When Words Break Systems: The Semantic Collapse of Modern IT

Language as the Fabric of Coordination

Language once oiled the machine of value creation. In well-functioning organisations, it sharpened clarity, aligned intent, and accelerated trust. Today, in many failing companies, language has turned corrosive. Misused, weaponised, or hollowed out, it no longer supports systems. It infects, distorts, and collapses them.

We are not merely suffering from poor delivery. We are enduring semantic entropy. Meaning is no longer a shared foundation but a contested battlefield.

Without a coherent language, no company can build a foundational system of values.

A belief system needs clarity to take root. If language becomes a corrupted novlang, the moral and strategic compass of an organisation collapses with it.

From Acceleration to Apocalypse: The Fall of Language

In high-functioning environments, language accelerates ownership and execution. It creates frictionless paths between what must be done, who will do it, and why it matters. But something has changed.

Over the last fifty years, postmodernist ideas slowly escaped the academic sphere. At first, they challenged rigid assumptions. Eventually, they were promoted from speculative theory to structural truth. One of their core claims, that reality is bendable through language, has infected entire domains.

This ideology, once confined to critique and discourse, now shapes how companies communicate. In tech, especially, we find:

• Engineers and leaders created by title, not craft.
• Agile declared before it is practised, then abandoned when it fails.
• Stories and epics issued with no narrative, no commitment, no context.

Postmodernism claimed it aimed to free thought, but in practice, it dissolved standards, definitions, and shared meaning. What was once precision is now performative ambiguity.

The Semantic Root of the Dunning-Kruger Epidemic

Without shared language, false confidence thrives. Today, it is easy to appear competent while knowing very little. It is even easier when words themselves are hollow.

For example, vibe coding is not about AI misuse, but about people believing they understand software development because they have acquired some basic vocabulary. They speak of "apps", "APIs", and "platforms" without the grounding to use them responsibly. The real danger is not automation. It is linguistic inflation.

This is how you create systems where, for example, product roles begin dictating to engineers how to perform their work, rather than focusing on the what and the why, because language no longer marks the boundary between intent and implementation.

Every core concept, MVP, PoC, DoR, DoD, carries operational significance. When those terms lose their depth, teams deliver shells, not systems. Theatre replaces Strategy. Claims do replace genuine Craft.

Conceptual Rot and Interface Collapse

The interface between product and engineering is now a semantic warzone. There is no shared conceptual layer anymore.

Ask a team why they chose Kafka and you will hear, "It is the standard." Few will explain whether the team needed message passing, event sourcing, or real-time stream processing. The distinction is not technical. It is conceptual. Yet that conceptual layer has been poorly replaced with brand recognition.

When language fails, so do the boundaries between architecture, strategy, and collaboration. No one knows what anything means. Decisions revert to noise. Misalignment becomes chronic, and rework multiplies.

Titles, Taxonomies, and the Death of Apprenticeship

Title inflation is now routine. People are made "senior" without experience, "IC" without ownership, and "leaders" without followers.

This semantic inflation collapses the apprenticeship model. When titles are detached from the craft, the path to mastery disappears. How can one be mentored when the very steps have been renamed or erased?

Language does not just describe roles. It encodes responsibility, trust, and time served. Destroy that structure, and you break the ladder itself.

Novlang and the Corporate Delusion

Clear language is not just internal housekeeping. It is the foundation of healthy interfaces between teams, and with stakeholders. In platform teams, especially product platform or enablement-focused teams, language and semantics are essential. A shared, intentional vocabulary helps communicate scope, manage expectations, and reflect the right level of abstraction to stakeholders.

When platform teams speak with clarity and precision, they reduce misinterpretation and protect the integrity of their mission. They teach stakeholders to engage at the right level, and what outcomes are expected, not how implementation should be dictated. The same principle applies to customer-facing teams: the quality of external relationships depends on the precision and mutual understanding of the language exchanged.

In many environments, it is now forbidden to speak clearly. Terms like "Definition of Ready" or "Definition of Done" are dismissed as rigid. Metrics are rejected for being "unfair". Principles are called "gatekeeping".

The result is not inclusion. It is entropy. By eliminating structure from language, we eliminate strategy from execution. Spray-and-pray semantics replace deliberate delivery. We have kept the same words but altered their purpose, diluting their original meaning. This semantic drift erodes trust and precision, making it appear as if we are aligned while we are, in fact, working from entirely different assumptions.

This is not agility. It is semantic nihilism.

From Data to Information: The Last Semantic Confusion

In the age of hype, the final confusion is the simplest one: data is not information. Yet companies now pivot based on headlines, LinkedIn posts, or 19-line blog entries.

Strategic decisions require context, structure, and interpretation. Most organisations no longer demand any of the three. They operate on hunches dressed as insights.

We are now witnessing the consequences. Companies that restructured teams or laid off entire departments based on vague AI promises are faltering. Duolingo’s public valuation swing and instability post-AI hype, or Chegg’s collapse in user trust following its rushed AI integration, are not outliers. They are symptoms. These failures are not technological. They are semantic.

As a result, the capacity to think long-term collapses. There is no space left between noise and reaction.

Conclusion – Shrinking Language, Collapsing Systems

We did not lose velocity because of poor tooling or weak talent. We lost it when we abandoned meaning.

When language collapses, craft dies.
When semantics rot, systems fail.
When meaning disappears, strategy becomes impossible.

Recovery does not begin with tools or titles. It begins with words.
Defined. Aligned. Restored.

This is a cultural repair job. It starts by restoring meaning where it has faded. Teams must relearn the difference between intent and implementation, between signal and noise, between label and value.

But there lies the paradox: the very language we must use to repair the connection to reality is the same language that was corrupted to break it. On paper, this may seem easy to fix. In practice, we face a generational wound. It took two to three generations to dissolve the connection to reality. How long will it take to restore it? Likely far longer than the average modern company is designed to survive.

Because once language breaks, everything else breaks with it.