Currently very interested in John von Neumann:

Why does complexity in nature grow (e.g., a seed into a tree), while isolated man-made systems tend towards decay (complex factory to less complex car)?

Von Neumann’s solution is the universal constructor, which describes the minimum requirements for a process to allow for non-degenerating complexity.

Its three components are:

* A universal computer for general computation.
* A universal construction arm that can build any object from a description.
* A blueprint (information) that is both interpreted by the constructor and copied for the new creation.

At first glance, this may appear trivial. However, it fundamentally answers how to build systems capable of growing in complexity, being antifragile (Taleb), and evolving.

How does this enable growth if an ideal universal constructor only builds identical copies? The solution lies in copying errors (mutations) of the blueprint. This allows for variance, enabling complexity not only to remain static but also to increase.

The principles underlying the Universal Constructor provide more than an interesting parallel between fields; they form a single, unified framework for understanding any creative process in the universe. This framework links the fundamental laws of physics, the logic of computation, the adaptive engine of biology, and the dynamics of economics.

All these domains can be seen as different substrates running the same core operating system for generating complex, adaptive order.

The Criterion of Generative Capacity

This unified theory even allows us to judge competing economic and societal models on a more rigorous, scientific basis than pure ideology. We can move past subjective debate and apply a concrete criterion: generative capacity.

Generative capacity is the measure of a system’s ability to efficiently explore the vast space of possibilities to produce novel, valuable, and resilient structures. A system with high generative capacity excels at creating solutions to problems, generating wealth, and adapting to change. When we use this as our metric, the conclusions are profound.

The Principle of Indirect Design

The lesson, for me, from this entire line of reasoning—from physics to politics—is a shift in how to judge different complex systems.

The most effective method is not top-down engineering, where a central authority attempts to design a desired outcome.

This approach is brittle, information-poor, and fundamentally limits the system’s creative potential.

Instead, the superior method is indirect design: focusing on crafting the environment in which solutions can emerge from the bottom up. This means obsessively perfecting a simple, clear, and impartial set of rules—the rule of law—that creates a fertile ground for decentralized experimentation.

In this model, the role of governance is not that of an engineer building a machine, but that of a gardener who cultivates the soil, ensures access to sunlight and water, and then allows a million different plants to compete, adapt, and flourish in ways the gardener could never have designed or predicted.