The Best of Times

“There is no energy crisis, only a crisis of ignorance.”
— R. Buckminster Fuller

There are two visions of prosperity that have always competed in my imagination.

The first is the one we see in architectural renderings of the future: gleaming glass towers rising above verdant parks, magnetic trains gliding silently between districts, vertical farms feeding millions, clean energy powering everything. A world where cancer is cured, where we travel effortlessly, where abundance flows from the command of powerful technologies. This is the prosperity of capability, what becomes possible when human ingenuity meets powerful tools.

The second vision is quieter, but no less profound. It's the one I often find in the emerging markets that I love traveling through, in villages where families live with dignity in their painted cinder-block homes. Where people have time for you, where smiles abound and warm cups of tea await, and where those who stay do so because they love their life there. This is the prosperity of meaning. It is what becomes possible when humans have enough to live well.

Throughout history, we've been forced to choose between these two visions. The gleaming towers existed, but only for the privileged few who could afford Park Avenue penthouses and Mayo Clinic treatments. The simple dignity of the idyllic village existed in scattered pockets, but always came with a terrible cost: no access to modern medicine, no ability to travel beyond your village, no opportunity for your brilliant daughter to become an engineer.

Most of the world sat in between, with neither.

The middle-class American dream of the 1950s came closest to bridging this gap. Factory workers could afford homes, healthcare, and college for their kids. But even that prosperity was limited, bound by geography, by the manual labor required to produce it, by the fact that only some nations could achieve it while others remained trapped in poverty. And it’s gone.

If we make the right choices, we can have the gleaming towers and the gardens of Eden. We can have advanced medicine and time with family. We can have global travel and deep local roots. We can have breakthrough technologies and communities where people know their neighbors' names. But only if we make the right choices.

The Fractal Nature of Progress
Here's what most people get wrong when they imagine an automated future: they think the problems are solved and just disappear. AI solves everything, robots build everything, and humans have nothing left to do. But that's not how problems work.

Problems are fractals. The closer you look, the more you see. Solve one, and you reveal ten more inside. This is the fundamental nature of science. Frontiers expand. Take something as simple as "solve global warming." That breaks down into: transition to renewable energy, capture existing carbon, adapt infrastructure for climate resilience, shift agricultural practices.

Pick just one: transition to renewable energy. That breaks down into: improve solar cell efficiency, solve battery chemistry for storage, redesign electrical grids, retrofit buildings, create new manufacturing processes, figure out recycling for old panels, manage the supply chain for rare earth materials.

Pick just one of those: improve solar cell efficiency. That breaks down into: test new materials, model quantum effects, design manufacturing processes, optimize for different climate conditions, reduce production costs, improve durability, figure out installation methods for different roof types.

Pick just one of those: test new materials. That breaks down into: synthesize candidate compounds, run durability tests, measure efficiency across temperatures, analyze failure modes, optimize crystal structures, scale from lab to production.

And it keeps going. A knowledge tree. Every solution reveals more potential solutions. Every puzzle solved unlocks new possibilities that themselves need solving.

Individual breakthroughs unlock cascades of innovation. The transformer architecture didn't just improve language models. It spawned ChatGPT, code generation, protein folding prediction, and thousands of derivative applications that are themselves causing cascades of innovation. mRNA technology didn't just give us a vaccine platform. It opened entirely new frontiers in medicine, from cancer treatments to personalized therapies. An advanced microscope doesn't just let us see smaller. It reveals new materials, new structures, new possibilities across semiconductors, drug design, and materials science.

Healthcare isn't just "cure diseases". It's endless puzzles about diagnostics, treatments, prevention, delivery, training, cultural adaptation. Education isn't just "teach students". It's infinite variations on how to reach different minds, in different contexts, with different needs. Housing isn't just "build houses". It's millions of potential decisions about materials, techniques, designs, systems, local contexts. This is true for every aspect of building a better world.

Like the cosmos, the further we can see, the more we discover there is to see.

