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We live in an era where technology is everywhere, within reach, and seemingly capable of solving any problem. Frameworks, libraries, architectures, and automation tools are emerging and evolving at a dizzying pace. Anyone today can learn to build a distributed app with microservices, automatic orchestration, asynchronous queues, CI/CD pipelines, and cloud infrastructure—all this, often before even understanding whether the end user actually needs that product.
And it is precisely here that one of the most serious, yet most underestimated, problems in our sector arises: over-engineering.
A destructive, insidious tendency that hides behind good intentions, but ends up hindering what should be the primary objective of every project: work, be useful, generate real value.
Over the past 15 years, I've closely observed dozens of projects—internal, client, consultancy, startup, and established company—fail under the weight of overly sophisticated technical choices. Almost never was the problem a lack of tools or expertise. Almost always, however, the failure was caused by wanting to build a spaceship to do a bicycle's job.
The ego behind every technical decision
Too often technology is chosen not to solve a problem, but to to prove something.
Demonstrate your expertise, your capabilities, your vision. Demonstrate to your team, your clients, and yourself that you can manage Kubernetes, adopt event-driven architectures, and work with distributed stacks. But all of this, without a concrete need, becomes a mere exercise in style.
- How many projects have adopted microservices for applications used by a few hundred users per day?
- How many teams have spent months building hyper-scalable systems… for an internal management system with limited access?
- How many headless frontends, SPAs, and PWAs have been released? without even a solid backend or a real user base?
The point is not to belittle these technologies, but contextualize themIf the goal is to impress, perhaps complexity makes sense. But if the goal is to release a functional, useful, and maintainable product, then simplicity is often the most courageous and professional choice.
Everyday reality in development teams
Over-engineering isn't an abstract or theoretical concept. It's something that manifests itself every day within technical teams in the form of poor decisions that slow everything down: decisions that seem sensible on paper, but which in practice turn into obstacles to delivery.
It's easy to succumb to the allure of complex solutions, especially when you're convinced that "doing things right" means structuring the project as if it were going to support millions of users from day one. But this belief, in practice, becomes the starting point for a series of inefficiencies that stall development and consume time, resources, and enthusiasm.
In practice, over-engineering results in delays, inefficiencies, misunderstandings, and frustration.
It often happens that we witness scenarios like these:
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A startup that spends months designing “ready-to-scale” infrastructure before having an MVP.
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A team that debates for weeks on which architectural pattern to adopt, without having defined the data model.
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An app that relies on distributed asynchronous events… but fails to send a confirmation email.
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Separate repositories for each microservice, each with its own pipelines, which break with every commit.
Meanwhile, the customer waits. The market moves. Needs change.
And the project remains stationary, wrapped in its elegant complexity.
The false myth of early scaling
One of the most common reasons for adopting overly complex architectures, especially in early-stage projects, is the supposed need to be "ready to scale." It's a phrase heard everywhere, from startups to corporate teams, and it always sounds rational. No one wants to be unprepared when traffic increases or the project explodes. The problem, however, is that most projects never get to that point. And in the meantime, the choice to structure everything as if success were guaranteed becomes a burden.
Chasing premature scalability is, in reality, one of the most dangerous forms of over-engineering.
It means dedicating time, budget, and resources to optimizing for a hypothetical future, while the present is still being built. It's like designing a 12-lane highway for a city that hasn't even been founded yet.
One of the most common justifications for over-engineering is this:
“Let’s do it this way, because we have to climb later.”
But the truth is Scaling is pointless if you don't have real users first.
There's no point in designing a distributed infrastructure if your load can be handled with a single instance.
There's no need to introduce Kafka or RabbitMQ if you can achieve the same result with a simple cron job.
There is no need to orchestrate 10 containers if your stack can run locally with a docker-compose.
When talking about scalability, it's important to remember that:
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Simplicity is the best starting point: what you understand and control scales best.
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Performance issues should be addressed when they exist, not foreseen months in advance.
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Modular doesn't mean complicated, but prepare naturally for growth.
Scaling is a need that is earned, not an excuse to complicate everything from the start.
What really works in a software project
Regardless of technological trends, the latest frameworks, or the most complex architectures, every software project that works consistently and generates value has one thing in common: It is built to be useful, understandable and sustainable over time.
There's no need to invent anything. Just look at the common threads of resilient applications, those that are maintained with ease, and that manage to grow without becoming a nightmare.
These are projects that do not always shine for their technical originality, but which they do exactly what they promise to do, reliably and without surprises. In many cases, they're also boring—in the best sense of the word. No one is afraid to touch them, no one has to restart five services to run a test, no one gets lost in a thousand different repos.
Experience teaches us that successful projects share some very simple, but fundamental characteristics:
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The code is readable, even from those who didn't write it.
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Deployment is fast, predictable and non-anxiety generating.
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Features are released often, tested quickly and integrated seamlessly.
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The technologies chosen are known and manageable from those who work there every day.
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End-user problems are always at the center, not sacrificed for technical elegance.
You don't need spells or exotic stacks. You just need concreteness.
It is important to remember that Winning isn’t about impressing your team with sophisticated solutions, but about delivering a product that works and that people actually use.
True seniority is knowing how to say no
In the world of software development, the concept of "seniority" is often misunderstood. Too often, it's associated with the amount of technology you know, the ability to use complex tools, or the number of architectural patterns you can apply by heart. In reality, true professional maturity emerges in another form, much less visible, but definitely more useful for projects: the ability to recognize when a solution is excessive. And above all, to be able to state it clearly.
Being senior doesn't mean chasing complexity. It means have the clarity to understand when it is not necessary, and the authority to stop.
It means writing simple, yet robust code.
It means designing with future maintenance in mind, not just personal satisfaction.
It means choosing reliable, familiar, and well-supported tools, even if they're not the latest releases.
Being senior, in practice, also means saying:
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“We don’t need a Redis cluster, we can manage the logic at the application level.”
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“Let's avoid fragmenting into eight microservices: there are only three of us, it would complicate our lives.”
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“We know PHP and MariaDB well, and with these we can go online safely.”
Knowing how to say "No" isn't a technical limitation. It's a conscious design choice.
It's about giving up complexity to ensure stability.
It's about putting the result at the centre, not the form.
It's delivering today, without compromising the ability to scale tomorrow.
In a world where many chase novelty, those who know how to defend simplicity are, today more than ever, true professionals.
Conclusion: Build solutions, not monuments
When developing a digital project, it's easy to get caught up in the technology itself: the idea of using a cutting-edge stack, creating a highly modular structure, showcasing elegant, textbook architectural solutions. But it's crucial to remember that the ultimate goal is not to demonstrate skills, but to solve real problems.
The customer doesn't pay to see your microservices architecture.
It doesn't care how many containers you're orchestrating, or whether you're using GraphQL, gRPC, or event sourcing.
Pay for an app that works, a website that loads quickly, a dashboard that returns the right data in a timely manner.
Pay for an outcome, not the underlying infrastructure.
Your value as a developer, architect, or team lead It's not measured by how many tools you know, but in your ability to choosing the right ones in the right context.
And above all, in your ability to know when not to use any more than necessary.
So, next time you're designing a new solution, stop and ask yourself:
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Do you really need it?
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Is this the easiest way to fix the problem?
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Will the team be able to maintain it in six months, without anxiety or roadblocks?
If even one of these answers is “no,” you are likely building a technological cathedral to pitch a tent.
And in that case, maybe it's time to get back to basics:
Write clear code.
Use what you need.
Release quickly.
Making things work.
Because in the end, What remains is the solution. Not just and always architecture.
