I’ve seen a growing number of posts lately about how terrible AI-generated code will supposedly be to maintain. The argument usually goes something like this: “Sure, it’s fast now, but in a year or two no one will understand it.” And while that might sound reasonable on the surface, it misses an important point—maintaining code has always been difficult. Anyone who has joined a new project knows the pain of trying to decipher another developer’s “clever” logic from three years ago.

AI doesn’t change that reality. What it changes is the speed and accessibility of getting to a working solution. Whether that code is maintainable or not still comes down to the same thing it always has: the habits and discipline of the person writing it. If you’re sloppy, AI will happily amplify your sloppiness. But if you care about structure, clarity, and testing, you can guide AI to produce the same level of quality you would yourself—and then improve it further.

That’s the key mindset shift. Using AI doesn’t absolve you of responsibility; it amplifies it. You become the reviewer, the architect, and the quality gate. You’re no longer just typing code—you’re designing how that code should exist and evolve.

The irony is that AI is also excellent at refactoring. It can take legacy code and clean it up faster than most developers can finish their morning coffee. The trick is knowing how to use it: guiding it with context, giving it examples, and holding it to the same standards you’d expect from any human teammate.

When used properly, AI isn’t lowering the quality bar—it’s raising it. It gives us the opportunity to focus on architecture, testing, and maintainability instead of boilerplate. And yes, it’s faster. Much faster. But speed isn’t the problem—lack of care is.