The work never runs out. The problems are inexhaustible.

And here's the critical insight: every single one of these problems, from the grandest to the tiniest, requires a human paired with the most powerful tools available to solve it.

You can't just tell an AI "solve global warming" and walk away. You need humans working with AI to break down the problem, evaluate options, understand contexts, make tradeoffs, adapt solutions to real-world constraints. You need people who understand both the technology and the domain, who can see what the AI misses and direct it toward what matters.

You can't just tell robots, "build affordable housing" and disappear. You need humans who understand what makes a home livable, who can adapt designs to local needs, who can coordinate systems, who can make the thousand tiny decisions that turn a structure into a place people want to live.

The beautiful future, whether it's gleaming towers or garden villages, is built from millions of these small acts of human intelligence combined with powerful tools. Every puzzle is waiting for someone who knows how to use the right technology to solve it.

The question isn't whether there will be enough work for humans in an age of AI and robotics.

The question is: will there be enough humans who know how to do that work?

Abundant Labor

For most of human history, prosperity has required massive amounts of physical labor. Building cities. Growing food. Manufacturing goods. Moving materials. Caring for the sick. That labor had to come from somewhere. And for millennia, it came from the exploitation of humans.

Slaves built the pyramids and the Roman roads. Serfs worked the fields of medieval Europe. Colonial subjects extracted resources under brutal conditions. Desperate workers toiled in factories for pennies. The great civilizations, the monuments we admire, the prosperity we inherited: much of it was built on the backs of people whose lives were crushed to create it.

This is the irony at the heart of human history: prosperity required grunt work, and grunt work meant someone's potential was stolen, someone's dreams were extinguished, someone's life was diminished so others could thrive.

We've made progress. We've abolished the worst forms of exploitation. But the basic pattern remains: someone still has to do the hard, dangerous, repetitive work. Construction workers in 110-degree heat. Agricultural laborers bent over crops for twelve-hour days. Factory workers on assembly lines. Their labor is compensated now, yes. But it's still backbreaking. Still dangerous. Still paid a pittance. Still not what any parent dreams for their child.

For the first time in history, we have an alternative. As Norbert Wiener put it in Cybernetics, “Let us remember that the automatic machine is the precise economic equivalent of slave labor.”

Robots can do the grunt work. Not humans who suffer, but machines that don't. Construction robots that can work around the clock without exhaustion. Agricultural robots that can plant and harvest without breaking their backs. Manufacturing robots that can repeat precise tasks without mind-numbing boredom.

This is the promise: The physical labor still happens. We still need houses built, food grown, goods manufactured. But machines do it. Without suffering. Without crushed dreams.

Robots can be our slaves. And unlike human slaves, this doesn't create a moral catastrophe. It resolves one.

But here's the question that determines everything: whose robots are these?

We’ll come back to that one in a bit.

The Convergence: To Build A Better Future

The massive improvements in intelligence and robotics converge. Together, they unlock entirely new paradigms in some of our most important industries.

Let's double click into construction. The built environment is one of the markers of the heights of civilization (think of the grandeur of Paris or Rome). It is one of the core drivers of quality of life (from the town square to a spacious living room) and is the single largest cost of living (on average accounting for 25-35% of income). A revolution in construction could have as profound of an effect on the lived human experience as anything. I count it as among the most important industries to breathe life into and yet this $11 trillion industry is still built upon the same technologies of our great-grandparents: concrete, rebar and structural steel.

When Elon Musk was starting SpaceX, he realized something important: “If you say, what is a rocket made of? It's made of aluminum, titanium, copper, carbon fiber. And you can break it down and say, what is the raw material cost of all these components? And if you have them stacked on the floor and could wave a magic wand so that the cost of rearranging the atoms was zero, then what would the cost of the rocket be?” The answer was that the raw material cost was only 2% of the cost of a rocket. With that insight, he set forth to make rockets.

