-40% of jobs are displaced, Europe has the infrastructure. America has a crisis waiting to happen.
In the old model, Europe’s longer lifespan was almost “wasted” years consumed without producing GDP. An economist might look at that and say: Europe’s ahead on time but behind on productivity.
But in an AI-augmented world, where work is increasingly optional, and lifespans are expanding, those extra years become opportunity years.
What matters isn’t how many hours you grind. What matters is the quality of the decades you get to live.
Europe already has the infrastructure for long, healthy lives: walkable cities, universal healthcare, strong social connections, lower inequality, and a culture that values presence over productivity.
America has suburbs, car dependency, an opioid epidemic, gun violence, and healthcare disparities. The reason Americans die younger than Europeans at every income level isn’t mysterious. It’s a civilizational design.
When you remove the structure that employment gives to people’s lives, those design problems become catastrophic.
Here’s the paradox nobody talks about: The entire US-EU productivity gap is driven by one sector: tech.
Multiple analyses confirm that, excluding the tech sector, EU productivity growth has matched the US for twenty years. Three sectors — computing, communications, IT — explain more than two-thirds of the American advantage.
But the very tech sector driving America’s GDP advantage is building the AI that will commoditize its own workforce.
When Opus 4.6 can do the work of 100 software engineers, when AI can write code, design systems, build products, the crown jewel of American advantage becomes everyone’s crown jewel.
Europe, which has been “behind” on tech, could leapfrog by adopting AI without dismantling an existing tech-employment complex that’s already starting to crack.
America already has enormous inequality. AI will concentrate wealth further — the owners of AI capital will capture most of the value while displaced workers face a system with no safety net.
Europe’s lower inequality, stronger unions, and redistributive systems mean AI’s gains are more likely to be shared. A society where AI makes ten billionaires richer is less stable than one where AI makes 400 million people’s lives slightly better.
This isn’t idealism. It’s systems design.
This one keeps me up at night because I study consciousness. Americans derive identity from work to a degree that Europeans fundamentally don’t.
When you ask an American, “Who are you?” they tell you their job title. When you ask a European, they tell you about their family, their city, and what they love doing in their free time.
When AI takes away the American’s work, you get an identity crisis layered on top of an economic crisis. Who are you if you’re not your job?
Europeans have rehearsed for this for decades. Six weeks of vacation. 35-hour work weeks. Café culture. A philosophy that work is something you do, not something you are.
The civilization that already knows how to live well without working all the time is better prepared for a world where machines do most of the work.
I want to be honest about the bull case for America. Innovation requires dynamism. Risk-taking. Brutal competitive pressure. That’s real. Silicon Valley is unmatched. America produced Google, OpenAI, and Tesla.
But there are two problems with that argument for the future.
First: AI itself commoditizes what made Silicon Valley special. The engineering talent premium shrinks when AI can write code and design systems. You still need a few frontier labs to build the technology. But you need an entire civilization to live well with that technology. Building AI is an American strength. Living with AI well may be a European one.
Second: The American model’s “dynamism” comes at a cost that compounds. Shorter lifespans. Worse health outcomes. Higher addiction rates. More gun deaths. More car deaths. Less vacation. More burnout.
I’ve lived on both continents. The American model works like a startup that never stops sprinting. Impressive growth numbers. Everyone is burned out. And the founder dies of a heart attack at 62.
The European model works like a company that figured out how to scale sustainably.
I’m not telling you to move to Europe. Though some of you should consider it.
I’m telling you this because the data reveals a principle that applies to your individual life, not just nations:
Optimize for output per hour — not total hours — and you’ll have both wealth and a life worth living.
The European model works at scale because it does what the best individual entrepreneurs already do: maximize efficiency, then use freed time for health, relationships, growth, and meaning.
The American model is like a startup that never ships the product, never takes the VC money off the table to actually enjoy it, just keeps grinding for the next funding round.
As AI accelerates, ask yourself:
Am I optimizing for total hours worked, or for output per hour?
Is my identity tied to my job title, or to who I actually am?
Am I building a life that only works if I keep grinding, or one that gets better when some of the grinding is automated?
Am I investing in the infrastructure of a good life — health, relationships, community, meaning — or deferring all that until “retirement”?
What happens to me if my job disappears in the next five years?
The data is brutally clear: The workers who produce the most per hour, work the fewest hours, live the longest, and retire the earliest are in Northern and Western Europe.
They’re not lazy. They’re not poor. They’re not less ambitious. They’ve solved for the right variable.
