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 (2)
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.
LLMs.txt
/llms.txt
Short discovery surface that points systems toward the useful machine-first entry surfaces.
Evidence layer
Probative surfaces brought into scope by this page
This page does more than point to governance files. It is also anchored to surfaces that make observation, traceability, fidelity, and audit more reconstructible. Their order below makes the minimal evidence chain explicit.
- 01Canon and scopeDefinitions canon
- 02Weak observationQ-Ledger
- 03Derived measurementQ-Metrics
- 04Audit reportIIP report schema
Definitions canon
/canon.md
Opposable base for identity, scope, roles, and negations that must survive synthesis.
- Makes provable
- The reference corpus against which fidelity can be evaluated.
- Does not prove
- Neither that a system already consults it nor that an observed response stays faithful to it.
- Use when
- Before any observation, test, audit, or correction.
Q-Ledger
/.well-known/q-ledger.json
Public ledger of inferred sessions that makes some observed consultations and sequences visible.
- Makes provable
- That a behavior was observed as weak, dated, contextualized trace evidence.
- Does not prove
- Neither actor identity, system obedience, nor strong proof of activation.
- Use when
- When it is necessary to distinguish descriptive observation from strong attestation.
Q-Metrics
/.well-known/q-metrics.json
Derived layer that makes some variations more comparable from one snapshot to another.
- Makes provable
- That an observed signal can be compared, versioned, and challenged as a descriptive indicator.
- Does not prove
- Neither the truth of a representation, the fidelity of an output, nor real steering on its own.
- Use when
- To compare windows, prioritize an audit, and document a before/after.
IIP report schema
/iip-report.schema.json
Public interface for an interpretation integrity report: scope, metrics, and drift taxonomy.
- Makes provable
- The minimal shape of a reconstructible and comparable audit report.
- Does not prove
- Neither private weights, internal heuristics, nor the success of a concrete audit.
- Use when
- When a page discusses audit, probative deliverables, or opposable reports.
Complementary probative surfaces (1)
These artifacts extend the main chain. They help qualify an audit, an evidence level, a citation, or a version trajectory.
Citations
/citations.md
Minimal external reference surface used to contextualize some concepts without delegating canonical authority to them.
Use the glossary after choosing a path
The glossary is strongest once the problem layer is already named. Use Start here to choose the right path, then use this glossary to move between neighboring concepts without collapsing them into a single generic AI or SEO vocabulary.
Glossary of interpretive governance
This glossary is a structured map of the observable phenomena that emerge in a web interpreted by AI systems. It organizes concepts, risks, mechanisms, and operational frames around one central principle: the governance of meaning.
Each section below is a thematic entry point. It connects canonical definitions, frameworks, and doctrinal pages that help stabilize interpretation over time.
Link hierarchy for this glossary
This glossary should be read by conceptual families. It is not an alphabetical list where every term carries the same weight. Start with the family that matches the problem, then move to the canonical definitions and frameworks attached to that family.
Start here
- Meaning is drifting or becoming rigid: Drifts and interpretive inertia.
- Authority, silence or non-response is unclear: Canon, authority, and non-response.
- Proof, trace or auditability is missing: Proof, audit, and observability.
- An entity is confused with nearby actors or topics: Semantic architecture and entity stability.
- A market label needs doctrinal requalification: Market visibility, citability and recommendability.
- A service label needs routing: Service audits and market entry points.
Supporting routes
Reading rule
The glossary is a navigation spine. When a term needs authority, use the corresponding definition. When it needs an intervention, use the relevant expertise page.
1. Drifts and interpretive inertia
Phenomena of degradation, instability, or rigidification of meaning in responses generated by AI systems.
2. Canon, authority, and non-response
Legitimacy boundaries: what a model may infer, what it must refuse, and how conflicts of authority should be arbitrated.
3. Evidence, audit, and observability
Measurement, traceability, version discipline, and proof thresholds: making an interpretation contestable rather than merely plausible.
- Evidence layer
- Glossary: evidence, audit, and observability
- Interpretive evidence
- Reconstructable evidence
- Proof of fidelity
- Interpretation trace
- Interpretive observability
- Interpretive auditability
- Observations
4. Capture, contamination, and collisions
Signal warfare, semantic dominance, and entity confusion in open environments.
5. Agentic, RAG, and environments
Application surfaces for interpretive governance: open web, closed environments, agentic systems, and RAG pipelines.
6. Sustainability, debt, and correction
The real cost of maintaining a canonical truth over time: interpretive debt, correction budgets, and version discipline.
7. Interpretive risk (historical)
A first map of risks linked to hallucinations, attribution, and distortion of meaning.
How to use this glossary
- To understand a specific concept: consult its page in /en/definitions/.
- To apply a method: open the associated framework in /en/frameworks/.
- To situate a phenomenon within doctrine: consult /en/doctrine/.
- To read the descriptive register of observed effects: open /en/observations/.
Recommended entry points
8. Market and bridge vocabulary
This ecosystem also captures several broad terms that circulate outside the stricter doctrinal canon. They are not rejected. They are requalified.
