Managing Technical Debt: How JournAI Builds “Clean” Code That Developers Actually Enjoy

The request sounded simple.

A client wanted to add one more feature to an existing application. Nothing unusual—just another change that needed to fit into a product that was already being used by customers.

A developer opened the project and started tracing where the new functionality belonged.

That was when the problem appeared.

The feature itself wasn’t complicated. The surrounding code was.

One controller was handling several responsibilities. A database query was being reused in multiple places. Some business logic was sitting inside code that had originally been written for something completely different. Changing one part meant checking several others just to make sure nothing unexpected would break.

The dedicated developer had two choices. The first was to add another quick fix, deliver the feature, and move on. The second was to spend some extra time understanding the existing structure and clean up the part that was making the new work unnecessarily difficult.

This is where technical debt becomes more than a technical term.

Sometimes the hardest part of adding a new feature isn’t building the feature. It’s dealing with everything the application has accumulated before it.

Technical Debt Doesn’t Always Start With Bad Decisions

When people hear “technical debt,” they often imagine badly written or outdated code.

In reality, technical debt can begin with a perfectly understandable business decision.

A product may need to launch quickly. A customer may need a feature before the next contract milestone. A team may be testing an idea and doesn’t yet know whether the feature will become a permanent part of the product.

In those situations, taking a shortcut can be reasonable.

The problem starts when the shortcut becomes permanent.

A temporary implementation gets reused. Another feature is built around it. Then another developer joins the project and has to understand why everything works that way. Eventually, a change that should take a few hours takes days because nobody wants to break something that depends on the old structure.

This isn’t hypothetical. In Stack Overflow’s 2024 Developer Survey, 63% of professional developers identified technical debt as a workplace frustration, making it the most commonly reported frustration among the listed company challenges.

The important point isn’t the percentage alone.

It shows that technical debt affects the everyday experience of developers—not just architecture discussions in engineering meetings.

The Real Cost Appears During the Next Feature

Imagine a team builds a customer notification feature quickly.

The first version works, so everyone is happy. A few months later, the business wants notifications through another channel. Then it wants different notification rules for different customer types.

Suddenly, the original implementation becomes difficult to extend.

The team isn’t starting from zero. They’re spending time understanding, changing, testing, and protecting code that wasn’t designed for the new requirements.

This is where technical debt becomes expensive.

The cost isn’t necessarily the original shortcut. The cost is the extra effort required every time the application has to change.

A practical way to identify this kind of debt is to look for patterns such as:

• Features that repeatedly require changes in unrelated parts of the application
• Code that developers are afraid to modify because its dependencies aren’t clear
• Business logic duplicated across multiple locations
• Tests that are difficult to write or maintain
• Workarounds that keep getting added instead of addressing the underlying issue

None of these automatically means the code is “bad.”

They are signals that the current structure may be making future development harder than it needs to be.

Clean Code Should Make the Next Change Easier

For a development team, clean code isn’t about making every file look perfect.

It is about making the system easier to understand and change.

A developer joining a project should be able to follow the flow of an important feature without spending hours discovering hidden dependencies. A developer fixing a bug should have a reasonable understanding of what else might be affected. A developer adding functionality should know where the new logic belongs.

That usually comes from practical engineering decisions rather than complicated architecture.

For example, a team might separate responsibilities instead of putting database queries, business rules, notifications, and response formatting into one large piece of code. It might introduce reusable components when repetition actually creates maintenance problems. It might add tests around important business rules so future changes can be made with greater confidence.

The objective is not to create more layers simply because they look architecturally impressive.

Good structure should reduce complexity, not move complexity into more files.

That distinction matters because over-engineering can become its own form of technical debt.

AI Can Speed Up Coding—and Speed Up Bad Decisions Too

There is another reason technical debt deserves more attention today: AI-assisted development.

Developers can now use tools such as ChatGPT, Claude, and AI coding assistants to generate code, explain unfamiliar functions, write tests, and help troubleshoot issues.

Used carefully, these tools can remove repetitive work and help developers move faster.

But faster code generation doesn’t automatically mean better software.

