How to Handle Tech Debt Without Slowing Down Your Dev Team

You’ve probably felt that rush to hit delivery deadlines, the pressure to push features fast, and the quiet voice in your head saying, “We’ll fix it later.” Well, you’re not alone because every engineering team faces those trade-offs that leave cracks beneath the surface of the software projects.

The moment bugs start piling up or features take twice as long to ship, those quick decisions begin to cost you. That’s when tech debt comes back with interest.

Whether it came from tight deadlines, code debt, or just limited resources, it won’t wait quietly in the background. In this article, you’ll learn how to face tech debt head-on, where it shows up, how to measure it, and how Axify helps you take practical steps to handle it before it spirals.

So, let’s look at what technology debt means for you.

What Is Technology Debt?

Technology debt refers to the cost incurred when relying on outdated tools, systems, or infrastructure to maintain software functionality. You might not feel it at first, but over time, that old setup begins to slow you down.

From rising maintenance costs to blocked upgrades, it becomes harder to scale or support new work. Unlike technical debt, which occurs from code-level trade-offs, technology debt sits deeper in your stack. It typically leads to performance issues, higher operational costs, and delays in reaching your business goals.

Now that you understand technology debt, let’s break down what technical debt is and how it shows up in your work.

What Is Technical Debt?

Technical debt is the cost you incur when you choose faster, less ideal solutions during the development cycle, knowing you'll need to rectify them later. Ward Cunningham first introduced the debt metaphor to help explain this trade-off.

Like financial debt, tech debt accrues interest, and if ignored, your team pays the price in the form of slower delivery, bugs, and frustration. 63% of professional developers say technical debt is their top workplace frustration.

Whether it comes from a lack of documentation, insufficient testing, or decisions made under pressure, it doesn’t go away on its own. Instead, it creeps into every part of your product, holding you back just when you need to move fast.

Now, let’s look at a few real-world examples to see how technical debt can build up and what it can cost you over time.

Technical Debt Examples

You’ve probably seen it play out in day-to-day work, but here are three real situations that show how tech debt can scale into something devastating:

• The Y2K Bug: In the 1960s and 1970s, developers saved memory by storing years as two digits (e.g., '73' for 1973). This shortcut led to widespread issues as the year 2000 approached, requiring a massive global effort to fix date-related bugs. The remediation cost was estimated between $300 billion and $600 billion.
• Knight Capital (2012): In 2012, Knight Capital reused outdated code without proper testing. A software glitch triggered $7 billion in unauthorized stock trades, resulting in a $440 million loss within minutes. The firm never recovered and was forced to sell the following year. This is one costly example of what happens when technical debt goes unchecked.
• Nokia’s Fall: Nokia failed to modernize its outdated operating system due to years of ignored technical debt. When smartphones, such as the iPhone, emerged, Nokia couldn’t adapt quickly enough. The result was a fall from market dominance, a sale to Microsoft, and billions of dollars lost, which proves that even giants can fall when tech debt accumulates.

These aren't rare outliers but reminders of what happens when debt is pushed aside for too long. Those examples show how everyday tech debt can quietly snowball into a company-wide crisis. Now, let’s compare it to technology debt and see how they differ.

Technology Debt vs. Technical Debt

You might hear both terms used interchangeably, but they have distinct impacts on your team and product. Understanding that difference helps you choose where to focus your time and energy.

Here are the key contrasts to keep in mind:

If you're leading a software team, you're probably juggling both. One delays progress, the other chips away at software quality.

And if you're dealing with legacy code or infrastructure debt, you’re likely dealing with both at the same time. With the differences clear, it’s time to understand how technical debt starts to accumulate within your projects.

How Does Technology Debt Appear?

Tech debt usually slips in quietly, but it rarely stays that way. You’ll typically see it pop up when technical leadership is missing. If your codebase feels like it was written by a dozen people with no shared vision, or worse, like one person with no guidance, it’s a red flag.

You can spot weak leadership when patterns don’t align, and you’re constantly cleaning up after decisions made without a plan. Here are the usual signs that technology debt is building up:

• Rushed development due to tight deadlines.
• Poorly documented or inconsistent code.
• Outdated dependencies and unmaintained libraries.
• Lack of automated testing and CI/CD processes.
• Frequent workarounds for architectural limitations.
• Incomplete or skipped regular code reviews.
• Knowledge loss from key team members leaving.

Each of these creates friction in your process and makes future work harder. If you don’t catch these early, you’ll be paying in lost development time and long-term consequences.

80% of enterprises report that tech debt has led to delays or cancellations of critical projects. All of this takes us to our next point.

Why Should You Follow Technology Debt?

If you ignore tech debt, it won’t only slow your team down, but it will also burn your budget. Studies show that software developers spend between 23% to 42% of their time dealing with tech debt. The longer you wait to fix issues, the more expensive they become.

According to IBM’s Systems Sciences Institute, a bug caught during testing can cost up to 15 times more to fix than one found during the design phase. If it slips into implementation, it can be six times more costly.

While KTLO (Keep the Lights On) work keeps your system running, it doesn’t drive innovation or improve time to market. You need more than patchwork to stay competitive. Without active tracking, debt can accumulate, negatively impact software quality, and increase business costs.

