Technical Debt: What It Is and How to Tackle It

Introduction: Why technical debt matters

When you push a product to market quickly, some shortcuts are taken—less documentation, rushed coding, postponed refactoring. These trade-offs may speed delivery in the short term, but over time they accumulate into technical debt.

For CTOs, CIOs, product managers, and digital leaders, technical debt is more than a coding issue. It directly affects product scalability, performance, and long-term innovation capacity.

What is technical debt?

Technical debt is the implied cost of additional work caused by choosing quick, easy, or suboptimal solutions in software development instead of more robust approaches.

Just like financial debt, technical debt accrues “interest”—the longer it remains unresolved, the more difficult, expensive, and risky it becomes to address.

What causes technical debt?

• Rushed delivery: Prioritizing speed over code quality.

• Changing requirements: Features built for outdated needs.

• Lack of documentation: Knowledge gaps in maintaining systems.

• Legacy systems: Old technology not updated over time.

• Poor testing: Bugs and vulnerabilities left unresolved.

• Skill gaps: Inexperienced teams producing fragile solutions.

What are the types of technical debt?

• Deliberate debt – Taken knowingly to deliver faster (with intent to fix later).

• Accidental debt – Caused by lack of knowledge or oversight.

• Bit rot debt – Systems degrade over time due to neglect or outdated dependencies.

• Design debt – Weak architecture that makes scaling difficult.

• Code debt – Poorly written, duplicated, or unoptimized code.

• Testing debt – Incomplete or missing test coverage.

What are the risks of technical debt?

• Slower delivery: Future features take longer to build.

• Higher costs: Fixing debt is more expensive than preventing it.

• Reduced performance: Applications may lag or crash.

• Security vulnerabilities: Unpatched issues create attack surfaces.

• Lower team morale: Developers frustrated with messy codebases.

• Blocked innovation: Difficult to adopt new tools or platforms.

How can you measure technical debt?

While exact measurement is complex, you can track indicators such as:

• Code quality metrics: Complexity, duplication, maintainability scores.

• Defect density: Frequency of recurring bugs.

• Velocity impact: Reduced speed of delivering new features.

• Technical debt ratio: Remediation cost vs development cost.

• Team feedback: Developer pain points in working with the system.

What are best practices to manage technical debt?

• Acknowledge and track it: Use backlogs or dedicated tools.

• Prioritize fixes: Focus on high-risk areas affecting scalability or security.

• Allocate sprint capacity: Reserve 10–20% of each sprint for debt reduction.

• Refactor regularly: Improve code incrementally, not all at once.

• Adopt CI/CD and automation: Reduce testing and deployment bottlenecks.

• Promote clean code principles: Encourage proper documentation and reviews.

Real-world example

• Twitter struggled with technical debt in its early years. The original Ruby on Rails architecture could not scale, leading to the infamous “Fail Whale” outages. Refactoring into a more scalable system solved the issue, but only after costly downtime.

• Netflix, by contrast, invested early in microservices and cloud migration, reducing long-term debt and enabling faster scaling.

What is the future of managing technical debt?

• AI-driven code analysis: Tools that automatically detect and suggest fixes.

• Cloud-native modernization: Migrating legacy apps to containerized, scalable architectures.

• Shift-left testing: Catching issues earlier in the development cycle.

• DevSecOps: Integrating security into development to avoid risk debt.

Organizations that actively manage technical debt will innovate faster and compete better. Those that ignore it risk higher costs, security failures, and loss of agility.

Key Takeaways

• Technical debt is the cost of shortcuts in software development.

• It can be deliberate, accidental, or the result of neglect.

• Risks include higher costs, reduced agility, and security vulnerabilities.

• Best practices: track, prioritize, allocate sprint capacity, refactor, and automate.

• Future management will rely on AI tools, cloud-native approaches, and DevSecOps.

Conclusion

Technical debt is inevitable but manageable. It is not always bad—it can be a strategic trade-off—but unmanaged debt threatens scalability, security, and innovation.

At Qodequay, we approach digital transformation with a design-first mindset, helping enterprises modernize while minimizing technical debt. Our solutions focus on balancing speed with sustainability, so technology becomes an enabler rather than a burden.