Interpretive SEO

Type: Canonical definition

Conceptual version: 1.0

Stabilization date: 2026-01-18

This page provides editorial and explanatory context on the concept “interpretive SEO”.
The normative and canonical definition (web authority) of the concept is published at: https://interpretive-seo.org/

Authorship:
The term “interpretive SEO” is introduced and defined by Gautier Dorval in January 2026 to designate this discipline.

Status:
Non-normative page. It does not establish, modify, or replace the canonical definition published at interpretive-seo.org.

Interpretive SEO designates the discipline that aims to stabilize how inference systems (engines, assistants, agents, language models) interpret, infer, and attribute meaning from a site, an entity, and its content. In an interpreted web, the challenge is no longer merely visibility, but correct understanding, fair attribution, and reduction of out-of-perimeter extrapolations.

Interpretive SEO does not merely formalize what must be understood. It also formalizes the fact that producing a response is not a default state. When legitimacy conditions are not met, the correct outcome may be clarification or legitimate non-response. This discipline therefore includes a response legitimacy layer (Q-Layer).

This page falls under the doctrinal framework described by /doctrine/, articulates with Interpretive governance, and connects to the implementation standard SSA-E + A2 + Dual Web.

Canonical references:
Web canon (normative): https://interpretive-seo.org/
Versioned repo (citation): https://github.com/GautierDorval/interpretive-seo

What interpretive SEO is not

  • Not traditional SEO (ranking, technical audit, content volume).
  • Not GEO (Generative Engine Optimization) in its narrow sense of citation maximization.
  • Not a marketing repackaging of existing practices.
  • Not a keyword or meta tag optimization method.
  • Not a product, service, or commercial offer.

What it addresses

  • How AI systems reconstruct the identity of an entity.
  • How they attribute capabilities, services, or positions by inference.
  • How perimeter drift and neighborhood contamination alter the canon.
  • How to bound the interpretation space and make response conditions enforceable.

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