And in an age where machines will handle the volume, and humans will be left with the question of how to actually live, their model isn’t just competitive.
It might be the only one that works.
I’ve made my choice. I moved my family to Europe. I’m taking one week off every month. I’m learning flamenco and comedy. I’m building companies with AI as my co-founder, so I can work 20 hours a week instead of 80.
I’m choosing the European model not because I’m abandoning ambition, but because I realized ambition without a life is just burnout with a better brand.
The question for you is: What are you choosing?
Because in the next few years, as AI reshapes work, that choice is going to become the defining difference between people who thrive and people who break.
I want to hear your honest take. Leave a comment below: if AI removed 30% of your workload tomorrow, would you feel free or lost? And if you had European hours with American opportunities, how would you redesign your life?
With presence,
Vishen
P.S. The data I referenced comes from IMF World Economic Outlook 2024-25, OECD Productivity Indicators 2025, Eurostat, CDC life expectancy data, and recent analyses from Bruegel and Banque de France. If you want the full breakdown, I can send it. But the headline is simple: Europe didn’t get left behind. America is optimized for the wrong variable. And AI is about to make that blindingly obvious.
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Vishen
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Asian Efficiency is one of the leading productivity training companies. We help people become more productive at work and in life. We believe that you should be able to get everything done without having to sacrifice your health, family and things that matter to you. We’ve helped millions of people save time, be happier, and become more productive.
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Lee H. Baucom, Ph.D.
Lee H. Baucom, Ph.D.
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Einstein said we can’t solve our problems with the same thinking that created them.
And if you’ve been working on your marriage—trying hard, putting in effort, doing everything you can think of—but nothing’s actually changing? You might be spinning the wheel.
Pursuing harder. Forcing conversations. Making grand gestures. Reading every article, watching every video, trying every technique the algorithm throws at you.
That’s effort. Real effort. But it’s pointed in the wrong direction.
In the last episode, I talked about why “if it’s meant to be” is dangerous thinking. This episode is about what you do instead. Not just recognizing the myth is wrong, but understanding what intelligent effort actually looks like when you’re trying to save a marriage.
Because here’s what most people miss. The marriage that’s in crisis right now? It didn’t fail because you picked the wrong person or because your love wasn’t strong enough.
It failed in design.
The culture gave you a destination—happily ever after—and almost nothing about how to actually get there and stay there. So when things fall apart, it’s not a destination failure. It’s a navigation failure.
And that changes everything.
In this episode, I walk through what it actually means to rebuild a marriage. Why it feels so much harder than it did at the beginning. Why you’re not maintaining orbit—you’re relaunching. And what to do when you’re the only one putting in the energy.
Listen below.
RELATED RESOURCES
“If it was meant to be” Episode
Why Your Spouse Doesn’t See a Change
Save The Marriage System
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Lee H. Baucom, Ph.D.
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We talk about collagen, elastin, and hyaluronic acid all the time in skin care, usually in the context of a serum we love or a moisturizer we can’t live without. But these ingredients are also dietary components and can nourish your skin from the inside-out.*
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Growing a business is the dream. But scaling one? Honestly, that is a completely different reality.
Most entrepreneurs start with a clear vision and a small, dedicated team where everyone knows their role. You know, those days when you could just shout across the room to get an answer.
When you decide to scale, that simplicity begins to change. Scaling is not just about doing more of what you are already doing. It is about building a structure that can handle more without breaking under the weight of its own success.
Many businesses find that the very things that made them successful in the beginning are the things that hold them back when they try to expand. And that’s the point. What got you here won’t necessarily get you there.
One of the most common hurdles is trying to grow before the foundation is actually ready. It is easy to see a spike in revenue and assume it is time to double the size of the team or move into a larger office.
However, if your internal processes are still manual or rely entirely on your personal involvement, scaling will only magnify those inefficiencies. But have you ever stopped to ask if your current systems can actually handle ten times the volume without you being there to fix every hiccup?
When you scale prematurely, you risk burning through your cash reserves before the new growth can sustain itself. I guess it’s like trying to build a second story on a house before the cement in the foundation has even dried.
You might find that your product has not yet achieved a perfect fit with the larger market, or that your customer service team cannot keep up with the influx of new tickets. This creates a cycle of stress. You are constantly reacting to problems instead of building for the future.
In the early days, culture is often felt rather than defined. You know your employees, you talk to your customers directly, and there is a shared sense of mission. As you add more layers of management and dozens of new hires, that direct connection starts to fade.
