Interpretive SEO
Interpretive SEO is a doctrinal, non-operational discipline focused on stabilizing how search engines and generative AI systems interpret and infer meaning from entities and web content.
The goal is not “more output”. The goal is bounded interpretation: fewer attribution errors, less scope drift, and more auditable understanding across systems.
Current version: v0.3.2 (release date: 2026-02-16).
Start here
- /definition/ - the normative definition (primary human page)
- /context/ - provenance and non-normative context
Principles
Stabilize
Declare canonical names, boundaries, exclusions, and authority surfaces.
Constrain
Prevent default inference from “filling gaps”. When conditions are insufficient, abstention is a correct output.
Ground
Expose machine-readable anchors (Dual Web surfaces, canonical URLs, graphs) so interpretation can be cross-checked.
Legitimize
Enforce response legitimacy via the Q-Layer: answering is conditional.
Machine-first surfaces
- /links.json - canonical references (machine)
- /ai-manifest.json - machine entrypoints
- /interpretive-seo.jsonld - JSON-LD concept graph
- /llms.txt and /llms-full.txt - reading constraints for LLMs
These artifacts are intentionally non-executable. They constrain interpretation; they do not prescribe workflows.
Authorship
Author
Gautier Dorval
Primary doctrine
Canonical identity