As an engineering manager, you are often faced with the financial and operational pressure to launch products not only more quickly but more frequently—while keeping reliability high. Technical debt is when you choose to write subpar code by not following all the best practices in order to deliver the product quicker, knowing you’ll need to fix or improve it later.
On one hand, tech debt is not all bad, as taking on some of it can definitely allow a company to ship quickly, test features, and gain an early edge in the market, by reducing time-to-market. On the other hand, however, if left unchecked, it can (and most certainly will) drive up maintenance costs, slow down development speed (as engineering teams spend around 33% of their time, which comes down to 13.5 hours of a 41.1 hour work week, dealing with technical debt alone), and hurt your company’s and your teams’ ability to bring new ideas to life.
This article explains the theory of tech debt and analyzes its false stigmas. We will explain the difference between planned and unplanned tech debt, examine the cost of code debt and how to measure it, and, of course, present some best practices on how to control and, in many cases, even eliminate tech debt.
What is Technical Debt?
Technical debt refers to the long-term challenges that happen when software development teams prioritize speed over code quality. It occurs when engineers take shortcuts—like writing inefficient code, skipping tests, or delaying refactoring—to meet deadlines, leading to future recoding and increased maintenance costs.
Why Should Technical Debt Be on Your Radar?
Code debt is like a hidden tax over your engineering organization, and it can consume approximately 40% of IT expenses, with engineers spending an average of 6 hours weekly managing existing debt rather than building new value.
Not only that, but it drains productivity; 60% of engineers report technical debt, which actively slows development (Stepsize research) and reduces the ability to respond to market changes.
By putting it in focus and building a strategy to handle this situation, you’ll be able to recoup a lot of the resources lost from their intended purpose. Here’s how to do it:
9 Tips to Manage and Prevent Technical Debt
Managing technical debt in an effective way not only maintains software quality and team morale, but also ensures your engineering team can remain agile and responsive to business needs.
Here’s how:
Step 1: Identify your Major Weaknesses
Before you can focus on dealing with any of your tech debt issues, you actually need to figure out what they are.
To do that, begin by examining your code so you can pinpoint the modules and/or services that are causing you these three issues: 1. most frequent bugs, 2. performance lags, and 3. support tickets. Use automated testing and code analysis tools to help you figure out what your “hot stops” are.
With the results, make a list of your top offenders. And work with your team so each one can be tackled at a time, and make it a point to focus on the most problematic issues first.
Step 2. Quantify the Debt
To effectively assess and manage your technical debt, it’s essential to quantify it using specialized tools. SonarQube and CodeScene are two prominent platforms that can assist in this process.
These technical debt tools help you calculate and find out both what your Tech Debt Ratio is (the cost to fix issues vs how much it actually cost to build the original software) and what your Maintainability Index is (a score from 0 to 100 of how easy your code is to work with).
Here’s a formula to calculate the technical debt:
Technical Debt Ratio (TDR) is calculated using the following formula:
Where:
- Remediation Cost: The estimated effort required to fix the identified issues in the codebase.
- Development Cost: The effort invested in developing the existing codebase, calculated as the number of lines of code multiplied by the time taken to develop each line.
Assuming it takes 0.06 days to develop a single line of code, the Development Cost can be expressed as:
Therefore, the Technical Debt Ratio becomes:
If your Tech Debt Ratio goes over 10–20% or your Maintainability Index drops below 50, it’s definitely time to fix your code.
Step 3. Prioritize Based on Business Impact
Now, in reality, knowing your code debt scores doesn’t mean you should focus on fixing the ones that have the highest scores first as it might not be the smartest business call.
Our advice to you is that you focus on prioritizing the ones that actually impact your business and your product the most. Meaning the ones that, when fixed, will result in the most advantages—be it improved speed, lower risk, or more flexibility.
And to figure what out these are, sit down with your dev team and product leads. Talk to them about which ones are actually causing the most harm and deal with them first.
Step 4. Allocate Dedicated Time
By now you know what tech debt is, where it is, and what’s affecting your business the most. It’s time to remove it. Yet it’s not about simply getting rid of it and going on your merry way.
Taking care of tech debt requires a continuous and conscious effort by you and your programmers.
So don’t expect a big cleanup that will magically eliminate all your problems. Instead, dedicate time in each sprint to refactoring. The Software Engineering Institute’s research shows that you want to put tech debt into your process and create a culture of code quality.
You can even run a “debt sprint” once in a while or just save a portion of every sprint to clean up the code.
Step 5: Refactor in Manageable Waves
After you have your list of the main problem areas, schedule small refactoring and cleanup tasks to each sprint section. By doing so, you can tackle the worst debt little by little without compromising progress on new work. Focus on simplifying logic, removing redundant code, and updating structure with current best practices.
