Systems Thinking

Emotional override of rational processing.

Systems that gain from disorder.

Negative feedback returns a system toward a target.

Approach motivation — pursuit of rewards and goals.

Avoidance motivation — sensitivity to punishment, uncertainty, and threat.

Expensive off-range storage cannibalizes funds needed for on-range management.

Federal oversight intended to protect tribal assets creates friction that devalues the land.

Map reinforcing (R) and balancing (B) feedback loops between variables to see system behavior.

A system with many interacting parts that learn and adapt.

Many interacting parts producing emergent behavior nobody designed.

The relationship between inputs and outputs changes.

Underlying data distribution changes over time.

Single-loop fixes the action. Double-loop questions the goal or model that produced it.

System 1 is fast, automatic, intuitive; System 2 is slow, effortful, deliberate.

Prices driven far above intrinsic value by feedback loops of belief and behavior.

Interdependent network of actors evolving together.

The whole has properties that the individual parts do not.

Cold-state decisions don't survive hot-state moments.

Systems maintain stability by self-regulating around a setpoint.

Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.

Continuing a failing course of action because of prior investment.

Evaluation suites that no longer reflect real-world conditions.

Costs or benefits that affect third parties not involved in a transaction.

Output of a process re-enters as input.

Outputs of a system are routed back as inputs, amplifying or dampening change.

Self-reinforcing loops of momentum.

The brain's overnight cleaning system; clears metabolic waste during sleep.

Deep specialization improves local output but breaks cross-domain understanding.

Reward systems slowly diverge from the outcomes they were meant to drive.

People copy the choices of others, assuming they have private information.

Insurers profit when claims are denied, delayed, or abandoned.

How much delay the user experience tolerates.

Three-stage cycle: learn by seeing, learn by doing, learn by teaching — looped continuously.

A deliberately curated set of people, sources, and feedback loops you draw on to learn faster than alone.

Children who delay gratification at age 4 show better outcomes across nearly every metric decades later.

Performance degradation as real-world data shifts.

A state where no player benefits from changing strategy unilaterally.

Value grows with the number of users.

Systems with weak corrective feedback drift unchecked into failure modes.

Observe, Orient, Decide, Act — faster than your competitor.

Insurer approval workflows delay or deny care to lower medical-loss ratios.

A behavioral relaxation of Nash: players choose better strategies more often, but not always — errors are smooth, not binary.

Output amplifies input — virtuous or vicious cycle.

When budgets follow self-reported numbers, the numbers drift toward what funders want to see.

Single-loop fixes errors; double-loop questions the assumptions producing them.

Single-loop: fix the action. Double-loop: question the governing assumption behind it. Chris Argyris.

Manager calibration produces predictable distortions over years.

Stocks are accumulations; flows are rates of change that affect them.

Behavior emerges from structure, not from individuals.

Shared resources get over-consumed by individual rational actors.

Old systems decline as new ones emerge in parallel; leaders steward both, not just kill the old or chase the new.

The context that shapes behavior

Patterns between two people

Rules shape competition

Laws, systems, and governance