“Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away.” — Antoine de Saint-Exupéry
This isn’t a technical guide, or a tutorial on prompts, or a love letter to the latest framework. It’s something quieter. A reflection on a mindset. On how, as technology accelerates especially with AI we’re beginning to rediscover old ideas under new light.
There was a time when writing code felt like sculpting. Every line held intention. Every decision carried the weight of future maintainability, readability, and pride. Maybe you’ve known someone who’d refactor a function not because it was broken, but because it could be clearer. Maybe you’ve been that someone. And while others rushed ahead, you stayed behind naming things well, splitting methods with care, shaping the invisible structure with the same reverence an architect might shape a quiet, sturdy home.
That wasn’t wasted effort. That was a kind of poetry. We didn’t call it over-engineering we called it love for the craft.
But something has shifted. Not for the worse, not for the better just… algorithmically different. Today, with AI tools like GPT, Claude, Copilot, Cursor, Amazon CodeWhisperer, Tabnine, and the ever-mysterious "vibe coding" mood board that is Twitter dev threads, more and more of our code is being drafted by something that doesn’t sleep, doesn’t snack, and definitely doesn’t understand context.
We’re no longer just authors we’re editors, reviewers, damage control. We’re the second pair of eyes that needs to see what the first pair a well-meaning, overconfident autocomplete engine might have hallucinated into existence.
Perfectionism, once feared as a productivity sinkhole, is quietly reclaiming its space. But not as pixel-pushing or infinite refactoring. Now, it shows up as thoughtful inspection. As a pause. As a second thought. It’s less about elegance, more about integrity.
Aristotle spoke of the Golden Mean the virtue that lives between two extremes. For many years, we believed the middle path in software was shipping fast, keeping things simple, and avoiding the rabbit hole of over design. But maybe that balance is shifting. Maybe, in the age of AI-assisted development, a little more scrutiny, a little more intention, is what brings us back to the center.
In this new world, being a perfectionist doesn’t mean resisting change or clinging to old ways. It means adapting without forgetting why we cared about quality in the first place. It means knowing that while AI might take the wheel, we’re still the ones reading the road.
Between Autopilot and Paranoia: The Mindful Path of Perfectionism
In practice, balance today looks like mindful development. The kind that asks you to slow down, even when the machine speeds up. It’s less about resisting AI and more about learning how to work alongside it without losing your own sense of judgment.
It’s a bit like the mindset from Zen Buddhism: be present, be deliberate. When the AI spits out a chunk of code, I don’t react with blind trust (too lax) or with immediate rejection (too rigid). I try to sit with it. Ask questions. Is it readable? Is it safe? Does it actually solve the right problem?
There’s a Zen saying: “Before enlightenment, chop wood, carry water. After enlightenment, chop wood, carry water.” For us, it’s: Before AI, write code, debug code. After AI… write code, debug code. The work hasn’t disappeared it’s just shapeshifted. The same rituals remain. I still have to carry water, so to speak. Just now, I carry it in a review comment, a test case, a rewritten function.
If Marcus Aurelius were a tech lead, he might remind us to “love the framework of fate” not to curse the tools for what they get wrong, but to treat their flaws as part of the job. We don’t get to choose the wave, but we do get to learn how to surf it.
Finding that balance isn’t formulaic. It’s an instinct built over time. It’s noticing when the AI starts hallucinating confidence into broken logic. It’s choosing to simplify a generated solution instead of praising its complexity. And sometimes, it’s about trusting your own discomfort when something looks right but doesn’t feel right.
The Golden Mean isn’t static. It shifts with context. And in 2025, it just might live somewhere between accepting every AI suggestion and rewriting everything by hand.
The Return of Thoughtful Perfectionism
I find it ironic and exciting that a thoughtful form of perfectionism is making a comeback in software engineering. No, we’re not back to obsessing over whether to name a variable tempData or intermediateResult for hours, nor are we adding pointless abstractions for theoretical use cases.
This new perfectionism is different: it’s human-guided, principle-driven, and focused on safety and clarity. It’s a recognition that in an age where code can be machine-generated in an instant, the real value a seasoned developer adds is thoughtfulness the kind of careful thinking that machines can’t (yet) do.
In practical terms, this means we care about things like correctness, security, and transparency of code more than ever. We double-check that the AI’s code doesn’t have hidden pitfalls. We enforce coding standards so that the next human (or next AI) reading the code can understand it without psychic powers. We pay attention to performance implications and edge cases that an auto-generated solution might miss. We treat code not as an ephemeral throwaway just because it was easy come, easy go, but as an artifact that will live on and needs to be trustworthy.
Ultimately, this is leading us to a more balanced engineering culture. Speed and efficiency from AI plus careful human oversight can coexist. We are learning to harness the brute-force productivity of our silicon sidekicks while applying the nuanced judgment that comes from experience and yes, from our human sense of craftsmanship. The goal is no longer perfection for perfection’s sake (it never really should have been), but a kind of perfectionism with purpose: making the software better in ways that truly matter more robust, more secure, more understandable. It’s almost like we’re channeling that old perfectionist energy, but instead of pouring it into gold-plating the design, we’re pouring it into fortifying the code’s integrity.
So, is perfectionism in software engineering dead now that AI is writing code? Far from it. It’s evolving. We’ve gone from lovingly hand-carving every solution, to sometimes accepting quick and dirty code, and now to lovingly cleaning up quick code. In this journey, we may have rediscovered why we cared about “perfect” code in the first place. Not to satisfy some OCD impulse or to impress others with cleverness, but to ensure our software works well and can be maintained by real people. In the end, the “perfect code” was never about having zero flaws that’s impossible but about striving for excellence where it counts.
The quest for quality has come full circle. The tools and techniques have changed, but the heart of the matter is the same.
this is the beginning of a new era not where machines replace our standards, but where they challenge us to uphold them with even greater clarity.