It’s a bit unsettling when you walk through the office and realize you don’t know everyone’s name anymore.
Maintaining a strong company culture during rapid growth is incredibly difficult. New employees may not understand the original values that drove the business. Communication becomes more formal and less frequent.
And if you are not careful, the soul of the business can get lost in a sea of spreadsheets and performance metrics. This dilution of culture often leads to lower employee engagement and, eventually, a decline in the quality of work.
For many founders, the biggest challenge of scaling is themselves. In the beginning, you are the person who does everything. You are the salesperson, the visionary, and the person who fixes the coffee machine. To scale successfully, you have to transition from a doer to a leader.
So, are you prepared to step back and let someone else take the wheel on the day-to-day decisions?
This requires a massive shift in mindset. You have to learn how to delegate real authority, not just tasks. If every decision still has to go through you, you become the ultimate bottleneck. Scaling requires trusting other people to make mistakes and learn from them.
It means spending more time on strategy and less time in the weeds. Many businesses stall at this stage because the founder cannot let go of the control that got them to where they are today. Maybe it is a pride thing, or maybe it is just a habit. Either way, it’s a hurdle.
Growth is expensive. You often have to spend money on hiring and infrastructure months before you see the return on that investment. This creates a significant strain on cash flow.
Many businesses grow themselves to death because they do not have the capital to support their expansion. They take on large contracts that they cannot fulfill or hire too many people too quickly without a clear path to profitability.
Managing finances at scale requires sophisticated forecasting and a deep understanding of your unit economics. You need to know exactly how much it costs to acquire a customer and how long it takes for that customer to become profitable.
Additionally, many growing companies find that leveraging equipment financing is a vital way to acquire the necessary tools and technology for expansion without depleting their immediate working capital.
It’s a smart move, really. It keeps the cash where it needs to be, right in your operations.
What worked for a team of five will almost certainly fail for a team of fifty. Scaling requires a level of operational discipline that many startups find boring. You need systems that are repeatable and documented.
If your knowledge only exists in the heads of a few key employees, your business is fragile. Scaling requires investing in technology and software that can automate repetitive tasks.
It means creating standard operating procedures so that a new hire can be productive in a week rather than a month. Without this infrastructure, growth feels like chaos. You will find yourself constantly firefighting instead of focusing on the big picture.
The hum of the laptop at midnight becomes a lot louder when you’re fixing errors that a simple system could have prevented.
As volume increases, quality often takes a hit. It is much easier to provide a premium experience to ten customers than it is to ten thousand. When you scale, you have to find ways to maintain your standards without your personal oversight on every project.
And that leads to a tough question: Can your brand survive a dip in quality while you figure out the logistics of growth?
Customers who loved you when you were small will notice if the service becomes impersonal or the product quality drops. In a world of social media and instant reviews, a decline in quality can be fatal to a growing brand.
Successful scaling involves building quality checks into every stage of the process so that excellence becomes a system rather than an accident of hard work.
Hiring is always hard, but hiring at scale is a different beast entirely. When you need to fill roles quickly, it is tempting to lower your standards just to get a body in the seat. This is a mistake that will cost you dearly in the long run.
One bad hire in a small company is a problem. Five bad hires in a growing company can change the entire trajectory of the business. You need a hiring process that screens for both skill and cultural fit. You also need to think about leadership roles.
The people who helped you get the business off the ground may not be the same people who are best suited to lead large departments. Navigating these transitions with empathy and clarity is a major part of the scaling journey.
Finally, scaling often brings a lot of shiny object syndrome. As you become more successful, more opportunities will come your way. You might be tempted to launch new products, enter new markets, or start new partnerships.
But is it better to be a master of one thing or mediocre at five?
Scaling a business requires more focus, not less. Trying to do too many things at once will spread your resources too thin and confuse your team. The most successful companies scale by doing one or two things exceptionally well at a much larger scale.
They have the discipline to say no to good opportunities so they can say yes to the great ones.
Scaling is a marathon, not a sprint. It requires a balance of ambition and patience. By focusing on your foundation, your people, and your core values, you can navigate these challenges and build a business that stands the test of time.
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Addicted2Success Editor
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About 10 years ago I had the chance to be exposed to real Buddhist teachings—and by “real” I mean coming from a real Geshe monk who had been practicing Tibetan Buddhism for more than 20 years. It was a serendipitous encounter at the co-working space I used to manage in Bucharest. The Geshe visited us for 2 days, held a couple of events and, as a result, a local group based on his teachings was started. I was also personally involved in the seeding of that group, but life unfolded for me differently: a couple of years after that I left Romania, following my location independence calling and moved to Spain. That was the beginning of an 8-year-long trip, still unfolding, that took me to Spain, as I said, and then Portugal, and then Asia, with stays in Korea, Thailand and, recently, Vietnam.