Step 6: Automate Testing and Integration
Even if you have these first two steps in place, bugs can still pop up at the last minute and slow everything down. So what you want to do to avoid that is to automate your tests—unit, integration, and end-to-end—and have them in a continuous integration (CI) pipeline. That way, every new commit gets automatically tested and checked, making it less likely that new changes will end up breaking old features.
Step 7: Communicate and Document
Clean code is not really the sole basis of a strong codebase—good communication and documentation is a big part of it as well. So keep architectural diagrams, onboarding guides, and API references updated while communicating clearly and openly so as to ensure all stakeholders (developers, QA, and product managers) understand what the priorities and constraints are.
Step 8. Continuously Monitor Progress
Consistently and continuously watch how you’re doing, which means keep an eye on your technical debt progress.
To do so, we suggest you use dashboards and regular reports to track how much debt you’re actually paying off over time.
And remember to celebrate even the smallest of wins, as dealing with technical debt can be hard on your tech team, and when you do so, you can lift their spirits and show your team that their hard work is making a difference.
Step 9: Design for the Future
Finally, embrace up-to-date modular designs that can grow with your company. By using microservices or clear component limits, your dev team can substitute or upgrade specific parts without really touching the whole app.
By taking these nine steps and adopting them as part of your technical debt strategy, you’ll not only clear out old liabilities, but also set the stage for a more sustainable and flexible development environment, ultimately preventing technical debt and saving your organization both time and money.
How to Communicate Code Debt to Stakeholders
Now that you know how to both measure and manage tech debt, it’s key you also know how to explain what it is and why it matters to your stakeholders.
And in order to do that, you first need to connect technical details with business goals, making the idea a bit easier to grasp. So we suggest you skip the tech talk and instead use relatable analogies, which means calling your technical debt a “financial liability” that incurs “interest” to represent the ongoing costs and resource drains it causes.
Besides, so information is even more accessible, use visual aids and executive dashboards to present key metrics like the Tech Debt Ratio and Maintainability Index, as simple graphs and heat maps can point out high-debt areas while making it clear how they slow down projects and raise costs.
And, of course, you want to highlight the ROI and long-term gains of tackling tech debt, since you want them not only to see it as a problem, but as a key part of the overall success of the company that ultimately boosts profits and keeps the business going and growing. To do that, show how cleaning up and improving code leads to cheaper maintenance, faster feature building, better adaptation to market changes and new technology, and more reliable systems.
As a result, by following these tips, you make a strong case that fixing tech debt is not just an expense but actually key to staying competitive and making money long-term. Which in turn ensures that technical debt management is as important as other big business plans, thus creating a culture of lasting growth and state of the art operations.
4 Common Myths and Misconceptions About Tech Debt
- Myth: Technical debt is always the result of poor coding or lazy developers.
Reality: In truth, it can be an intentional, strategic choice made under pressure to accelerate time-to-market. - Myth: Once incurred, technical debt irreversibly damages a project.
Reality: Actually, just like financial debt, tech debt can be “paid off” if you implement thoughtful and dedicated refactoring, automated testing, and regular maintenance. - Myth: Only legacy systems accumulate technical debt.
Reality: In reality, even the most cutting-edge projects and startups can end up accumulating it if they consistently take shortcuts when they want and need to deliver new features quickly. - Myth:Technical debt always means a messy, unmaintainable codebase.
Reality: As a matter of fact, tech teams can take on tech debt deliberately to speed up delivery, but normally with a plan in place to refactor down the line. The real danger comes in when teams end up neglecting their “repayment plan.”
Intentional vs. Unintentional Technical Debt
Understanding the difference between intentional and unintentional code debt allows you to know when to plan for a future update and when to fix errors right away.
Intentional technical debt is when a team makes a deliberate, quick fix to hit a deadline, knowing they’ll improve it later. Unintentional technical debt, on the other hand, happens by accident—often due to mistakes, changing needs, or rushed work.
Here’s how they differ:
Intentional (Deliberate) Debt
Teams knowingly and willingly choose quicker or easier solutions to meet pressing and urgent needs.
Example: A startup launches an MVP to attract early users and adopters, with a plan to refactor and improve once product-market fit is confirmed.
Unintentional (Accidental) Debt
Occurs as a consequence of limited expertise, evolving requirements, or poor coding/testing practices.
Often leads to legacy code that breaks or becomes outdated over time.
What Causes Tech Debt and What Are its Consequences?
Tech debt doesn’t just magically appear suddenly and out of nowhere—it’s often and typically the byproduct of rushed deadlines, shifting priorities and requirements, a lack of alignment between dev teams and business’s goals, among others. And it doesn’t just result in money lost, as it comes with other unwanted effects as well.
