The Hidden Cost of "It Works": Why Quick Fixes Kill Long-Term Speed

It was a Thursday afternoon when the Teams message came in.

A bug in production. A date formatting issue causing checkout to fail for users in certain timezones. Small bug, real impact: the payment flow was broken for roughly 8% of users.

The fix took twelve minutes. A single condition, a timezone offset, a hotfix deploy.

Everyone was relieved. The PM sent a thumbs up emoji. The on-call engineer closed the ticket.

Six months later, that same timezone logic had been copy-pasted into four other places across the codebase. Each with its own slight variation. Each slightly wrong in a different way.

The bug that took twelve minutes to "fix" ended up costing the team three days of a proper refactor, plus two additional incidents in the meantime.

That's the hidden cost of "it works."

TL;DR

• Quick fixes feel like speed. They are actually deferred cost and the interest rate is brutal.
• The damage is dual: it hits the codebase (fragility, duplication, entropy) and the team (decision fatigue, false confidence, loss of standards).
• The solution isn't to never move fast. It's to develop a decision framework that tells you when a quick fix is acceptable and when it will cost you ten times its weight.

Table of Contents

• The Anatomy of a Quick Fix
• The Two Places Quick Fixes Do Damage
• The Broken Windows Effect in Codebases
• Why "It Works" Is the Most Dangerous Phrase in Engineering
• The Hidden Cost, Quantified
• The Quick Fix Decision Framework
• When Quick Fixes Are Actually the Right Call
• Building a Culture That Pays Debt on Schedule
• Final Thoughts

The Anatomy of a Quick Fix

Not all quick fixes are created equal.

Some are intentional trade-offs: "we know this isn't the right solution, we're doing it to ship, and we'll revisit it next sprint."

Others are accidental: "this solves the immediate problem, let's move on", with no intention of revisiting.

And then there's the most dangerous kind: the ones that start as intentional and silently become permanent.

Ward Cunningham, the person who coined the term "technical debt" in 1992, described debt as something you take on deliberately, with a plan to pay it back. The problem isn't the debt itself. The problem is when the plan to repay it disappears.

// "Temporary" quick fix. Added: March 2023.
// TODO: replace with proper timezone utility
const offset = user.country === 'IT' ? 2 : 0
const adjustedDate = new Date(date.getTime() + offset * 3600000)

If you've worked in any codebase for more than a year, you've seen comments like this. The TODO is still there. The "temporary" fix shipped two years ago.

The Two Places Quick Fixes Do Damage

Quick fixes are often discussed as a purely technical problem.

But the damage happens in two places, and only one of them shows up in your code.

In the codebase

This is the visible damage. Over time, quick fixes create:

• Duplication without intention: logic that should live in one place spreads across multiple files, each with slight variations.
• Fragile dependencies: workarounds that assume things about the system that aren't guaranteed to stay true.
• Entropy: the codebase slowly drifts from its original architecture. Modules that were designed to do one thing start doing three.

You've already seen this pattern described in Bad Code Is a High-Interest Loan: each shortcut adds interest that compounds over time.

Quick fixes are where most of that interest originates.

In the team

This is the invisible damage and it's often more costly.

Decision fatigue. Every quick fix that goes unaddressed adds a micro-decision to every future change: "should I work around this, or fix it properly?" Over time, this is exhausting.

False confidence. "It works" becomes the team's de facto quality standard. The bar for "acceptable" slowly lowers. Nobody notices because the shift is gradual.

Loss of standards. When quick fixes stop being exceptions and start being the norm, new team members learn that the norm is acceptable. Standards don't erode from the top down, they erode from repeated practice.

"Any fool can write code that a computer can understand. Good programmers write code that humans can understand."

• Martin Fowler, Refactoring

The hidden cost of quick fixes isn't just the code they leave behind. It's the culture they quietly teach.

The Broken Windows Effect in Codebases

In 1982, criminologists James Q. Wilson and George Kelling proposed the Broken Windows Theory: a broken window left unrepaired signals that no one cares, which invites more disorder. One broken window becomes ten.

