Engineers must do the right thing, not the easy one. The best solution almost always lives in simplicity, but simplicity is not the same as ease. The easy path hides problems, piles up debt, and collapses under its own shortcuts. The simple path demands discipline, clarity, and the courage to say no to unnecessary complexity. That’s the sharp edge of Ockham’s Razor, a reminder that the simplest solution is the right one, and the right one is almost never the easiest.
Simplicity begins with the discipline to keep the edge clean.
Engineers spend their lives making choices between competing solutions. Centuries before the first line of code was written, a friar named William of Ockham gave us a principle that still guides those choices today. Ockham’s Razor tells us that when faced with multiple explanations or solutions, you should prefer the one that makes the fewest assumptions. Or in the Latin phrasing often attributed to him: entia non sunt multiplicanda praeter necessitatem - “entities should not be multiplied beyond necessity.”
William of Ockham
William of Ockham was a 14th-century English friar, philosopher, and theologian who lived during the turbulence of the Middle Ages: the Black Death, conflicts between emperors and popes, and endless scholastic debates. He is remembered not only for the principle that bears his name but also for his sharp critiques of authority, which often forced him into exile. His “razor” was less a tool of science than of philosophy: a way to strip away unnecessary assumptions and focus arguments on what could be defended. Though Ockham never imagined computers or data pipelines, his insistence on parsimony echoes through modern engineering as a call for designs that are lean, purposeful, and free of excess.
In practice, this means that unnecessary complexity is your enemy: every extra assumption is another place logic can break, every additional moving part another opportunity for failure. The Razor urges you to cut away what isn’t necessary, to reduce a problem to its cleanest expression without diminishing its truth. For engineers, that instinct toward simplicity is less about elegance for its own sake and more about building clarity and resilience into the systems you depend on every day.
And here’s where the real challenge begins. You’ve been there before: staring at a problem with two paths stretching ahead. One looks smooth and inviting - the easy solution. The other looks steeper but more direct - the right one.
In engineering, you often face this tempting fork in the road. The easy path skips the edge cases, patches over the messy parts, or hardcodes what should have been abstracted. It feels good in the moment - it ships quickly and quiets the task board - but it almost always comes back to haunt you. Easy is the friend of the lazy. It whispers that a half-baked solution will be “good enough.” But good engineering is rarely about “enough.” It’s about building something correct, reliable, and maintainable. Always do the right solution, even if it costs more in thought and care. Because in the long run, the easy path is the expensive one.
Now here’s the twist that catches everyone: the right solution is not necessarily the most elaborate or the most technically dazzling. When you finally see it clearly, the right solution is almost always the simplest. This is where Ockham sharpens the blade for you.
A good design leaves no fat, no unnecessary scaffolding, no speculative “we might need this later” cruft. It feels inevitable, almost obvious in hindsight. That’s the essence of simplicity in engineering - not naivety, but elegance. Not “quick and dirty,” but “clear and complete.” As Einstein warned, everything should be made as simple as possible, but not simpler. The best solutions are the simplest ones that still cover the real problem space without cheating or cutting corners.
Think of a data pipeline that needs to aggregate sales data. The easy solution is to bolt on another transformation script, tucked into cron. It works - until three months later, no one remembers how it fits together, and you’re playing archaeology to figure out why the numbers don’t match. The simple solution might be to refactor the logic into the existing ETL flow. It takes longer today, but saves hours of debugging tomorrow. Easy ignores problems; simple solves them.
Or take system monitoring - every engineer’s favorite nightmare. The easy fix for an alert storm is to silence noisy checks and hope the real issues surface later. It’s like turning down the smoke detector because the kitchen gets smoky when you cook. The simple solution is harder: redesign the alert thresholds, consolidate metrics, and make sure every alarm reflects an actionable problem. It takes more discipline, but it leaves you with a system you can trust when things go wrong.
And yet simplicity is rarely easy. The simplest solutions often require the hardest work. They demand that you dig through complexity, explore alternatives, discard clever over-engineering, and wrestle with tradeoffs until only the essential remains. It is far easier to pile on another framework, add another layer of abstraction, or create another ETL job than it is to ask the uncomfortable question: do we really need this?
You know this pattern. It’s easier to add a new piece than to refactor an existing one. Easier to write a wrapper than to fix the underlying issue. Easier to add another dependency than to implement it yourself. But each easy choice is a small debt that compounds. Simplicity means saying no, and saying no is never easy.
So the next time you find yourself at that fork in the road, remember Ockham’s old advice. Don’t mistake the easy path for the simple one. Easy is what gets built when you’re tired or rushed. Simple is what emerges when you refuse to multiply assumptions beyond necessity.
Sharpen the razor often. Use it to cut through the noise, but never to cut corners. The right solution is always the simplest one - and the simplest one is almost never the easiest. But here’s the thing: once you’ve built it, you’ll sleep better knowing it won’t collapse under its own complexity.
After all, there’s a beauty in engineering not in the things we build, but in the discipline of choosing what not to build.