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How to Know When You're Over (or Under) Engineering


Helping you learn practical, straightforward methods to boost your soft skills and enhance your career as a software engineer.


Weekly Newsletter

April 8th, 2025

A Smarter Way to Scope Your Engineering Work

It's easy to over-engineer a feature. It's even easier to hack something together and hope it holds. Both come with costs — whether it's wasted time or work you'll soon regret.

Over-engineered systems waste time solving problems that may never show up. Under-engineered work creates messes that slow everything down, making it harder to deliver value.

The best software engineers I know scale their solutions to fit the feature. They build with the problem, the customer, and the future in mind.

This week, we're digging into what it means to build the right thing at the right scale, spotting when you're going too far, and stopping yourself from phoning in a half-baked solution.

The Two Extremes: When Engineering Misses the Mark

Engineers don't wake up and decide to over-engineer a solution. It usually starts with good intentions.

You want the feature to scale. You want it to be flexible. So, you build something generic enough to support future use cases, even if those use cases don't exist yet. Weeks later, no one wants to touch the code — it's already too complex.

Under-engineering happens just as easily.

The deadline is tight. The scope is fuzzy. You cut corners and figure you'll clean it up later. But "later" never comes, and your quick fix becomes someone else's long-term headache.

The problem isn't ambition or speed. It's misalignment. When you're unclear on the actual need, you default to habits: build too much or too little.

Getting it right means staying close to the context: the customer, the timeline, and where this work fits in the bigger picture.

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How to Scale Your Solutions

Not every feature needs the same level of engineering.

Some problems need a quick solution so you can test an idea or move the product forward. Others demand stability, performance, or flexibility right out of the gate.

What matters is matching your engineering effort to the value and risk of the work.

Here's how to think about it:

  • If the problem isn't fully defined, keep the solution simple. Focus on clarity. You can revisit it once things are more detailed.
  • If the feature touches revenue or is part of a critical workflow, take your time. This is where resilience and accuracy matter.
  • If it's internal or low-risk, choose speed. Solve the problem, make it readable, and move on.

It's fine to treat your code as a first pass at the solution. In fact, that's how most software starts. Just know that "temporary" code often sticks around longer than expected. So, even if you move fast, make sure the next person can understand what it does without guessing.

Think less about perfect code and more about appropriate investment. Let the problem size and business context set the bar.

How Great Engineers Decide What to Build

There's a difference between writing solid code and making good decisions.

The best engineers are exceptional at asking questions that help them build at the right scale.

Here's what they do differently:

  • They get clear on the problem. They don't start coding until they understand the goal. If the problem isn't well defined, they ask questions until it is.
  • They don't chase perfection. They look for the right amount of polish based on how the feature fits into the product. Not everything needs to be a reusable component.
  • They keep one eye on the future. They don't overbuild, but they think ahead. They leave room for growth, especially in areas likely to evolve.
  • They work with the business, not just the code. They talk to product, design, and other engineers to understand what matters most. Their decisions aren't based on preference — they're based on context.

Great engineering is about building the right thing, at the right scale, for the problem in front of you.

That takes judgment — and good judgment comes from staying close to the work: the problem, the timeline, the user, and the impact.

So before you open up your next pull request, ask yourself:

  • What matters most for this feature: speed, resilience, or flexibility?
  • Who's impacted if it fails?
  • If this lives longer than expected, will it still hold up?

I'd love to hear if you've seen a great example of right-sized engineering (or a painful one). Just hit reply

David Ziemann

Founder of MoreThanCoders.com
david@morethancoders.com

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