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I Deleted Half My Codebase and Nobody Noticed

AI Summary4 min read

TL;DR

Deleting 48% of a backend codebase improved development speed without causing issues, revealing that much code exists for developer comfort rather than product value. The author advocates for simplicity, building only for current needs, and treating complexity as a cost.

Key Takeaways

  • •Most code is added to make developers feel safe, not to enhance the product, leading to unnecessary complexity and slower development cycles.
  • •Removing generic abstractions, premature microservices, and unused utilities can significantly reduce codebase size and improve feature delivery times without increasing bugs.
  • •Developers should focus on current reality, avoid over-engineering for hypothetical future scale, and prioritize simplicity and readability over clever architectural patterns.
  • •Complexity should be measured as a cost, with every new layer adding to onboarding, debugging, and cognitive overhead, and only justified if it reduces real risk.
  • •The most valuable code is often the code deleted, and production systems benefit more from boring, practical decisions than from career-driven, overly sophisticated designs.

Tags

programmingsoftwareengineeringproductivitycareer

Last quarter, I deleted 48% of our backend code.

No new bugs.
No outages.
No customer complaints.

And no one noticed.

That was the moment I realized something uncomfortable:

Most code exists to make developers feel safe, not to make products better.

The Backstory

We had a “mature” codebase:

  • Service layers
  • Repository patterns
  • DTO transformers
  • Event emitters
  • Abstractions for “future scale”
  • Utility folders with 200+ helpers

It looked impressive.

It was also slowing us down.

Every new feature required:

  • Touching 6 files
  • Updating 3 interfaces
  • Writing adapters for edge cases that never happened
  • 2 days of PR discussions about naming

Velocity was dying quietly.

The Experiment

I asked one simple question:

If we were rebuilding this feature today, what would we NOT build?

Then I started removing things.

Not refactoring.

Deleting.

What I Removed

1. Generic Abstractions

We had abstractions for:

  • Payment providers (we only use one)
  • Notification services (we send one type of email)
  • Caching strategies (we use Redis. Period.)

Removed all generic layers.

Result: nothing broke.

2. Premature Microservices

We had split logic into separate services because:

“We’ll scale one day.”

Traffic never justified it.

Merged them back into a single service.

Latency improved.
Deployment got simpler.
No scaling issues.

3. “Reusable” Utilities Nobody Reused

Half the helpers were used exactly once.

Inline.
Delete.
Move on.

The Metrics

Before cleanup:

  • 220k lines of backend code
  • 14 services
  • Avg feature cycle: 6–8 days

After cleanup:

  • 114k lines of backend code
  • 6 services
  • Avg feature cycle: 3–4 days

Bug rate: unchanged.

The Real Problem

We overestimate:

  • Future scale
  • Hypothetical flexibility
  • Edge cases that never happen

We underestimate:

  • Simplicity
  • Readability
  • The cost of cognitive load

Every abstraction has rent.

Most teams forget to calculate it.

Why This Happens

Developers are rewarded for:

  • Cleverness
  • Architecture diagrams
  • Pattern knowledge
  • “Senior-level” structure

We are not rewarded for:

  • Deleting code
  • Simplifying systems
  • Saying “we don’t need this”

So we optimize for visible sophistication.

Not operational clarity.

The 3 Rules I Follow Now

1. Build For Current Reality

If the scale isn’t here, don’t architect for it.

When it arrives, you’ll have better information anyway.

2. Duplication Is Cheaper Than Abstraction

Until duplication becomes painful.

Then refactor.

Not before.

3. Measure Complexity Like a Cost

Every new layer adds:

  • Onboarding time
  • Debugging time
  • Cognitive overhead
  • Review friction

If it doesn’t reduce real risk, it’s expensive decoration.

What I Learned

The most valuable code I wrote last year was the code I deleted.

And the best architecture decision was admitting:

We are not Google.

Most startups and teams don’t need:

  • 15 services
  • Hexagonal architecture
  • Event-driven everything
  • Enterprise-grade patterns

They need clarity.

The Hard Truth

A lot of “clean architecture” is career-driven design.

It signals seniority.
It feels advanced.
It looks good in interviews.

But production systems reward boring decisions.

Final Thought

If your system disappeared tomorrow and you rebuilt it in a week…

What would you NOT rebuild?

Start there.

Curious:
How much of your current codebase would survive a rebuild?

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