The Restructuring of Programming Paradigms

A “paradigm” is not just a form—it’s a mode of thinking.

As a branch of the writing profession, programmers interact with tens of thousands of lines of code, and naturally, they rely on paradigms for guidance. It’s like having a built-in “system prompt”—you don’t need to explain “what object-oriented programming is” to your colleagues every time, nor do you have to argue endlessly about the details of design patterns. There’s an unspoken understanding that you’re “playing by the rules” in a certain context.

After all, the human “mental window” is limited in size. Collaborating without a paradigm is like chickens talking to ducks—utter miscommunication. If you insist on piling all your functions into a single file with no abstraction or categorization, the consequence is writing documentation until you break down.

But now that artificial intelligence is part of the programmer’s workflow, paradigms are shifting.

First, the way we handle code has transformed from “manual carving” to “semantic understanding.” Those obedient little “coding assistants” can automatically modify your code based on a single instruction. So under this transformation, do traditional coding paradigms still matter?

It depends on your perspective.

They do matter—because large language models deal in language. The clearer the linguistic structure, the easier it is to extract and recreate information. It’s the difference between a pile of unclassified documents and a meticulously organized file cabinet. The information entropy is not the same, and naturally, neither is the efficiency.

But from another angle, maybe they’re no longer that important. After all, paradigms were originally for humans to read. Now, LLMs can develop their own paradigms—or even revive those long-abandoned “classical practices.” For instance, directly manipulating binary code: who needs layers of abstraction? From a model’s perspective, that quaint notion of “human readability” might be completely unnecessary.

Second, there’s the transformation of the programmer’s role. Whether we accept it or not, this wave of change has quietly pushed us into a new position. The days of hand-crafting code were like seasoned artisans refining woodwork—there was a kind of pride and dignity woven into every character.

But from a business standpoint, when websites and apps are the final product, the programmer is just one link in the industrial chain. Whether you code by hand or use AI to generate it, the user doesn’t care. Our mindset must shift accordingly. I am not just a code porter or a keystroke operator—I am an engineer solving problems. Writing code is a means to that end, not the end itself.

To me, the value of paradigms lies in helping us organize our thoughts, so that our future selves—or others—can quickly get into the zone when reading our code. This was once a form of self-rescue for programmers. But now, LLMs effortlessly surpass us. They have stronger memory, faster analysis, and even if your code is a mess, they can still make sense of it.

So, do we still need paradigms in the future?

Perhaps the real question is: are we willing to hand over our thinking to the model, or do we want to preserve a trace of human logic?

Paradigms are road signs in the world of programming.

But when the roads are no longer built by humans—does that mean we are no longer travelers, or just moving where the machine tells us to go?