Friction Has Not Disappeared
In 1987, a surgeon in Lyon, France, performed one of the first laparoscopic cholecystectomies: a gallbladder removal using a camera and instruments inserted through tiny incisions rather than traditional open surgery.
The open surgeons were horrified. Not because the procedure was dangerous, but because it violated something they held sacred: the tactile relationship between the surgeon's hand and the patient's body. In open surgery, you felt the tissue. You knew through the resistance of your fingers where the gallbladder ended and the liver began. The friction of your hands in the body cavity was not an obstacle. It was your primary source of information.
They were partly right. Something real was lost. Surgeons trained exclusively on laparoscopic techniques do not develop the same tactile intuition as open surgeons. The embodied knowledge that comes from hands inside a body, feeling the difference between healthy tissue and diseased tissue, navigating by touch in a space where sight alone is insufficient – that knowledge disappeared from the discipline.
But something far more powerful was gained.
Laparoscopic surgery made possible operations that open surgery could never attempt – procedures in tight spaces, at odd angles, with a precision the human hand alone could not achieve. Recovery times collapsed from weeks to days. Infection rates plummeted. Patients who would have spent a month in the hospital went home the same afternoon. Lives were saved.
The surgeon was no longer wrestling with tissue; she was wrestling with the interpretation of a two-dimensional image of a three-dimensional space, with the coordination of instruments she could not directly feel, with the cognitive challenge of operating at a remove from the body. The work was harder. But harder at a higher level.
This is the single most important rebuttal to Han's arguments.
Han believes that when friction is removed, depth disappears. I agree in part. There is a real, often quantifiable loss when difficulty is smoothed out. But Han makes an error in assuming that the friction that has been removed is the only friction that matters. It is not. It is the friction that was there. The friction that matters is the friction that replaces it.
I call this ascending friction. In the same way you are climbing the tower with me. The principle that every significant technological abstraction removes difficulty at one level and relocates it to a higher cognitive floor. The difficulty does not vanish. It climbs.
The critique that abstraction produces shallow practitioners has been issued at every transition in the history of computing. Assembly language forced you to think about every memory address, every register, every instruction the processor would execute. When compilers abstracted that away, the critics said, “You will lose the understanding of the machine.” I must confess that I also hold onto a romanticized idea that the reason I have succeeded in running extremely technical teams is the fact that I was “raised by the machine code.” That somehow I absorbed a type of primal thinking that scaffolded my mind's ability to navigate all computer science challenges life has thrown my way.
Almost all programmers today cannot write assembly. But the programmers freed from assembly built operating systems, databases, and networked applications of a complexity that assembly-era programmers could not have conceived.
The lost depth was real. The gained breadth was larger.
Frameworks abstracted away code structure: routing, templating, database connections. The critics said, “You will lose understanding of the architecture.” They were right again: Most framework users could not build the framework they depend on from scratch. But the applications they built on top of those frameworks – real-time collaboration tools, machine learning pipelines, global distribution systems – represent a level of architectural thinking that hand-coders could never reach, because their bandwidth was consumed by the plumbing.
Cloud infrastructure abstracted away server management. I remember vividly the weeks that followed the launch of the first system my team built on AWS (Amazon’s pioneering cloud). It was such a departure from maintaining our own servers and needing to send someone to swap a server in our physical location in the middle of the night. I can’t even begin to describe what a relief this was for me and the team. It was like jumping from assembler to python on a different dimension of the tech stack. The critics warned about lost understanding of hardware, network topology, deployment. Right again. And wrong again about the trajectory. The practitioners who no longer managed servers were freed to think about scaling strategy and scalable dev-ops, system resilience, and now the use of AI to accelerate all of their workflows at a level that prior era server administrators could not remotely access.
The pattern is structural. Each abstraction simultaneously destroys a form of depth but creates an opportunity to work our way up the tower, making it possible to see further without necessarily understanding the foundations in the basement. And the view from the higher floor is worth the climb, though you cannot see that from the floor you are standing on, which is why every transition produces critics who can see the loss but not the gain.
Most of us are wired to view the present through the prism of our past experiences. Some of us have a mutation, a scratch in our makeup, a bug that is a feature.
For some of us, seeing our present through the lens of a possible future is a way of life. It’s not an easy journey, but it sure is interesting.
This applies elsewhere, too, across creative industries and the humanities and anything else being reshaped by our current moment. Knowledge and creative work is being transformed at breakneck speed. The short sighted might see just the opportunity of replacing humans with AI. The more strategic thinkers should focus on how to supercharge their teams to do both more and different work.
