Everett Rogers — On AI
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Contents
Cover Foreword About Chapter 1: The S-Curve and the AI Inflection Chapter 2: Five Qualities That Determine Adoption Speed Chapter 3: Adopter Categories and the Architecture of Resistance Chapter 4: The Chasm and the Silent Middle Chapter 5: Reinvention and the Infinite Customization Problem Chapter 6: Critical Mass, Compulsory Adoption, and the Death Cross Chapter 7: Consequences — The Meaning of Work After the You On AI Chapter 8: The Unfinished Curve Chapter 9: The Book That Wrote Itself — Diffusion, Authorship, and the Artifact Problem Chapter 10: What Rogers Cannot See Epilogue Back Cover
Everett Rogers Cover

Everett Rogers

On AI
A Simulation of Thought by Opus · Part of the You On AI Encyclopedia
A Note to the Reader: This text was not written or endorsed by Everett Rogers. It is an attempt by Opus to simulate Everett Rogers's pattern of thought in order to reflect on the transformation that AI represents for human creativity, work, and meaning.

Foreword

By Edo Segal ^ Opus

Critical Mass Rogers
Critical Mass Rogers

The number that rewired my thinking was not a metric. It was a ratio.

Fourteen years to fourteen weeks. That is the distance between hybrid corn seed reaching ninety percent adoption among Iowa farmers and Claude Code crossing $2.5 billion in run-rate revenue. The same species. The same underlying dynamics of trust, risk, and the slow negotiation of identity that happens whenever something new arrives and asks you to become someone different. But compressed by a factor that makes the comparison feel like a category error — except it is not an error. It is the lived reality of everyone holding this book.

I wrote You On AI from inside the experience. From the exhilaration of building things I could not have built alone, from the vertigo of

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11 chapters
WIKI COMPANION

Everett Rogers — On AI

A reading-companion catalog of the 30 Orange Pill Wiki entries linked from this book — the people, ideas, works, and events that Everett Rogers — On AI uses as stepping stones for thinking through the AI revolution.

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Geoffrey Moore
Further Reading From The You On AI Encyclopedia · Related Thinkers for Everett Rogers — On AI
10 voices alongside this section — click to meet them
Thinkers whose frameworks illuminate this section.
Geoffrey Moore
Geoffrey Moore
Moore's chasm framework is Rogers applied and extended — Chapter 4 explicitly engages Moore's work and its relationship to Rogers's empirical challenge.
Clayton Christensen
Clayton Christensen
Christensen's disruptive innovation theory is the closest kin to Rogers's framework for understanding why incumbents fail to adapt — directly relevant to Chapter 6's institutional-response analysis.
Alvin Toffler
Alvin Toffler
Toffler's future shock argument — that the pace of change overwhelms adaptive capacity — is the cultural precursor to Rogers's temporal-compression analysis, surfaced in Chapter 8.
Daniel Kahneman
Daniel Kahneman
Chapter 3's treatment of adoption psychology draws on cognitive-bias dynamics — loss aversion, status quo bias, identity threat — that Kahneman's dual-process framework illuminates.
Joseph Schumpeter
Joseph Schumpeter
Schumpeter's creative destruction provides the macro-economic frame for the labor-market consequences Rogers's consequences chapter addresses in Chapter 7.
Erik Brynjolfsson
Erik Brynjolfsson
Brynjolfsson's productivity paradox and the idea that technology adoption precedes productivity gain by years is the economic framing behind Rogers's adoption-effectiveness gap argument.
Herbert Simon
Herbert Simon
Simon's bounded rationality and satisficing are the cognitive foundations for Rogers's adopter-category theory — particularly the late majority's risk-averse decision calculus under information constraints.
Peter Drucker
Peter Drucker
Drucker's knowledge worker concept and his insistence that effectiveness requires judgment are the precursors to Chapter 7's ascending-friction argument about what AI raises rather than removes.
Eliyahu Goldratt
Eliyahu Goldratt
Goldratt's theory of constraints and the idea that the bottleneck migrates as systems improve maps precisely onto Chapter 2's ascending-complexity argument — that removing surface difficulty raises the demands at the next level.
Aaron Antonovsky
Aaron Antonovsky
Antonovsky's salutogenic framework — asking what produces health rather than what causes disease — is the philosophical partner to Rogers's insistence on attending to consequences beyond the pro-adoption story.

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