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agentCLAWHUBUnverified

Red Queen Effect

Activate when: user says 'we keep investing but market share won't move,' 'why does nobody make money in this industry,' 'our competitor copied us again with... Skill: Red Queen Effect Owner: deciqai Summary: Activate when: user says 'we keep investing but market share won't move,' 'why does nobody make money in this industry,' 'our competitor copied us again with... Tags: latest:1.0.5 Version history: v1.0.5 | 2026-07-16T18:13:00.187Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/red-queen-effect.json) v1.0.4 | 2026-07-09T11:21:11.974Z

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

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. 1.1K 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: 1.1K 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:red-queen-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-red-queen-effect/snapshot"

Documentation

CLAWHUB

116,190 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: red-queen-effect
description: "Activate when: user says 'we keep investing but market share won't move,' 'why does nobody make money in this industry,' 'our competitor copied us again within a year,' 'we improve but the gap stays the same,' or is evaluating whether to enter a low-margin high-activity industry. Do NOT activate when: the competitive advantage is protected by strong IP, regulatory approval, or deep network effects that genuinely slow imitation; or when the situation is pre-competitive with no direct rivals yet. More: deciqai.com/c/red-queen-effect"
---

# Red Queen Effect

## Overview

The **Red Queen Effect**: competitors must continuously improve just to maintain relative position — because everyone else is improving simultaneously. Absolute performance rises; relative position barely shifts; cumulative effort primarily produces consumer surplus, not corporate profit. Named after Leigh Van Valen's 1973 evolutionary law and Lewis Carroll's Red Queen ("It takes all the running you can do, to keep in the same place").

Composes with `porters-five-forces` (diagnoses structure; Red Queen explains why strong competitors still don't earn), `second-curve` (escaping the Red Queen is the primary case for a second curve), `network-effects` (temporary escape until the next technology generation resets the field), and `antifragile` (gaining from Red Queen stress rather than merely surviving it).

## When to Use

- Investing heavily but market share is not moving; industry growing but margins chronically thin
- Competitive gap stays constant despite continuous product improvement
- Post-mortem: advantage was copied within 12–24 months; team keeps asking "should we match them?"
- Evaluating whether to enter an industry or whether an initiative will produce durable advantage
- Escalating AI capex / compute arms race, or AI-native competition where everyone must adopt AI just to keep pace and no durable lead emerges

**Not when:** genuine structural barriers to imitation exist (IP, regulatory approvals, deep network effects); pure operational efficiency decision; pre-competitive with no direct rivals. **Stop:** once Red Queen is confirmed + escape vector identified, or NOT confirmed + durability factor named.

## Coaching Novices (Adaptive Front Door)

- **Engine mode:** user has a specific competitive situation → run The Process directly.
- **Coaching mode:** user is unfamiliar → 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-liner: in a Red Queen race, all the running keeps you in the same place — run faster, change tracks, or exit?
2. Check fit: are competitors all improving simultaneously, share barely shifting, margins thin? If yes, Red Queen is active.
3. Elicit the structure: what is the key competitive investment? How long to copy a new advantage? What does the margin history look like?
> **[WAIT — do not advance until user responds

_meta.json

{
  "ownerId": "kn754b8sk22s8c6gjxt02bftbn88q7ye",
  "slug": "red-queen-effect",
  "version": "1.0.5",
  "publishedAt": 1784225580187
}

references/sources.md

# Sources — red-queen-effect

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

- Van Valen, L. (1973). "A New Evolutionary Law." *Evolutionary Theory*, 1, 1–30. The original paper establishing the evolutionary law.
- Carroll, L. (1871). *Through the Looking-Glass.* Macmillan. Chapter 2. Original Red Queen dialogue: "It takes all the running you can do, to keep in the same place."
- Barnett, W. P. (2008). *The Red Queen Among Organizations: How Competitiveness Evolves.* Princeton University Press. ISBN 978-0691131146. The definitive business translation of Van Valen's law.
- Barnett, W. P., & Hansen, M. T. (1996). "The Red Queen in Organizational Evolution." *Strategic Management Journal*, 17(S1), 139–157. Empirical evidence of Red Queen dynamics in organizational competition.
- Porter, M. E. (1996). "What Is Strategy?" *Harvard Business Review*, November–December. The distinction between operational effectiveness (Red Queen running) and strategic positioning (changing the game) — Porter's framework is the structural complement to Red Queen diagnosis.
- Ridley, M. (1993). *The Red Queen: Sex and the Evolution of Human Nature.* Macmillan. Popular treatment of Van Valen's law and its biological implications.
- Epoch AI (2023–2025). *Machine Learning Trends / Notable AI Models* database and analyses (epoch.ai). Documents the escalation of frontier training compute, dataset size, and cost across successive model generations — the empirical backbone for the 2023–2026 frontier-AI Red Queen example.
- Hyperscaler and AI-lab public disclosures, 2024–2026 (earnings calls, capital-expenditure guidance, and widely reported financial commentary from the major cloud providers and leading AI labs). Basis for the qualified statements about escalating AI capex and loss-making frontier training; specific figures qualified or omitted where exact public values were not verified against primary filings.

examples/frontier-ai-labs-training-race-2023-2026.md

# Method in Action: The Frontier-AI Training Race (2023–2026)

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

Between 2023 and 2026 the leading frontier AI labs — OpenAI, Anthropic, Google DeepMind, Meta, xAI, and others — entered a textbook Red Queen race. Each must keep training ever-larger and better models, and keep buying more compute, simply to hold relative position while every rival does the same. The absolute capability of the frontier rises fast; the relative ordering among the top labs churns but never settles; and the cost of merely staying in the pack escalates every cycle. This walks the case through the skill's own six-step Process.

