The hidden liability in working code is the debt you cannot see—until a tiny change triggers days of debugging. When structure decays, understanding lives only in someone’s head, not in the codebase. Here is how I learned that lesson the hard way and what you can do to avoid the same trap.
Why “it works” can fool you
Large projects rarely fail because a feature refuses to run. They fail because nobody can explain why it works, or how new features might break it. That gap between functionality and understanding is the true liability.
My early pattern: build, then tidy
As a solo developer I tackled the gnarliest task first, produced a quick solution, then spent a day refactoring the resulting spaghetti. Each cycle yielded cleaner components, and eventually an architecture emerged—object pools for a game engine, reusable screens, tidy layers. It felt safe.
The wake-up call on a team project
A friend and I started a Java Spring Boot application. Existing libraries handled most technical hurdles, so I sprinted ahead, believing Spring’s conventions kept things clean. My teammate disagreed: “Great demo code,” he said, “but the business logic is buried. We can’t maintain this.” He pointed out that controllers, services and repositories all held fragments of the same rule set. Any new feature would spread across multiple files, inviting bugs.
Enter clean architecture
By isolating the business core into plain Java objects and treating persistence as an implementation detail, we contained complexity. After the overhaul:
• Business changes stayed in one place.
• New services plugged in without touching legacy code.
• Development velocity increased while stress dropped.
Two sources of hidden liability
1. Arcane knowledge – when behaviour exists only in tribal memory or a dusty document.
2. Spaghetti code – when the “why” is invisible inside tangled conditionals and duplicate logic.
Frequent, disciplined refactoring tackles both.
Why documentation alone is not enough
Maintaining parallel records adds overhead and often drifts out of sync. The goal is self-explanatory code: clear names, small functions, explicit boundaries—and concise comments that capture intent, not implementation trivia.
A note on AI tools
Large language models can format code neatly, yet they still rely on your architectural guidance. Without a clear structure they generate elegant-looking spaghetti. Use AI after you have defined entities, layers and rules, not before.
Key takeaways
• Working code is not the finish line; sustainability is.
• Clean architecture moves knowledge from brains into modules.
• Refactor in short, regular intervals—liability compounds quickly.
• Treat documentation as a complement, not a crutch.
• Guide AI with well-defined boundaries to avoid disguised debt.
Are you sitting on hidden liability in working code? Schedule a codebase diagnostic with Bijuterie Software and turn fragile success into reliable growth.