There’s a quiet tragedy in software development that we don’t talk about enough: the projects that fail not because they were rushed, hacked together, or underfunded—but because they were too well-engineered.

We’ve all seen it. A new project kicks off, and the team wants to “do it right.” That means:

  • Everything configurable.
  • Extensible plugin systems.
  • Abstracted interfaces for hypothetical future use cases.
  • Performance optimizations for scale that may never come.

These are all “best practices,” right? But here’s the thing: they often kill projects.

The Trap of Premature Scalability

The desire to build scalable, flexible, future-proof software is usually rooted in unexamined dogma. We’ve absorbed the idea that “good” software is general-purpose, modular, and ready for anything. But in reality, most software doesn’t need to be any of those things—at least not at first.

The result? Teams spend months (or years) building elegant architectures that never ship. Or they ship something so complex that no one wants to touch it. Meanwhile, the “lazy” dev who just hardcoded a few things and moved on? Their tool is in production, solving real problems.

Survivorship Bias in Software

We look at broken systems and say, “They should’ve done it properly from the start.” But we don’t see the graveyard of projects that did try to do it properly—and failed before they were useful.

This is classic survivorship bias. The systems that survive are often the ones that were hacked together quickly, met a need, and evolved just enough to keep going. They weren’t “correct” in the abstract sense. They were useful.

The Myth of the Lazy Dev

There’s a narrative that “lazy” developers cut corners and leave messes for others to clean up. But many of the systems we rely on today were built by people who just wanted to get something working. They weren’t lazy—they were pragmatic.

Ironically, the most successful systems often become invisible. They just work. No one writes blog posts about them. No one rewrites them. They quietly do their job until they’re replaced—not because they failed, but because the people who understood them moved on, and no one wanted to maintain a system that didn’t need fixing.

When Success Leads to Failure

Here’s a paradox: a project that succeeds wildly—solves the problem, requires little maintenance—can fail in the long run because it doesn’t justify ongoing investment. Knowledge fades. People leave. Eventually, the system needs to change, but no one remembers how it works. So it’s replaced.

Meanwhile, a painful, messy system that requires constant attention keeps a team staffed and engaged. It survives because it hurts just enough to justify its own existence.

So What Should We Do?

This isn’t a call to abandon good engineering. But maybe we should be more skeptical of “best practices” that aren’t grounded in the actual needs of the moment. Maybe we should value working code over elegant abstractions. Maybe we should stop shaming “lazy” devs and start learning from them.

Sometimes, the right thing to do is the simplest thing that works.