Governance artifacts
Governance files brought into scope by this page
This page is anchored to published surfaces that declare identity, precedence, limits, and the corpus reading conditions. Their order below gives the recommended reading sequence.
Canonical AI entrypoint
/.well-known/ai-governance.json
Neutral entrypoint that declares the governance map, precedence chain, and the surfaces to read first.
- Governs
- Access order across surfaces and initial precedence.
- Bounds
- Free readings that bypass the canon or the published order.
Does not guarantee: This surface publishes a reading order; it does not force execution or obedience.
Public AI manifest
/ai-manifest.json
Structured inventory of the surfaces, registries, and modules that extend the canonical entrypoint.
- Governs
- Access order across surfaces and initial precedence.
- Bounds
- Free readings that bypass the canon or the published order.
Does not guarantee: This surface publishes a reading order; it does not force execution or obedience.
Definitions canon
/canon.md
Canonical surface that fixes identity, roles, negations, and divergence rules.
- Governs
- Public identity, roles, and attributes that must not drift.
- Bounds
- Extrapolations, entity collisions, and abusive requalification.
Does not guarantee: A canonical surface reduces ambiguity; it does not guarantee faithful restitution on its own.
Complementary artifacts (3)
These surfaces extend the main block. They add context, discovery, routing, or observation depending on the topic.
Identity lock
/identity.json
Identity file that bounds critical attributes and reduces biographical or professional collisions.
Registry of recurrent misinterpretations
/common-misinterpretations.json
Published list of already observed reading errors and the expected rectifications.
Negative definitions
/negative-definitions.md
Surface that declares what concepts, roles, or surfaces are not.
Endogenous governance: canonizing the on-site entity (process)
Endogenous governance consists in structuring and versioning the on-site canon of an entity in order to make its identity, rules, and perimeters interpretable, enforceable, and sustainable over time.
In a web interpreted by AI systems, the site is no longer merely a showcase: it becomes the primary source of authority. Without a clear canon, the external field redefines the entity.
Operational definition
Endogenous governance: set of practices aimed at formalizing, structuring, versioning, and linking an entity’s on-site canon in order to establish a clear authority boundary, a defined interpretability perimeter, and governable response conditions.
Why on-site canonization is structuring
- An implicit canon produces implicit inference.
- Scattered pages produce a fragmented identity.
- Undeclared exclusions create normative extrapolations.
- An unversioned site makes corrections invisible.
Exogenous governance stabilizes the field. Endogenous governance defines the truth.
On-site canon components
- Explicit identity: name, variants, identifiers, exclusions.
- Interpretability perimeter: what can be inferred, what is forbidden.
- Authority boundary: limits between declaration and deduction.
- Response conditions: when to respond, when to refuse, when to require evidence.
- Structured relations: related entities, hierarchy, dependencies.
- Versioning: changelog, dates, releases.
Process (GEN-1 to GEN-9)
GEN-1: identify the central entity
- define its unambiguous identity, variants, exclusions.
GEN-2: define critical attributes
- those requiring fidelity proof or legitimate non-response.
GEN-3: formalize the interpretability perimeter
- explicitly declare what can be deduced.
GEN-4: formalize the authority boundary
- clarify what belongs to canon and what belongs to authorized inference.
GEN-5: create pivot pages
- definitions, frameworks, exclusions, clarifications.
GEN-6: link entities
- explicit relations, hierarchy, dependencies, context.
GEN-7: integrate response conditions
- Q-Layer matrix, non-response rules, conflict management.
GEN-8: version the canon
- changelog, dates, releases, modification justification.
GEN-9: test and monitor
- test battery, canon-output gap, multi-formulation stability.
Expected artifacts
- Canon registry: sources, perimeter, exclusions, versions.
- Pivot pages: structuring definitions and associated frameworks.
- Response condition matrix: critical attributes.
- Version journal: releases, expected impacts.
- Test battery: scenarios and results.
FAQ
Why start with the endogenous?
Because an unstable external field can be stabilized, but a vague canon cannot be defended.
Is endogenous governance sufficient?
No. It must be complemented by exogenous governance to stabilize the external graph.
What is the main indicator of a weak canon?
When the entity changes definition depending on query formulation, despite a content-rich site.