What makes Lindy Effect notable?

1K downloads. Trust evidence available

How should Lindy Effect be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Lindy Effect

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... Skill: Lindy Effect Owner: deciqai Summary: 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... Tags: latest:1.0.5 Version history: v1.0.5 | 2026-07-16T18:05:02.675Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/lindy-effect.json) v1.0.4 | 2026-07-10T10:26:43.819Z | user Ad

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.0k

Updated

Oct 11, 2026

Version

1.0.5

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.5release · observed Jul 16, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17a4mqcnk515kvaca5ze55d0x88pfpx:lindy-effect

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-deciqai-lindy-effect/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

136,599 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: lindy-effect
description: "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 been around forever — is that meaningful', 'we should modernize / this time is different', 'how long will this practice / tool / framework last'.
Do NOT activate when: the item is perishable or has a deterministic life cycle (humans, hardware, organisms); elimination forces are absent and the old thing survives only due to regulatory lock-in. More: deciqai.com/c/lindy-effect"
---

# Lindy Effect

## Overview

For **non-perishable items** — ideas, books, technologies, institutions, practices — life expectancy is proportional to current age. The longer something has survived competitive elimination, the longer its expected remaining life. Math: if survival follows a Pareto distribution with α ≈ 1, expected remaining life ≈ current age. Not nostalgia — statistical inference from a track record of passing elimination tests.

Composes with `antifragile` (Lindy-survival is the signature of antifragility), `survivorship-bias` (paired warning), `first-principles` (Lindy says *that*; first-principles says *why*), `switching-costs`, and `chestertons-fence`.

## When to Use

- Choosing a foundational technology / library / framework with high switching cost
- Evaluating a long-established practice or institution someone is proposing to discard
- Assessing a new methodology being marketed as "modern" or "evidence-based"
- Allocating reading time across old vs. new books
- Designing institutional partnerships with multi-decade horizons
- Deciding which layers of an AI stack to build on time-tested foundations (SQL, Unix, TCP/IP) vs. fast-churning AI frameworks amid the AI adoption hype
- Someone says "this has stood the test of time," "we should modernize," "this time is different"

**Not when:** item is perishable or has a deterministic life cycle; elimination forces are absent (old institution survives only via regulatory protection); conditions have genuinely changed enough to invalidate survival evidence; decision time-horizon is too short for long-run durability to matter.

## Coaching Novices (Adaptive Front Door)

- **Engine mode:** user has a concrete old-vs-new decision → run The Process directly.
- **Coach mode:** user unfamiliar or no concrete case → guide step by step.

In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.

1. One-line: for non-perishable items where elimination forces still operate, prefer the older — its survival is evidence of durability the newer item hasn't yet earned.
2. Check fit: perishable item or absent elimination forces → Lindy doesn't apply.
3. Elicit their case: what's the old item? the new? the domain?
> **[WAIT — do not advance until user responds]**
4. Run The Process: non-perishable? elimination forces continuous? Lindy prior? conditions justify this-time-is-

_meta.json

{
  "ownerId": "kn754b8sk22s8c6gjxt02bftbn88q7ye",
  "slug": "lindy-effect",
  "version": "1.0.5",
  "publishedAt": 1784225102675
}

references/sources.md

# Sources — lindy-effect

> *Primary sources for the [lindy-effect](../SKILL.md) skill.*

- Goldman, A. (1964). "Lindy's Law." *The New Republic*, 13 June 1964. The original.
- Mandelbrot, B. (1982). *The Fractal Geometry of Nature.* W. H. Freeman. ISBN 978-0716711865. Mathematical foundation.
- Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable.* Random House. ISBN 978-1400063512.
- Taleb, N. N. (2012). *Antifragile: Things That Gain from Disorder.* Random House. ISBN 978-1400067824. Chapter 20 "Time and Fragility."
- Taleb, N. N. (2018). *Skin in the Game: Hidden Asymmetries in Daily Life.* Random House. ISBN 978-0425284629.
- Cirillo, P., & Taleb, N. N. — peer-reviewed work on fat-tailed and power-law statistics (e.g., their studies on tail risk in *Physica A* / *Nature Physics*) provides the closest formal grounding for Lindy-style power-law longevity. Confirm the exact article and venue before citing a specific one.
- Reinhart, C. M., & Rogoff, K. S. (2009). *This Time Is Different: Eight Centuries of Financial Folly.* Princeton University Press. ISBN 978-0691142166 (2009 hardcover). The complementary anti-novelty argument.
- Stack Overflow. *Developer Survey* (2024 and 2025 editions). Longitudinal industry data showing SQL, and Unix/Linux-family environments remaining among the most-used technologies through the 2024–2026 AI build-out — the survival-under-pressure evidence for the 2024–2026 example.
- Codd, E. F. (1970). "A Relational Model of Data for Large Shared Data Banks." *Communications of the ACM*, 13(6), 377–387. The foundational paper behind the relational model / SQL, one of the Lindy-strong foundations in the 2024–2026 AI-stack example.

examples/goldman-1964-mandelbrot-1982-taleb-2012.md

# Method in Action: Goldman 1964, Mandelbrot 1982, Taleb 2012

> *Example for the [lindy-effect](../SKILL.md) skill.*

The principle has three formal moments.

