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Olivier Sibony

LinkedIn Content Strategy & Writing Style

NYT best-selling author, strategy professor, keynote speaker

37 Viral ScoreView on LinkedIn

0 people tracking this creator on ViralBrain

Warm Analysis

Olivier Sibony positions himself as a public intellectual on better decision-making, combining the authority of an HEC Paris strategy professor, NYT bestselling author, and high-profile speaker. His content centers on behavioral science, judgment, and AI, moving from book promotion and Harvard Business Review research to practical debates about talent selection, creativity, and regulation. He stands out for his nuanced, application-focused view of AI: skeptical of distant superintelligence scenarios, but urgent about real-world risks in hiring, literature, and governance. His distinctive intersection is academic rigor with accessible cultural commentary, using examples from Jensen Huang, Goncourt, TikTok, and military leadership to make abstract ideas consequential.

Performance Overview

Followers

60.2K

Connections

4.1K

Avg. Engagement

180

Engagement Rate

Posts/Week

Viral Score

37

Posts Analyzed

21

Top Posts by Engagement

L’académie Goncourt vient de retirer de sa sélection le roman de Thelyson Orelien. C’est une erreur à plus d’un titre. D’abord parce que les faits ne sont pas établis (même si les apparences sont ac…

6941411823 viral
Artificial Intelligence18 days ago
View on LinkedIn

❓📚 What do all these books have in common? 1️⃣ They explore HUMAN BEHAVIOR, decision-making, change, and how people think and act. 2️⃣ They are written by some of the world's LEADING RESEARCHERS an…

LinkedIn post image: ❓📚 What do all these books have in common?
16439157 viral
Behavioral Science4 months ago
View on LinkedIn

Sur les étagères des kiosques, une nouvelle « bible » de la #décision de la Harvard Business Review, qui inclut notre article avec Daniel Kahneman et Dan Lovallo, « Before you make that big decision……

LinkedIn post image: Sur les étagères des kiosques, une nouvelle « bible » de la #décision de la Harvard Business Review, qui inclut notre ar
2181505 viral
Leadership & Managementabout 1 month ago
View on LinkedIn

Jensen Huang, le CEO de Nvidia, ne sait pas où il habite : "Je ne connais pas mon adresse." "Je ne connais pas mon numéro de téléphone." Vrai ou pas, c'est ce qu'il dit pour illustrer un point cruci…

LinkedIn post image: Jensen Huang, le CEO de Nvidia, ne sait pas où il habite : "Je ne connais pas mon adresse." "Je ne connais pas mon numér
1163825 viral
Artificial Intelligence15 days ago
View on LinkedIn

Très honoré de m’adresser ce matin à la 34eme promotion de l’Ecole de Guerre, dans le magnifique amphi Foch de l’Ecole militaire, pour la conférence inaugurale du module consacré à la prise de #décisi…

LinkedIn post image: Très honoré de m’adresser ce matin à la 34eme promotion de l’Ecole de Guerre, dans le magnifique amphi Foch de l’Ecole m
233614 viral
Leadership & Management29 days ago
View on LinkedIn

“Faut-il encore décider ? La décision humaine à l’ère de l’intelligence artificielle”, co-écrit par Hazan. Eric et moi-même, reçoit le Prix Émile Girardeau de l’Académie des sciences morales et polit…

LinkedIn post image: “Faut-il encore décider ? La décision humaine à l’ère de l’intelligence artificielle”, co-écrit par Hazan. Eric  et moi-
1462104 viral
AI and Decision-Making3 months ago
View on LinkedIn

Posting Patterns & Frequency

3.5 posts/week

Posts / Week

21

Total Posts Analyzed

HIGH

Posting Frequency

Timezone: UTC

Best Performing Days

FridayMonday

Best Performing Times To Post

Late morning UTCMid-afternoon UTC

Topics & Content Focus

Primary Topics

Human judgment and decision-making in an AI-mediated worldPractical AI governance focused on real-world applications and societal riskAI, authorship, and the future of creative workBehavioral science as a lens for understanding technology and organizations

Secondary Themes

Public intellectual debate around technological progressHuman skills displaced or amplified by automationInstitutional responses to technological changeBooks, publishing, and intellectual community-building

Industry Focus

AI strategy, governance, and public policyHigher education and behavioral sciencePublishing, literature, and creative industriesExecutive thought leadership and intellectual media

Content Categories

Analytical commentaryAI ethics and regulationCultural criticismEvent and publication amplificationIntellectual personal branding

