Introduction
When I refer to modern computing, I mean the technological world we live in today and how systems have evolved to their current state.
The core problem is that features, security, and performance are often bolted on over time, resulting in fragile systems with unpredictable behaviour and unreliable performance.
This pattern has been visible since at least the early 2000s, as technology has advanced by layering new abstractions and versions on top of old foundations rather than rethinking those foundations entirely.
Many people do not notice this problem because systems appear to work well enough most of the time. Issues are only addressed when failures occur, and fixing individual problems creates the illusion that the approach is sustainable.
In reality, this leads to an endless cycle of patches, increasing security risks, and growing system complexity. As more technology is built on top of already fragile systems, especially with the introduction of AI, the potential impact of failures becomes larger and more difficult to control.
This article focuses on explaining how modern systems reached this state and why continuing down this path creates long-term technical and security risks.
Complexity Built on Complexity
Systems usually grow by reacting to problems as they appear. When an issue is found, it is added to a list of fixes, and in many cases the solution becomes an add-on or a temporary patch that works well enough to ship and eventually becomes part of production.
When new features are added on top of older foundations, unnoticeable bugs begin to appear. These bugs can cause strange behaviour or introduce security issues where attackers can bypass certain layers because there is no clear or consistent relationship between them.
As systems grow larger, security vulnerabilities, performance issues, and design failures become more common. This leads to increasingly fragile systems. As technology advances, attacks become more frequent and more sophisticated, making it easier for attackers to disrupt operations or cause real harm.
To compensate, systems demand more powerful and expensive hardware just to maintain acceptable performance. In many cases, this cost is unnecessary, as better-designed systems could run efficiently on cheaper hardware, reducing pressure on both companies and consumers.
Once complexity reaches a certain point, understanding how a system truly works becomes extremely difficult. When layers are bolted on without clear structure, the system turns into a web of disconnected parts where reasoning about behaviour can take years, even for simple changes.
Why "Working" Is Not Enough
When people say a system “works”, they usually mean it has minimal bugs and can complete the task it was designed for. This does not mean the system is effective, secure, fast, or pleasant to use.
Fixing issues only when they appear often creates more problems than it solves. The fixes are rarely integrated into the system’s foundations and instead sit on top, increasing complexity and hiding deeper issues.
Fragile systems are often accepted because they are cheaper and easier in the short term. The mindset becomes “don’t fix it until it breaks”, even though many problems could be prevented by designing solutions that are built into the system rather than bolted on later.
Over time, this leads to predictable outcomes: weak security, slow performance, frustrating user experiences, and poorly designed systems that are difficult to maintain or improve.
Why This Is Becoming More Dangerous
Modern systems operate at a scale far larger than in the past, often forming the foundation for entire industries, governments, and daily life.
For example, operating systems like Windows have evolved over decades. While parts of the system have been redesigned and reworked over time, much legacy code and structure remains, which can lead to inconsistencies and limitations when new features are added. Changes such as major UI redesigns demonstrate that some problems cannot simply be bolted on forever and eventually require foundational rework.
When fragile systems are used at massive scale, small bugs can cause widespread outages, and hidden vulnerabilities may remain undiscovered until serious damage has already occurred.
Automation often operates without a full understanding of a system’s foundations. As a result, it tends to encourage additional abstraction and layering, which can amplify existing structural problems rather than resolve them.
When failures occur in these environments, the consequences are no longer small. People lose money, lose access to critical services, and in some cases lose their ability to work altogether.
What Needs to Change
The mindset needs to shift from “I want a new feature” to asking how that feature fits into the existing system, how space is made for it properly, and what testing is required to ensure it does not introduce vulnerabilities or failures.
Time and automation should not be used to bolt solutions on faster. They should be used to identify risks early and help integrate changes into the system’s foundations, where security, performance, and usability can be strengthened rather than compromised.
Systems should be designed around security, design, and performance from the start, not treated as concerns to address later.
Continually patching problems creates more work over time and increases the risk of causing harm to users or to the system itself.
The deeper the understanding of a system’s foundations, the better decisions can be made about integrating new features with minimal side effects.
Rushing solutions skips important considerations and leads to repeated rework later. Slowing down to build solutions that fit properly results in more stable and future-proof systems.
Why This Matters Now
This problem is harder to ignore today because technology has advanced to a point where fragile foundations are being pushed to their limits. Continuing without change risks widespread failure rather than isolated issues.
If systems continue to grow without fixing their foundations, outages will become more frequent, more severe, and affect far more people across critical platforms and services.
Now is the right time to rethink how systems are built because we have both the experience and the tools to do so. Technologies such as AI can help analyse systems more deeply, but they also demand high performance and reliable foundations to operate safely and effectively.
Without stronger foundations, advanced systems amplify existing weaknesses rather than solving them.
The goal is a future where technology is strong, understandable, and reliable, rather than fragile, unpredictable, and difficult to trust.
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