By Arjun Mehta
Technical debt isn't one thing. It's a category of problems with different origins, different costs, and different solutions.
Most teams treat debt as a monolithic problem: "We have too much debt, we need to refactor." That's like saying "our business has problems, we need a strategy." It's true but useless.
Better: understand the types of debt. Recognize the patterns. Know which ones are killing you.
1. Architecture Debt
Your system was built for one thing. Now you're trying to do something else. The architecture doesn't support it.
Example: You built a monolithic application. Now you need real-time features. Monoliths are hard to make real-time. You need to rearchitect. But that's expensive.
Architecture debt compounds fast. Early decisions become hard constraints. New features have to work within the architecture. They get contorted. Code gets ugly. Velocity drops.
Cost: 20-40% of engineering time goes to working around architectural constraints.
Solution: Recognize it early. When you're hitting the same architectural constraint repeatedly, it's time to rearchitect. Don't wait until velocity is 50% lower than it should be.
2. Testing Debt
You shipped features without tests. Code is brittle. Changes break things. Now you can't refactor safely.
Testing debt is insidious because it slows you gradually. You don't notice until you try to change something fundamental and realize: everything breaks.
Cost: 15-25% of engineering time goes to debugging and rework from undetected bugs.
Solution: Write tests going forward. For legacy code, write tests for critical paths. Don't try to test everything retroactively. That's too expensive.
3. Dependency Debt
You used a library. It solved your problem at the time. Now it's outdated. Upgrading breaks things. Not upgrading leaves you on an old version.
Dependency debt is especially painful with security-critical libraries. You're stuck on an old version with known vulnerabilities, or you have to rework code to upgrade.
Cost: 5-10% of engineering time on dependency management and security patches.
Solution: Be selective about dependencies. Prefer boring, stable libraries over trendy new ones. Monitor dependencies for updates. Upgrade regularly, not all at once.
4. Knowledge Debt
The person who built the system left. Nobody else understands it. Code is hard to maintain because the decision-making is encoded in your head, not in the code.
Knowledge debt doesn't show up as slow code. It shows up as high coordination costs. Everything takes longer because multiple people need to understand the system to change it.
Cost: 10-20% of engineering time on coordination, rework, and knowledge transfer.
Solution: Invest in code clarity and documentation. Avoid single points of knowledge. Rotate responsibilities so knowledge is distributed.
5. Data Model Debt
You structured your data one way. Now you need to query it differently. The queries are inefficient. You need to denormalize. Or you need a migration that takes hours.
Data model debt is expensive because data is hard to change. You can refactor code in a day. Migrating data takes planning, testing, and downtime.
Cost: 5-15% of engineering time on inefficient queries and workarounds.
Solution: Design data models carefully at the beginning. But know you'll need to change them. Plan for evolution. Use databases that support schema changes without downtime.
6. Code Quality Debt
You shipped code that works but is hard to read. Functions are too long. Variables are poorly named. Copy-paste code is everywhere.
Quality debt is the most visible but least urgent. The code works. But maintaining it is expensive. Changing it is risky because you're not sure what it does.
Cost: 5-10% of engineering time on rework and debugging.
Solution: Code reviews. Refactoring time in your sprint. Invest in clarity early. It's cheaper to write clear code than to refactor ugly code.
7. Process Debt
Your process was designed for 10 engineers. Now you have 50. The process doesn't scale. Code reviews take forever. Deployment is brittle. Testing is manual.
Process debt shows up as slowness. Not in the code, but in how fast you can ship.
Cost: 10-20% of engineering time on process overhead.
Solution: Invest in infrastructure. Automate testing. Automate deployment. Make code review asynchronous. Scale your process as your team grows.
How Much Debt Is Too Much?
You'll always have debt. The question is: how much?
As a rough guide:
- 0-10% of time managing debt: healthy. You're keeping up.
- 10-25% of time managing debt: starting to accumulate. Plan a refactoring quarter soon.
- 25-40% of time managing debt: problem. You're compromising velocity and quality. Urgent action needed.
- 40%+: crisis. Your team is drowning. New features are nearly impossible.
Most teams are at 25-40%. They don't realize how much debt is costing them.
Why This Matters
When you understand debt patterns, you can:
- Identify which debt is actually killing you (vs. which is theoretical)
- Prioritize: fix the high-cost debt first
- Plan refactoring: architecture debt needs long-term investment; code quality debt is short-term
- Make tradeoffs: sometimes taking on architecture debt is worth it if it gets you to market faster
Without understanding patterns, you treat all debt the same. You refactor equally at every debt type. You waste effort.
With Glue
With Glue, you can identify debt types across your codebase: where's the architectural constraint? Where's the testing gap? Where are knowledge silos? Which dependencies are outdated? Data model inefficiencies? Code quality hotspots?
Once you can see debt types, you can prioritize and attack the right problems.
Frequently Asked Questions
Is some debt intentional? Absolutely. Ship fast, incur debt, pay it back later. That's a legitimate strategy. The problem is teams that incur debt and never pay it back.
How do we explain debt costs to leadership? Invest 1-2 weeks quantifying it. "We estimated 30 features for Q3. We're on pace for 18. Why? 40% of our time is managing technical debt." Leadership understands opportunity cost. Once they see what debt is costing, they'll authorize refactoring.
Should we have a debt-only sprint? Debts vary. Some can be tackled in a week. Some take a quarter. Better: include debt work in every sprint. "We're 70% feature work, 30% debt reduction," is healthier than "90% features, then a surprise debt crisis."