Everything works
There is a phase in many systems where everything works.
No alerts. No complaints. No visible failures. The system feels calm. Almost reassuring. This phase is comfortable, but it is also the one I trust the least.
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The Comfort of Perfection
Often, “everything works” simply means the system is still early. Assumptions are hardcoded. Implementations are concrete. Decisions were made before real pressure appeared.
Nothing has had enough time to resist yet.
At this stage, missing structure does not hurt. Missing decisions do not surface. Naive choices remain invisible.
Everything works because reality has not arrived.
The Illusion of Functionality
Another reason everything works is that we are blind to what doesn’t.
A system that actually operates in the real world leaves traces. It produces metrics, latency, alerts, noise. Even small complexity leaves a footprint.
When there are no traces at all, something is usually missing: either traffic, observability, or reality itself.
This usually goes unnoticed: suspiciously low latency can be a strong signal. Not of efficiency, but of logic that never executes.
The False Production Effect
Sometimes the system is “in production” only by name.
It is deployed, but traffic never reaches it. Feature flags are disabled. Configuration points to the wrong storage. The code exists, but the path is never triggered.
Even when the deployment is tested, this state can persist. The tests often exercise what already worked before.
Everything works because nothing new is really happening.
This is hard to detect. From the outside, dashboards look green. From the inside, there is no friction at all.
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Organizational Blind Spot
Organizationally, the “Everyhing Works” illusion is easy to sustain.
Developers may say “it works” simply to reduce pressure. Management wants reassurance without understanding the mechanics. Operations see green graphs and no alerts.
No one explicitly owns the question: “Does this system actually work in reality?”
This is not a people problem. It is a structural gap.
Where Ownership Ends
Eventually, reality arrives.
A real user appears. A real combination of needs. A real dependency activates.
What usually breaks first is user-facing functionality. And the worst case is when the user is the first one who notices the problem.
At that moment, the question often asked is: “Why didn’t we see this earlier?”
The honest answer is rarely lack of skill or intent. More often, the failure lived between zones of responsibility: one team built the feature, another deployed it, someone else monitored it, and the gap between them had no owner.
Even within a single full-stack or microservice team, the same gap can exist. Different people operate with different assumptions, and those assumptions rarely meet until reality forces them to.
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Seeing the Illusion
Over time, I developed a simple internal heuristic.
When everything works, I start worrying about what we don’t see: how much insight we have from inside the system, and whether there are enough real users to expose its weak points.
“Everything works” is not a guarantee of health. Sometimes, it is just a sign that the system has not been tested by reality yet.
And sometimes, the calm is real.
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