Back in my undergrad days, I stumbled on the phrase “systems theory.”

A rationalist forever chasing logical completeness, I naturally assumed it was about design. That’s the impression the word “system” gives — how you stack a large program together with good structure. And it had “General” in front of it, no less. Something beyond any one language or domain, an ultimate design principle: I felt some kind of mastery would land in my hands once I’d read it.

As it happened, I was devouring Scott Meyers’ More Effective C++ at the time. A cursed manual that sends you into qi-deviation. The kind of book that, once you finish it, drops you into design hell where your actual work can’t advance a single step. I had learned every tiny trap of pointers, destructors, and exception safety, so writing even one line felt like crossing a minefield. Naturally I couldn’t let a keyword like “General System Theory” slide by.

But finding a book that actually explained it, at a level I could enter, was harder than expected. The first ones I picked up were all abstract and stiff, with nowhere to get a foothold. I combed the university library stacks and spent days wandering the bookshops of Sinchon, hunting for one volume a beginner could read.

And when I finally cracked open the book I had tracked down, what came out was biology.

Cells, organisms, metabolism. Open systems instead of design patterns; flow equilibrium instead of architecture. I was surprised.

Life is not matter but organization

General System Theory was the work of Ludwig von Bertalanffy, an Austrian biologist. His starting point was a revolt against reductionism, the reflex of the science of his day. Reductionism holds that to understand life you break it into small parts and examine the pieces.

He said no. What makes something alive is not a special substance but the way the parts are arranged — their organization. Don’t go hunting for a vital force. Aliveness lives not in the parts but in the relations among them.

A few core ideas, in plain terms.

First, a living thing is an open system. Matter and energy pass through it constantly. Most of the atoms that make up your body get replaced over the years. And yet “you” persist. The substance flows through while the form remains — Bertalanffy called this flow equilibrium, also known as dynamic equilibrium. Think of a candle flame or a whirlpool in a river: the shape holds steady while the material composing it changes every instant.

Second, equifinality. An open system can reach the same final state from different starting points and along different paths. A closed physical system is pinned down by its initial conditions; a living system is not. Jostle a developing embryo and it still grows into the same adult.

Third, hierarchy. Living things stack in layers. Cells gather into tissues, tissues into organs, organs into an organism, organisms into an ecosystem. Each layer is made of the layer below, yet takes on properties the lower layer never had.

Fourth, emergence. That “new property” just mentioned is emergence. The whole is more than the sum of its parts, and “aliveness” resides precisely in that organized whole.

And here is the striking part: the same principles recur at every one of these layers — cell, organism, ecosystem, even society. That is why it is “general.” It was a theory not of any particular creature but of living systems as such.

No design mastery, but still

So systems theory was not a story about software architecture. My mistake.

But its bedrock claim is, in hindsight, exactly the thing a person thirsty for logical completeness should have pricked up their ears at. If life is not matter but organization — if it is a question of arrangement rather than any specific material — then in principle you can build life out of anything able to hold that arrangement.

Not carbon required. Even numbers on a grid would do.

I didn’t grasp that implication at the time. The thing that would show it to me, right before my eyes, I met only much later.

Half a century on, Lenia

It begins with Conway’s Game of Life (1970). Cells on a grid switch on and off, and a few simple rules give rise to moving patterns like the glider. It is, plainly, blocky, digital-looking life.

Lenia takes one step further. Released by Bert Chan around 2018, it makes everything about the Game of Life continuous. A cell’s value is no longer 0 or 1 but anything in between, and space, time, and rule are all smooth.

The result is astonishing. Instead of the angular glider, an organically shaped “creature” appears. The most famous, Orbium, glides smoothly across the screen like a microorganism under a microscope, or a jellyfish.

Above is the official WebGL demo by Bert Chan, Lenia’s creator (source: Lenia). You can load various species and run them in real time. There is only one rule — each cell looks at its neighbors and nudges its value up or down a little — and yet a creature rises on top of it, holding its own shape as it glides. Poke it and it mostly returns to form. You are watching the equifinality from earlier with your own eyes.

These creatures keep their shape while moving, wobble and recover when nudged, and come in a whole zoo of species. No one designed them cell by cell. They arise from the rule on their own and persist as self-sustaining patterns.

Bertalanffy’s definition, on a computer

Watching a Lenia creature crawl, I am watching Bertalanffy’s definition run.

Flow equilibrium. The creature holds its form even though every cell value is overwritten each frame. The material — numbers — flows past while only the pattern remains. A whirlpool made of computation.

Equifinality. Perturb it and it self-repairs to its original shape. Start from a different initial blob and it converges to the same creature. Same destination, many paths.

Hierarchy. A single cell is dead. Cells woven together become a creature, and creatures in turn collide and push against one another, forming relations. Layers rise out of one flat rule.

Emergence. The “creature” is nowhere in particular. There is no living cell. The organized pattern itself is the animal.

And crucially, there is no chemistry here, no carbon, not a scrap of biology. Only organization. If you strip away every material substrate and the thing still crawls, still sutures itself back together, still holds its own body — then Bertalanffy was right. Aliveness lies in the arrangement, not the stuff. Because Lenia keeps nothing but the pattern, it proves his claim in its most extreme form.

The most beautiful evidence for a theory that refused the machine

Here is the twist.

Bertalanffy built General System Theory in part as resistance to mechanism — a refusal to reduce life to a machine. In spirit it was a humanist gesture: life is more than a mechanism.

And yet the most beautiful demonstration of his idea turns out to be a machine. A deterministic automaton running on a computer.

What would he have made of Lenia? Would he have welcomed it as a triumph of his self-organization, or waved it off — “that’s just another mechanism imitating life”? A founder failing to recognize his own heir is not rare in the history of ideas.

Chris Langton called artificial life “life as it could be.” Not only life as we know it, but every form life could take. The whole field, in truth, inherited Bertalanffy’s wager — that life is organization unbound from any medium. Lenia is that wager paying out on a screen.

Artificial life, meeting artificial intelligence

Lately this current meets artificial intelligence.

On one side, neural networks are made to learn the rules of an automaton. Instead of a human setting the rules by hand, the network learns for itself the rule to grow and to repair damage. Like a lizard’s tail, a pattern that regrows into its own shape after being cut away is produced by learning.

On the other side, AI searches universes like Lenia in our place. Creatures like Orbium were originally found by hand, but now large AI models recognize “lifelike” patterns and automatically discover new creatures. Machines go hunting for Orbium’s descendants.

And there is a deeper question. Rather than designing intelligence, could we let it grow like life? This is the current that treats open-ended evolution — endlessly generating novelty — as a condition of intelligence. Intelligence not as a finished blueprint but as a process that keeps surpassing itself.

And on a personal note, it is also a story that came full circle. To that rationalist who went looking for design mastery and, disappointed, met biology instead, half a century of ideas flowed on and the biology came back as computation. My youthful mistake — “surely systems theory must be about design” — was not wrong. It was merely early.

Life was a design problem after all. Just not the design I had been looking for in a C++ book.

Sources · Further reading