Design too much, build just enough

Source: Dev.to

“Overengineering is the hallmark of an inexperienced engineer”

Introduction

The narrative that “the simplest solution is always the best” is taught in computer‑science classrooms worldwide. I bought into it, spending hours redesigning systems to make them as simple as possible—only to realize I’d gone too far and had to redesign again. By the end of the day I was spending more time tweaking designs than actually implementing them.

Conversations with senior engineers during an internship showed me that overengineering can be an asset. In robotics, for example, I began to view overengineering not as a vice to be squashed but as a skill to be embraced.

The truth is that simple implementations are better than overengineered ones, but overengineered designs are a valuable tool for ensuring those simple implementations are the right ones.

Ground Rules

Overengineering is dangerous; there’s a reason people are warned against it. To avoid causing more harm than good, we need to follow strict ground rules.

Overengineered solutions should never be fully implemented

Design a broad solution that considers as many edge cases as possible, then ruthlessly simplify during implementation. Thinking through failure modes during design is easier than discovering them later. Treat overengineering as a mental stress test, not a blueprint for production.

Solution complexity should match problem complexity

A to‑do‑list app does not need the architecture of a virtual machine. Overengineering a complex problem can be risk management; overengineering a simple problem is just procrastination.

Clarity over cleverness

The final solution must be clear. Nobody cares about clever one‑liners or “10x engineer” tricks if they hinder understanding. Write robust code that others (and your future self) can read, and document the why behind the what.

Understanding the Problem Space

“All I know is that I know nothing.” – Socrates

Overengineering should not be about showing off; it’s about exploration. No one can know everything about every problem, and it can be hard to discern what you need to know. Overengineering forces you to ask the right questions:

• Should my simulator use spatial hashing, or will that add too much overhead?
• Should my wear‑levelling algorithm include bit masking, or am I storing unnecessary information?

There’s no need to force something into a design where it doesn’t belong, but the bar for exclusion should be high. Knowing exactly why a particular problem doesn’t need a certain solution is just as important as knowing why it does.

Increasing the surface area of our design also brings a hidden benefit.

Failure Coverage

“The best thing you can do is figure out everything that can go wrong before you start writing code. It’s much better to filter out non‑issues than to add fixes later.”

A throwaway comment from my tech lead about my wear‑levelling solution stuck with me. I initially tried to handle every conceivable error: page wear, power loss mid‑write, radiation‑induced bit flips, etc. Implementing all of that at once was impossible, but the exercise highlighted which edge cases truly mattered.

When you overengineer during the design phase, you make it easier for your future self. Implementation is already hard; having to invent new design parts to cover unforeseen failure modes only adds decision fatigue.

The benefits aren’t purely pragmatic. Overengineering can be fun—an explorative play that motivates you. If you have a tendency to overengineer, embrace it, but keep it reined in.