The Lindy effect
The Lindy effect says that for non-perishable things — ideas, books, technologies — life expectancy grows with age. The longer something has already survived, the longer it’s likely to last. A book in print 50 years will probably outlast one published this year.
How it works
For things that don’t age biologically, survival is evidence of robustness. Each extra year a non-perishable thing endures raises the expectation of its remaining life, because it has passed more tests of time.
How to use it
- Favour time-tested ideas, tools, and texts over the merely new when betting on durability.
- Discount hype around the brand-new — most novelties don’t last.
- Read old books and use proven technologies for problems where longevity matters.
Worked example
Euclid’s geometry has been used for ~2,300 years and will likely be taught for centuries more; this year’s trendy framework will probably be forgotten within a decade. Age predicts survival for non-perishables.
Where it fails
It applies only to non-perishable things — for people, machines, and biological systems, age means closer to the end, not further from it. And it’s probabilistic: some old things die, some new things endure.
The deeper point
Lindy is a filter against your own novelty bias. The new feels important because it’s loud, not because it’s likely to last — and most of what’s loud today is invisible in a decade. Age is unglamorous but honest evidence.
Frequently asked
- What is the Lindy effect?
- The idea that for non-perishable things like books and ideas, the longer they’ve already survived, the longer they’re likely to keep surviving.
- Does the Lindy effect apply to people?
- No — only to non-perishable things. For humans and machines, more age means less expected life remaining, the opposite of Lindy.
- How do you use the Lindy effect?
- When durability matters, favour time-tested ideas, tools, and texts over the merely new, and discount hype around unproven novelties.
Related
Editorial synthesis © ReadGlobe 2026, drawing on the mental-models tradition (Charlie Munger, Farnam Street) and the primary sources for each model. · Last reviewed 2026-05-29.