The same dynamic plays out in codebases.

One unaddressed quick fix signals to everyone else that this kind of code is acceptable here.

Another quick fix lands nearby. Then another.

Nobody makes a deliberate choice to lower standards. But collectively, the team's behavior changes in response to what they see around them.

Robert C. Martin and colleagues described it in The Pragmatic Programmer:

"Don't leave broken windows (bad designs, wrong decisions, or poor code) unrepaired. Fix each one as soon as it is discovered."

This doesn't mean stop everything and refactor whenever you spot a problem. It means that leaving problems unaddressed always has a cost, even if that cost is invisible today.

Why "It Works" Is the Most Dangerous Phrase in Engineering

"It works" is a binary measurement.

It either works or it doesn't.

But software quality isn't binary. It exists on a spectrum, and "it works" tells you almost nothing about where on that spectrum your code actually lives.

A function can "work" and still be:

• impossible to understand without context
• brittle in edge cases nobody has hit yet
• completely untestable in isolation
• a ticking clock for the next developer who needs to modify it

The problem with "it works" as a standard is that it optimizes for the present and ignores the future. Every codebase "works", right up until it doesn't.

// This "works"
function getPrice(p: any, d: any, t: any) {
  return p - (p * d) + (p * t)
}

// This also works and tells you what it actually does
function calculateCheckoutPrice(
  basePrice: number,
  discountRate: number,
  taxRate: number
): number {
  const discountedPrice = basePrice * (1 - discountRate)
  const finalPrice = discountedPrice * (1 + taxRate)
  return finalPrice
}

Both functions return the same number. Only one communicates intent. Only one is safe to modify six months from now by someone who wasn't there when it was written.

"It works" describes behavior. What you actually need is behavior plus clarity plus maintainability.

The Hidden Cost, Quantified

Let's make this concrete, because abstract arguments about code quality are easy to dismiss in a sprint planning meeting.

Here's a rough model of what quick fixes actually cost over time:

The 1-3-10 rule (based on the well-documented cost-of-change curve in software engineering):

Every quick fix that lands in production without a remediation plan starts at 10x cost, minimum.

Now add compounding.

If that quick fix becomes the foundation for a new feature, the new feature inherits all of its fragility. Every subsequent change that depends on it pays interest too.

The timezone example from the opening of this article illustrates this precisely:

• 12 minutes to apply the quick fix.
• 2 incidents caused by copy-pasted variations of the same logic.
• 3 days to trace, consolidate, and properly fix all four instances.

That's roughly a 36x multiplier on the original time investment, not counting the user impact and the on-call stress.

The Quick Fix Decision Framework

Here's the tool I wish I'd had earlier: a simple framework for deciding whether a quick fix is acceptable, or whether you're about to create a future problem.

Before merging any quick fix, run through these four questions:

1. Is it documented?

A quick fix without a paper trail becomes permanent by default.

At minimum, leave a comment with:

• the date
• why this was chosen over a proper solution
• a link to the ticket for the future refactor

// QUICK FIX - 2025-06-12
// Using a hardcoded offset to unblock the checkout bug (INC-4421).
// Proper fix: centralize timezone handling in a utility module.
// Tracked in: https://linear.app/yourteam/issue/ENG-889
const offset = user.country === 'IT' ? 2 : 0

This comment costs you thirty seconds. It saves the next developer thirty minutes of archaeology.

2. Is it isolated?

A quick fix that touches a core abstraction is fundamentally different from one that lives in a leaf node of your architecture.

Ask yourself: "if this assumption turns out to be wrong, how many places break?"

If the answer is more than one: it's not a quick fix, it's a risk.

3. Does it have a scheduled remediation?

A quick fix without a ticket is just a bug you haven't found yet.

Create the ticket. Assign it. Don't let the sprint end without it existing in your backlog.

The fix doesn't have to be immediate. It has to be visible.

