In January 2023, ChatGPT passed a Wharton MBA exam. And like most people, I got distracted by the headline. An AI passing a business school exam. The implications for education. The implications for white-collar work. The implications for the knowledge economy.
I missed the deeper signal entirely. It took me months to see it. The deeper signal was not that a machine could pass an exam. The deeper signal was that a machine could pass an exam using natural language. No code. No programming. No technical skill of any kind. A person typed a question in plain English, and the machine answered at MBA level.
That is not an AI story. That is an abstraction story. And abstraction is the most powerful force in technology — more powerful than any individual technology, more consequential than any single breakthrough, and almost completely invisible to the people it is about to disrupt.
What abstraction actually means
Every technology in history follows the same curve. It starts complex. It starts in the hands of specialists. And then, layer by layer, decade by decade, it gets abstracted — simplified, packaged, made accessible — until eventually anyone can use it.
Electricity started with engineers wiring their own generators. Then it became a utility. You plug into the wall. You do not need to understand electromagnetic induction.
Photography started with darkrooms, chemical baths, and fifteen-minute exposures. Then it became a button on your phone. You do not need to understand silver halide crystals.
Computing started with machine code — ones and zeros punched into cards by specialists. Then assembly language. Then high-level languages like FORTRAN and C. Then visual interfaces. Then the web. Then apps. Each layer of abstraction moved computing further from specialists and closer to everyone.
This is not a trend. It is a law. Every technology gets abstracted. The endpoint is always the same: democratisation. The thing that required a specialist last decade requires a generalist this decade and requires no skill at all next decade.
Software is no exception. Software is, in fact, the most dramatic abstraction curve in history. And the next layer is being added right now. English.
The abstraction curve applies to everything
Here is the part that most people miss. The abstraction curve does not only apply to software. It applies to every technology. Including biology.
In 2023, CRISPR was a tool for trained geneticists working in specialised labs. Gene editing required deep expertise, expensive equipment, and years of training.
By 2024, AI-assisted gene editing was reducing the expertise required. The machine suggests the edits. The scientist approves them. The barrier is dropping.
By November 2025, I wrote about “gene prompting.” The concept: instructing biological systems using something analogous to the prompts we use with AI. Describing the desired genetic outcome and letting the machine design the edit. The abstraction of biology following the identical curve that software followed — from specialist to generalist to natural language.
Hackable cells. Programmable biology. Gene prompting. The same pattern. The same direction. The same endpoint: democratisation.
And it is not just biology. 3D printing followed the same curve — from industrial machines costing millions to desktop printers costing hundreds. Robotics is following it now — from custom-built industrial robots to modular, programmable, combinable platforms that anyone can configure. Even consciousness practices are being abstracted — meditation apps taking techniques that required years of monastic training and packaging them into ten-minute daily sessions.
Prepare for abstraction
The abstraction curve is not coming. It has arrived. Code is being commoditised. Biology is being programmable. Every technology you depend on is moving toward a state where anyone can use it.
The questions to ask are:
- What is the core technical skill that your business currently depends on? The thing that requires specialists? What is the thing that creates your competitive advantage through the scarcity of talent?
- Now ask: where is that skill on the abstraction curve? Is it still in the specialist phase? The generalist phase? The natural language phase? And what happens to your business model when it reaches the endpoint — when anyone can do it, when it costs almost nothing, when the barrier to entry disappears?
If the answer makes you uncomfortable, that discomfort is a signal. It means the abstraction curve is closer than you think. And the time to respond is not when it arrives. The time to respond is now — while the skill is still scarce enough to give you a head start.
Because abstraction curve does not just democratise creation. It democratises competition. Every barrier you relied on — technical complexity, specialist talent, proprietary code, expensive infrastructure — is being abstracted away. What remains is context, culture, and the speed of your response.
