Low-Quality Code Is Costing You More Than You Think: Here’s How to Stop It

Code quality often becomes an invisible thread that ties together an engineering team’s productivity, morale, and ability to deliver value. When that thread starts to fray, the effects aren’t always dramatic or immediate, but they’re deeply disruptive.

But low-quality code doesn’t usually scream “I’m broken.” Instead, it lurks in the everyday frustrations—debugging sessions that stretch hours, pull requests that spark endless debates, and new features that take twice as long because of “that one function no one wants to touch.”

It’s the kind of issue that slips past the radar until it’s too big to ignore. 

So why does it persist, even among teams with top-notch talent? 

And more importantly, what’s the true cost of letting it linger?

We discuss this in depth below. 

What Is a Low-Quality Code, Really? 

Low-quality code isn’t always about glaring bugs or rookie mistakes. Sometimes, it’s the perfectly functional, yet subtly flawed, code that does the most damage. Consider this: a function that works perfectly today may require an hour to debug in isolation. Now multiply that by dozens of functions scattered across a sprawling codebase. As businesses grow and expectations evolve, "good enough" turns into "not enough." 

The cost of maintaining this code rises exponentially as cracks in the foundation become more visible. 

But this is not new information, right? So why do we keep running into these problems again and again? 

Well, for instance, the engineers who built it often don’t see the cracks forming. In fact, they’re likely the ones patching those cracks later, cursing the decisions they were forced to make under impossible deadlines. Sometimes, the most functional-looking code carries hidden inefficiencies—like an iceberg, with the bulk of the problem lurking below the surface.

The Hidden Ripple Effect of Low-Quality Code

Think of it this way: one poorly written code might not seem like a big deal. But what happens when every new feature has to navigate around that function? Debugging takes longer. New features get delayed. Collaboration starts to feel more like untangling a mess than building something meaningful. Slowly but surely, the entire engineering team feels the weight.

Here’s how low-quality code shows up in your daily work:

• Endless Debugging: Those small quirks and inconsistencies add up, turning quick fixes into multi-hour rabbit holes.

• Slower Progress: Every new feature feels like it’s dragging an invisible anchor as engineers work around existing issues.

• Frustration and Fatigue: Engineers spend their time firefighting instead of creating. Over time, this chips away at morale and leads to burnout.

• Missed Opportunities: Instead of focusing on innovation, the team is stuck maintaining a creaky foundation, falling behind competitors.

For smaller engineering teams, this might mean occasional slowdowns. For larger engineering teams, it can snowball into missed deadlines, frustrated engineers, and mounting hidden costs of poor quality code.

So, Why Does Low-Quality Code Stick Around?

If we know the damage it causes, why does low-quality code still find a way into even the best teams? The truth is, it’s not about carelessness—it’s about survival in a fast, high-pressure environment.

Source: Refactoring by Luca Rossi

1. The Race to Deliver

Deadlines don’t wait for perfect code. Engineers often have to choose between “done” and “done right,” and “done” usually wins. Those quick fixes? They have a way of becoming permanent.

2. Too Many Cooks

In a growing engineering team, ownership of the codebase gets murky. If no one feels responsible for cleaning up, the mess just grows.

3. Short-Term Thinking

When leadership values speed over sustainability, it’s easy to focus on the next feature and ignore the cracks forming in the foundation.

4. Shifting Priorities 

Code written for today’s problems can become tomorrow’s bottleneck. Refactoring takes time, and time is hard to justify when there’s a new feature to ship.

So this becomes more of a conversation about rethinking how we approach engineering. Addressing poor code quality means acknowledging its impact, not just on the codebase, but on the people who work with it every day.

Next up: How can engineering teams tackle the root causes of low-quality code while staying fast, agile, and productive? Let’s explore the strategies that make the difference.

So, How Can We Lower the Cost of Low-Quality Code?

The analogy I like to use when defining low-quality code is that it’s often like a houseplant you forgot to water: a little neglected, but still fixable. It sneaks into the codebase not because people are careless, but because deadlines loom, requirements shift, and engineers make trade-offs to ship something now.

Here’s how teams can handle low-quality code without losing momentum or sanity:

1. Refactoring Doesn’t Have to Be a Full Overhaul

Let’s be honest—no one has time to refactor the entire codebase. But refactoring doesn’t have to mean pulling everything apart. Start small.

For example, while fixing a bug, take five extra minutes to clean up variable names or simplify a confusing block of code. Over time, these small improvements add up. Think of it like paying off a credit card: tackling little pieces of debt gradually makes the whole balance more manageable.

One engineering team I worked with created “refactoring Fridays.” Every week, engineers spent the last hour cleaning up the area of the codebase they worked on that week. No huge commitments—just small, meaningful fixes.

💡Suggested Reading: Building a Code Quality Culture: A Path to Reducing Technical Debt

2. Make Code Reviews About the Why

Code reviews often feel like nitpicking: “Why isn’t this function named better?” or “You missed a semi-colon.” Sure, those things matter, but what really matters is understanding the why behind decisions.

When reviewing code, ask questions like:

• “What are the trade-offs here?”

• “Could this logic be simpler or more reusable?”

• “How might this scale as more features are added?”

Treat reviews as a chance to share context, not just critique. One engineer I worked with had a habit of leaving comments like, “This works, but we might hit a bottleneck if the user count grows. Could we explore X instead?” It wasn’t judgmental—it was collaborative.

3. Deadlines vs. Quality: Finding the Middle Ground

Deadlines are a fact of life, but they don’t have to mean sacrificing quality. Instead of choosing between “ship it now” and “make it perfect,” try breaking work into stages:

• Release an MVP that’s functional, but acknowledges its limitations.

• Use feature flags to separate experimental code from the core system.

• Keep a visible list of tech debt for the engineering team, and revisit it regularly.

You could try setting aside a “last 10% day” at the end of each sprint. It’s a low-pressure way for the engineering team to clean up, optimize, or document anything that might’ve felt rushed during the sprint.

4. Ownership Without Bureaucracy

Code ownership can get political fast, especially in big engineering teams. But it doesn’t have to.

Instead of rigid silos, think of ownership as caretaking. Rotate who “owns” different parts of the codebase each quarter, so no one feels permanently stuck with the same thing. And make sure documentation explains why certain decisions were made—future-you (or future teammates) will thank you.

I’ve seen this work beautifully when engineering teams set up informal “caretaker chats.” Whoever’s currently “on duty” for a module can answer questions, but they also keep notes on recurring issues for the next person who rotates in.

5. Be Smart About Automation

Automation is supposed to make life easier, not create more noise. Use tools strategically:

• Linters are great, but make sure the rules match your engineering team’s standards.

• Test coverage tools help, but don’t chase 100% coverage—it’s better to have a meaningful 80% than a meaningless 90%.

• Use complexity analysis tools sparingly to flag problem areas without overwhelming the team.

You might try integrating a lightweight CI tool to flag overly complex code during pull requests. The key is to make it a nudge, not a roadblock—highlighting areas that could benefit from simplification without forcing immediate action. Over a few months, this kind of subtle, proactive feedback can lead to noticeable improvements in code clarity without adding friction to the development process.

It’s About Progress, Not Perfection

Low-quality code isn’t going away overnight, and that’s okay. The goal isn’t to eliminate it completely—it’s to manage it in a way that keeps the engineering team moving forward without creating panic or chaos.

Every small improvement, whether it’s a cleaner function, a helpful comment, or a meaningful discussion in a code review, is a step toward a healthier codebase. And when the codebase feels manageable, everything else—debugging, shipping, and even collaboration—gets easier.