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thinking-lindy-effect

thinking-lindy-effect

github.com/tjboudreauxDevelopment1.7k561 installsUpdated 12w ago
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About thinking-lindy-effect

A reasoning skill for applying the Lindy Effect when assessing the longevity of non-perishable ideas, technologies, and practices. It uses survival age as a prior while checking domain changes and whether a newer option meets a necessary gap.

Key features

  1. 01Check whether the subject is non-perishable
  2. 02Estimate remaining life from survival age
  3. 03Assess paradigm and domain drift
  4. 04Require a stated case for newer options
  5. 05Record residual risk and fallback

Use cases

  1. 01Choosing a language, framework, or protocol
  2. 02Comparing dependencies by longevity
  3. 03Assessing whether an architecture bet may last

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-lindy-effect

After installing, type/thinking-lindy-effectin Claude Code to confirm it loaded.

Details

From the project README

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

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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