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Leon Pennings
Leon Pennings

Posted on • Originally published at leonpennings.hashnode.dev

Improve Your Application Quality and Stability: Here’s How We Lost Focus — and How to Get It Back

For many organizations, the promise of Agile was to become more adaptive, more product-focused, and more aligned with user needs. And yet the reality in many teams today is the opposite: the process has become the center, not the product. Teams execute ceremonies with discipline — stand-ups, refinements, sprint goals, retros — while the software quietly degrades over time.

The irony is sharp:

We are following the playbook for better software, but the software is getting worse.

Quality issues increase. Stability declines. Change becomes more expensive.

So what’s happening?


The Process Slowly Became the Goal

When Agile first emerged, it was about shortening feedback loops and learning quickly. But as organizations scaled and formalized it, Agile became a work management system rather than a product evolution system. Velocity, throughput, and story completion became the measures of success.

This shift caused a subtle but powerful change:

Originally Now in Many Teams
Focus on improving the product Focus on finishing the story
Value measured by user outcomes Value measured by points delivered
Developers guided by product insight Developers guided by ticket boundaries

A user story is no longer a change to the system — it is a unit of work to close. Once the acceptance criteria are met, it’s declared “Done,” even if while working in that area of the code, the developer encountered:

  • An inconsistency

  • A confusing abstraction

  • A small bug

  • An outdated naming decision

  • A hidden duplication

In a process-driven environment, the instruction is:

Create a ticket for that. We’ll prioritize it later.

The result is predictable:

  • The fix is deferred.

  • Context is lost.

  • The issue is forgotten.

  • The next person encounters the same complexity, but worse.

This is where rot begins — not with dramatic failures, but with small, reasonable deferrals repeated over months and years.


Quality Decline Is Not Caused by the Absence of Testing

Most systems that degrade do not lack:

  • Unit tests

  • Code coverage

  • Static analysis

  • Pipeline automation

Those are diagnostics and guardrails.

The real issue is understanding.

Developers avoid improving code not because they don’t care, but because the code is hard to reason about.

If understanding is expensive, refactoring is expensive.

If refactoring is expensive, improvements are deferred.

If improvements are deferred, entropy compounds.

This is the fundamental economic mechanism behind software decay.

And here is the key insight:

Understanding comes from conceptual clarity.

Not from test coverage, not from architecture diagrams, not from code style rules.

Which brings us to the real pivot in the argument.


The Foundation of Maintainable Software: A Rich Domain Model

When code reflects the domain clearly — when class names correspond to real business concepts, and behavior lives where it naturally belongs — the code explains itself.

A rich domain model:

  • Gives every piece of code a conceptual home

  • Encodes meaning directly into structure

  • Makes consequences of change visible

  • Allows any developer to pick up a piece and make improvements safely

In other words:

Context is embedded in the code itself.

This makes refactoring and fixing cheap — especially when already working in that area.

Compare this with procedural, transaction-script, or “service layer soup” architectures:

  • Behavior is scattered

  • Names are generic (Manager, Handler, ServiceImpl)

  • Logic is driven by flow, not domain meaning

  • The developer must reconstruct the domain mentally just to understand what the code is doing

That is cognitively expensive.

And when understanding is expensive, developers do the safe thing:

They leave the code as it is.

So the decay continues.


Why Many Teams Don’t Have Rich Domain Models

Conceptual modeling is a skill — not a pattern, not a framework, not something gained by years alone. It requires:

  • Understanding the business domain deeply

  • Distilling it into precise conceptual boundaries

  • Naming correctly

  • Locating behavior at the correct abstraction layer

  • Protecting the model against accidental entropy

This is senior engineering in its real sense.

Not age. Not title. Not “years of Java.”

You can teach syntax.

You can enforce style.

You can template architecture.

But:

You cannot automate conceptual modeling.

This is why many organizations quietly try to compensate with more process:

  • More grooming

  • More story detail

  • More documentation

  • More gates and review steps

But process cannot create a coherent model.

It can only schedule work assuming one already exists.

If the model is weak or absent, the product will decay — process or no process.


The Path Back to Quality

The shift is simple to describe, and difficult to execute:

  1. Place the product back at the center.

    Story completion is not the definition of done.

    System integrity is.

  2. Adopt “fix what you touch” as the default behavior.

    Not as a hero effort — as standard engineering hygiene.

  3. Ensure conceptual modeling capability exists in the team.

    This is non-negotiable.

    One person with strong modeling intuition can anchor the whole codebase.

  4. Let the domain model be the shared language.

    So every engineer operates with the same conceptual map.

This does not require:

  • More process

  • More documentation

  • More ceremony

It requires:

  • Clarity

  • Responsibility

  • Permission to improve the system continuously

Because the cheapest moment to fix a problem is when you are already there and still understand it.


Conclusion

You do not improve software quality by enforcing process discipline, or by increasing test coverage, or by adding more governance.

You improve quality by making the system easy to understand while working inside it.

And the way you make a system understandable is by giving the code a clear and accurate conceptual model — one that reflects the domain, not the implementation details.

When developers can understand the system, they improve it continuously.

When they improve it continuously, stability increases.

When stability increases, velocity increases naturally — without pressure.

The process should support this.

Not replace it.

The product is the heartbeat.

Everything else is only scaffolding.

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