If you want the index, start here: Systems Across Domains.
The issue this taxonomy solves is not “lack of information.” The issue is that people confuse domain vocabulary for system structure. When you can see the structure, you can act. When you only know the vocabulary, you end up repeating mistakes with different labels.
This section is built around a simple conversion:
Abstract concept → concrete structure → operational implication → next decision
Cross-domain systems thinking works because many of the underlying shapes repeat even when the surface details change. Components, interfaces, flows, constraints, incentives, and feedback loops show up in software, organizations, markets, media, physical systems, and personal operating systems alike. If you can see those primitives, you can reason about where a system will fail, stall, or compound.
The practical questions I use across domains are consistent:
- What are the actual components?
- Where are the interfaces, and what breaks them?
- What is flowing: money, data, attention, trust, inventory, or decisions?
- What are the real constraints and operating costs?
- Who is rewarded, penalized, blocked, or ignored?
- What feedback loops reinforce behavior or force correction?
Why This Kind Of Breadth Matters
- Transfer learning becomes real. A pattern from routing, marketplaces, or team design can unlock a problem somewhere else.
- Translation gets easier. You can coordinate specialists when you can name the shared structure underneath their local language.
- Naive mistakes get rarer. People who have seen enough systems respect constraints and incentives earlier.
- Judgment under uncertainty improves. When precedent is missing, cross-substrate analogies become a practical advantage.
What’s In The Library
The taxonomy is organized as a set of system domains — concrete substrates where systems thinking can be practiced with real constraints. The full set is browsable alphabetically on the taxonomy page, but the major groupings are:
- Physical and infrastructure substrates
- Software, compute, and platform systems
- Data, analytics, and AI systems
- Organizations, coordination, and market systems
- Media, knowledge, and meaning systems
- Personal and human systems
If you want the full index (and the terms themselves), use the taxonomy page: Systems Across Domains.
How To Use This Section
The trade-off here is breadth versus depth. Skimming everything produces a false sense of coverage. The value comes from reading a few domains seriously, then noticing what stays the same.
So the next step is simple:
- Pick one domain you know well and one you do not.
- Read both pages looking only for structure (components, interfaces, flows, constraints, incentives, feedback).
- Write down the pattern you see repeating, then look for it in your current work.
If you want the shorter route into the broader philosophy first, pair this section with About, Work & Ventures, and Start Here.