Six domains. The same framework runs in all of them, because they all describe dissipative systems. Biology takes up four of the six because that is where the measurements are sharpest and most of our current evidence lives. Organisations and AI are the two non-biological domains, where the same questions reach into the systems we live inside.

How do cells decide to live, divide, kill, or surrender?
Cancer is the example we know best, but the question is older than the disease. We work at the resolution where decisions happen — the cycle, the synapse, the threshold — and ask which patients have a cycle that can complete.

What does it take for a population to renew itself under pressure — and what fails first when it can't?
Adaptation, selection, resistance. Most of what we currently see in cancer is evolution in real time. Collaborations with evolutionary oncologists anchor this domain; the questions reach further into ecology and population biology.

What is the shape of the menstrual cycle, and why does menopause happen the way it does?
The most explicit cyclic system in human physiology, and structurally under-studied. The four-regime cycle should have something to say about hormonal feedback, follicular selection, and the transition through menopause.

Why do some organizations renew themselves, and others quietly collapse from the inside?
Organizations are dissipative systems too. Conservation debt, intelligence as observation depth, the cost of mismatched viewing angles between levels. Practical work alongside Pacmed and adjacent practitioners.

Most change efforts fail to complete. What does it take for a change to land — and what stage does it usually fail at?
Organizations attempt change constantly and most attempts stall. We work with teams that are inside an active change program, mapping where the program is in its own cycle and what the next move requires.

What shape does a technology run as, and what does it do to ours?
Technologies are dissipative systems too, and they perturb the cycles we live in. Mapping a technology architecture onto the four-regime cycle locates its bottlenecks and its conservation debt. The same lens also reads where the technology lands in the cycles we live in (work, learning, expertise, identity), and what restructures around it. AI, quantum, gene editing, and whatever comes next: all read through one lens.
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