How to recognize technical debt before it becomes a crisis — 12 warning signs with practical explanations and a prioritized action plan for addressing each one.
What is technical debt? Technical debt is the accumulated cost of shortcuts, outdated decisions, and deferred maintenance in a software codebase. Like financial debt, a small amount is normal — but when it compounds, it slows development, increases bugs, and can eventually make the software more expensive to maintain than to rebuild.
Technical debt is like financial debt: a little is normal and manageable. Too much becomes crippling. The difference is that financial debt shows up on a balance sheet. Technical debt is invisible until it starts costing you — in speed, in stability, in developer frustration, and ultimately in revenue.
This guide helps you identify technical debt in your software before it becomes a crisis, even if you're not a developer.
Technical debt is the accumulated cost of shortcuts, outdated decisions, and deferred maintenance in your codebase. It's not always "bad code" — sometimes it's code that was perfectly fine when it was written but hasn't been maintained as the product evolved.
Common sources:
What it looks like: Adding a new field to a form takes a week. Changing a button color requires a deployment. Small requests consistently take 5–10x longer than you'd expect.
What it means: The code is tightly coupled — everything is connected to everything else, so changing one thing requires understanding and modifying many other things.
Severity: High. This directly impacts your ability to compete and iterate.
What it looks like: You ship a new feature and something unrelated stops working. The checkout breaks when you update the product catalog. The search stops working when you add a new filter.
What it means: There are no automated tests, and the code doesn't have clear boundaries between features. Changes propagate unpredictably.
Severity: High. This erodes user trust and makes your team afraid to ship.
What it looks like: Page load times creep up over months. What used to load in 1 second now takes 3–5 seconds. Users complain. Mobile is especially bad.
What it means: Unoptimized database queries, missing indexes, no caching, bloated JavaScript bundles, or architecture that doesn't scale with data volume.
Severity: High. Speed directly impacts conversion and retention.
What it looks like: You report a bug, it gets fixed, and it reappears a month later. Or a variation of the same problem keeps surfacing in different places.
What it means: The root cause was never addressed — only the symptom. Without tests, the fix can regress when other code changes.
Severity: Medium. Wastes developer time and frustrates users.
What it looks like: There's one developer who "knows where everything is." When they're on vacation, nothing gets fixed. When they're sick, development stops.
What it means: No documentation, no code comments, no consistent patterns. The knowledge is in one person's head, not in the code.
Severity: Critical. This is a business continuity risk.
What it looks like: Your team visibly avoids certain parts of the codebase. Tickets involving "the payments module" or "the reporting engine" sit unassigned longer than others.
What it means: Those areas are poorly written, poorly documented, or both. Developers avoid them because changes are risky and unpredictable.
Severity: Medium. Leads to uneven product quality and deferred improvements.
What it looks like: You're stuck on an old version of your framework, language, or libraries because upgrading breaks things. Security patches can't be applied because they require dependency updates you can't make.
What it means: The code relies on deprecated APIs, version-specific behavior, or libraries that have breaking changes between versions.
Severity: High. Security risk compounds daily.
What it looks like: Your error monitoring tool shows hundreds of errors per day, but "most of them are known issues" that nobody fixes. Actual new errors get lost in the noise.
What it means: Error handling was never properly implemented. Known issues are tolerated instead of resolved.
Severity: Medium. When a real crisis happens, you won't notice in time.
What it looks like: Ask your developer: "How many automated tests do you have?" If the answer is "none" or "a few," every deployment is a gamble.
What it means: The only way to verify the software works is for a human to click through every feature manually — which nobody does thoroughly.
Severity: High. Without tests, you can't refactor, update, or improve safely.
What it looks like: Deploying to production involves multiple manual steps, takes 30+ minutes, and everyone holds their breath. Deployments happen infrequently because they're risky.
What it means: No CI/CD pipeline, no automated checks, no rollback strategy. Each deployment is a manual ceremony.
Severity: Medium. Slows iteration and increases risk.
What it looks like: Nobody can explain the complete data model. There are tables that "might not be used anymore." Columns named temp_fix_2024 or old_price_backup. No documentation of relationships.
What it means: The database has grown organically without deliberate design. Migrations weren't used, or were used inconsistently.
Severity: High. The database is the foundation. If it's a mess, everything built on it is fragile.
What it looks like: Your team has been talking about a "rewrite" or "v2" for months or years, using it as a reason not to fix current issues. But the rewrite never starts because there's always something more urgent.
What it means: The debt has compounded to the point where the team has given up on the current codebase. But without a concrete plan, the rewrite is a fantasy.
Severity: Critical. This is the final stage before a forced rebuild or system failure.
You don't need to fix everything at once. You need to understand what's hurting you most.
Map each sign to its business impact:
| Priority | Fix | Why |
|---|---|---|
| Immediate | Security vulnerabilities, data loss risks | Existential threats |
| This month | Performance issues, deployment pipeline | Revenue and velocity |
| This quarter | Test coverage, documentation, dependency updates | Long-term sustainability |
| Ongoing | Code cleanup, architecture improvements | Continuous health |
The "20% rule" works well: dedicate 20% of development time to reducing technical debt. If you have a 2-week sprint, 2 days go toward debt. This prevents debt from accumulating while still allowing feature development.
If you're not sure how bad things are, get a technical audit. A fresh set of eyes can identify issues that your team has normalized — things that seem "fine" because they've always been that way.
If more than 8 of the 12 signs apply to your software, patching may be more expensive than rebuilding. Read our guide on how to evaluate whether to fix or rebuild for a concrete decision framework.
Worried about technical debt? Request a free technical audit — we'll assess your codebase, identify the highest-priority issues, and give you a clear action plan. Or book a call to discuss your situation.
If this guide resonated with your situation, let's talk. We offer a free 30-minute discovery call — no pitch, just honest advice on your specific project.
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