Activate when: user asks 'should we use this old technology or switch to something newer', 'how do I know if a book is worth reading', 'this institution has...
Coding
thinking-lindy-effect
Try itUse when longevity of a non-perishable option matters. Treat survival duration as a remaining-life prior, then check domain drift before favoring the proven.
What it does
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.
The skill document
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
- Confirm non-perishable scope. Concept/tech/practice continues; vendor/device → score fit/risk only and stop.
- Record survival age. First significant production use and current age (ecosystem-relative if the ecosystem is young).
- Form the Lindy prior. Expected remaining life ≈ current age; mark confidence from age and continued active use.
- Run domain-drift checks. Problem class changed? Paradigm shift invalidating old assumptions? New option uniquely closes a real present gap?
- 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.
- 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
Options:
Drift: stable | discontinuous —
Burden: on new | waived because
Decision:
Rejected:
If Lindy wrong:
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.
Related skills
Use when search or investigation could run forever. Set an explicit good-enough threshold first, then stop at the first option that clears it.
Use when a selective defect needs IS/IS-NOT difference analysis or a consequential option choice needs must/want weighting and adverse-consequence comparison.
Deciding what to build or why adoption fails. Recover the progress users hire a solution for under a circumstance, then rank by outcome and competing workarounds.
When provisioning, setting a limit, or committing an estimate under uncertainty, size a buffer to residual error and the cost of breach—not to the optimistic edge.
Use when the reflex is to add a feature, layer, or process. Prefer removing harmful or nonessential elements first, with an irreversibility guard before deletion.