To help you understand these technical shortcomings and their true consequences, here’s a quick look at the most common causes of technical debt and their consequences.
Causes of Technical Debt
- Tight Deadlines and Short-Term Fixes
Quick fixes made in order to hit rushed deadlines that never get revisited and ultimately accumulate into layers of complexity, making every new feature more painful to implement.
- Evolving Technologies and “Shifting Landscapes”
Even solid designs can fall behind when frameworks, safety standards, and business landscapes (where the system’s original assumptions no longer match current business realities) move forward, forcing rework on old structures.
- Inadequate Testing and QA
When code is not tested well and thoroughly, it hides problems that cost more to fix down the road and also pushes deadlines back even further.
- Misalignment Between Business and Dev Teams
When business and product goals aren’t crystal clear, dev teams work on building features without really seeing the bigger picture, which leads to patchwork solutions that end up fulfilling immediate needs while ignoring future maintainability or scalability.
- Low-Priority Upkeep
If regular cleanups or updates get bumped by “more pressing” features, the codebase eventually and gradually becomes fragile and harder to update.
Consequences of Unchecked Software Debt
- Higher Operational Costs
Putting out fires means less time and investment on growth initiatives and more time spent on rework.
- Slowed Progress & Frequent Bottlenecks
When every little necessary change requires tiptoeing around messy code or old complicated systems, progress grinds to a crawl.
- More Errors
Systems that are fragile and tangled and under-tested are more prone to bugs, which means that even the simplest updates can break unrelated parts of the application.
- Unhappy Customers
When user experience is poor due to either glitches or recurring downtime even your most loyal customers might decide to look elsewhere for better options.
- Team Burnout and High Turnover
Developers hardly ever enjoy wrestling with legacy code that resists improvement, and so, always fixing issues rather than working on exciting challenges ultimately wears them out and opens the door for them to attrite.
How Code Debt Affects Product Quality & Innovation
When it comes to both product quality and innovation, technical debt can actually have both directly and indirectly impact them. Here’s how:
Diminished Product Quality
When technical debt accumulates, your product becomes more prone to errors and glitches. When that happens, your software starts to frequently crash or have noticeable slowdowns due to performance lags. And this really annoys users as it makes your product much less enjoyable to use.
Also, as design debt piles up more and more, your teams may be forced to take even more shortcuts, which ends up making your existing quality issues much worse.
Slowed-Down Innovation
When your developers are stuck doing maintenance work and fixing old problems, their time to research, develop, and create next-generation features, therefore innovating, gets significantly reduced.
Also, long wait times and tricky and painful deployment processes can make your team frustrated, and so less eager to try new things, which puts a damper on possible creative progress and advancements.
Longer Time to Market
Although technical debt is most often accrued in order to reduce time to market, it can actually slow it down, as if your dev team is trying to build new features upon a fragile, outdated core, it gets much more difficult to do. That happens because developers then must work around an unstable base, which drags out the process.
As a result, it takes much longer to launch updates or react to market threats, putting your company at a disadvantage in quick-moving markets.
Organizational Fatigue
Ultimately, persistent and long-lasting code debt most often than not leads to burnout in organizations, as your teams are always putting out fires. When this happens, it doesn’t only wear down their energy and spirit, it also breeds a “quick fix” mindset.
This knee-jerk, reactive approach, in the end, can definitely speed up the buildup of technical debt starting a harmful loop that hurts both day-to-day work and future growth.
Signs Your Team Might Be Accumulating Too Much Technical Debt
It’s not always that easy, really, to tell if your team is swimming (not drowning) in technical debt. But there are some telltale signs that can help you figure it out before it becomes a major issue.
One simple way is to track your bug counts. If you see more bugs popping up, as in an uptick of bugs, or old problems coming back, as in frequent regressions, it might mean that the shortcuts your team took earlier on have started to cause bigger issues.
Another red flag is when your feature delivery starts to drag, which means your time-to-market also does. So pay attention: if adding new features takes longer than it used to, or even small and minor updates end up requiring a lot of rework, it could definitely be a sign that your codebase is being burdened by debt.
Also keep an eye out for signs of code duplication and needless, unnecessary complexity. If and when you notice the same code patterns showing up again and again or logic that new team members have difficulty understanding and grasping, it’s time to refactor. Besides, be on the lookout for declining code quality, which shows up along with sketchy documentation, a lack of automated tests, and coding practices that don’t match up can all suggest that technical debt is, indeed, building up.
