The Age of Imagineering

“We choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard.”

More than sixty years ago, President Kennedy stood before a crowd in Houston and asked a nation to imagine something that, at the time, bordered on the impossible. The technology was not ready. Some of the materials required did not yet exist. The systems had not been engineered. The problems had not been solved.

But the destination had been imagined.

That distinction has been on my mind lately because I believe we may be living through one of the most significant transitions in human history, and I do not think we fully understand yet what is changing. I do not mean biological evolution in the traditional sense. I mean the evolution of human capability.

The evolution of human capability

For most of our history, progress has been defined by our ability to overcome constraints. We learned to control fire, build tools, cultivate food, survive disease, cross oceans, fly through the atmosphere, and eventually leave the planet. Each major technological leap extended some part of ourselves. Tools extended our physical strength. Writing extended memory. Telescopes extended vision. Computers extended our ability to calculate. The internet extended our ability to communicate and access information.

Artificial intelligence feels different because it extends the thing behind all of those inventions: intelligence itself.

I see this becoming more tangible every day while working with AI in an enterprise environment. Until very recently, the first questions surrounding an ambitious idea were practical ones. Do we have enough people? Do we have the right developers? Do we have the expertise? What will it cost? How many months will this take? Can the organization realistically execute it?

Increasingly, those questions are giving way to a more interesting one: what should we build? That shift is easy to underestimate.

Software that once required large teams, deep specialization, significant capital, and months or years of coordinated work can increasingly be prototyped by a small number of people in days, sometimes hours. Expertise still matters. Architecture, security, judgment, context, and domain knowledge still matter enormously. But the relationship between expertise and execution is changing.

A person no longer needs to personally possess every technical skill required to bring an idea into existence. Increasingly, that person needs to understand the problem, imagine the desired outcome, communicate it clearly, and direct intelligence toward the solution.

That shift also raises a commercial question: what are we paying for when the work takes minutes?

The Age of Imagineering

A colleague, Alex Mendoza, recently introduced me to the phrase “forward-deployed imagineering,” and it immediately struck me as a useful way of thinking about this transition. We may be moving into an era where execution becomes less of a limiting factor and imagination becomes more important. I have started thinking of this as the Age of Imagineering.

The Industrial Age multiplied our physical capacity. The Information Age dramatically expanded our ability to store, process, and distribute knowledge. The Age of Imagineering could be defined by something different: a collapse in the distance between an idea and its realization.

For most of history, ideas were cheap and execution was expensive. You could imagine a product, a machine, a company, or a piece of software, but turning that idea into reality required access to capital, specialized expertise, infrastructure, and labor. Many good ideas never moved beyond the imagination of the person who had them because the cost of execution was simply too high.

AI is beginning to change that equation. Today, we can describe a system and have artificial intelligence help architect it, write portions of the code, generate documentation, test assumptions, identify vulnerabilities, research alternatives, and deploy infrastructure. As AI agents become more capable, the amount of human effort required between intention and execution will continue to shrink.

From thought to physical outcome

Now extend that trajectory beyond software. Combine increasingly capable AI with robotics, automated manufacturing, autonomous laboratories, synthetic biology, advanced materials, and eventually more natural interfaces between human beings and machines. The idea of moving from thought to physical outcome starts becoming less abstract.

At some point, the process may look less like traditional engineering and more like expressing intent. A person identifies a problem, describes the outcome they want, and a network of intelligence and machines determines how to produce it. The system researches, designs, simulates, builds, tests, and iterates. The human remains involved, but increasingly at the level of judgment, direction, and imagination rather than performing each layer of execution manually.

If access to intelligence becomes abundant, what becomes scarce?

That raises an interesting question. If access to intelligence becomes abundant, what becomes scarce?

I suspect imagination becomes far more valuable. So do curiosity, judgment, taste, perspective, empathy, wisdom, and lived experience. Knowing how to write code may matter less in some contexts than understanding which problem is actually worth solving. Knowing every technical detail of a system may matter less than being able to imagine what the system should accomplish and recognize whether the result is good.

This does not make expertise irrelevant. If anything, deep experience may become more valuable because it gives people better raw material from which to imagine. Someone who has spent twenty years working in healthcare, logistics, finance, manufacturing, or education has accumulated thousands of observations about where systems fail, where people struggle, and where opportunities exist. AI gives that person an increasingly powerful way to translate those observations into working solutions.

Every human being carries a unique combination of experiences. Where we grew up, the jobs we held, the people we knew, the problems we encountered, the things we failed at, the things we became obsessed with, and the seemingly unrelated interests we collected over a lifetime all shape the ideas we are capable of having.

