Staying on Top of Technical Debt and System Complexities – Axon Active

We’ve all been there—tight deadlines, rushed decisions, habitual spillover, and a “fix it later” mindset. Everything seems fine until your system starts creaking under the weight of shortcuts and complexity. Suddenly, what felt like a small trade-off is now a big, messy problem. Whether you're launching a new product or maintaining an existing one, staying on top of technical debt and system complexity can make all the difference in keeping things running smoothly.

If you leave it too long, your code is going to become unmanageable and break, leaving you fighting fires constantly instead of making any real progress.

Understanding Technical Debt

What is Technical Debt?

Technical debt is a term used in software development to describe the additional work that results from choosing a quick or easy solution over a better, more time-consuming one. It’s not always bad, though—it’s often a strategic choice. You might choose to take on technical debt when you’re facing tight deadlines or need to deliver a feature quickly to beat a competitor to market.

Think of it like borrowing time from the future: you save time now by cutting corners, but you’ll need to repay that time later when you go back and clean up the mess. Just like with financial debt, there’s a cost attached. The longer you leave technical debt unaddressed, the more problems it can cause, such as bugs, slower performance, and more difficulty adding new features.

“It took twenty-four times longer. If a bug was addressed on the day it was created, it would take an hour to fix; three weeks later, it would take twenty-four hours. It didn’t even matter if the bug was big or small, complicated or simple—it always took twenty-four times longer three weeks later. As you can imagine, every software developer in the company was soon required to test and fix their code on the same day.” — Jeff Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, p. 100

Types of Technical Debt

Deliberate Debt: This is when you knowingly take a shortcut to get something done quickly. You know you’ll have to come back and fix it later, but for now, you need to meet a deadline or ship a product fast.

Accidental Debt: Sometimes technical debt happens by accident. Maybe the original design or architecture was fine at the time, but as the project grows, that design becomes a bottleneck. It’s not that you made a bad choice—it’s just that circumstances have changed.

Outdated Technology Debt: Technology moves fast, and code that worked well a few years ago might not be the best choice today. If you don’t keep your software up to date, you can end up with technical debt because your system is no longer optimized for current standards.

Why is Technical Debt Unavoidable?

It’s important to understand that technical debt isn’t always something you can avoid, nor should you always try to. In some cases, it’s more important to deliver quickly, especially if you’re trying to meet market demands. The key is to recognize when you’re taking on debt and to have a plan to manage it. In other words, it’s not about avoiding debt altogether—it’s about being smart about it.

For example, a startup launching a new product might decide to prioritize speed over perfection. They know that some corners will be cut in the early development stages, but they also know they’ll need to go back and address those issues later. This is a deliberate decision to take on technical debt in exchange for getting the product to market faster.

Breaking Down System Complexity

What is System Complexity?

System complexity refers to how interconnected and unpredictable a software system becomes over time. In the early stages of a project, the system is typically just complicated, it might have many parts, but they’re manageable with logic and expertise. You can think of this like a car engine or the tax code: detailed and intricate, but ultimately solvable.

As the system grows, however, it often becomes complex. New features, third-party integrations, and layers of logic create a web of interdependencies that evolve over time. In complex systems, small changes in one area can trigger unexpected effects in another, making outcomes hard to predict. This is especially true in large-scale systems where multiple teams are working simultaneously on different components.

The key difference is that complicated systems are hard, but they’re static and solvable—whereas complex systems are dynamic, adaptive, and unpredictable. Software systems often start off complicated and become complex as they scale, which is why managing them requires more than just technical skill—it demands adaptability, fast feedback, and strong collaboration.

Why Does System Complexity Matter?

When a system becomes too complex, development slows down. Instead of focusing on building new features, developers spend more time understanding the system, untangling dependencies, and debugging issues caused by the complexity. It also increases the risk of introducing bugs, because it’s harder to predict how changes in one part of the system will affect other parts.

Imagine trying to add a new feature to a system that’s been developed over several years. The codebase is massive, and every module depends on multiple other modules. A small change in one module might cause something to break in a completely unrelated part of the system. This is where complexity becomes a major pain point: even routine updates can turn into lengthy, difficult tasks because the system is so tangled.

How Does System Complexity Build Over Time?

System complexity often grows naturally as more features are added and the codebase expands. In the beginning, everything is neatly organized, but as new requirements come in, developers start adding layers of logic, external dependencies, and integrations. These changes aren’t inherently bad, but if they’re not managed carefully, they can lead to a system that’s difficult to maintain.

Over-engineering

Developers sometimes try to predict future requirements and build features or architectures that are more complex than necessary. This can lead to an overly complicated system that’s hard to maintain.

Tight Coupling

When different parts of a system (such as third-party libraries, APIs, or cloud native apps, for example) are too closely tied together, changes in one area can ripple through the entire codebase. This makes it harder to modify or replace individual components without affecting others.

Poor or Outdated Documentation

As the system grows, documentation becomes increasingly important. Without it, new developers (or even the original team) will struggle to understand how the system works, adding to the complexity.

Legacy Code

As systems evolve, they often end up with a mix of old and new code. Legacy code, which may not follow modern practices, adds complexity because it’s harder to work with and may not integrate well with newer parts of the system. Legacy code can also be left behind thanks to rushed deadlines or applying a temporary fix to a long-existing problem.

The Risks of Ignoring System Complexity

Ignoring system complexity is a bit like ignoring a leaky pipe. At first, it might not seem like a big deal, but over time, the problems compound, and you end up with a flooded basement (or in the case of software, a system that’s nearly impossible to maintain).

If complexity isn’t managed, it can reach a point where even small changes take a disproportionate amount of time. New developers struggle to onboard because the system is so complicated, and even seasoned team members spend more time deciphering the code than building new features. Eventually, this can slow down the entire development process to a crawl.