4. Does the team know about it?

Quick fixes made in isolation, under deadline pressure, on a Friday, without review, are the ones that become permanent.

A fifteen-second mention in standup ("I shipped a workaround for X, ticket ENG-889 tracks the proper fix") changes the dynamic completely. It creates shared accountability.

The decision matrix

Use this as a quick gut-check:

When Quick Fixes Are Actually the Right Call

This wouldn't be an honest article without acknowledging that quick fixes are sometimes the right decision.

There are moments where speed genuinely matters more than perfection:

Production incidents. When a bug is actively impacting users and revenue, stopping to architect the perfect solution is the wrong call. Ship the fix. Create the ticket. Come back.

Validated uncertainty. If you're building a feature you're not sure the product will keep, over-engineering it is waste. A deliberate quick fix on an experimental feature is good product thinking.

Clear blast radius. If the workaround is contained, isolated, and fully documented, the risk is manageable. Not every quick fix becomes a monster. Some stay small.

The difference between these and the dangerous kind isn't the code itself. It's whether you're making a conscious trade-off with a plan or an unconscious shortcut with denial.

As Kent Beck put it:

"Make it work, make it right, make it fast."

The problem isn't "make it work", that's always step one. The problem is treating step one as the finish line.

Building a Culture That Pays Debt on Schedule

Individual decisions matter. But so does the environment in which they're made.

If your team is consistently reaching for quick fixes, the problem usually isn't the developers. It's the system they operate in.

A few structural changes that make a measurable difference:

Allocate explicit time for debt reduction.
The teams that manage technical debt best treat it like any other work: they schedule it. A common approach is dedicating 15–20% of every sprint to debt reduction. Not "if we have time." Scheduled.

Make quick fixes visible in your backlog.
Every quick fix should produce a ticket. The backlog is the team's shared memory. If a workaround isn't in the backlog, it doesn't exist as far as future planning is concerned and it will never get fixed.

Normalize "good enough for now, better by [date]".
The goal isn't to eliminate quick fixes. It's to make them explicit. When a developer says "this is a quick fix, the proper solution is tracked in ENG-889, and we've agreed to address it in the next sprint", that's a healthy team.

Review quick fixes in retros.
Not to blame anyone. To learn. Which quick fixes turned into real problems? Which ones stayed contained? What made the difference? Patterns will emerge.

This connects directly to what we explored in Corporate Amnesia: teams don't lose knowledge in dramatic moments. They lose it in accumulation, one undocumented workaround at a time.

Final Thoughts

"It works" will always be a seductive phrase.

Especially at 5 PM on a Friday with a deadline looming.

But after years of working in codebases shaped by the accumulated weight of "it works," I've come to think of it differently.

"It works" isn't a finish line. It's a starting point.

The real question that comes after it is: "and will it still be safe to touch in six months, by someone who wasn't here when we wrote it?"

Every quick fix that answers "I don't know" to that question is a bet. Sometimes the bet pays off. Often it doesn't. And when it doesn't, you don't lose the twelve minutes it took to write, you lose the three days it takes to untangle.

Speed and quality are not opposites. The teams that move fastest over time are not the ones that cut the most corners. They're the ones that cut corners deliberately, visibly, and with a plan to fix them.

That's not perfectionism. That's how you protect your velocity.

This is part of the **Clean Code for Business* series, which explores how code quality decisions translate into real business outcomes.*

If you missed the earlier articles:

• Code Doesn't Quit, But People Do - Clean Code, Technical Debt, and the Bus Factor
• Bad Code Is a High-Interest Loan - How Technical Debt Slowly Kills Team Velocity
• Corporate Amnesia - What Happens When Your Team Forgets How Its Own Code Works

What's the most expensive "it works" you've ever shipped?

Drop it in the comments, the more specific, the better. I'll start: mine was a hardcoded locale string that somehow ended up in twelve files before anyone noticed.

If this resonated, a ❤️ or a 🦄 helps more people find it.

And if you want to follow the series, hit follow, the next article is already in the works.