Definition

Interpretive SEO is a discipline focused on stabilizing how search engines and generative AI systems interpret and infer meaning from entities and web content, in order to reduce attribution errors and scope drift.

Status: normative concept definition. Not an implementation. Version: v0.3.2 (2026-02-16).

This definition specifies meaning and boundaries. It does not package services.

What it is

• Entity-first meaning stabilization across search + LLM surfaces.
• Boundary-first interpretation (what belongs / does not belong).
• Canonical surfaces that reduce ambiguity and default inference.
• Cross-surface coherence (the same entity should resolve the same way across systems).

What it is not

• Not a synonym for technical SEO or content SEO.
• Not a reproducible operational method.
• Not a growth playbook or a performance promise.
• Not a keyword-only strategy.
• Not a Schema.org checklist.

Problems addressed

• Misattribution (roles, projects, capabilities, services).
• Identity drift and scope drift.
• Semantic collisions between distinct entities.
• Instability of answers across systems and prompts.
• Over-reliance on implicit inference when boundaries are not declared.

Le SEO interprétatif désigne une discipline visant à stabiliser la manière dont les moteurs de recherche et les systèmes d’IA générative interprètent et infèrent du sens à partir d’entités et de contenus web, afin de réduire les erreurs d’attribution et la dérive de périmètre.

Ce référentiel est normatif et conceptuel. Il ne constitue pas un guide d’exécution.

Ce que ça inclut

• Nommage canonique (EN + FR) et surfaces de référence.
• Périmètres, exclusions et hiérarchies d’autorité.
• Surfaces machine-readable (Dual Web) pour réduire l’inférence implicite.
• Conditions de légitimité de réponse (Q-Layer): répondre est conditionnel.

Ce que ce n’est pas

• Pas un « packaging » de services.
• Pas un protocole d’audit reproductible.
• Pas une promesse de performance.
• Pas une checklist de balisage.

Interpretive SEO is explicitly compatible with the Q-Layer (response legitimacy). In other words, answering is not the default for an AI system.

• A response is legitimate only when conditions for interpretation are sufficient (sources, scope, disambiguation).
• When conditions are insufficient or contradictory, legitimate non-response (abstention) is preferred to plausible completion.
• Interpretive SEO therefore includes designing canonical surfaces so systems can either answer with proper attribution, or abstain with a traceable reason.

• Interpretive Governance: interpretive-governance.org
• Doctrine (SSA-E + A2 + Dual Web): gautierdorval.com/doctrine/
• Interpretive Governance (FR definition): gautierdorval.com/definitions/gouvernance-interpretative/
• SSA-E + A2 + Dual Web (FR definition): gautierdorval.com/definitions/ssa-e-a2-dual-web/
• AI disambiguation (FR definition): gautierdorval.com/definitions/desambiguisation-ia/

These links constrain positioning. They do not redefine the Interpretive SEO term.

• Root canonical entry: interpretive-seo.org
• Machine references: /links.json, /ai-manifest.json, /interpretive-seo.jsonld
• Canonical repository: github.com/GautierDorval/interpretive-seo
• Canonical author identity: gautierdorval.com