The Relationship Between Technical Debt and System Complexity

Technical debt and system complexity go hand in hand. Every time you take a shortcut in your code—like skipping tests or using a quick fix—you’re adding technical debt. Over time, these shortcuts pile up and make the system more complex. More complexity means more tangled code, which makes future changes harder and riskier.

On the flip side, when a system is overly complex, developers are more likely to take shortcuts just to get things done, adding even more technical debt. It’s a cycle: more debt creates more complexity, and more complexity leads to more debt.

In short, when you let either technical debt or system complexity build up unchecked, they’ll feed off each other, making both harder to manage. This is why keeping an eye on both from the start is critical to maintaining a healthy, efficient codebase.

10 Tips to Manage Technical Debt and System Complexity

1. Refactor Regularly

Keeping your code clean with regular refactoring helps reduce technical debt and prevents system complexity from growing unchecked. Instead of letting issues pile up, dedicate time in each sprint or project phase to tidy up the code. This keeps things manageable and prevents major problems later.

2. Review Code Thoroughly

Having fresh eyes on your code through reviews is key. Code reviews help catch issues early, ensuring no one’s adding unnecessary complexity or piling on more technical debt. A good review process also encourages collaboration, helping developers spot potential problems or inefficiencies.

3. Prioritize Testing and Automation

Comprehensive testing, especially automated testing, ensures that changes to the system don’t introduce new bugs or complications. When testing is embedded into your workflow, it acts as a safety net. You can confidently make changes and refactor without worrying about breaking other parts of the system.

4. Simplify Where Possible

Over-engineering is one of the biggest contributors to system complexity. Keeping things simple, whether it's in your architecture or feature design, makes the system easier to maintain. Aim to build only what’s needed and avoid unnecessary complexity that could lead to technical debt later.

5. Track and Manage Technical Debt[SS1] 

Make technical debt visible and part of the conversation. Use tools like Jira, Trello, or other project management systems to log and track areas of debt so they don’t get lost in the shuffle. More importantly, bring non-technical stakeholders into the loop. Help them understand the long-term impact of technical debt on agility, speed, and product quality. When stakeholders see the trade-offs clearly, it's easier to align on when and how to prioritize paying down that debt.

6. Modularize Your Code

Breaking your system into smaller, independent modules reduces complexity. When parts of your system are isolated from each other, changes become easier to manage, and there’s less risk of one update causing issues elsewhere. This approach keeps your codebase flexible and scalable as it grows.

7. Document as You Go

Keeping good documentation is essential for long-term management. Without clear notes on why certain decisions were made, future developers—or even you—will struggle to understand how the system works, adding to the complexity. Good documentation helps keep technical debt in check by ensuring everyone knows how to navigate the system.

8. Invest in Training

Well-trained developers are better equipped to avoid adding unnecessary complexity and creating debt in the first place. Regular training on the system’s architecture, best practices, and refactoring strategies keeps your team aligned and more effective at managing both debt and complexity.

9. Allocate Time for Debt Reduction

Sometimes, you need to dedicate specific time to paying down technical debt. Schedule “debt sprints” where the focus is solely on cleaning up the codebase, refactoring, and reducing complexity. This might feel like it slows progress, but in the long run, it speeds up development by making the system easier to work with.

10. Leverage Agile Practices

Agile practices encourage regular iteration and feedback, making it easier to manage technical debt and complexity in small chunks. Also, Agile helps keep problems from getting worse by focusing part of each sprint on changing and reviewing code. This helps make sure the work keeps improving and responds quickly to possible problems.

11. CI and DevOps

Continuous Integration (CI) is a development practice that helps teams catch issues early by automatically testing and integrating code as it's written. This leads to faster bug detection, making fixes easier and less disruptive. Because CI relies on frequent commits and automated testing, it encourages cleaner, more modular code that’s easier to maintain. It also enforces a culture of testing, which boosts overall code reliability. By running tests continuously, CI helps avoid last-minute scrambles and risky releases. Plus, it makes technical debt more visible through quality metrics, allowing teams to address problems before they grow. Ultimately, CI improves collaboration by reducing integration conflicts and keeping everyone aligned as the codebase evolves.

12. AI Supported Coding

AI-assisted coding accelerates development but also introduces new risks around technical debt. When developers rely too heavily on generated code, without fully understanding or reviewing it, low-quality or inconsistent code can accumulate. This "vibe coding" approach can lead to hidden complexity and future rework. To avoid this, teams should treat AI as a coding partner, not a replacement, using it to boost productivity while maintaining oversight, standards, and intentional design to keep technical debt in check

Staying Ahead of Technical Debt and System Complexity

Technical debt and system complexity have the ability to derail any product, whether it’s on the path to success or not. If you implement strong practices from the start, you’ll be in a much better position to keep your system efficient and manageable. But even if you’re already dealing with a tangled mess of shortcuts and complexity, all is not lost.

With consistent refactoring, careful planning, and a focus on long-term health, you can bring your system back under control. It’s never too late to regain stability and ensure smoother development moving forward.

Involve Stakeholders in Trade-off Discussions: Help non-technical stakeholders understand the cost of technical debt and why addressing it matters for long-term agility and performance.

Take Control of your Technical Debt and System Complexity

At Axon Active, we help businesses tackle technical debt and system complexity by providing expert Agile development, scalable architectures, and dedicated software teams that keep your systems efficient and future-proof. Whether you're modernizing legacy code, optimizing workflows, or implementing CI/CD pipelines and microservices, our tailored solutions ensure long-term maintainability and growth. Don’t let complexity slow you down—partner with us to build high-quality, scalable software that evolves with your business. Contact us today and let’s transform your development process together!