---name: thinking-second-orderdescription: When a change has effects past the immediate fix—incentives, scale, feedback—trace consequence chains with timing and probability before committing.disable-model-invocation: true---

Second-Order Consequence Chains

Do not stop at the intended first effect. Trace what happens next across actors, time, and feedback until the chain stops changing the decision.

When to Use

• Strategic, policy, incentive, or architecture choices with lasting coupling.
• The obvious fix feels too easy or has known backfire patterns.
• Success or scale would create new problems (load, gaming, debt).
• Need to compare options by delayed effects, not only day-one benefit.

When NOT to Use

• Local reversible edit with no incentive or cross-component coupling—just ship and observe.
• Full system structure (stocks, many loops, leverage ranking) is the goal—use systems.
• Pre-mortem of failure modes for a plan already chosen—use pre-mortem.
• Pure mechanical changes (rename, format) with no behavioral effect.

Procedure

1. State decision and first-order effect. One sentence each: action and intended immediate result.
2. Chain "and then what?" At least two further orders. For each link record: effect, who responds, rough probability (high/med/low), timing (immediate / next cycle / at scale), and whether it feeds back into the original problem (reinforce or counteract).
3. Expand affected parties. Who else reacts (users, operators, other teams, attackers, markets)? What incentives does the change create or destroy?
4. Scale test. Ask what happens if everyone does this or usage grows 10x. Mark paths that only appear under scale or repetition.
5. Prune and decide. Drop speculative links that do not change the choice. Keep only effects that alter go/no-go, design, or mitigations. Revise the action or add guards where second-order harm exceeds first-order gain.

Stop when further "and then what?" no longer changes the decision, or the remaining chain is pure speculation without mechanism.

Output

decision: <action>
first_order: <intended immediate effect>
chain:
  - order: 2
    effect: <what>
    actors: <who>
    p: high|med|low
    when: immediate|next_cycle|at_scale
    feedback: none|reinforce|balance
  - order: 3
    ...
scale_if_universal: <one sentence or n/a>
revised_decision: <same | modified action | no-go>
mitigations: <guards for kept risks>

Verification

• Falsify: If no credible second-order path changes the choice, first-order is enough—stop inventing cascades. If the core issue is multi-loop structure rather than one decision's trail, switch to systems.
• Stop: End at the first order that no longer affects the decision; do not pad to a fixed depth.
• Over-application guard: No low-probability sci-fi chains. No treating parameter tweaks as deep strategy. Probability and timing required on kept links; omit decoration without mechanism.