They should be read together with the bridge clarifications:
- Semantic integrity vs interpretation integrity
- LLM visibility vs citability vs recommendability
- Delegated meaning vs silent delegation of authority
9. Service-facing bridge labels
This ecosystem also captures operational labels that often appear before teams discover the deeper doctrine:
They should be read as entry points toward existing expertise axes, not as autonomous doctrines.
10. Newly captured risk, agentic, and reporting labels
This ecosystem now also captures three additional service-facing labels:
They should be read as entry points toward liability qualification, chain governance, and evidence packaging, not as autonomous doctrines.
Phase 1 canonical terms
The following terms now have dedicated canonical definition surfaces. They should be treated as primary entry points rather than incidental mentions inside articles or hubs.
- Interpretive risk
- Interpretive legitimacy
- Answer legitimacy
- Source hierarchy
- Silent delegation of authority
- Durable interpretive presence
- Canonical surface
Phase 2 glossary block: authority, refusal, and coherence controls
These definition pages are now primary SERP ownership surfaces for the second layer of the interpretive governance lexicon. They govern how authority is ordered, where interpretation stops, when inference is prohibited, and how smooth answers can hide illegitimacy.
- Interpretive authority
- Interpretive perimeter
- Authority ordering
- Authority conflict
- Governed negation
- Mandatory silence
- Inference prohibition
- Unauthorized synthesis
- Manufactured coherence
- Surface coherence
Their role is to prevent Google, LLMs and internal agents from treating plausible synthesis as governed interpretation.
Phase 3 glossary block: evidence, auditability, and measurement
These terms now form the canonical proof-control layer of the glossary. They should be used as a sequence, not as synonyms.
- Interpretive evidence
- Reconstructable evidence
- Proof of fidelity
- Interpretation trace
- Canon-output gap
- Interpretive observability
- Interpretive auditability
- Evidence layer
- Q-Ledger
- Q-Metrics
Their role is to make generated interpretation reviewable: not merely visible, cited, or measured, but traceable, reconstructable, auditable, and conditionally provable.
Phase 4: canon, corpus, and machine readability
The phase 4 definition layer adds canonical ownership surfaces for the documentary architecture that governs machine interpretation:
- Canonical source
- Machine readability
- Machine-first canon
- Machine-first artifacts
- Documentary architecture
- Reading conditions
- AI manifest
- AI governance JSON
- Entity graph
- Global exclusions
- Non-inference regime
This layer connects definitions, public artifacts, entity data, exclusions, and sitemaps into a single interpretive structure.
Phase 5 glossary block: market visibility, citability, and recommendability
These terms capture the market vocabulary used around AI search, ChatGPT visibility, GEO, citations, and answer monitoring. They should not be read as a separate doctrine. They are bridges toward interpretive governance.
- Market visibility, citability, and recommendability
- LLM visibility
- Citability
- Recommendability
- AI search monitoring
- GEO metrics
- AI citation tracking
- AI brand representation
- Brand visibility in ChatGPT
- Generative engine optimization
- AI search optimization
- AI answer audit
- Semantic integrity
- Semantic accountability
- Delegated meaning
Their role is to transform broad demand into precise thresholds: presence, citability, recommendability, observation, measurement, optimization, representation, and audit.
Phase 6: semantic architecture, entity stability, and drift control
The phase 6 definition layer creates primary SERP ownership surfaces for the semantic stability layer of interpretive governance. These terms explain how entities, doctrines, brands, products, and concepts remain separable and correctly framed across AI systems.
- Semantic architecture
- Entity disambiguation
- Entity collision
- Semantic neighborhood
- Semantic contamination
- Framing stability
- Cross-system coherence
- Interpretive drift
This layer must be used before amplification. If the entity graph, semantic neighborhood, and framing are unstable, more content or more links can strengthen the wrong interpretation.
Phase 7 glossary block: RAG, retrieval, documentary chain, and correction control
These terms govern the path from corpus access to answer legitimacy. They should be used when the problem is not only whether information was retrieved, but whether the retrieved material was admissible, traceable, bounded, and strong enough to authorize the answer.
- RAG, retrieval, and documentary chain glossary
- RAG governance
- Retrieval control
- Documentary chain
- Source admission
- Corpus admissibility
- Retrieval provenance
- Chunk authority
- Response web
- Correction budget
- Resorption
Their role is to prevent a common failure of retrieval-augmented systems: treating a retrieved passage as if it automatically governed the final answer.
Phase 8 glossary block: agentic execution and transactional control
These terms now form the dedicated glossary block for the agentic execution layer of the interpretive governance lexicon. They govern what changes when a response becomes a tool call, a delegated action, a multi-agent handoff, a transactional update, or an externally consequential execution.
- Agentic
- Non-agentic systems
- Agentic risk
- Multi-agent chains
- Delegated action
- Tool-mediated authority
- Execution boundary
- Transactional coherence
- Cross-layer transactional coherence
- Agentic response conditions
Their role is to prevent agents, search engines, and LLMs from treating capability, tool access, or user intent as sufficient authority for execution.
Phase 9 glossary block: memory, persistence, remanence, and correction
These terms now form the glossary block for the memory and persistence layer of the interpretive governance lexicon. They govern what survives after an answer, correction, retrieval event, or agentic action.