During this time I did my best to follow the teachings and that was by far one of
the best things I did. I am by no means a monk, and I do not aim at becoming one. But I
am grateful every day for my renewed understanding of the world through Buddhist
lenses.
Why this long introduction?
Well, one of the things I wanted to do for a long time was to shorten the path between my tech endeavors and the practice. As you know, I’m a geek, that’s how I put bread on the table, and I’ve been a coder for more than 35 years. What if, instead of separating practice from work, I could bring them together? What if I could find a way to integrate the teachings into my coding, or into my apps?
That’s how Zen Tales – Buddhist Stories was born. It’s an app that lets you listen
to short Buddhist stories adapted from various public domain sources. They range from
koans to Buddha life stories, packed as short intermezzos (one to four minutes) that
can be interwoven into the fabric of your day at any moment.
I went the extra mile here, and, on top of the listening experience, I added a
little bit more.
After each story is listened to, you can start a series of reflections on that piece, with the help of a specially crafted AI model. Let’s say you finished listening to the koan about “What is the sound of one hand clapping?” You can now tap on a series of pre-made reflections, like “Have you ever understood something by giving up rather than figuring it out?” and the AI model will gently give you more insights, based on the story and on general Buddhist principles.
There are 50 hand-picked stories in this first release, and each of them has 3
pre-made reflections. What happens after you tap on all 3 reflections? Well, you get
your own chat window and can ask your own free-form questions.
Of course, as with any app, there are some guardrails and incentives, like in-app purchases for more chat credits (like going to a retreat to deepen your wisdom). There is no advertising, everything is clean, and for those who really get the benefits there is even a “Practice Dana” section in the Settings, where you can express your gratitude with small tips (like lighting a candle, or ringing the temple bell).
All in all, Zen Tales is the app I wish I’d had 10 years ago. I hope it will support your practice.
Even if you’re not practicing Buddhism, I hope you’ll find some food for thought—or,
who knows, some genuinely useful wisdom—in this ever-changing Samsara.
You can download the app here: https://apps.apple.com/us/app/zen-tales-buddhist-stories/id6758518121
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dragos@dragosroua.com (Dragos Roua)
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“Compassion,” Karen Armstrong wrote in her stirring meditation on the true meaning of the Golden Rule, “asks us to look into our own hearts, discover what gives us pain, and then refuse, under any circumstance whatsoever, to inflict that pain on anybody else.” But when our own hearts are gripped with the threat and terror of imminent pain, how can we step outside this fear-fraught circumstance and consider, with kindness and openhearted goodwill, the reality of another?
That’s what the wise and wonderful Oliver Sacks (July 9, 1933–August 30, 2015) captures in one of the many ennobling anecdotes in On the Move: A Life (public library) — his altogether magnificent memoir of love, lunacy, and a life fully lived.
He recounts an incident from the spring of 1963, in the heyday of motorcycling and weightlifting obsession, embedded in which is an allegory of the singular genius that would come to define his career and legacy — the delicate and demanding art of peering into another’s mind with empathetic curiosity and seeing the vulnerable humanity that animates it.
Dr. Sacks writes:
I was riding along Sunset Boulevard at a leisurely pace, enjoying the weather — it was a perfect spring day — and minding my own business. Seeing a car behind me in my driving mirror, I motioned the driver to overtake me. He accelerated, but when he was parallel with me, he suddenly veered towards me, making me swerve to avoid a collision. It didn’t occur to me that this was deliberate; I thought the driver was probably drunk or incompetent. Having overtaken me, the car then slowed down. I slowed, too, until he motioned me to pass him. As I did so, he swung into the middle of the road, and I avoided being sideswiped by the narrowest margin. This time there was no mistaking his intent.
I have never started a fight. I have never attacked anyone unless I have been attacked first. But this second, potentially murderous attack enraged me, and I resolved to retaliate. I kept a hundred yards or more behind the car, just out of his line of sight, but prepared to leap forward if he was forced to stop at a traffic light. This happened when we got to Westwood Boulevard. Noiselessly — my bike was virtually silent — I stole up on the driver’s side, intending to break a window or score the paintwork on his car as I drew level with him. But the window was open on the driver’s side, and seeing this, I thrust my fist through the open window, grabbed his nose, and twisted it with all my might; he let out a yell, and his face was all bloody when I let go. He was too shocked to do anything, and I rode on, feeling I had done no more than his attempt on my life had warranted.