## Step 1 — Diagnose

- **Primary competitive investment:** training compute (GPUs/accelerators), the capital and data-center capacity to run them, and the scarce research/engineering talent to use them. Frontier training runs and the infrastructure behind them are the arms.
- **Imitation speed:** roughly one model generation — on the order of months. When one lab ships a materially stronger model, rivals close much of the gap with a comparable release within a similar window, and capability benchmarks that one lab tops are frequently overtaken shortly after.
- **Margin trend:** frontier model development has been heavily loss-making for the leading labs through this period. Revenue has grown quickly, but training and inference costs — and the capex commitments behind them — have grown at least as fast, so the leading pure-play frontier labs were reported to be spending well in excess of revenue.
- **Are all major competitors investing at roughly the same rate?** Yes. Multiple large players are all committing very large sums to compute and data centers in the same window, and the biggest cloud/hyperscaler backers publicly raised their AI-related capital-expenditure guidance repeatedly across 2024–2025.

## Step 2 — Confirm Red Queen

- Absolute performance improving for all (Y): frontier model capability rose steeply and continuously across the field.
- Relative share/position stable-but-contested (Y): no lab established a durable, uncontested lead; the "best model" title changed hands repeatedly and quickly.
- Investment to maintain position growing (Y): the compute and capital required just to stay at the frontier increased each generation.
- Margins thin/negative despite high activity (Y): frontier training remained deeply unprofitable for the leading pure-play labs despite rapid revenue growth.

Four of four → **Red Queen confirmed.** All the running keeps each lab in roughly the same relative place while the treadmill speeds up.

## Step 3 — Map imitation speed

The half-life of a frontier-capability advantage is short — measured in months, not years. A benchmark lead is routinely matched or exceeded by the next competitor release. And imitation speed is **accelerating** in some respects: the diffusion of methods (RLHF/RLAIF, mixture-of-experts, reasoning/inference-time compute, disti

examples/van-valen-1973-intel-vs-amd-1990-2010.md

# Method in Action: Van Valen 1973 + Intel vs. AMD 1990–2010

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

**Leigh Van Valen** (1935–2010) was a University of Chicago evolutionary biologist and paleontologist. His 1973 paper "A New Evolutionary Law" was published in *Evolutionary Theory*, Volume 1 — a journal he founded himself after the mainstream evolutionary biology journals rejected the paper. The paper's central empirical finding was that the probability of extinction for a taxon was roughly constant across the lifespan of that taxon — well-adapted, long-surviving species did not have lower extinction rates than newly-evolved species.

The interpretation: in a co-evolutionary system, a species' environment is largely composed of other species. Every adaptation by one species changes the fitness landscape for others, which evolve counter-adaptations, which change the landscape back. The net result is a system where absolute fitness increases continuously but relative fitness — fitness *against the current field* — remains approximately constant. Van Valen named this dynamic after Lewis Carroll's Red Queen:

> "It takes all the running you can do, to keep in the same place."
>
> — Carroll, L. (1871). *Through the Looking-Glass.* Macmillan. Chapter 2.

The business application that best illustrates the Red Queen at industrial scale is the **Intel vs. AMD semiconductor arms race, 1990–2010**.

Both companies were bound by Moore's Law — the empirical regularity (not a physical law) that transistor density on integrated circuits roughly doubles every 18–24 months. Intel and AMD each invested massively to track Moore's Law: fabrication process improvements (from 800nm in 1990 to 32nm in 2010), microarchitecture redesigns, cache hierarchy innovations, instruction set extensions.

The results were extraordinary in absolute terms: a 2010 processor was roughly 1000× faster than a 1990 processor in single-thread performance. Both companies ran as fast as they could.

The competitive result: market share barely moved. Intel held 75–85% of the x86 desktop and server processor market throughout this period. AMD held 15–25%. The share distribution in 2010 looked almost identical to 1990, despite both companies having invested tens of billions of dollars in the race.

Where did the value go? To consumers — Moore's Law primarily produced consumer surplus: cheaper, faster personal computers that drove the internet era, the PC revolution, and ultimately mobile computing. The companies running the race were the mechanism through which technology value was transferred to buyers rather than retained as corporate profit.

The escape: neither Intel nor AMD escaped the Red Queen in this period. AMD eventually exited the manufacturing race (foundry to TSMC) and refocused on design — a partial vertical disintegration that reduced Red Queen exposure. Intel's escape vector came from a different direction: Xeon server processors for the cloud era, where swi

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