Sassination or Hypernation

Split image showing a trader on a stock exchange floor above and an executive meeting below, illustrating market narratives versus operational reality.

I recently listened to a Bloomberg Odd Lots episode and a few things really stood out.

First, they were unusually candid about how detached market pricing can be from day-to-day product reality. They openly acknowledged that many traders and even specialist investors rarely use the software they trade, which means conviction can be built on screens, not on lived operational experience. Financial models become proxies for understanding. Multiples become arguments. The product itself becomes almost optional.

Second, it highlighted just how hyper this market is right now. A single narrative shift can ricochet through an entire sector in hours, even when the underlying reality is more nuanced. “AI can write code” becomes “software is dead” with remarkable speed. The story tightens, spreads, and hardens into a trade.

The useful part, the silver lining, is what this reveals about how modern organisations think under pressure. It is easy to imagine the C-suite as somehow insulated from the news cycle, too busy building to be distracted by the noise. But leadership teams are not immune to information that moves at light speed. They read the same headlines. They see the same charts. Their boards forward the same think pieces. Their investors ask the same questions.

And that matters, because the cognitive environment is shifting faster than operational reality.

Yes, the ground is moving. Knowledge work is changing. The economics of building software are changing. But the reality inside organisations remains stubbornly slow. Not because leaders are dim or resistant, but because enterprises are made of people, permissions, processes, and legacy decisions. They are systems with memory. They do not pivot on command just because a narrative got traction on Tuesday.

There is a reason major platform transitions still cause missed quarters. It is not the code. It is the semantics, the data definitions, the governance, the training, the behavioural change, and the risk of disrupting revenue flows. “What does this field actually mean?” is still a meeting. “Who owns this workflow?” is still politics. “Are we allowed to do it this way?” is still compliance. In many environments, the constraint is not capability. It is coordination.

The more we accelerate change at the edge, the more we rely on stability at the core.

This is why the current moment produces such cognitive dissonance. At the top of the funnel, AI makes creation feel effortless. A demo appears in minutes. A prototype ships in days. A founder posts a screenshot and a promise. It can look like the future has arrived in full.

But a lot of what is being built right now is not enterprise-grade software. It is persuasionware: impressive interfaces stitched together quickly, often on brittle foundations. Many AI start-ups are being built on vibe coding, and that approach can work remarkably well right up until the first serious customer, the first security review, the first audit, or the first request to support a critical process without downtime. In other words: it works until it has to.

This is not a critique of speed. Speed is valuable. It is a critique of confusion. We are confusing “I can build it” with “I can run it”. We are confusing “a working demo” with “a dependable system”. And markets are especially prone to that confusion because markets love clean narratives.

The irony is that the same forces that make software cheaper to build also increase the premium on what is hard to replace. The more we automate creation, the more value shifts towards trust, reliability, integration, governance, and ownership of the system of record. The more agents do work on our behalf, the more we need clear controls, audit trails, and accountability. The more we accelerate change at the edge, the more we rely on stability at the core.

So perhaps the right way to read the “SaaSpocalypse” is not as an extinction event, but as a sorting event.

Some software businesses were always selling scarcity: scarce engineers, scarce features, scarce ability to ship. AI compresses that scarcity. Those companies will feel the squeeze. But other software businesses are embedded in operations, compliance, and organisational muscle memory. They are not just code. They are how work gets done. Those platforms may look slow from a terminal, but they are durable on the ground.

The market is not wrong to be anxious. It is wrong to assume that the speed of the story is the speed of reality.

If the world is entering a period of hypernation, where capability compounds quickly and narratives move faster than ever, then the practical challenge for leaders is not to chase every wave. It is to distinguish signal from theatre, and to build for a future that arrives unevenly: overnight in the headlines, and gradually in the organisation.

That is not pessimism. It is operational truth.