Introduction to Systems Thinking
What systems thinking is, why it matters, and how to start seeing systems everywhere
Systems thinking is the discipline of seeing wholes, recognizing patterns and interrelationships, and learning to structure those interrelationships in more effective ways.
What Is a System?
A system is a set of interconnected elements organized to achieve a purpose. The key word is interconnected—the elements affect each other, creating feedback loops and emergent behaviors.
Examples are everywhere:
- A restaurant kitchen (equipment, ingredients, staff, tickets, timing)
- A cannabis plant (genetics, environment, nutrients, stress responses)
- An AI agent pipeline (prompts, models, context, outputs, corrections)
- A business (customers, employees, processes, capital, reputation)
Why It Matters
Most problems we face are system problems. They resist solutions because:
- We focus on symptoms instead of structures
- We optimize parts at the expense of the whole
- We ignore feedback loops and delays
- We underestimate interconnection
Traditional analytical thinking breaks problems into parts. Systems thinking sees how parts interact.
The Core Practices
See Feedback Loops
Every action creates reactions. Reinforcing loops amplify (growth spirals, vicious cycles). Balancing loops stabilize (thermostats, market prices).
Identify Delays
Effects don’t happen instantly. A change today might show results in weeks, months, or years. Ignoring delays leads to overreaction and oscillation.
Map Mental Models
Our assumptions about how things work shape what we see and do. Making mental models explicit reveals blind spots.
Find Leverage Points
Not all interventions are equal. Some points in a system give much more return on effort than others.
Donella Meadows
My north star in systems thinking is Donella Meadows, author of Thinking in Systems and the famous Leverage Points essay. Her work provides the framework I apply across every domain.
Where I Apply This
- Restaurant operations — seeing the kitchen as a complex adaptive system
- AI orchestration — designing agent systems with proper feedback
- Cannabis cultivation — understanding plants as responsive systems