Imagine if Elon Musk took that same magic wand approach to construction? What would he do?

I imagine him pointing all of his genius, and all of his geniuses, and all of his dollars, at creating reams of code and mountains of machines. He would embrace the messiness, trying the crazy ambitious ideas, letting buildings break spectacularly to get something that works even more spectacularly. He would throw young geniuses at the problem and give them latitude to run at it. He would patiently iterate through the engineering until he got what he needed. He would throw the dollars necessary at the problem. Mostly those dollars would go to hiring smart people, to steel, to compute power and motors. I imagine them huddled, debriefing their prototype as they build towards a world in which you press a button and a building emerges from the ground.

I imagine launch: entire towers sprouting from the earth as if by some magical force.

What would it look like if an entire generation of young engineers tackled housing this way?

The Ecosystem of Innovation

Consider just the technologies currently in development: 3D printing systems that can extrude entire walls. Robotic brick-laying that's faster and more precise than human masons. Autonomous systems that can frame, wire, and finish buildings with minimal supervision.

Each of these sounds simple when you say it like that. But zoom in. The complexity explodes.

Take 3D printing for construction. It seems straightforward until you realize: we need materials that can support multi-story loads while still being printable. We need fast-drying compounds that set quickly enough to keep construction moving but not so fast they clog the printer. We need methods to embed plumbing and electrical conduits during the printing process, not after. We need structural engineering that accounts for the unique properties of printed buildings - the layer lines, the material distribution, the way forces flow through printed structures differently than traditional framing.

Or robotic brick-laying. Seems simple - just stack bricks, right? But someone needs to develop the computer vision systems that can identify defects in real-time. The actuators precise enough to place each brick within millimeters. The algorithms that optimize mortar application for different temperatures and humidity. The coordination systems that manage material delivery to keep the robot fed. The quality control systems that verify structural integrity as the wall goes up.

AI-enhanced design tools enable the sort of architecture that we drool over on Instagram, structures that are optimized for beauty and material efficiency simultaneously - creating flowing, organic forms that would be impossible to build with traditional methods. You'd need design software that gives architects precision control over every curve and surface, then automatically generates construction drawings and machine-readable instruction sets that robots can execute.

Every technology that feels like "a simple innovation" is actually an ecosystem of dozens of sub-innovations. Fast-drying concrete alone requires materials scientists developing new compounds, chemists optimizing setting times for different climates, engineers designing mixing and delivery systems, roboticists creating application methods, quality experts developing testing protocols. This is probably thousands of companies, each specializing in different pieces of the stack: design tools, structural analysis, material optimization, robotic coordination, quality control, all powered by an interoperable software ecosystem.

And here's the critical part: each of these innovations requires humans who are specialized in their domain, armed with the most powerful tools available.

We need materials scientists working with AI to model material properties. We need structural engineers using simulation tools to verify that printed buildings can withstand earthquakes and hurricanes. We need roboticists coordinating fleets of machines with software that adapts to changing conditions on the job site. We need construction coordinators who understand both traditional building and emerging automation, bridging the old world and the new.

Labor typically accounts for 20-40% of total construction costs. At its extreme, as Sam Altman put it, “if robots can build a house on land you already own from natural resources mined and refined onsite, using solar power, the cost of building that house is close to the cost to rent the robots. And if those robots are made by other robots, the cost to rent them will be much less than it was when humans made them.”

And, with the right AI-enabled design software, these would be architectural masterpieces.

This world is possible, if we have the abundance of technical talent it takes to create this world.

Yes, there are a slew of realities slowing progress in construction and every other industry. Regulations and unions, material properties uncertainty, complexity in integrating tech stacks. But those are simply explanations of why progress is slow. But all of them are addressable. And in a society of technically sophisticated people, we see those manmade impediments crumble.

You'd replace jobs, of course, but instead of some young person pouring concrete, they would grow up to be the person optimizing the actuator on a robotic arm that could be used for building all buildings going forward. For every young person we turn into someone capable of advancing the frontier, we create both a better job for that person and a better technology for the rest of us.

