When the automobile was first invented, many called them “horseless carriages,” and early websites for newspapers were designed just like their paper counterparts. Even today, computers still have “desktops” and “files,” mirroring office setups from decades ago. Some say that the width of railroad tracks traces back to Roman chariot wheels—though that story is debated. This tendency to stick with old ways when adopting new technology is often called “paving the cow paths.”

The Tradition of Using Old Paths

Cows don’t naturally walk in straight lines, so their tracks in fields aren’t the shortest route between two points. Yet, humans tend to follow familiar paths, even if they’re not the most efficient. This behavior was summed up by management expert Peter Drucker, who said, “There is surely nothing quite so useless as doing with great efficiency what should not be done at all.” In tech, this manifests as developers replicating old processes rather than seeking new, better ways.

This idea applies to how we develop software. We’re used to writing code a certain way—using comments, meaningful variable names, and modular classes—because it helps humans understand and maintain the code later. But as AI tools become more advanced, the question arises: do we still need to follow these old conventions? Or are we just paving paths that might no longer be necessary?

The Impact of AI on Coding Practices

Recently, some developers have started using AI code generators to build applications. When using tools like Claude Code, programmers often focus on guiding the AI to produce code that aligns with best practices—designing with interfaces, small single-purpose classes, and clear structure. The AI then does most of the heavy lifting, creating code that’s easy to read for humans, but it doesn’t necessarily understand why certain decisions are made.

This raises an interesting point: if AI is writing our code, does it need to follow the same human-centric principles? Comments, naming conventions, and decoupled design are all meant to make code easier for other humans to understand. But if AI can generate highly optimized, maintainable code directly, are these practices still relevant? Could AI eventually compile high-level language directly into machine code, bypassing many traditional steps?

This would mean the current process—writing code, reviewing it, compiling, and running—becomes almost obsolete. Instead, we’d communicate our intentions to an AI, which then produces the final product. If this process is just another cow path, a roundabout way of getting from idea to execution, then what’s the most direct route?

The Straight Line to Software Development

Thinking about the shortest path leads to an intriguing question: what is the most direct way to create software? In theory, if AI can understand our goals and translate them into machine instructions instantly, the need for all the intermediate steps diminishes. Instead of writing code line by line, we could describe what we want, and AI could turn that into a binary that runs directly on hardware.

This concept challenges the traditional craft of coding, which has grown complex over decades. Developers have spent years honing skills, learning best practices, and structuring code for clarity and maintenance. But as AI tools improve, the importance of these conventions might fade. The focus could shift from manual coding to defining high-level instructions, turning the whole process into a more direct, efficient pipeline.

Ultimately, the question is whether our current methods are the best path forward or just well-worn cow paths. If technology allows us to bypass the old routes, it might be time to reconsider how we approach software creation. Finding the shortest, straightest route could revolutionize not only coding but the entire way we develop and think about software in the future.

Inspired by

• https://www.infoworld.com/article/4122881/is-code-a-cow-path.html

Sources

• snopes.com