Even our bodies have been elevated by eliminating friction: Look at how fast an MLB pitcher throws, and how far the ball cuts over the course of sixty feet, six inches, now that coaches and players have a better understanding of the mechanics that affect a ball’s spin rate and velocity and the connection between your fingers, your wrist, your arm, your hips, your legs. Think too about how hitters have had to adjust to those improvements, by evaluating bat paths and stances and what success looks like at the plate.
These players, and most of today’s athletes, have higher ceilings because the friction along the path to greatness lessened. LeBron invests over a million dollars a year in his body and is still in the top of the NBA at 41. Cognition, thought, science elevates us on every front of our lives and in every aspect of the human condition.
That doesn’t mean it’s easy now. In fact, it means that being great takes more.
The practitioners at the higher level are not shallower. They are wider, but in a different set of multi-disciplinary dimensions. Each abstraction freed cognitive resources, but those freed resources were not wasted. They were invested in the next level of complexity. The practitioners ascended, and the friction ascended with them.
When I was debugging a null pointer exception, I was not thinking about product strategy. When I was resolving a dependency conflict, I was not thinking about whether the product should exist at all. The friction occupied the floor. I could not get upstairs.
Claude Code removed the friction of implementation – syntax, debugging, the mechanical labor of converting design into code – and relocated it to vision, architecture, product judgment, and the question no tool can answer: What should we build, and for whom? Breaking a challenge down into a set of separate teams and practitioners was the norm for my entire career. Now each of us is liberated from a trade label, and all of us can take part in a much wider set of skills that were inaccessible to us before.
The film writer-director does not operate a single camera or speak a line of dialogue. The director sees the whole movie before a single frame is shot. The narrative arc. The emotional beats. The places where the tension must mount, and the scenes where the pace must ease. The director's instrument is not the lens or the script. It is vision. It is the space between concept and final cut, held with enough conviction that an entire crew and cast can feel the shape of the reality that is being asked for and manifest it.
For most of my life, that space was enormous. The gap between what I saw in my mind and what I could communicate to the people who would build it was the hardest thing about my work. Not because my teams lacked skill. Because translation creates friction. Every conversion introduces noise. Every layer between the vision and the artifact erodes the signal. Like a life scale version of the game “broken telephone”. By the time you see work product time passes, comments are given and iteration cycles can take weeks or months.
AI gave me a better instrument. One that could hold the full complexity of what I was reaching for and play it back with enough fidelity that the orchestra could hear the same thing I heard.
That is a different kind of power than the power to execute. It is the power to articulate, to externalize a vision with enough clarity that the people around you can see it, believe it, and build toward it with the confidence that comes from shared understanding at a fraction of the time and cost.
When my team could see what the Napster Station would look like before the first screw was tightened, something shifted. Not just in the timeline. In the energy. People moved faster because they were not guessing. They were building toward something they could already see. And that clarity, more than any technical capability, is what made thirty days of development enough to develop something that would have taken 6-12 months of work in the past.
I learned that even in this age of AI acceleration. Human fast trust is not a shortcut. It is the hardest thing to build and the most valuable thing to have, and it cannot be manufactured or mandated or optimized. It can only be earned, through the specific intimacy of having navigated chaos together and survived it without losing respect for one another. Today, the term trust takes on an even more elevated meaning.
If used correctly, AI amplifies the human ingredients. It reveals how essential they always were. When the mechanical friction is gone, what remains is the thing that actually matters: the vision, the taste, the willingness to make a call when the data is ambiguous and the deadline is real and no algorithm can tell you whether the thing you are building will make someone smile or leave them cold.
I learned that amplification is not a metaphor. It is the most precise description I have found for what happens when human creativity meets AI. Not replacement. Not automation. The signal, made louder. The vision, carried further. The distance between imagination and reality, compressed to the width of a conversation.
Thirty days. An entirely new product. Standing. Talking. Alive. And we were only at the beginning.
Standing on the CES floor, watching hundreds of people interact with Station, I knew that the thirty days of building had been the easy part. The hard part was the thousand small decisions about what Station should be that were still to come.
That work was not possible before and showed how an entire team guarded by deep trust and amplified by AI can achieve the impossible.
The skill of being a “Creative Director” has been my strongest muscle most of my professional life. Now we enter an era where we all need to develop that muscle as we are all Creative Directors that can manifest any vision we can contemplate with accelerating ease. Nano Banana Render Of Station