Technical debt is often used as an excuse
If you’re calling everything in your codebase “technical debt,” you’re not being honest with yourself, or your company. The term “technical debt” wasn’t meant to be a placeholder for bad code or misaligned decisions. Ward Cunningham coined it to describe something very specific, a deliberate trade-off. You move fast, take a shortcut, and commit to fixing it later. You make that decision with your eyes open, not because you were in a panic or didn’t know better, but because the cost-benefit made sense. But somewhere along the way, we diluted that meaning. Now, teams slap the label onto whatever mess they don’t want to explain.
The problem is, this mindset spreads. It creates lax habits on your engineering teams. Deadlines become excuses to compromise quality, and everyone assumes the damage will just be fixed “someday.” That’s not how you build reliable systems, or reliable teams. Real technical debt is structured. It’s documented in the backlog. There’s a Jira ticket attached to it. There’s a timeline to pay it back. If those things don’t exist, you’re not carrying technical debt. You’re just carrying risk disguised as a plan.
From a leadership perspective, this isn’t just a vocabulary problem. It’s a signal. When teams misuse terminology like this, it often points to deeper issues in how technical decisions are being managed. Product is probably pushing too hard. Engineering may be under-resourced. Or maybe there’s no shared understanding of what “done” actually means. Either way, the result is the same, misalignment, inefficiency, and snowballing complexity. You won’t see it right away, but you’ll feel it later in system performance, customer satisfaction, and engineers burning out.
You don’t need to overcomplicate this. Create clarity. If something’s broken because we decided to borrow time, then call it technical debt, document it, track it, fix it. If it’s just poor implementation under excuse-heavy management, then say that too. As a leader, your job isn’t to buffer truth, it’s to clarify it and drive momentum. Don’t hide behind bad terms. Make your teams define debt by commitment, not by default.
Not every instance of problematic code qualifies as true technical debt
When everything is labeled “technical debt,” you lose precision, and with it, the ability to solve the right problems. In reality, there are three separate kinds of substandard code you’ll find in most systems, and they each need a different approach.
The first is real technical debt, the type Ward Cunningham actually defined. This is intentional. The team makes a clear decision to cut a corner, document it, and commit to fixing it. This is calculated risk-taking. Not surprising, most code doesn’t fall into this bucket.
Next is accidental complexity. Fred Brooks described this decades ago. It’s what happens when teams misunderstand a system or make flawed architectural choices. It’s not always due to carelessness. Sometimes it’s just inexperience or outdated assumptions. Teams might choose frameworks that are too heavy or engineer features that don’t align with the rest of the design. These mistakes grow slowly, and by the time you notice, unwinding them requires major rework.
Then there’s just bad code. These are the emergency fixes, the weekend check-ins, the unreviewed patches under pressure. There’s no process, no design, and usually, no one is proud of it, because it wasn’t meant to last. But it ends up staying in the system far longer than planned, simply because it works and no one wants to touch it again.
Each of these categories exists for different reasons. Treating them the same leads to wasted time, mismanaged investment, and unresolved foundational problems. If you call it all “debt,” you risk applying the wrong fix. You’ll build plans based on false assumptions, and the real issues, like training gaps, architectural flaws, or misaligned priorities, go unsolved.
As a C-level executive, you need that clarity to lead effectively. Teams should be trained to diagnose the problem, not just name it. Push them to classify the issue accurately. This improves how you prioritize work, allocate engineering resources, and make product trade-offs. If your team can’t explain whether they’re dealing with poor execution, misjudged complexity, or a carefully calculated shortcut, the system will reflect that confusion. You don’t scale confusion. You solve it.
Mislabeling substandard code as technical debt
When teams constantly label broken or careless code as “technical debt,” they’re not clarifying the problem, they’re cushioning it. That comfort slows down progress. It gives teams permission to sidestep responsibility by pretending there’s a plan when there isn’t. Over time, this erodes technical discipline and opens the door to more shortcuts that never get corrected.
This kind of thinking becomes cultural. Leaders start to tolerate rushed, undocumented patches because they’ve seen it before. Developers stop pushing back on unrealistic deadlines. Resources get diverted from maintenance to feature delivery. Engineering’s ability to scale reliably declines, and no one catches it early because everything looks “planned.” But if the code is substandard and there’s no explicit commitment to fix it, no timeline, no backlog item, it’s not debt. It’s unmanaged technical risk.
Language impacts behavior. If you use precise language, you drive more accurate decisions. Repeated mislabeling limits transparency. It hides deeper operational issues like insufficient QA, lack of technical oversight, or overly aggressive time constraints. These are symptoms of a system under pressure, and if you’re not careful, they compound.
Executives need to recognize what this signals. When teams overuse the term “technical debt,” they’re not just describing code, they’re describing a culture where bad decisions are normalized. That’s not a prioritization strategy. That’s drift. You solve it by being direct. Encourage your engineering org to call things what they are. Don’t inflate intent where it doesn’t exist. Push for clarity, not comfort.
You can’t hold the system to high standards without visibility. You don’t need a new framework or methodology; you need truth in how work is described and tracked. That’s what drives performance. Straightforward definitions and honest conversations make engineering stronger. Everything else delays progress.
True technical debt should be associated with a clear prioritization and remediation plan
If you’re going to call something technical debt, then you need to treat it like an actual liability, tracked, reviewed, and resolved. Without a specific backlog item, a documented plan to fix it, and a target timeline, it’s just neglected code, not debt. Having a label isn’t enough. Execution matters.
Real debt is intentional. It comes from a deliberate trade-off where speed is prioritized and long-term costs are accepted. But that deal only makes sense when there’s a roadmap to pay it back. If there’s no follow-up plan, you’re simply carrying unresolved problems from one release cycle to the next. That compounds disorder in your systems and makes scaling harder.
From a leadership perspective, this is about commitment. Strategy isn’t just about what you launch next quarter; it’s also about what technical decisions you’re going to resolve, and when. If your teams are making short-term decisions that affect structural components of your platform, you need to see that on paper, clearly scoped, with ownership and deadlines assigned.
When debt is logged and actively managed, it can be part of a smart engineering process. But when there’s no intent to fix it, calling it “debt” only creates noise. You can’t improve what you don’t track. And no CTO or VP of Engineering should be comfortable with ambiguity in system integrity.
Executives should set the expectation: technical debt must be visible and actionable. Treat it like the operational risk it is. If it exists only in conversation but not in the backlog, it doesn’t count. That kind of selective attention weakens trust across product, engineering, and leadership. Clarity keeps teams accountable. It also protects what matters most, momentum and reliability. Without both, scaling becomes guesswork.
Main highlights
- Misused terminology erodes accountability: Technical debt should only refer to intentional, short-term trade-offs with a clear repayment plan. Leaders must enforce precise language to prevent poor code from being disguised as strategy.
- Categorization drives the right solutions: Most bad code stems from accidental complexity or rushed execution, not deliberate debt. Executives should push teams to classify issues accurately to ensure effective prioritization and resource alignment.
- Culture shapes code quality: Normalizing the misuse of technical debt fosters engineering complacency and masks deeper operational failures. Leaders should address this pattern early to preserve system integrity and team performance.
- Visibility distinguishes intention from neglect: Real technical debt must have tracked ownership, timelines, and backlog placement. Without these, leaders risk scaling on top of unresolved liabilities instead of deliberate decisions.