The Multiplier Effect

And this is just construction. The same pattern repeats across every industry that matters.

In agriculture: precision farming systems need agronomists working with AI, roboticists developing harvesting machines, data scientists optimizing yields, supply chain coordinators connecting farms to markets. The result: abundant, healthy food (typically 10-15% of income).

In healthcare: diagnostic AI needs doctors who can interpret results in context, robotic surgery needs surgeons who can direct the systems, drug discovery needs researchers working with AI to identify candidates, healthcare coordinators ensuring systems integrate. (8-12% of income.)

In education: AI tutoring systems need educators who understand pedagogy, content creators developing adaptive materials, learning scientists studying what actually works, coordinators ensuring technology serves students rather than replacing human connection.

Each field requires an army of humans wielding modern tools. Each innovation unlocks ten more that need solving. Each solved problem reveals new possibilities.

We have no shortage of problems to solve.

We have a shortage of people who can arm themselves with the most powerful technologies to solve them. And these technologies are only going to get more powerful, more quickly, with every improvement in AI, every advance in robotics, and every tool that those two unlock.

We are on the cusp of having the tools to tackle all of these problems. In the Best of Times, we also have the humans equipped to harness them, ready to build solutions in every corner of the world's greatest challenges. That's the convergence. Intelligence meets labor. Humans meet machines. And together, they build the future that's been waiting to emerge.

The Abundance That Awaits
Let me paint you a picture of what that future could look like.

It begins with an ordinary morning.

A parent wakes up in a home that is solid, beautiful, and affordable, not because it was subsidized, but because the cost of building collapsed. The walls regulate temperature. Energy is cheap. Housing is no longer the source of constant anxiety it once was.

Breakfast is simple. Food is fresh, local, and plentiful. The fear of scarcity, of prices spiking, of supply chains snapping, has receded. Agriculture is precise now. Resilient. Quietly efficient.

Children leave for school, but “school” no longer means a fixed track decided early and rarely escaped. Learning adapts to them. Tools amplify curiosity. Mentors guide. Progress is visible, earned, and cumulative.

And somewhere in a town like the ones I love, a brilliant daughter becomes an engineer, not by leaving her community behind, but by connecting it to the world. She contributes to real problems. She earns real income. She stays because she wants to.

Work feels different. Machines do the lifting, the repetition, the dangerous tasks. Humans do the judgment. The coordination. The design. The care. A former laborer now oversees robotic systems. A farmer spends more time thinking than straining. A nurse spends time with patients instead of paperwork.

What changed wasn’t just technology. It was who could use it.

The skills to wield intelligence, once locked inside elite institutions, became universal. Everyone learned how to work with AI. How to break problems down. How to contribute small pieces to large systems. How to turn insight into value. Everyone became a creator. Everyone earned something. Not as charity, but because of their contribution.

Income no longer came only from owning capital or selling exhausted hours. It came from solving problems, locally and globally. From adding value wherever you stood. The floor rose, quietly but permanently. No one was invisible. No one was told their best role was to wait.

Outcomes still varied. Ambition still mattered. Talent and taste still shaped lives. But dignity became universal, because contribution was universal.

This is what an equal society actually looks like.

Cities became more humane. Communities re-formed, not because people were forced together, but because they finally had time and greater equality.

And here’s the truth most depictions of the future get wrong:

This world was not built by AI. It was built with it, by millions of people who know how to wield powerful tools in service of real problems. People who could see systems, make tradeoffs, adapt solutions, and improve what came before. It was built by human intelligence.

The final constraint was no longer materials, or energy, or even capital. It was human capability.

If we get it right, if intelligence and labor truly converge and if everyone can build, then we don’t just get a richer world.

We get the best of times.

But the same technologies that build that world can build a very different one. Same robots. Same AI. Same fractal of problems. The variable is who knows how to wield them.