We’re in a Dissipative Phase of Agentic AI (i.e., Rapidly Increasing Entropy)

By Dan Jaye, CTO

We’re in a moment of extraordinary acceleration. Every week, new agentic AI systems appear: frameworks, tools, and protocols designed to reason, adapt, and act. Innovation is exploding in every direction. But beneath the excitement lies a clear signal: we’re in what physicists call a dissipative phase – a period of rapidly increasing entropy, where creativity outpaces organization.  

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What ‘Entropy’ Really Means Here

In thermodynamics, entropy is a measure of disorder in a system. In technology, it’s what happens when progress outstrips coordination, when too many teams solve the same problem in different ways. Each new model, agent, or API might add value, but collectively they create friction, fragmentation, and fatigue.

That’s exactly where we are today with agentic AI. The Model Context Protocol (MCP), for example, has evolved in months from a clean client-server concept to a sprawling web of hosts, servers, tools, and orchestrators, each interpreting the spec differently. The result: massive creative energy, and equally massive complexity.

Recognizing the Pattern

Every major innovation wave follows this pattern:

1. Invention: A new idea ignites experimentation.
2. Proliferation: Many versions emerge, and entropy rises.
3. Standardization: Shared frameworks and governance restore order.
4. Maturation: The system stabilizes, setting the stage for the next leap.

We saw it with the early web (HTML and HTTP), with programmatic advertising (OpenRTB and Prebid), and now with AI agent frameworks. Each time, the “dissipative phase” is where progress looks chaotic but is, in fact, a necessary precursor to coherence.

Entropy isn’t new. It’s a predictable byproduct of innovation.

The Leadership Lesson

Here’s the key insight: entropy doesn’t mean failure; it signals momentum. The only way to reduce disorder is to inject new forms of energy, like structure, standards, and deliberate coordination. That’s leadership’s role during the dissipative phase: not to resist the chaos, but to shape it.

Every time we simplify one layer of AI infrastructure, complexity shifts somewhere else, into governance, data pipelines, or compliance. The challenge is systemic, not local. The organizations that thrive are those that see the whole system and manage it holistically.

From Chaos to Clarity

At Aqfer, we see our role as applying that organizing energy. We help enterprises bring order to their AI ecosystems: standardizing data pipelines, enforcing governance, and ensuring interoperability across tools and cloud platforms. Our mission isn’t to slow innovation but to make it sustainable; to turn entropy into intelligence.

Entropy is not the enemy of progress. It’s the price of evolution. Every breakthrough creates its own turbulence. What separates winners from the rest is how quickly and intelligently they channel that energy into something coherent.

Build for Clarity, Not Control

The dissipative phase always feels messy, but it’s also when the future is written.

If you can see the patterns beneath the chaos and build for clarity instead of control, you don’t just survive the entropy. You can turn it into your competitive advantage.