The Case Against Always Using Design Patterns

You know that feeling when you’re at a buffet and you fill your plate with everything because it’s all available, then realize halfway through that you should’ve just stuck with the pizza? That’s basically what happens when developers discover design patterns. Don’t get me wrong—I love design patterns. They’re like a well-organized toolkit for solving recurring problems. But here’s the uncomfortable truth that nobody wants to admit at tech conferences: design patterns have become the duct tape of modern software development. We slap them everywhere, and then we wonder why our “elegant solutions” are held together with complexity.

The Uncomfortable Truth About Pattern Worship

For years, I bought into the gospel of the Gang of Four. I’d read about Singleton, Factory, Observer, Strategy—all 23 canonical patterns—and thought, “Finally, the keys to good software design!” What I didn’t realize was that I was learning to see problems through the lens of solutions I’d already memorized. Classic case of the hammer looking at the world and seeing only nails. The real issue isn’t design patterns themselves. It’s our relationship with them. We’ve elevated them to something approaching religious doctrine, when they’re really just documented problem-solving techniques. The trouble starts when we forget that crucial word: problems.

The Pattern Paradox: Accessibility as a Trap

Here’s a paradox that keeps me up at night: design patterns were created to make software development more accessible to average developers. And they succeeded brilliantly. Now developers who wouldn’t otherwise be capable of building complex systems can do exactly that. But then something weird happens. We watch inexperienced teams take patterns like Singleton and create architectural nightmares. I once worked on a codebase with hundreds of Singletons. Not twenty. Hundreds. The developer who built it clearly knew the pattern well enough to recognize it was useful… just not well enough to recognize when to stop. The asymmetry is brutal: implementing a design pattern takes three minutes. Removing it takes three days, when you finally realize it was a mistake. And by then, the entire system depends on it.

When Flexibility Becomes Fragility

Let’s talk about what complexity actually looks like. Here’s a classic example of what I call “Pattern Creep”:

# The simple solution that actually works
class UserRepository:
    def __init__(self, database):
        self.database = database
    def find_by_id(self, user_id):
        return self.database.query(f"SELECT * FROM users WHERE id = {user_id}")
    def save(self, user):
        self.database.execute(f"INSERT INTO users VALUES (...)")
# The "flexible" solution using patterns
class DatabaseConnection:
    _instance = None
    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance
class RepositoryFactory:
    @staticmethod
    def create_user_repository():
        return UserRepository(DatabaseConnection())
class UserRepositoryAdapter:
    def __init__(self, repository):
        self._repository = repository
        self._cache = {}
        self._observers = []
    def register_observer(self, observer):
        self._observers.append(observer)
    def find_by_id(self, user_id):
        if user_id in self._cache:
            return self._cache[user_id]
        user = self._repository.find_by_id(user_id)
        self._cache[user_id] = user
        self._notify_observers('user_found', user)
        return user
    def _notify_observers(self, event, data):
        for observer in self._observers:
            observer.update(event, data)
class CachingStrategy:
    def execute(self, repository, user_id):
        return repository.find_by_id(user_id)

Both do the same thing. One is eight lines. One is fifty. Guess which one the developer felt prouder about shipping? The first one solves the problem. The second one solves the problem and three hypothetical problems that never materialized.

The Hidden Cost: Cognitive Load

There’s something nobody talks about when they discuss design patterns: they multiply the cognitive load on your entire team. Every new developer who joins your project now has to learn not just your business logic, not just your framework, but also every pattern your codebase has accumulated over the years. If your team has used Factories, Adapters, Decorators, and Strategies—all legitimate patterns!—you’ve just added hours to their onboarding. And then there’s the code review nightmare. Did the developer use the right pattern? Did they use it correctly? Should that have been an Adapter or a Facade? Now you’re debating design minutiae instead of discussing the actual problem.

The Creativity Killer

Here’s what haunts me about pattern-heavy codebases: they stifle creative problem-solving. When you have a hammer made of Gang of Four patterns, every problem starts looking like you need another hammer. New developers especially fall into this trap. They learn five patterns and try to use all five on their next feature. The result is “design-driven development” instead of “problem-driven development.” I’ve watched developers refactor a simple conditional into a State pattern just because they’d learned about it last week. The code went from ten lines to a hundred. The functionality remained identical. The “flexibility” never got used. Consider this scenario:

