The Easiest Ways to Generate “Technical Debt” in Product Development!
Technical debt isn’t solely born from bad code; often, it stems from our strategic and managerial decisions that lead projects into a dead end. Here are 6 guaranteed ways to incur technical debt, which might sound all too familiar to many of us:
1) Ignoring AI: Pulling the Handbrake!
Today, overlooking AI tools is effectively ignoring a critical accelerator in development. It’s not just about code generation; it’s about architectural analysis, design pattern suggestions, checking edge cases, and reviewing project structure. When a team doesn’t utilize AI as a technical assistant, decisions become slower, repetitive errors increase, and optimization opportunities are lost.
My personal experience here reminds me of the not-so-distant past before the rise of AI. Back then, just to make a decision and start on a product, I had to think for ages, hold numerous meetings with the tech team and the client, and run endless trials just to get close to the desired result. And that was only assuming we could maintain that standard throughout the development process.
2) Incorrect Architecture: Building on Quicksand
Perhaps one doesn’t realize the depth of this disaster until they experience it firsthand, but one of the fastest routes to technical debt is a “stormy start” without proper architectural design. A wrong architecture might not show cracks in version 1.0, but as the project grows, every new feature becomes more complex and costly. Changing architecture mid-way usually costs exponentially more—not just financially, but also regarding the heavy mental toll on the team and the client.
Essentially, principled thinking at the start—a mix of knowledge, experience, team collaboration, and tools—regarding layers and dependency management directly dictates the product’s future.
3) Distrusting the Developer: Sacrificing Sustainable Quality
When an experienced developer offers a technical suggestion, but the final decision is made solely based on time pressure or a non-technical perspective, the result is usually a temporary “workaround.” Ignoring expert advice replaces sustainable solutions with short-term fixes. This approach might save time today, but it multiplies maintenance costs tomorrow.
I have personally experienced this many times: the opinions of excellent programmers were sacrificed for clients who claimed to know better. Even if the project succeeded on the surface, the real mental burden remained squarely on the developers’ shoulders.
4) Chaotic Task Management: Sailing Without a Compass
Technical debt doesn’t just come from code or architecture; it also stems from a lack of supervision and continuity in product management. Poor prioritization, constant context switching, and a lack of focus lead to half-baked code and hasty decisions. When tasks lack a clear structure, quality is sacrificed for speed.
Most readers here are technical and use project management tools daily, so I’ll put it simply: I’ve often seen product managers—or even developers—use these tools merely as a simple “To-Do List,” operating without knowing exactly where they are now or where they need to be in a few weeks. This lack of continuity in project tracking is a breeding ground for technical debt.
5) Dirty Code and Stylistic Islands
The absence of coding standards (conventions) and weak Code Reviews turn a project into a patchwork of different styles. The result is code that is risky and time-consuming to understand or modify. Technical debt isn’t just about “bad code”; it’s also about “inconsistent code.”
I always expect that when a team works on a product, an “unwritten law” or common language will eventually form among them to minimize stylistic differences in problem-solving. Unfortunately, I have rarely seen this level of team maturity in practice.
6) Documentation Poverty: Knowledge That Dies with Departures
Code that only its author understands is a hidden and dangerous debt. A lack of architectural documentation, missing explanations for technical decisions, or even the absence of minimal comments forces every new developer to waste significant time figuring out the system.
Unwritten knowledge creates a dangerous dependency on specific individuals. When a team member leaves (or is laid off), part of the project’s logic and intelligence effectively walks out the door with them. The cost of this is far heavier than expected, and in smaller projects, it sometimes leads to a complete rewrite of the product.