HN Debrief

Perfection is not over-engineering

  • Programming
  • Software Architecture
  • Product
  • Startups

The post argues that perfection in engineering is not bloat for its own sake. In the author's framing, a system becomes "perfect" when it fits a tight set of constraints and requirements exactly, while over-engineering happens when teams solve for constraints they do not actually have. That landed with people who are tired of hearing “don’t let perfect be the enemy of good” used to excuse fragile software, sloppy architecture, and feature churn that leaves core bugs and maintainability untouched. The common example was small teams adopting microservices for imagined scale, then inheriting distributed-systems pain without any of the benefits.

Treat “good enough” as an explicit tradeoff, not a virtue signal. If requirements are fuzzy, document what you are intentionally not handling yet, so speed today does not turn into blame and rewrites later.

Discussion mood

Mostly positive toward the post's instinct to defend quality and reject "good enough" as an excuse for junk, but skeptical of its philosophy. The strongest resistance was to the idea that most software problems have one perfect solution and to the vague treatment of changing requirements, deadlines, and tradeoffs.

Key insights

  1. 01

    Microservices mostly solve organizational scale

    Microservices make sense when the company itself has to operate like an internal economy, with semi-independent groups owning interfaces between them. That is a Conway's law problem more than a pure software design win. Using that model in a tiny product with few users buys you coordination overhead, distributed debugging, and partial solutions to scale problems you do not yet have.

    If a small team is proposing microservices, ask which team boundary or deployment constraint forces them. If the answer is future scale in the abstract, keep the monolith.

      Attribution:
    • win311fwg #1
    • var0xyz #1
    • xnx #1
  2. 02

    Dropped edge cases need receipts

    Accepting a 90th percentile solution can be sane, but only if the missing 10 percent is explicit and traceable. Otherwise the pain gets socialized onto whoever gets paged later, while the original tradeoff vanishes from memory and the code looks like developer negligence. The better pattern is to document the cut, wire in logging or deliberate failure paths, and preserve a path to extend the design later instead of hard-coding today's shortcut into tomorrow's architecture.

    When you cut scope for speed, record it in tickets, commits, and monitoring. Make unsupported cases observable so future incidents point back to a decision, not just a line of code.

      Attribution:
    • sesm #1
    • okwhateverdude #1
    • ozim #1
    • skydhash #1
    • tetha #1
  3. 03

    Most software has multiple acceptable optima

    The sharpest criticism was not that quality is unimportant, but that software rarely collapses to one uniquely right answer. Teams juggle time, cost, familiarity, maintainability, and changing business needs. That leaves a frontier of decent choices with different tradeoffs, not one perfect endpoint. This matters because talking as if the right constraints will reveal one inevitable design can hide real judgment calls and make contingent choices sound objective.

    Force architectural reviews to name the tradeoffs being bought and the ones being deferred. If two designs are both viable, choose on explicit business grounds instead of arguing that one is uniquely correct.

      Attribution:
    • tombert #1
    • lalitmaganti #1
    • IanCal #1
    • yuliyp #1
    • 0x20cowboy #1
  4. 04

    The useful distinction is accidental complexity

    Several comments translated the post into a more grounded lens. Some complexity is essential to the problem itself and has to live somewhere. The failure mode is accidental complexity introduced by bad architectural choices or misunderstood abstractions. That framing makes the debate less moralistic. Elegance is not over-engineering if it removes accidental complexity, while a supposedly pragmatic design can still be the worse choice if it spreads unavoidable complexity across more moving parts.

    When someone calls a design over-engineered, ask whether it removes or adds accidental complexity. That question is more useful than debating whether the design feels too abstract.

      Attribution:
    • dondraper36 #1
    • godelski #1
    • zzzeek #1
  5. 05

    Requirements discovery still needs discipline

    People agreed that requirements are often learned through shipping, but pushed back on treating that as license for vagueness. A trial only helps if it tests a real hypothesis. Teams get into trouble when every decision is hedged with "we may want this later," which keeps all options open and makes every tradeoff expensive. Experience helps here by making people less attached to perfect mental models before users show up, not less rigorous about what is being tested now.

    Write experiments as hypotheses with a success condition and a kill condition. Do not let "we're still learning" turn into permanent refusal to make local decisions.

      Attribution:
    • bad_username #1
    • bluefirebrand #1
    • calebkaiser #1

Against the grain

  1. 01

    Perfectionism does block real shipping

    Not everyone bought the claim that perfectionists are mostly mythical. Some pointed to side projects and startup attempts that die in private because rewriting feels safer than release, feedback, and business work. In that world, polishing is not engineering rigor. It is avoidance. There was also a narrower version of this view from people who simply enjoy endless refinement and do not care about shipping at all, which is fine as a hobby but useless as a business model.

    If a product effort keeps rewriting before users see it, treat that as a go-to-market failure, not a code quality strategy. Put a date on external feedback and make rewriting justify itself against that date.

      Attribution:
    • malux85 #1
    • ryandrake #1
    • datakan #1
  2. 02

    Some rigor really is too expensive

    A credible minority argued that over-engineering is best understood as effort with poor payoff, not as solving the wrong problem. The examples were manufacturing tolerances that barely affect the final machine and software teams sinking huge effort into practices like exhaustive test regimes with little business value. The point is not anti-quality. It is that diminishing returns are real, and mature engineers should be able to say when extra rigor costs more than the risk it removes.

    Use cost-benefit language for quality investments. If a test, abstraction, or tolerance is expensive, estimate the failure rate and impact it prevents before making it mandatory.

      Attribution:
    • prmph #1
    • starky #1
    • 0xbadcafebee #1

Reference links

Engineering essays and references

Concepts and historical framing

  • Worse is better
    Offered as the classic counterpoint that simpler, faster-moving systems can beat more theoretically perfect designs.