When I started as a coupling supplier over a decade ago, I got asked the same question at least three times a week from engineering teams, small and large: “Is it possible to eliminate all coupling from a software system?” At first, I’d fumble around in my background, thinking about how I engineer flexible, durable couplings for industrial machinery and transfer that logic to code. I’d say something vague about modular design, dependency inversion, and “minimizing tight coupling.” Now, I answer with a more honest, grounded take: zero coupling in software isn’t just unlikely—it’s fundamentally impossible. But that doesn’t mean you shouldn’t chase it. Coupling
Let me break this down with a parallel to my actual work, because that’s how I’ve always thought about software lessons. A coupling, in my world, is a mechanical component that connects two shafts or parts of a machine to transfer power, while accommodating misalignment, vibration, and thermal expansion. If you removed all coupling from a gearbox or a conveyor line, you wouldn’t have a working machine—you’d have two separate, useless parts sitting next to each other. They can’t do the job they were built for without that middle piece that bridges the gap, absorbs the inconsistency between moving parts, and lets them work together.
Software is no different. Every software system is built from discrete components—modules, functions, services—that are meant to work together to deliver a feature. That collaboration is coupling. When you strip it all away, you have a pile of independent, unconnected code that can’t process user requests, store data, or generate output. That’s not a robust system; that’s a collection of scripts that do nothing on their own.
Let’s get specific about the types of coupling I see software teams struggle with most, because this is where the parallel to my coupling business is clearest. First, there’s tight, harmful coupling—the kind you want to minimize, not eliminate. This is when a checkout service in an e-commerce app hardcodes the logic for shipping into its own code, so if your shipping provider changes their API, you have to rewrite the entire checkout module. This is the bad coupling that causes outages, slows down releases, and makes teams reluctant to update parts of their system. My business spends a lot of time designing couplings that eliminate this kind of tight linkage: we use flexible shafts, precision-fit interfaces, and shared tolerances so that two parts can connect without forcing one to match the exact dimensions of the other. That’s exactly what good software engineering aims for: loose coupling, not zero coupling.
Then there’s loose coupling—the kind that’s actually necessary. Loose coupling is when your checkout service depends on a generic payment interface, not a specific payment gateway, so you can swap out Stripe for PayPal with minimal changes. It’s when a notification service sends events to a message broker, so the team managing user profiles doesn’t need to know who’s receiving their updates. This is the coupling that makes systems scalable and maintainable, and it’s the only kind that should exist in a well-designed system. Zero coupling would mean removing even this essential loose coupling. What would that look like? It would mean every service runs in a silo, no service can send or receive data from any other, and there’s no way to coordinate actions across components. You could never build a feature that requires two services to work together—like a user updating their profile and having that change reflected in their order history. That’s not a system; that’s a set of isolated tools, each with a single purpose, incapable of doing anything useful at scale.
I’ve seen teams fall into the zero coupling trap over the years, and it’s always because they misunderstood the goal. A few years back, I worked with a fintech startup that swore they wanted their new banking platform to be “100% decoupled.” They split their system into 47 tiny services, each handling one trivial task: one service only validates email addresses, another only checks zip codes, a third only logs user clicks. They used every pattern they learned in a microservices course—event-driven architecture, dependency inversion, inversion of control. But six months in, they hit a wall. To transfer money between two accounts, they had to coordinate 12 different services, each sending and waiting for events, each with its own retry logic. A single network blip would leave a transfer stuck in limbo, because no central coordination service existed. They’d cut out all intentional coupling, even the necessary kind, and their system became fragile instead of flexible.
That’s the mistake. Coupling isn’t a flaw to be eradicated; it’s a design choice to be managed. The question isn’t “how do I get to zero coupling?” It’s “how do I structure my coupling so that changes to one part of the system have minimal impact on others?” That’s the work my team does every day when we engineer couplings for industrial equipment. We don’t make couplings that connect two parts so tightly that they can’t move—we make couplings that balance the need for connection with the need for flexibility. For example, a jaw coupling we manufacture has a rubber insert that absorbs vibration between two shafts, so if one shaft misaligns, the coupling compensates instead of breaking. That’s loose coupling at work: the two shafts are connected, but not dependent on each other’s exact position. If we tried to make a coupling that doesn’t connect at all, it wouldn’t do anything. Same with software.
Don’t get me wrong—there are benefits to minimizing coupling. I’ve seen teams that reduce tight coupling cut their release cycles by 50%, reduce bug rates by 30%, and make it easier to onboard new developers. But trying to hit zero is a fool’s errand. Even the most decoupled systems still have coupling. Let’s take a system built with event-driven microservices, which people often call “decoupled.” A user service emits a “user_created” event. An email service listens to that event to send a welcome message. A billing service listens to that event to create a subscription. That’s coupling. The user service is coupled to the event schema it emits, the message broker it uses, and the pattern of events that other services expect. If you change the “user_created” event to include a middle name, you have to update every service that consumes that event. That’s coupling, just not the tight, hardcoded kind. You can’t eliminate it; you can only make it visible and predictable.
I’ve also talked to software architects who argue that functional programming or service-oriented architecture can get closer to zero coupling. But even in pure functional systems, functions depend on inputs and outputs—they’re coupled to the interfaces they use. A function that adds two numbers is coupled to the concept of numbers. A function that fetches a user is coupled to the structure of user data. That’s a soft kind of coupling, but it’s still there. It’s the same as the coupling between two gears in a machine: you need them to mesh to transfer power, but you design the mesh to last, to accommodate wear, to not break if there’s a small shift.
So why do people keep asking about zero coupling? Because it’s an appealing ideal. It sounds like a perfect system where every part works independently, no dependencies, no conflicts, no outages. But that ideal is a myth. It’s like asking for a machine that can transfer power without any connecting parts. You can’t do it. You need something to bridge the gap, to handle the differences between parts, to make them work together.
That’s where my team comes in. Just like we design couplings that turn two separate shafts into a working system, we help software teams manage their coupling—minimizing the tight, harmful kind, and embracing the loose, necessary kind. We don’t sell you a one-size-fits-all coupling; we work with you to design the right connection for your system. Whether you’re building a small startup app or a large enterprise platform, we can help you identify where your coupling is too tight, where it’s too loose, and how to balance it so your system is flexible, maintainable, and scalable.
If you’re tired of fighting harmful coupling that slows down your releases, causes outages, and makes it hard to innovate, don’t aim for zero. Aim for intentional, well-managed coupling. Reach out to our team to talk through your system, understand where you’re struggling, and find solutions that fit your needs. We’ve worked with hundreds of software teams over the years, and we’ve seen firsthand that the best systems aren’t the ones with zero coupling—they’re the ones that use coupling as a tool, not a problem.
Jumbo Roll Tissue References
- Fowler, M. (2003). Patterns of Enterprise Application Architecture. Addison-Wesley.
- Newkirk, J., & Vorontsov, A. (2005). Test-Driven Development in Microsoft .NET. Microsoft Press.
- Pairman, J. (2018). Microservices vs. Monoliths: Choosing the Right Architecture. O’Reilly Media.
- Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1994). Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley.
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