Why I Care More About Clarity Than Cleverness in Software

Early on, I used to associate “good code” with cleverness.

If a solution was concise, abstract, or showed off something technically impressive, I felt good about it. And to be fair, clever code can be satisfying to write.

But over time, through coursework, real projects, and maintaining systems longer than I expected to, my definition of good software has shifted. Today, I care much more about clarity than cleverness.

The hidden cost of clever code

Clever code often optimizes for the person writing it in the moment.

It might:

• compress multiple ideas into a single abstraction
• rely on implicit behavior
• assume deep context that isn’t written down
• prioritize elegance over explicitness

The cost doesn’t show up immediately. It shows up later:

• when you return to the code after a few months
• when someone new tries to understand it
• when a bug appears in an unexpected edge case

I’ve learned this the hard way, both from my own code and from inheriting systems where understanding the intent took longer than implementing a fix.

What clarity actually means (to me)

Clarity isn’t about writing “dumb” code. It’s about writing intentional code.

For me, clarity looks like:

• readable control flow
• explicit data movement
• predictable interfaces
• naming that reflects why, not just what
• structure that matches how the system is mentally modeled

Clear code reduces cognitive load. It makes debugging easier, onboarding faster, and future changes less risky.

This mindset is especially important when you’re dropped into an unfamiliar codebase, something I’ve had to do repeatedly across different projects and environments.

When cleverness does matter

This isn’t an argument against sophistication.

There are places where cleverness is appropriate, even necessary:

• performance-critical paths
• algorithmic optimizations
• constrained systems
• well-isolated, well-documented abstractions

The difference is intent and containment.

When cleverness is required, I try to:

• isolate it
• document it
• justify it with evidence
• make sure the surrounding code remains simple

That way, complexity is localized instead of spreading through the system.

Clarity as a team skill

One of the biggest shifts in how I think about software is realizing that code is rarely a solo artifact.

It’s read by:

• teammates
• future maintainers
• reviewers
• sometimes, your future self under pressure

Optimizing for clarity is a form of respect for the people who will interact with the system after you. It also creates a shared language within a codebase, which makes collaboration smoother and decisions easier to explain.

This perspective has influenced how I write documentation, structure projects, and explain technical choices, even when the “clever” option is tempting.

Long-term thinking beats short-term elegance

Software almost always lives longer than we expect.

What feels elegant today can become opaque tomorrow. What feels slightly verbose today might save hours of confusion later.

Choosing clarity over cleverness isn’t about lowering standards, it’s about raising them in the dimensions that matter most over time.

It’s a principle I try to apply consistently, whether I’m writing a small utility, designing a system, or reviewing someone else’s work.

This philosophy shows up throughout the projects and case studies on this site, and it strongly shapes how I think about engineering as a long-term craft rather than a short-term puzzle.