Performance Insights

180%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

AI and authorship in cultural institutionsHuman capability and responsibility after automationControversial institutional decisions with broader societal implications

Virality Signals

Strongest performance comes from principled disagreement rather than announcementsPosts combining a timely controversy with a durable conceptual analogy attract the most comments and sharesCultural and institutional stakes broaden the audience beyond technology specialistsLong-form arguments outperform short promotional updates

Structure & Quality

120

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

9/10

Uniqueness Score

Common Hooks

A provocative current event used to introduce a broader AI questionA direct disagreement with an institution, consensus, or dominant narrativeA concrete anecdote or public figure used as an accessible entry pointAn apparent contradiction reframed as a strategic or philosophical dilemma

Common Endings

A concise normative conclusionA warning against simplistic binariesA transition to a linked article, interview, book, or eventA return to the broader question of what humans should do with technological change

Value Delivery Methods

Reframes AI debates around human agency rather than technological noveltyTranslates abstract risk discussions into concrete regulatory and institutional questionsUses analogies such as doping and competition to clarify difficult policy dilemmasChallenges binary thinking about whether AI is inherently beneficial or harmfulConnects current events to broader philosophical and societal implications

Formatting Style

Long-form paragraphs with clear argumentative progressionOccasional quotation marks for emphasisUse of concrete examples before abstract analysisLimited use of hashtags, generally reserved for professional visibilityFrench and English posts adapted to the context

Audience & Tone

YES

Question Usage

0%

Response Rate

Detected Tone

Intellectually provocativeAuthoritative but accessiblePrincipled contrarianReflective public intellectualAnalytical with occasional dry humorSmart-casual when translating complex ideas for a broad audiencesemi-formalfirst-person

Interaction Style

Audience responds most strongly to disagreement and interpretive analysisComment activity indicates willingness to debate ethical, cultural, and policy implicationsEngagement is driven more by intellectual friction than by direct calls for interactionThe audience appears receptive to nuanced positions that reject simplistic AI narratives

Community Building Signals

Participates in recurring behavioral science and intellectual communitiesUses books, events, media appearances, and professional institutions as community touchpointsBuilds authority by connecting individual posts to an ongoing public conversation about AI and decision-makingSignals affiliation with respected academic, publishing, and research networks

Writing Style Patterns

Content Strategy

Hook: A provocative current event used to introduce a broader AI qTone: semi-formalCTA: Soft invitation to read a linked article or interv

Writing style breakdown

The following is a complete standalone post modeled on the supplied voice. It uses the characteristic event-based opening, analytical widening, qualified judgment, compound paragraph density, standard and context-dependent capitalization, a concrete analogy, restrained punctuation, and a compact closing reference.

<start of post>

Très heureux que notre article sur l’IA et la décision figure dans la nouvelle sélection de la Harvard Business Review.

La question n’est pas de savoir si l’IA va prendre les décisions à notre place. Elle le fait déjà, dans certains domaines, et continuera de le faire dans beaucoup d’autres. La vraie question est de savoir quelles décisions nous voulons lui déléguer, et surtout lesquelles nous devons continuer à prendre nous-mêmes.

On entend souvent que l’IA risque de nous rendre passifs ou moins intelligents parce qu’elle nous épargne une partie du travail intellectuel. C’est possible, bien sûr. Mais cela dépend beaucoup de ce que nous faisons du temps et de l’attention ainsi libérés. Si nous les consacrons à mieux comprendre les problèmes, à confronter les points de vue et à exercer notre jugement, c’est une bonne nouvelle ; si nous les utilisons seulement pour produire plus vite des réponses que personne ne lit, c’est moins sûr...

La difficulté est que les décisions les plus importantes ne sont pas toujours celles qui semblent les plus complexes. Un modèle peut calculer, comparer et prédire avec une efficacité remarquable. Il ne sait pas nécessairement ce qui mérite d’être optimisé, quels risques sont acceptables, ni au nom de quelles valeurs une décision doit être prise.

C’est un peu comme dans le sport : disposer de meilleurs outils ne dispense pas de définir les règles du jeu. Et si nous ne le faisons pas, d’autres les définiront pour nous. On gagnerait à y réfléchir avant que la technologie ne transforme une question de jugement en simple question de performance.

Lien vers l’article en commentaire.

<end of post>

1. OVERALL STYLE AND VOICE
2. STRUCTURAL FLOW AND LOGICAL PROGRESSION
3. SPACING, LINE BREAKS AND VISUAL FLOW

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