// What the code needed
const processUser = (user) => {
  if (user.status === 'active') {
    sendNotification(user);
  } else if (user.status === 'pending') {
    sendApprovalEmail(user);
  } else if (user.status === 'inactive') {
    archiveUser(user);
  }
};
// What someone inevitably suggests
class UserState {
  execute(user) { throw new Error('Not implemented'); }
}
class ActiveUserState extends UserState {
  execute(user) { return sendNotification(user); }
}
class PendingUserState extends UserState {
  execute(user) { return sendApprovalEmail(user); }
}
class InactiveUserState extends UserState {
  execute(user) { return archiveUser(user); }
}
class UserProcessor {
  constructor() {
    this.states = {
      active: new ActiveUserState(),
      pending: new PendingUserState(),
      inactive: new InactiveUserState()
    };
  }
  process(user) {
    return this.states[user.status].execute(user);
  }
}

The second implementation is “elegant.” It’s also solving a problem you don’t have. You have four users statuses. Maybe you’ll get five more. Maybe you won’t. Why add seventeen files and one hundred lines of code for a “maybe”?

When Patterns Make Sense

I’m not advocating for code chaos. Some contexts genuinely benefit from design patterns.

Situation A: You're building a UI library where plugins can hook into multiple lifecycle events → Observer pattern makes sense
Situation B: You have several ways to create complex database connections → Factory pattern has actual value
Situation C: You need to swap entire implementations at runtime → Strategy pattern solves a real need
Situation D: You might need to support multiple database backends someday → Maybe implement an abstraction layer
Situation E: You have a simple CRUD operation that currently works fine → Put that pattern DOWN

The key word in all the legitimate cases: actual value. Not theoretical value. Not hypothetical value. Not “the book says we should.”

The Anti-Pattern Pattern

There’s something darkly funny about this: we’ve started treating “simplicity” as a design pattern in itself. “Don’t repeat yourself,” “YAGNI” (You Aren’t Gonna Need It), “Keep It Simple, Stupid”—these are all pattern-adjacent principles that are supposedly protecting us from pattern abuse. But guess what? They’re often ignored just as easily. YAGNI becomes a principle people mention in standup while adding a Factory for a class that gets instantiated exactly once. Here’s the decision framework I actually use now, and I’ve found it cuts through the noise:

The Real Skill: Knowing When to Say No

The developers I respect most aren’t the ones who can recite all twenty-three Gang of Four patterns. They’re the ones who can look at a codebase where someone tried to be “clever” and confidently say, “This needs to be simpler.” That requires a different kind of expertise: the ability to distinguish between legitimate architectural challenges and problems you’re creating to justify using a pattern. I’ve seen teams that adopted this philosophy explicitly. They have one rule: “You can use a design pattern if you can articulate the specific, current problem it solves.” Not “problems it might solve.” Not “problems in similar systems.” Current problems. Real requirements. The codebases built under that rule? They’re usually the easiest to maintain.

The Maintenance Reality

Nobody talks about the long-term cost of pattern accumulation. You ship a feature using the Decorator pattern. Elegant. Then you ship another using Strategy. Then another using Adapter. After a year, you have Factories creating Builders that construct Facades that delegate to Decorators that implement Strategies. And someone new joins your team. Good luck explaining that architecture in your onboarding doc. Actually, let me rephrase: your onboarding doc probably doesn’t explain it because nobody thought it was worth documenting. They thought the patterns were self-explanatory. They’re not.

A Personal Confession

I once spent two days implementing a beautiful Observer pattern for a feature that needed a simple callback. The pattern made me feel intelligent. It impressed my code reviewers. It also made the code harder to test, harder to understand, and harder to modify when requirements changed. The requirements changed on day three. That experience was humbling. It taught me that intelligence in programming isn’t about how many patterns you know. It’s about choosing the simplest possible solution and having the maturity to resist the urge to “improve” it with architecture.

The Way Forward

Design patterns are tools. Tools are useful. Sledgehammers are useful. They’re just not useful for hanging a picture frame. The next time you find yourself reaching for a design pattern, ask yourself these hard questions:

• Am I solving an actual problem, or preventing a hypothetical one?
• Would someone else understand my code faster with or without this pattern?
• Is my team already familiar with this pattern, or am I introducing new complexity?
• What’s the cost of getting this wrong, and does the pattern meaningfully reduce that cost?
• Could I solve this problem in half the lines of code if I wasn’t thinking about patterns? Most importantly: can you delete this pattern later if you need to, or have you committed to it forever? The codebases I enjoy working with aren’t defined by the patterns they use. They’re defined by their restraint—by the patterns they didn’t use, by the flexibility they didn’t add, and by the code they kept simple enough that a new developer can understand it in an afternoon. That’s not sexy. That’s not impressive in tech talks. But it’s what actually makes software good. Design patterns are tools for solving real problems. The trick is having the wisdom to know when you actually have a problem, and the discipline to walk away when you don’t.