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thinking-second-order

When a change has effects past the immediate fix—incentives, scale, feedback—trace consequence chains with timing and probability before committing.

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name
thinking-second-order
description
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 ```text 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.
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