Historically, only a tiny fraction of those ideas could be realized. Execution filtered most of them out. That filter is weakening.

Who gets to create?

This is also why I think the conversation about AI becomes much more interesting when we move beyond the question of whether it will eliminate particular jobs. Employment is obviously important, and the disruption will be real, but jobs may be only one small part of a much larger historical transition.

The more profound question is what happens when billions of people gain access to capabilities that once belonged only to governments, large corporations, elite universities, and highly specialized technical teams.

What happens when a teacher can build software for her classroom without becoming a software engineer? What happens when a doctor can explore a new workflow without assembling a development organization? What happens when a small business owner can automate processes that once required an IT department? What happens when a scientist can work alongside AI systems capable of exploring thousands of hypotheses? What happens when an individual can direct the equivalent of an entire team of researchers, developers, analysts, and designers?

The answer will not simply be more productivity. It could change who gets to create.

A different kind of human evolution

That brings me back to the idea of human evolution. I sometimes think about the periods in prehistory when different human populations lived alongside one another. Neanderthals and Homo sapiens interacted, competed, cooperated, and interbred. It would be too simplistic to describe that history as one species merely being a more intelligent version of another. Human evolution was far more complicated than that.

But as a thought experiment, I wonder what it would have felt like to live during a period when the trajectory of humanity itself was changing. Did anyone notice? Could any individual living through that transition have understood what was happening over generations?

Perhaps not.

That possibility makes our current moment fascinating because this time the transition may be visible while we are living through it. It is not primarily occurring through biological selection over hundreds of thousands of years. It is occurring through tools, culture, and technology on a timescale of decades.

Human beings have always augmented themselves. Clothing changed where we could live. Glasses altered our vision. Books gave us access to thoughts from people who died centuries ago. Smartphones outsourced portions of memory, navigation, communication, and information retrieval. Very few of us think of ourselves as cyborgs when we use these technologies because the integration happened gradually enough to feel normal.

Artificial intelligence may simply represent a much deeper version of the same pattern.

Where does individual capability end?

Today, AI largely sits outside of us. We access it through screens, keyboards, microphones, and software. Over time, those interfaces will likely become less visible. AI systems will understand more of our context, history, preferences, work, and intentions. Brain-computer interfaces may eventually make the interaction even more direct.

At some point, the distinction between “my intelligence” and “the intelligence available to me” may become increasingly difficult to define. If I can instantly access knowledge I do not personally remember, reason alongside systems far more capable than myself in specific domains, communicate an idea and have it executed across digital and physical systems, where exactly does my individual capability end?

Perhaps the important concept eventually stops being artificial intelligence versus human intelligence. Perhaps it is simply intelligence, expressed through different substrates and combined into increasingly powerful systems.

The oldest human story

That possibility does not diminish humanity. I think it could represent the continuation of the oldest human story.

We have always used intelligence to escape constraints that biology alone could not overcome. Our bodies were not designed to survive winter, so we made clothing and shelter. We were not built to fly, so we built aircraft. We cannot survive in space, so we built spacecraft. We cannot naturally communicate across continents, so we built global networks.

Our greatest adaptation has never been claws, speed, strength, or armor. It has been our ability to imagine something that does not yet exist and then create it. Now we are building intelligence that can participate in that process with us.

If humanity survives for another thousand years, ten thousand years, or a million years, it is difficult to imagine that our descendants will remain biologically and technologically identical to us. They will adapt to new environments. They may augment themselves. They may live throughout the solar system and eventually beyond it. The conditions of life may be so different from ours that we would have trouble recognizing their world.

Artificial intelligence could be one of the primary technologies that makes that future possible, not because AI represents the end of humanity, but because intelligence has always been the mechanism through which humanity has transcended its limitations. For the first time, we are learning how to create, scale, and distribute intelligence itself.

Bigger than another wave of software

That is why I think this moment is bigger than another wave of software. We talk about models, agents, benchmarks, tokens, productivity, and automation because those are the things directly in front of us. They are important, but future generations may view them the way we view the technical details of the first steam engines. Historically significant, certainly, but only the opening chapter of something much larger.

The deeper story may be that humanity reached a point where intelligence was no longer confined to biological brains and execution was no longer the primary barrier between imagination and reality.

The Industrial Age asked us what we could manufacture. The Information Age asked us what we could know and communicate. The Age of Imagineering may ask a much more expansive question:

What can we imagine, once imagination becomes the limiting factor?