Systems at the Edge
The previous four essays in this series developed a framework for thinking about adaptive physiology—velocity, stability, signal quality, consolidation, form. But somewhere along the way, I started noticing the same patterns everywhere. The concepts aren’t specific to endocrinology. They’re specific to complex adaptive systems in general.
This essay is an attempt to unpack that intuition. I want to see whether the framework scales—whether velocity, stability, and form are useful lenses for thinking about organizations, learning, cities, relationships, and other systems that have nothing to do with thyroid hormone or testosterone.
What I’ve found is that these ideas are old. They’ve been discovered and rediscovered across disciplines. The vocabulary differs, but the underlying insight is the same: complex systems survive in a narrow band between rigidity and chaos, and their capacity to adapt depends on how they balance change against coherence.
The Core Insight
Strip away the biological details, and the underlying structure is this:
Any system that adapts must change fast enough to respond to its environment but not so fast that it loses its coherence. The quality of information flowing through the system determines how well it navigates this balance. And successful adaptations must be locked in somehow, or they’re just noise.
Prigogine: Dissipative Structures
The physicist Ilya Prigogine won the Nobel Prize in Chemistry in 1977 for work on “dissipative structures”—systems that maintain organization by dissipating energy. Far from equilibrium, small perturbations can amplify. The system can spontaneously reorganize into new patterns of greater complexity.
Kauffman: The Edge of Chaos
The biologist Stuart Kauffman found that systems seem to evolve toward a particular regime: not frozen in order, not dissolved in chaos, but poised at the boundary between them. This maps almost directly onto the Zone A/B/C model from the first essay.
Taleb: Antifragility
Nassim Nicholas Taleb’s concept of “antifragility” captures something I was circling around in the hormesis discussion. Antifragile things actually benefit from volatility. But the stressors must be bounded. Small, frequent shocks make the system stronger. Large, rare shocks destroy it.
Meadows: Leverage Points and Stocks
Donella Meadows conceptualized systems in terms of stocks and flows. In my vocabulary, flows are velocity—the rate at which things move through the system. Stocks are more like stability—the buffers that absorb variation and maintain coherence over time.
The Pattern Across Domains
| Thinker | Velocity analog | Stability analog | Optimal zone |
|---|---|---|---|
| Prigogine | Energy flux | Structure | Far from equilibrium |
| Kauffman | Mutation/change rate | Canalization | Edge of chaos |
| Taleb | Volatility exposure | Robustness | Antifragile regime |
| Meadows | Flows | Stocks/buffers | Balanced feedback |
| West | Metabolic rate / innovation | Network efficiency | Optimal scaling |
Applying the Framework
Organizations
Organizations with high velocity and low stability should be chaotic—lots of activity, no persistent improvement. Organizations with high stability and low velocity should be frozen—stable but unable to adapt.
Learning and Skill Acquisition
Optimal learning happens at the edge—challenges slightly beyond current ability, supported by adequate foundation. This is Vygotsky’s zone of proximal development, reframed.
Relationships
Relationships with high velocity and low stability should be volatile—intense but fragile. Relationships with high stability and low velocity should be stagnant—comfortable but dead.
What the Framework Predicts
- Sweet spots are narrow and unstable
- Different systems have different sweet spots
- Signal quality is a multiplier
- Consolidation is often the bottleneck
- Velocity and stability requirements scale together