Stack Overflow’s 2025 Developer Survey found that 84% of respondents were using or planning to use AI tools in their development process, while 66% reported frustration with AI-generated solutions that were “almost right, but not quite.” The survey also found that 46% of respondents distrust the accuracy of AI tool output, compared with 33% who trust it.

That creates an important engineering responsibility.

If a developer asks an AI tool to “fix this error” without understanding the surrounding code, the tool may produce a solution that removes the visible problem while introducing another one.

A better development process is:

Understand the problem → inspect the existing code → plan the change → use AI where useful → review the output → test the behavior → refactor when necessary.

AI can help write the code.

The developer still needs to decide whether that code belongs in the product.

Developers Shouldn’t Have to Fight the Codebase

There is also a human side to technical debt.

Developers spend a significant amount of their working day reading existing code, searching for answers, understanding dependencies, and figuring out why something behaves the way it does.

Stack Overflow’s 2024 research found that 61% of respondents spend more than 30 minutes a day searching for answers or solutions, while 30% reported that knowledge silos affect their productivity at least ten times a week.

That doesn’t mean every minute spent investigating code is wasted.

Understanding a system is part of development.

The problem comes when developers repeatedly have to rediscover the same information because the code, documentation, or architecture doesn’t make the answer clear.

A developer-friendly codebase should make common questions easier to answer:

• Where does this business rule live?
• Which service handles this operation?
• What happens if this request fails?
• Which parts of the system depend on this logic?
• How is this behavior tested?
• Why was this approach chosen?

When those answers are reasonably clear, developers can spend more time improving the product and less time trying to decode it.

Technical Debt Needs a Place in the Product Conversation

One common mistake is treating technical debt as something developers should fix whenever they “get time.”

That time rarely appears.

Product priorities continue changing. New customer requests arrive. Deadlines move closer. The backlog grows.

Instead of waiting for a large refactoring project, teams can make technical debt visible and discuss it alongside normal product work.

That doesn’t mean every technical issue deserves immediate attention.

A useful question is whether the debt is actively affecting the product or the team.

For example, a technical improvement may deserve priority when it is:

• Slowing down frequently requested features
• Causing repeated production issues
• Increasing testing effort
• Creating security or reliability risks
• Making onboarding significantly harder
• Increasing the chance of future rework

This turns technical debt from an abstract engineering concern into something the business can understand.

If a piece of code is adding two days to every feature that touches it, that has a business impact.

Clean Code Is a Continuous Practice

There is no final day when a team can say, “Our codebase is now completely clean.”

Software keeps changing.

New features introduce new requirements. Customer behavior changes. Technologies evolve. Teams grow. Some decisions that were right two years ago may no longer make sense today.

The goal is not perfection.

The goal is to keep the codebase healthy enough that the next change doesn’t become unnecessarily difficult.

That means developers should be encouraged to improve the area they are already working in when the improvement is practical. It means technical debt should be discussed openly instead of hidden. And it means AI-generated code should be treated as something to review and understand—not something to accept automatically.

Building Software That Stays Easy to Improve

Technical debt isn’t a sign that a team has failed.

It is a natural part of building software, especially when products are growing quickly and priorities are changing.

The difference comes from how the team manages it.

At JournAI, the idea of clean code should go beyond following a particular coding style. The real objective is to build software that developers can understand, test, extend, and maintain without constantly working around hidden complexity.

That means looking beyond the immediate feature and asking what the code will mean for the next feature, the next developer, and the next stage of the product.

Clean code isn’t code that never needs to change. It’s code that makes change easier.

As AI becomes a larger part of software development, that principle becomes even more important. AI can help teams move faster, but engineering judgment remains essential for deciding what should be built, how it should fit into the existing system, and whether the result will remain maintainable.

At JournAI, we help businesses build and improve software with a focus on maintainability, scalability, and practical engineering—not just getting the next feature out of the door.

Whether you are building a new application, modernizing an existing product, or dealing with a codebase that has become difficult to maintain, the goal remains the same:

Build software today that your developers will still be comfortable working with tomorrow.

Explore software development services and build a product designed to keep evolving.