From Liability to Leverage: Turning Technical Debt Into Investment

A Practical Guide to Knowing When to Pay It Down and When to Let It Ride

You’re racing against a deadline, juggling several urgent tasks. Your manager asks for status twice a day, and the pressure to deliver as soon as possible is mounting.

There’s a worrying piece of code that isn’t entirely up to par, but you tell yourself, “I’ll clean it up later.”, even though you know it’s not going to happen.

You ship the feature and score positive feedback from users. However, in the back of your mind, you know there’s a price tag on that corner you just cut. But have you ever asked yourself:

What is the price tag of that technical debt?

Traditionally, we think of technical debt as a ticking time bomb, a messy leftover. But what if we began viewing it more like a strategic investment?

When managed well, temporary shortcuts can deliver quick wins—faster market entry, early validation, or resource savings—that might outweigh the cost of refactoring later.

This article explores how to approach technical debt as a calculated risk rather than a looming liability and how to be a product-minded strategist.

Every Debt Has an Interest Rate

Technical debt refers to the design or implementation choices that speed up delivery in the short term but potentially incur higher maintenance costs later.

Ward Cunningham, who created the term, compared these compromises to financial debt:

When you borrow “quick fixes” now, you must eventually repay the “principal” (e.g., refactoring effort) with “interest” (increased complexity, defects, and slower feature delivery).

Unlike in finance, the time required to pay interest is not fixed in software development. Some codes can have large tech debt for years without incurring large interest payments. On the other hand, for some code, the interest rate can grow exponentially.

That means we can make deliberate choices to meet pressing deadlines or market opportunities while controlling how and where tech debt is created.

To start, let’s divide technical debt into Strategic (Positive) and Accidental (Negative) debt:

• Strategic Technical Debt:

  • Debt that is created intentionally.

  • Its goal is to maintain speed or quickly validate a product concept.

  • It’s strategic because you are accepting a known cost to capture a bigger opportunity in the near term.

  • Example: You take shortcuts when prototyping a new feature to test market interest. If the prototype flops, you’ve saved lots of time and resources. If it succeeds, you can refactor or completely redesign it later.

• Accidental Technical Debt

  • Unplanned debt.

  • Created by poorly managed processes—rushed sprints, inadequate testing or code review, lack of documentation—or poor architecture choices.

  • Leads to code that’s fragile and hard to maintain.

  • Often accumulates unnoticed, accumulating interest until it causes major slowdowns.

Recognizing Debt That Hurts

Not all debt impacts your codebase in the same way. Before deciding whether to refactor it, first identify whether the debt is actually hurting your ability to deliver quickly and reliably.

As stated above, Accidental tech debt is an unplanned or poorly managed debt that emerges from existing code. Therefore, deciding whether to pay it down must focus on its present impact:

On the other hand, for tech debt to be Strategic, it has to be a decision to skip certain best practices based on balancing its future impact and benefits:

The questions above should help you identify trouble spots in your existing or planned code. At the same time, from my experience, every dev team has an extensive “To Do” list of tech debt tasks they’d like to address. This list usually hangs at the very bottom of their backlog.

Since time is limited, which debt should be prioritized and addressed first?

When to Pay It Down

The key to deciding which tech debt to pay first is to identify the debt that is causing the most damage to your product and your team.

Three major factors often guide this decision: the Frequency of change, the Criticality of the area, and the Opportunity cost.

Frequency of Change

The more often you touch or modify code with already existing debt, the more debt you accumulate. Frequent changes increase the complexity and risk of introducing regressions.

❓Questions to Consider

• How often does the team update or extend the functionality in this part of the codebase?

• Have minor modifications caused production incidents, bugs, or required patching?

• Does the current design adhere to the Open-Closed principle, or would extending the current functionality require a rewrite?

💰 When to Pay It Down

• If the area sees constant churn and every update is painful or risky.

• If upcoming roadmap items depend heavily on this code.

• If the debt is likely to block or slow development.

🛵 When to Let It Ride

• If the code is stable or rarely touched.

• If you plan to deprecate or replace this section soon, making a full refactor unnecessary.

Critical Area

Certain parts of your product or system are inherently more critical. This could be the core architecture on which every feature is built, a must-have product experience your users rely on, or key non-functional requirements such as security or performance.

❓Questions to Consider

• Is this code integral to the product’s core value proposition?

• Would a failure here cause significant business or reputational damage?

• Is the current design flexible enough to accommodate future planned features and growth?

💰 When to Pay It Down

• If the debt exists in high-risk areas—e.g., security modules, payment processing, or core user flows—it’s often safer to resolve issues sooner rather than later.

• If a breach or major outage in this area would significantly harm customer trust or violate regulations.

🛵 When to Let It Ride

• If short-term pressure to validate a market assumption outweighs the cost of addressing a less critical part of the code.

• If the area isn’t mission-critical and the frequency of change is low.

Opportunity Cost

Every hour you spend refactoring is an hour not spent on feature development, experimentation, or other business drivers.

However, the reverse is also true. Ignoring crippling debt can block new initiatives or slow down the entire product roadmap.

❓Questions to Consider

• What features or improvements are you postponing because you’re stuck managing debt elsewhere?

• How does the debt impact your team’s overall velocity and creativity?

• Are there pressing business opportunities, like an upcoming launch, requiring a stable, robust product?

💰 When to Pay It Down

• If the technical debt is causing incidents over and over again, e.g., constant memory leaks crashing servers

• If the debt slows down development, leading to missed market opportunities.

• If cleaning up the debt now unlocks a more scalable architecture, making future feature-work simpler and faster.

🛵 When to Let It Ride

• If you’re in a critical go-to-market push and the debt is unlikely to impact the short-term milestone.

• If the product is still in an experimentation phase and the cost of continuous refactoring doesn’t justify the uncertain ROI.

Summary

As a product engineer, you must take a pragmatic approach to tech debt. It’s not just about how great or lousy a piece of code is but about the value it brings to both customers and the business.

Being strategic about where and how you create tech debt can result in debt that is well isolated, outside of the critical path, and not slowing down future expansion.

And that’s the yin-yang of the development, the balance in the force.

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