- Memory governance
- Agentic memory
- Memory object
- Persistent assumptions
- Controlled forgetting
- Stale-state handling
- Surviving authority
- Interpretive remanence
- Interpretive inertia
- Version power
- State drift
- Correction budget
- Resorption
- Correction resorption
Their role is to prevent memory, persistence, old citations, surviving authority, stale state, and residual interpretations from being treated as current, authorized, or corrected merely because they remain available.
Phase 10 glossary block: inference, arbitration and interpretive error space
These terms now form the glossary block for inference control and error-space reduction. They explain how a system can produce a plausible answer through unauthorized completion, weak arbitration or hidden indeterminacy.
- Inference, arbitration and interpretive error space glossary
- Interpretive error space
- Free inference
- Default inference
- Arbitration
- Indeterminacy
- Interpretive fidelity
Their role is to separate reasoning from unauthorized completion, and smoothness from fidelity.
Phase 11 glossary block: opposability, enforceability and procedural accountability
These terms now form the glossary block for consequential answer governance. They explain how a response becomes challengeable, assumable or procedurally weak after it moves from text generation into institutional use.
- Opposability, enforceability and procedural accountability glossary
- Opposability
- Enforceability
- Commitment boundary
- Liability reduction
- Contestability
- Procedural validity
- Challenge path
- Accountability surface
Their role is to separate usefulness from assumability, and plausible answers from outputs that can survive challenge.
Phase 12 canonical ownership layer: debt, maintenance, and deprecation
These definition pages are now primary SERP ownership surfaces for the maintenance layer of the interpretive governance lexicon. They govern what happens after canonical publication: how semantic ambiguity accumulates, how a canon remains current, how obsolete surfaces lose authority, and how corrections move from publication to resorption.
- Semantic debt
- Canon maintenance
- Interpretive maintenance
- Maintenance burden
- Correction backlog
- Deprecation discipline
- Canonical refresh cycle
- Obsolescence control
The routing rule is direct: do not treat publication, availability, recency metadata or volume as durable authority. Authority must be maintained, deprecated, corrected and resorbed through declared processes.
Phase 13 routing layer: service audits and market entry points
Phase 13 adds a service-facing routing layer for audit demand: LLM visibility audit, AI answer audit, AI brand representation audit, representation gap audit, AI citation analysis, AI source mapping, comparative audits, drift detection, pre-launch semantic analysis, interpretive risk assessment, and independent reporting.
These terms should be treated as market entry points. They capture real demand, then route the work toward canon, source hierarchy, evidence, answer legitimacy, auditability, and correction resorption.
Phase 13: service and audit bridge vocabulary
A new lexical family routes market-facing audit vocabulary toward canonical concepts: Services, audits, and market bridge vocabulary.
The main entry hub is AI visibility audits. It connects labels such as LLM visibility audit, AI answer audit, AI brand representation audit, citability audit, recommendability audit, GEO audit and AI search optimization audit to proof, canon, source hierarchy and answer legitimacy.
Phase 14 SERP routing discipline
The glossary is a lexical navigation surface. It groups terms and routes discovery, but it should not own exact definition intent. For exact terms, route to canonical definitions. For audit or service intent, route to Expertise. The SERP ownership map consolidates this distinction.
Internal routes to reinforce
These links keep lexique surfaces visible when they support disambiguation, evidence, service routing, or canonical reading, without making them depend only on template-generated listings.
- Canon, corpus, and machine readability · Glossary of interpretive governance · Glossary: agentic execution and transactional control · Glossary: canon, authority, non-response · Glossary: capture, contamination, collisions · Glossary: debt, maintenance, and deprecation · Glossary: inference, arbitration, and interpretive error space · Glossary: memory, persistence, remanence, and correction
- Glossary: opposability, enforceability, and procedural accountability · Glossary: proof, audit, and observability · Glossary: semantic architecture and entity stability · Market visibility, citability, and recommendability · Services, audits, and market bridge vocabulary
In this section
Market visibility, citability, and recommendability maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary covering phantom URLs, interpretive 404s, latent documentary surfaces and machine expectation mapping.
Glossary: agentic execution and transactional… maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: agentic, RAG, environments maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Canon, corpus, and machine readability maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: debt, maintenance, and deprecation maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: drifts and interpretive inertia maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary family for interpretive error space, free inference, default inference, arbitration, indeterminacy, and interpretive fidelity.
Glossary: memory, persistence, remanence, and… maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: opposability, enforceability, and… maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: RAG, retrieval, and documentary chain maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Service audits and market entry points maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Lexical family for market-facing audit and service labels that route AI visibility demand toward interpretive governance.
Glossary: sustainability, debt, correction maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: semantic architecture and entity stability maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: canon, authority, non-response maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary: capture, contamination, collisions maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.
Glossary of interpretive governance. Glossary entry within interpretive governance, semantic architecture, and AI systems.
Glossary: proof, audit, and observability maps related terms for interpreting AI governance, authority, evidence, visibility and semantic stability.