Design software so a feature can be removed without untangling unrelated parts of the system. That is the central idea in Adam – The Developer’s May 2, 2026 DEV Community essay, “Write Code That’s Easy to Delete: The Art of Impermanent Software”: treat reversibility as a design concern, using clear boundaries and localized behavior to make changes easier to contain.
What “easy to delete” means
In the essay, “easy to delete” is a way to think about reversibility: if a feature, dependency, or behavior is no longer wanted, how much of the system must change to remove it? Code is more reversible when it is localized, has a clear boundary, and depends on less of the surrounding system.
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This is not a call to write throwaway code, skip tests, or avoid structure. It is a prompt to choose structure that makes change easier. A component with a deliberate seam can be replaced or switched off; a behavior spread across unrelated areas may require tracing and editing many connections before it is truly gone.
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Adam – The Developer recommends bringing the question into design and code review: “What would it take to remove this?” It helps surface dependency reach and shared-state assumptions before they become difficult to unwind.
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- How widely does this feature reach into other parts of the system?
- Does it rely on dependencies or global state that other code also uses?
- Can its behavior be turned off or substituted through a clear boundary?
- Does a proposed abstraction isolate likely change, or merely avoid repeated lines?
These questions are a review aid, not a formula for predicting effort. The essay’s comment discussion adds a useful nuance: the number of files involved is only a warning signal. Entanglement—how much other code knows about a component, and how many lifecycle or shared-state concerns depend on it—also matters.
Use boundaries to contain change
The essay names interfaces, adapter layers, well-defined APIs, and feature flags as possible seams. Their value depends on whether they actually limit the change: an interface can make an implementation replaceable; an adapter can keep an external dependency’s details in one place; a feature flag can provide a handle for switching behavior off.
These are examples, not mandatory patterns for every feature. A boundary is useful when it gives the system a practical way to substitute or disable behavior. Adding a layer that does not reduce coupling can add complexity without making removal easier.
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Keep change-prone behavior localized
If a behavior is likely to change, the essay recommends keeping it in one place where replacement is easier to contain. It also warns that a shared utility can entangle contexts that would otherwise remain independent. Reuse is not automatically a gain if it makes distinct features depend on the same implementation.
Give optional behavior a switch or seam
Logging is one of the essay’s illustrations: routing it through a single seam can make it easier to change or silence later. Similarly, a feature flag can act as a deletion handle when turning off the feature is a real requirement. These approaches work best when the seam remains narrow and the behavior behind it does not leak into unrelated code.
Abstract to isolate change, not just repetition
Repeated code can be a reason to consider an abstraction, but it is not enough on its own. If two contexts are likely to change differently, forcing them through a shared utility may couple them and make future removal harder. Conversely, an interface or adapter can be worthwhile when it isolates a dependency or a change-prone implementation.
The practical test is whether the abstraction creates a useful boundary: does it reduce what other code needs to know, or provide a straightforward way to replace or switch off behavior? If it only removes duplicated lines while increasing shared assumptions, it may work against reversibility.
What the essay does—and does not—establish
The essay argues that features often change or are removed and that codebases can contain untouched areas, but it supplies no dataset, named organization, or dated measurement for those claims. They should be read as the author’s rationale, not as statistics about software projects or proof that a particular feature is likely to be deleted.
Its design advice is likewise a perspective rather than a technical standard or experimentally validated result. The discussion about entanglement offers a useful counterpoint to counting files, but reader comments do not independently establish a predictive measure of deletion cost.
The essay also includes the line “Write code that is easy to delete, not easy to extend,” attributed there to Tef, “programming is terrible.” That attribution is presented as the essay gives it; it is not independently verified here.
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