Every Time We Chose the ‘Clean’ Option, Our Tech Debt Got Worse

It looked clean on the surface — until it exploded underneath.

Every Time We Chose the ‘Clean’ Option, Our Tech Debt Got Worse

It started with the best intentions.
We wanted our codebase to be elegant. Maintainable. Clean.
So we did what every “good” developer is taught to do: refactor aggressively, abstract early, and chase the elusive goal of code purity.

But somewhere along the way, our architecture grew unrecognizable. The “clean” code was hiding dirty secrets. Simple bug fixes turned into archaeology. The deeper we dug, the worse the debt became.

Ironically, it was our obsession with cleanliness that created a mess.

Let’s talk about how this happens — and why developers, even experienced ones, fall into this trap.

The Myth of the “Clean” Option

In software development, “clean” is a seductive word. It suggests elegance, order, discipline. But clean doesn’t always mean right.

Here are a few patterns we mistook for “clean”:

• Over-abstraction: Wrapping everything in interfaces, factories, or services in the name of separation of concerns.
• Premature generalization: Making a function generic before the second use case ever arrives.
• Overengineering architecture: Creating layers of indirection to avoid “tight coupling” — which only made debugging a nightmare.
• Chasing 100% DRY: Refusing to repeat a line of logic, even if it made the code harder to read.

At first glance, each of these felt like the responsible thing to do. In isolation, they weren’t wrong. But together? They became a tower of tech debt.

How “Clean” Turns Into Tech Debt

We didn’t notice it at first. The code looked neat. Tests passed. PRs were approved.

But soon, small features took weeks. Junior devs were lost in abstractions. Fixes required modifying code across multiple layers. Something was wrong.

Here’s how our pursuit of cleanliness backfired:

1. Too Many Layers of Indirection

We abstracted everything.
Repositories, services, handlers, factories.
A simple CRUD operation went through four classes — just to get a value from the database.

Result:

• Debugging became painful
• Onboarding new developers took months
• Each new feature required threading logic through multiple layers

Clean architecture is great. But too much abstraction too early makes the codebase feel like an onion — one that makes everyone cry.

2. Generic for No Reason

We wrote reusable components… before reuse existed.

def handle_event(event_type, *args, **kwargs): 
    # logic based on event_type

At the time, it felt smart. Future-proof, even.

But no one else needed the function to be this generic. Not for months. And when we did, the abstraction didn’t even fit the new use case.

Lesson: Generalizing code is only “clean” if it’s solving today’s real problems — not tomorrow’s imaginary ones.

3. DRY to the Point of Confusion

Don’t Repeat Yourself (DRY) is a golden rule… until it makes the code unreadable.

We created shared utilities for logging, error handling, even business logic. But over time, it became impossible to trace where anything was happening.

Before:

log_error(e) 
rollback_transaction()

After:

handle_failure(e)

One line looked clean. But you had no idea what it did.

Irony: By trying to be DRY, we sacrificed clarity. A little repetition would have actually made things easier to understand.

The Real Meaning of Clean Code

“Clean” shouldn’t mean clever. It should mean clear.

Here’s what actually makes a codebase clean and healthy:

1. Readability Over Abstraction

• If an abstraction doesn’t simplify the code for others, it’s not worth it.
• Favor naming and clarity over design patterns.

2. YAGNI — You Aren’t Gonna Need It

• Don’t build for hypothetical future cases.
• Generalize only when at least two real use cases demand it.

3. Coupling Isn’t Always Bad

• Tight coupling can be good if it reflects actual business logic.
• Don’t decouple just for the sake of it — it creates confusion, not flexibility.

4. Simplicity Beats Purity

• Choose simple, clear solutions that solve today’s problems.
• Be pragmatic, not dogmatic.

What We Do Differently Now

After learning these hard lessons, we took a new approach.

We audit abstractions

Every quarter, we ask: Is this abstraction still pulling its weight?
If not, we collapse it.

We prioritize explicitness

Verbose but readable is better than clever and obscure.

We optimize for maintainability

That means:

• Short, focused functions
• Clear error messages
• Self-explanatory naming
• Docs and diagrams where needed

We trust developers, not rules

We don’t blindly follow DRY, SOLID, or Clean Architecture principles.
We encourage critical thinking and tradeoff discussions.

When “Clean” Becomes a Code Smell

Some signs your “clean” code is actually hurting you:

• New team members struggle to trace logic
• You spend more time navigating layers than writing code
• Fixing a bug means changing 5+ files
• Every abstraction feels like it needs its own documentation

If this sounds familiar, it might be time to refactor your refactoring.

Final Thoughts

Choosing the “clean” option felt safe. Responsible. Even professional.

But software development isn’t about writing code that looks good in a blog post.
It’s about solving real problems, collaboratively, and sustainably.

Don’t fall for the trap we did.
Clean isn’t about less code — it’s about less confusion.

Next time you’re tempted to abstract, decouple, or refactor for the sake of elegance, pause.
Ask yourself: Will this make the code easier for my team to understand and maintain?

If not, maybe it’s okay to keep it simple.

The cleanest code is the one that doesn’t need a manual to be understood.