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Updated Mar 15, 2026

Thinking in Systems

Most AI tools analyze problems in isolation. Ask about automating customer support and you get an answer about customer support. You do not get the second-order effect on employee morale, the third-order effect on company culture, or the feedback loop where cost savings lead to worse service which leads to customer churn which eliminates the savings. This chapter trains you to see interconnections that AI tools consistently miss.

Exercise 1: The Cascade Map (Human First)

Layers Used: Layer 1 (Predict Before You Prompt), Layer 6 (Iterative Drafts)

Building On Previous Chapters

You will use the Error Taxonomy from Chapter 2, Exercise 1 to identify errors in causal reasoning. Systems errors build on the error detection skills you practiced there.

What You Do

You receive a single decision. Without AI, draw a cascade map on paper or in a document — tracing effects across at least five domains: employees, customers, competitors, regulators, and the organization's own internal knowledge base. Identify at least three feedback loops (where an effect circles back to amplify or dampen the original decision). This map is your Draft 1 — submitted before any AI is consulted.

Choose Your Scenario

Scenario A (Finance): "A major bank decides to replace all loan officers with AI agents."

Choose one. The exercises work identically regardless of which you pick.


Your Deliverable

A cascade map (hand-drawn scan or digital document) showing: the central decision, at least 5 domains affected, first-order effects in each domain, at least 3 second-order effects, at least 3 third-order effects, and at least 3 feedback loops clearly labeled (e.g., "cost savings leads to reduced service quality leads to customer churn leads to reduced revenue leads to negated cost savings"). Each effect should have a one-sentence explanation of the mechanism.


AI Check Prompt -- Copy and paste into claude.ai or chatgpt.com
I am a student learning systems thinking. I was given this scenario:
"A major bank decides to replace all loan officers with AI agents."
Before using AI, I created a cascade map tracing consequences across
five domains with feedback loops.

Please:
(1) Evaluate the completeness of my map -- which important effects or
domains did I miss?
(2) Rate each of my feedback loops: are they logically sound? Would
they actually occur?
(3) Identify at least 3 second or third-order effects I missed that
are non-obvious but important.
(4) Rate the overall sophistication of my systems thinking from
Beginner / Developing / Proficient / Advanced.
(5) Do any of my causal chains have logical errors -- effects that
would not actually follow from the cause I described?

Here is my cascade map: [paste or describe your map in detail].

Finally, complete the Thinking Score Card for this exercise:
Independent Thinking (1-10), Critical Evaluation (1-10),
Reasoning Depth (1-10), Originality (1-10), Self-Awareness (1-10).
For each score, give a one-sentence justification.

Deliverable Template (click to expand)

CASCADE MAP TEMPLATE

  • Central Decision: ___
  • DOMAIN 1 [Employees]:
    • 1st-order effect: ___
    • 2nd-order: ___
    • 3rd-order: ___
  • DOMAIN 2 [Customers]:
    • 1st-order: ___
    • 2nd-order: ___
  • DOMAIN 3 [Competitors]:
    • 1st-order: ___
    • 2nd-order: ___
  • DOMAIN 4 [Regulators]:
    • 1st-order: ___
    • 2nd-order: ___
  • DOMAIN 5 [Internal Knowledge]:
    • 1st-order: ___
    • 2nd-order: ___
  • FEEDBACK LOOP 1: [A] leads to [B] leads to [C] leads back to [A] | Type: Amplifying/Dampening | Mechanism: ___
  • FEEDBACK LOOP 2: ___
  • FEEDBACK LOOP 3: ___

What This Teaches You

You learn to see consequences that do not appear on a linear list. By forcing yourself to map effects before AI does it for you, you build the mental habit of asking "and then what?" for every decision. The AI feedback reveals effects you missed — expanding your systems thinking vocabulary for future problems.

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