Metrics that Can Show Tech Debt

You can’t fix what you don’t measure. To stay ahead of technology debt, you need clear indicators that show where it’s impacting your delivery and performance. Here are the key metrics that engineering managers, DevOps leads, and SREs should watch:

Change Failure Rate

Change Failure Rate tracks the frequency of deployments that result in problems, such as rollbacks or hotfixes. A high rate suggests your team may be shipping bad code or skipping proper testing. It usually points to rushed work, typically caused by tight timelines or gaps in team experience or structure.

Failed Deployment Recovery Time/ Time to Restore Service

Time to Restore Service shows how long it takes to recover from a failed deployment. If fixes are taking days instead of hours, you’re probably dealing with poor processes or hidden service debt. Long recovery times are a red flag that your system isn’t as resilient as it should be.

Number of Bugs

Bug count reveals how much rework is piling up in your backlog. A steady increase suggests growing defect debt, which might occur from design debt or a lack of continuous integration. High bug volume makes it harder to maintain software quality over time.

How to Fix Technology Debt

You won’t erase all your technology debt overnight, but you can take steady, focused steps to get it under control. If you’re a VP of engineering, tech lead or engineering manager, here are the actions that can help you move in the right direction.

1. Follow the Metrics above and Watch Trends

Start with visibility. Keep an eye on metrics listed above, such as change failure rate, time to restore service, and bug count. When you notice patterns, such as a rising failure rate or longer recovery times, it’s time to dig in and take action. These signals indicate areas that require attention before your debt load begins to slow everything down.

2. Get Leadership Buy-in, but Make the Tech Debt Visible

If your product managers or execs can’t see the impact of tech debt, they won’t support fixing it. You should use data to make it visible. Demonstrate how debt impacts delivery time, bug frequency, and team morale. When everyone shares the same understanding, you can build trust and secure support for focused debt reduction.

3. Find the Root Cause

This is where Axify’s Value Stream Mapping (VSM) becomes essential. It shows you where your flow gets stuck and where automation would make the most significant difference. Whether it’s automation debt or a broken review process, seeing the whole picture helps you fix the right thing, not just symptoms.

4. Allow Time in Each Iteration to Tackle Debt, but Prioritize What Matters

Not all tech debt is bad. Some of it is intentional, taken on for strategic reasons to meet a tight product release. The key is knowing which debt is worth paying off now. Don’t waste effort refactoring something stable. Focus on debt that blocks new work or increases risk.

5. Implement Solutions According to the Problem

Different problems need different fixes. If you’re experiencing issues due to requirement debt, focus on developing better specifications and alignment early on. If bad tech debt is causing security vulnerabilities, strengthen your review and testing processes to mitigate these risks. Don’t reach for one tool. Instead, you should treat the problem, not just the code.

Best Practices to Prevent Tech Debt

Fixing technology debt is hard, but preventing it is easier if you build the right habits early. You don’t need a complete overhaul. Just focus on steady, simple actions that keep your codebase clean and your team aligned.

If you’re a CTO, VP of Engineering, or even a Staff/Principal Engineer, here are the practices that make a difference:

• Prioritize code stewardship. Make it clear that quality matters. Encourage your team to take ownership of their work beyond the ticket.
• Track and address maintenance tasks proactively. Don’t wait for things to break. Log and resolve small issues before they snowball.
• Reduce context loss. Ensure that code reviews and documentation are clear enough so that anyone on your team can step in later.
• Address architectural bottlenecks. If parts of your system are hard to change, flag them now instead of tiptoeing around them.
• Measure maintenance load impact. Keep track of how much effort goes into KTLO vs. new work so you can balance wisely.
• Make maintenance work recognized and rewarded. Call it out in retros. Treat it like the valuable contribution it is.
• Integrate maintenance work into roadmaps. Don’t hide it. Show it alongside features and tie it to delivery goals.
• Adopt continuous refactoring. Tidy as you go. Small cleanup now saves you big rework later.
• Ensure codebase survivability. Write code that someone else, not just you, can work with six months from now.

To help you put these ideas into motion, let’s see how Axify fits into this picture and gives you the insights you need.

Improve Your Workflow with Axify

You can’t eliminate technology debt with a single tool, but you can identify where it’s accumulating, and that’s where Axify helps. With clear, real-time insights into your delivery flow, Axify shows you bottlenecks, delays, and trends before they become long-term problems.

You’ll get the context you need to connect day-to-day decisions with long-term outcomes. From identifying gaps in your process to highlighting risky pull requests, Axify helps you make smarter choices and keeps your team aligned.

Want to see how it works in action? Book a demo with Axify and start making informed decisions today.

FAQ

What is the meaning of technical debt?

It’s the cost you take on when you use quick, less-than-ideal solutions in your code that need to be fixed later. Over time, this can slow down your team and make future changes more challenging and expensive to implement.

Is technical debt good or bad?

It depends. Some debt is a conscious decision to ship faster. However, if you never address it, it becomes a problem. The key is knowing when it helps you move forward and when it's quietly holding you back.

What's technical debt in Scrum?

In Scrum, technical debt builds up when you cut corners to meet sprint goals. If ignored, it slows future velocity. Over time, it can also reduce sprint predictability and make planning less reliable.

What are the 4 quadrants of technical debt?

Deliberate and reckless, deliberate and prudent, inadvertent and reckless, inadvertent and prudent. Each shows how and why the debt was introduced.