Shortly after this heart-stopping encounter, Dr. Sacks found himself in a strikingly similar incident while driving to San Francisco on a desert road. An aggressive driver suddenly appeared onto the empty expanse and, moving at 90 mph, deliberately forced the motorcycle off the road. What happened next reveals Dr. Sacks as a sort of gentle giant, both deeply human in his capacity for fury and in possession of superhuman empathetic sensitivity:
By a sort of miracle, I managed to hold the bike upright, throwing up a huge cloud of dust, and regained the road. My attacker was now a couple of hundred yards ahead. Rage more than fear was my chief reaction, and I snatched a monopod from the luggage rack (I was very keen on landscape photography at the time and always traveled with camera, tripod, monopod, etc., lashed to the bike). I waved it round and round my head, like the mad colonel astride the bomb in the final scene of Dr. Strangelove. I must have looked crazy — and dangerous — for the car accelerated. I accelerated too, and pushing the engine as much as I could, I started to overtake it. The driver tried to throw me off by driving erratically, suddenly slowing, or switching from side to side of the empty road, and when that failed, he took a sudden side road in the small town of Coalinga — a mistake, because he got into a maze of smaller roads with me on his tail and finally got trapped in a cul-de-sac. I leapt off the bike (all 260 pounds of me) and rushed towards the trapped car, waving the monopod. Inside the car I saw two teenage couples, four terrified people, but when I saw their youth, their helplessness, their fear, my fist opened and the monopod fell out of my hand.
I shrugged my shoulders, picked up the monopod, walked back to the bike, and motioned them on. We had all, I think, had the fright of our lives, felt the nearness of death, in our foolish, potentially fatal duel.
On the Move, for reasons articulated here, remains one of the most moving books I’ve ever read. Complement this particular passage with Jane Goodall on empathy and Brené Brown on the crucial difference between empathy and sympathy, then revisit Oliver Sacks on storytelling and the curious psychology of writing, the paradoxical power of music, and this final farewell to the beloved science-storyteller.
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Maria Popova
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You know that feeling when you’re busy all day but still can’t find your keys, your to-do list, or that one document you swear you just had? Disorganization is rarely a single big mess.
It’s usually a handful of tiny habits that quietly stack up until home feels cluttered and work feels chaotic.
The good news is that you don’t need a perfect system. You need a few repeatable routines that make staying organized the default.
If you wait for a free Saturday to get organized, it probably won’t happen. Instead, bookend your day with quick resets.
Morning: clear one surface you’ll use a lot, like the kitchen counter or your desk.
Evening: put five to ten items back where they belong and set out what you’ll need tomorrow.
That tiny rhythm reduces the daily buildup that turns into weekend stress. And when you do tackle a deeper clean, remember that even your workspace affects your thinking. Clear desk, clearer thinking explains why the physical environment can shape how well you focus.
Organization falls apart when items don’t have a clear place to live. Aim for obvious, easy-to-reach homes for high-traffic categories such as keys, chargers, mail, shoes, and work supplies.
A simple rule helps: the more often you use something, the fewer steps it should take to put it away. Hooks beat hangers. Open bins beat lidded boxes. A tray by the door beats setting things down temporarily.
If you need inspiration, the idea of building routines around zones and small maintenance habits is worth borrowing from easy habits for a tidy home and applying room by room.
Paper is sneaky. It starts as one letter and turns into piles that you avoid because sorting them feels like a project.
Create a single paper command center with three folders or trays:
If you send time-sensitive documents or need proof something was delivered, keep supplies together so you don’t have to hunt them down. Certified Mail Labels can help streamline the process when mailing important documents with tracking and confirmation.
Daily habits keep things from piling up, but a weekly reset keeps you ahead. Pick one consistent time, such as Sunday evening or Friday afternoon, and do a quick sweep.
Keep it short and specific:
Staying organized is less about being perfectly neat and more about reducing the small daily decisions that drain your energy. Start with a five-minute reset, create simple homes for essentials, and manage your paper flow intentionally.
Within a week, you’ll likely feel more focused and in control.
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Ask about CT angiography. If you have risk factors for heart disease (high blood pressure, high cholesterol, diabetes, family history, or smoking), ask your doctor whether a coronary CT angiography might be appropriate. It’s the imaging technique used in this study and can detect plaque before it causes symptoms.
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