Maybe a better question is: Is natural language to code what high-level programming is to hand-written assembly? Brooks claims the "essential complexity" lies in the specification: if a spec is precise enough to be executable, it’s just code by another name. But is the gap actually that large today? When I ask for a "centered 3x3 Tailwind grid", the patterns are so standardized that the ambiguity nearly vanishes. It’s like asking for a Java 8 main method. The implementation is so predictable that the intent and the code are one and the same. Or using jargons, most of the coding has a strong prior that leads to predictable posterior.
The key question now is: how far can AI go? It started with simple auto-completion, but as AI absorbs more procedural know-how, it becomes capable of generating increasingly larger chunks of maintainable code. Perhaps we are reaching a point where established patterns are so well-understood that AI can bridge the gap between a vague intent and a working system, effectively automating away what Brooks once considered essential complexity.
In the long run, this probably makes experts more valuable, but it’ll gut the demand for standard engineers. So much of our market value is currently tied to how hard it is to transfer expertise among humans. AI renders that bottleneck moot. Once the know-how is commoditized, the only thing left is the what and why.
The key question now is: how far can AI go? It started with simple auto-completion, but as AI absorbs more procedural know-how, it becomes capable of generating increasingly larger chunks of maintainable code. Perhaps we are reaching a point where established patterns are so well-understood that AI can bridge the gap between a vague intent and a working system, effectively automating away what Brooks once considered essential complexity.
In the long run, this probably makes experts more valuable, but it’ll gut the demand for standard engineers. So much of our market value is currently tied to how hard it is to transfer expertise among humans. AI renders that bottleneck moot. Once the know-how is commoditized, the only thing left is the what and why.