Lastly, do not ignore team frustration. Developers tend to become frustrated and might even burn out when they have to fight old problems all the time rather than coming up with new ideas and working on new challenges. So it’s important you also keep an eye on them, so you don’t let technical debt actually affect their daily work and motivation so much. Use your regular code checks and team meetings as your thermometer, so you can do something about it before it gets out of hand.
A Final Word: Why Addressing Tech Debt Is One of the Best Investments You’ll Make
As you can see, technical debt comes with the territory in software development and it’s neither all good nor all bad on its own. What ultimately matters is how you handle it. And that’s why it’s so important you have and implement a smart, well-informed plan and strategy that combines agile methods, clean software development practices, and consistent refactoring efforts. When you do that, you can change your tech debt from a possible problem and a potential liability into an actual manageable part of your software lifecycle.
Whether you’re in charge of a remote development team or working in-house, making smart choices about when—and how—to take on, handle, and pay off technical debt is key to success in the long run. Keep in mind technical debt is a tool: when used on purpose, it can speed up growth; when left unchecked, it can slow down progress.
By taking the steps we’ve shared in this article—identifying your major weaknesses, quantifying and prioritizing debt based on business impact, dedicating time for refactoring, automating testing, communicating clearly, continuously monitoring progress, and designing for the future—you can make sure it doesn’t eat up your budget. Instead, it can help your business grow steadily.
And last but not least, we cannot underestimate the power of a great IT hire when it comes to dealing with and preventing technical debt. The great news is that we can help you do that: here at DistantJob, a remote-first recruitment agency, we make sure you get access to skilled developers who can help turn tech debt into a strategic asset. By teaming up with us, you get the talent you need to keep a healthy codebase and drive your company’s lasting success.
Book a discovery call now and we’ll tell you how.
FAQs on Technical Debt
Technical debt has an impact on businesses by driving up maintenance costs, slowing down development cycles, and making systems unreliable. As tech debt builds up and accumulates, when more and new features need to be added, it takes more time and more money which results in longer time to market and less agility when it comes to responding to market changes. Besides, high technical debt usually means more bugs and system outages, which not only hurt the user experience but also damage your brand reputation. And to top it all off, it contributes if not leads to team burnout and higher turnover rates, as developers get frustrated and exhausted of dealing with highly complex and difficult codebases.
The technical debt quadrant, created by Martin Fowler, developer and author, divides debt into either reckless or prudent and deliberate or inadvertent. This means technical debt, according to him, can be one categorized as one of the following: Deliberate-Reckless Debt, Deliberate-Prudent Debt, Inadvertent-Reckless Debt, and Inadvertent-Prudent Debt.
The difference between intentional and unintentional debt comes down to, obviously, the intentionality behind the decision to accrue it. In simple terms, intentional (deliberate) tech debt comes up when dev teams are faced with either tight deadlines or business goals that suddenly shift and in order to meet them, end up choosing quick, less-than-ideal fixes in order to hit tight deadlines or shifting business goals, all the while knowing they’ll need to fix them later. Unintentional (accidental) technical debt, however, is not planned and happens without anyone actually meaning it to, often because of surprise issues, changing needs, or gaps in knowledge.
According to this academy study, there are 13 types of tech debt, which are: Architectural debt, Build debt, Code debt, Defect debt, Design debt, Documentation debt, Infrastructure debt, People debt, Process debt, Requirement debt, Service Debt, Test automation debt, and Test debt.
Spaghetti code is a term that describes tangled, messy and confusing code that has no clear structure. It usually happens when developers add features without looking at the overall design and end up creating paths so jumbled they look like spaghetti. This type of code debt results in more bugs and also in making both fixing issues and adding new features a lot harder.
A god class or a god object is actually a system that does so many things at once, has so many responsibilities, controls and oversees so many different objects, that it’s incredibly difficult to work with. God classes ultimately violate the Single Responsibility Principle, which leads to not only the code being very rigid but also extremely interconnected and not focused enough. As a result, the codebase is too fragile and bug-prone, adding to technical debt.
Architectural debt relates to the basic, fundamental flaws in a software system’s design that ultimately make it extremely difficult to not only maintain but also scale. It shows up in five ways: monolithic architecture where all components are tightly coupled together; excessive coupling leading to high dependency between modules; lack of modularity which results in components that are right and hard to update; obsolete design patterns that use outdated methods that make the codebase even more complex; and lack of architectural documentation, which eventually leads to misunderstandings and inefficiencies.
Code debt refers to bad coding habits—think spaghetti code, magic numbers, or quick-fix hacks. These are the messy parts coders add when they’re rushed and say they’ll fix “later.” On the other hand, technical debt covers more ground. It includes everything from old-fashioned system designs to half-finished product plans.
