July 20, 2026
Perfect? Or Perfectly Extra?
Perfection Is Not Over-Engineering
Techies fight over “perfect” as commenters call out overkill, ego, and fantasy planning
TLDR: The article argues that “perfect” design isn’t the same as overbuilding; the real mistake is solving problems nobody actually has. Commenters were split, with some calling that smart and others saying perfection is a fantasy in a fast-changing world where plans, teams, and needs keep shifting.
A spicy essay about software design has kicked off a very relatable internet brawl: is “perfect” a noble goal, or just a fancy excuse for making things way too complicated? The author argues that “perfect” isn’t the villain at all. In their view, a solution only becomes over-the-top when it solves the wrong problem. If you clearly know what you need, they say, the “perfect” answer naturally appears.
But the comments? Oh, they were not ready to let that slide. One camp basically said, “Nice theory, but real life is messy.” IanCal pushed back hard, arguing there usually isn’t one perfect answer because teams are always balancing different goals, and spending forever defining requirements can be a terrible business move. Another commenter, leugim, warned that chasing perfection in a changing world is how you end up with a bloated mess full of old decisions stuck together like geological layers — yes, they actually dropped the phrase “complexity astronauts,” which deserves a trophy.
Still, the anti-slop crowd had their moment too. MatrixMan cheered the pushback against the classic excuse of “don’t let perfect be the enemy of good,” saying it’s often used to defend software that’s just plain bad. And then, in peak comment-section fashion, W-Stool arrived like a movie sage with the minimalist mic drop: perfection is when there’s nothing left to take away. So no, the real drama wasn’t the essay — it was the crowd arguing whether “perfect” is wisdom, delusion, or just another meeting that should’ve been an email.
Key Points
- •The article distinguishes over-engineering from pursuing a perfect solution, defining over-engineering as solving the wrong problem.
- •It argues that a perfect solution can exist when requirements and constraints are clear enough to narrow viable options to a best fit.
- •Technology choices such as Python on Lambda or Django versus Flask are presented as requirement-dependent rather than universally correct.
- •The article says libraries, APIs, and internal tools should be treated as products because they have users with needs.
- •A small team operating multiple data-sharing microservices is used as an example of architecture that may sacrifice data integrity and add overhead without solving a real problem.