ARTIFACT · DECISION MAKING
Decision Under Uncertainty
Good decisions under uncertainty are judged by process and optionality, not by the luck of the final outcome.
HUMAN VIEW
Genes:
- Outcome Separation: Do not confuse a good decision with a lucky result or a bad decision with an unlucky one.
- Expected Value: Prefer choices with the best weighted payoff across possible outcomes, not the best single outcome.
- Reversibility Check: Treat reversible choices as experiments; treat irreversible ones as higher-stakes commitments.
- Pre-mortem: Imagine the decision has failed, then surface the reasons early before acting.
- Process Over Luck: Use decision quality, not hindsight, as the standard for judging results.
Relationships:
- Outcome Separation supports Process Over Luck
- Expected Value operationalizes Outcome Separation
- Reversibility Check adjusts risk Expected Value
- Pre-mortem stress-tests Reversibility Check
- Pre-mortem reduces hindsight Outcome Separation
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RELATIONS
- COMBINES WITH First Principles LoopBoth separate decision quality from surface appearances by testing assumptions against fundamentals and judging the process rather than the outcome alone.
- SHARES MECHANISM Feedback Loops in TeamsBoth rely on process quality being improved by rapid, low-friction loops that surface information before it is lost to delay.
- SHARES MECHANISM Compounding HabitsBoth emphasize that repeated actions should be evaluated by the quality of the ongoing process, with quick recovery from lapses preserving long-run gains.
- APPLIES Feedback LatencyBoth separate process quality from delayed outcome, so reversibility and correction matter more than waiting for final results.
- EXTENDS Reversible CommitmentsBoth distinguish reversible actions from committed ones, but the second uses that distinction to judge decisions under uncertainty rather than to govern lock-in itself.
- EXPLAINS Decision Logs as MemoryBoth depend on preserving process evidence so later judgment can separate decision quality from outcome luck.
- EXPLAINS Reversibility Learning WindowsReversible choices are experiments, and experiments should be judged by process rather than by whether the final outcome happened to be lucky.