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Use when longevity of a non-perishable option matters. Treat survival duration as a remaining-life prior, then check domain drift before favoring the proven.
--- name: thinking-lindy-effect description: Use when longevity of a non-perishable option matters. Treat survival duration as a remaining-life prior, then check domain drift before favoring the proven. disable-model-invocation: true --- # Lindy Effect For non-perishable ideas, technologies, and practices, expected remaining life scales with current survival age. Prefer proven survivors unless the new option clears a burden of proof or the domain has drifted. ## When to Use - Choosing languages, frameworks, databases, protocols, patterns, or dependencies where long-term survival matters. - Skill or architecture bets whose value depends on lasting relevance. - Ranking options when ages differ materially and the choice outlives a short experiment. ## When NOT to Use - Perishable targets: specific SaaS vendors, hardware, fashion, or products that can shut down regardless of concept age. - Active paradigm discontinuity where age in the old regime is weak evidence. - Throwaway work where longevity is irrelevant — optimize for fit and speed. - Treating "older" as "optimal for a new requirement"; survival predicts further survival, not best fit. ## Procedure 1. **Confirm non-perishable scope.** Concept/tech/practice continues; vendor/device → score fit/risk only and stop. 2. **Record survival age.** First significant production use and current age (ecosystem-relative if the ecosystem is young). 3. **Form the Lindy prior.** Expected remaining life ≈ current age; mark confidence from age and continued active use. 4. **Run domain-drift checks.** Problem class changed? Paradigm shift invalidating old assumptions? New option uniquely closes a real present gap? 5. **Assign burden of proof.** Default to the older adequate option. Accept newer only for a stated necessary advantage the Lindy option cannot meet at acceptable cost. 6. **Decide with residual risk.** Pick primary; note impact if the prior is wrong and any fallback. **Stop condition:** Primary chosen with age prior, drift check, and why new did or did not meet burden of proof. ## Output ```text Options: <name, age, Lindy prior> Drift: stable | discontinuous — <note> Burden: on new | waived because <gap> Decision: <primary> Rejected: <one line each> If Lindy wrong: <impact + fallback> ``` ## Verification - Falsify if age was used without non-perishable scope, or a paradigm shift was ignored. - Falsify if a new option was rejected solely for youth despite a documented necessary gap. - Over-application guard: skip throwaway prototypes and perishable vendor bets where fit and exit cost dominate.
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