Rethinking Refactors in Intent-Based Programming

In the classical view of software development, refactoring is both essential and painful. It means reshaping the internal structure of code -- extracting methods, collapsing classes, rearranging files -- without changing the system’s behavior. Done well, it improves clarity, reduces technical debt, and makes future changes easier.

But it’s also slow, risky, and cognitively expensive. Refactors require engineers to develop a deep understanding of both the current code and its unspoken design intent. Regression testing is mandatory. Entire teams may coordinate to ensure consistency across modules. Even with sophisticated tools, a large refactor often feels like open-heart surgery.

Intent-based programming changes this completely.

(Image Credit: 2023 r/ProgrammerHumor post which is based upon this earlier TheyCanTalk.com comic)

When Code Is Ephemeral

In intent-based systems, implementation code is no longer the core artifact. It’s a transient output -- an expendable build product generated from a higher-level specification. When you change your mind, you don’t edit the code. You edit the spec and regenerate the code.

This shift reframes what refactoring means. In fact, in many cases, it makes the very concept of refactoring obsolete.

If implementation code is always derived from an up-to-date specification, there’s no point in reorganizing that code manually. You don’t refactor the output of a compiler -- you modify the source. The same is true here. The source of truth is intent.

Refactors, in this new paradigm, are not operations on code. They’re signals that the specification has diverged from what the user now wants.

Refactors as Specification Drift

When should a developer refactor in an intent-based system? Only when the spec is outdated, unclear, or misaligned with current needs.

This kind of refactor doesn’t involve moving code around -- it involves realigning intent. Perhaps you started with a monolithic “blog app” spec and now want to split it into services. Or perhaps you want to switch architectural styles, restructure the user model, or swap your database strategy. These aren’t code changes. They’re shifts in requirements, priorities, and design assumptions.

📦 Quote: “In the future, refactors won’t require engineers -- just better YAML.”

Let’s break down how different kinds of refactors manifest in intent-based systems:

Specification Clarification

Sometimes the problem isn’t that your intent has changed, but that it wasn’t clearly expressed to begin with. Maybe the AI misunderstood your architecture, or your spec was too vague about component boundaries.

In this case, you don’t refactor the code. You rewrite the spec to be more precise. A better description yields a better implementation.

Implementation Style Override

Other times, your goals remain constant, but you want a different approach. Perhaps the AI built a class-based API, but you prefer functional programming. Or it picked Bootstrap for styling, and you want Tailwind. These are not logical changes -- just stylistic ones.

In an intent-based system, you introduce preferences or meta-specs. Instead of changing how the code is written, you change the style guide the AI uses during generation.

Semantic Realignment

The most dramatic kind of refactor happens when the purpose of the code changes. Maybe your app has grown, and the original abstractions no longer fit. What began as a task manager now needs team collaboration features, real-time sync, and role-based access.

In this case, the spec needs to evolve significantly. The regenerated code may look nothing like the old implementation -- and that’s fine. Unlike traditional refactors, where sweeping changes are dangerous and costly, here they’re just an efficient response to new intent.

Why Refactors Are Cheap, But Still Important

This all sounds like good news -- and it is. Refactoring becomes a regeneration operation. If your intent is clear, the cost of change drops to near-zero.

But this doesn’t mean refactors disappear. They just move to a new layer. The burden shifts from code manipulation to spec maintenance. You still need to think clearly about architecture, abstraction, and boundaries -- but now you do it declaratively.

The risk, too, changes form. It’s no longer about breaking implementation logic. It’s about accidentally over-specifying something brittle or introducing unstable inference. If your spec is ambiguous, regenerating the code could lead to jarring changes across unrelated parts of the system.

Toward Spec-Aware Refactorability

In this new world, the best specs are the ones that are easy to change. That means:

• Modularity of intent: Each part of your system is described independently
• Inference stability: Small spec changes don’t cause massive ripple effects
• Clear boundaries: Features are described at the right level of abstraction

Over time, we’ll likely see the emergence of new tooling to measure and guide spec refactorability. Instead of cyclomatic complexity, we’ll track “spec entropy.” Instead of code churn, we’ll measure “intent drift.”

Refactor Diffs = Spec Diffs

Perhaps the biggest mindshift is this: version control is no longer about the codebase. It’s about the intent space.

Refactor pull requests aren’t giant diffs of JavaScript or TypeScript. They’re precise, declarative changes to your specification files. You go from:

- function handleLogin(req, res) {
+ async function handleUserLogin(request, response) {

To:

- users must log in to access protected routes
+ users must authenticate using OAuth 2.0 with GitHub

The code that changes downstream is implementation detail. What matters is the evolution of requirements.

Anti-Patterns in the New World

Some legacy habits will become problematic if we carry them into intent-based systems. Examples:

• Over-specification: Trying to control every detail of implementation in the spec defeats the purpose and limits regenerability
• Spec sprawl: Duplicating intent across files leads to drift and incoherence
• Inference opacity: Not knowing what was inferred vs what was explicit can make future edits unstable

The best intent-based systems will have tooling to prevent this. Spec linters. Drift detectors. Visualizations of intent-to-code mappings.

Conclusion

Refactoring isn’t going away -- it’s just been reframed. In intent-based programming, you don’t restructure code. You revise and evolve intent.

This is liberating. It lowers the cost of change, encourages experimentation, and aligns software with what it was always meant to do: solve current problems, not preserve old abstractions.

In this new paradigm, "refactor early, refactor often" becomes "clarify intent continuously."