The first is **Albert Goldman's 1964 New Republic essay**, which named the principle after Lindy's Deli on Broadway, where television comedians ate and gossiped about each other's career prospects. Goldman wrote:

> "The notion is that the future life expectancy of a non-perishable item is proportional to its current age. The lifetime of a television comedian is proportional to the total amount of his exposure on the medium. The comedian who has been on for ten years has, on average, ten more years ahead of him in the business. The comedian who has been on for ten weeks will be off within ten weeks. The math is rough, the empirical correlation is striking."
>
> — Goldman (1964), as cited in Taleb (2012), p. 318.

Goldman's observation predated the formal mathematics but captured the structural principle. Subsequent empirical studies in show-business career durations have confirmed the pattern.

The second formal moment is **Benoit Mandelbrot's 1982 mathematical formalization** in *The Fractal Geometry of Nature*. Mandelbrot connected the Lindy-style observation to power-law (Pareto) distributions, which had been extensively studied in the context of city sizes, wealth distributions, and earthquake magnitudes. The mathematical insight: for any distribution where the probability of survival to age T+t given survival to age T is a function of t/T alone (rather than depending on T as an absolute), the distribution is power-law. This is "self-similarity" in time — and is the structural reason why the Lindy effect operates.

The third formal moment is **Nassim Taleb's 2012-2018 operational extension** in *Antifragile* and *Skin in the Game*. Taleb's contribution:

> "What stays in print stays in print. The Iliad has survived three thousand years, so we can expect another three thousand years. A new book released this year is likely to be forgotten within a year. The relevant time-horizons are not symmetric: an idea that has survived two thousand years has been tested by every century of those two thousand years; an idea that emerged five years ago has been tested by half a decade. The two are not in the same league of empirical robustness. ...
>
> The reverse logic also holds: anything that *needs* the new to validate itself is structurally weak. The book that requires a 2024 interpretation of a 2024 trend to be relevant is unlikely to remain relevant when the trend passes. The book that has remained relevant across multiple paradigm shifts has, by survival evidence alone, met a higher bar."
>
> — Taleb, N. N. (2012). *Antifragile.* Random House, pp. 318-322.

Taleb's *Skin in the Game* (2018) extended the principle to practices and information sources:

> "When you eat a dish that has been cooked the same way for 400 years by 30 generations of people in a particular village, you are eating the

examples/lindy-vs-ai-framework-churn-2024-2026.md

# Method in Action: Lindy vs. AI-Framework Churn in the 2024–2026 Tech Stack

> *Example for the [lindy-effect](../SKILL.md) skill.*

The decision facing most engineering teams in the 2024–2026 AI build-out: when you assemble a new AI application, which layers do you bet on the time-tested foundations for, and which layers do you deliberately keep on the fast-churning new tools? The Lindy effect does not say "never use the new" — it tells you *where* the survival evidence is, so you can put the durable choices in your load-bearing tier and the disposable choices where you can afford to rip and replace.

This walks the anchor case through the skill's own Process.

## Step 1 — Items

- **Old items (approximate ages, as of 2026):** SQL / the relational model (Codd's relational model 1970; SQL from the mid-1970s, ~50 years), Unix and its POSIX interface (1969–1971, ~55 years), email/SMTP (SMTP standardized 1982, ~40 years), TCP/IP (deployed on ARPANET on 1 January 1983, ~40 years), HTTP/the web (~35 years).
- **New items (approximate ages):** the current generation of AI application frameworks, agent orchestration libraries, and vector/AI tooling — most under ~3 years old, many under 18 months, with a churn rate high enough that popular libraries are rewritten or abandoned within a year or two.
- **Decision:** for a production AI application, which layers do we anchor on Lindy-strong foundations and which do we leave on the churning new layer?
- **Time horizon:** the app is meant to run for 5–10+ years.
- **Switching cost:** very high for the foundational layers (data model, transport, deployment substrate), low-to-moderate for the AI-orchestration layer (glue code that can be rewritten).

## Step 2 — Applicability

- **Non-perishable?** Yes. Protocols, data models, and interfaces are ideas/standards, not organisms with deterministic life cycles. Lindy applies.
- **Elimination forces operating?** Yes — and this is the crux. SQL, Unix, email, and TCP/IP have not merely persisted; they have survived *repeated, well-funded attempts to replace them*. The NoSQL wave of the early 2010s was pitched as the end of the relational database; a decade later SQL is more central than ever, and many "NoSQL" systems added SQL-like query layers. This is survival under active competitive pressure, not survival by regulatory lock-in — exactly the condition Lindy requires.
- **Power-law plausible?** Yes. Technology-adoption survival is a canonical fat-tailed domain: a small number of standards carry the overwhelming majority of the infrastructure, and their remaining life scales with their current age.
- **Conditions changed?** The "AI changes everything" claim must be examined in Step 4 — but note it up front as the this-time-is-different candidate.

## Step 3 — Lindy prior

- **Old remaining life (≈ current age):** a ~50-year-old foundation like SQL has a Lindy prior of roughly another ~50 years; ~40-year-old TCP/IP and SMTP, roughly another ~40. These are order-of-mag

Github ReposUpdated 2d agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW

Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular