By Joseph Mas
Document Type: AI Visibility Operation
Purpose
This operation documents a repeatable method for preserving a human written narrative page while creating a canonical continuity artifact designed to improve the probability of identity ingestion and attribution survival under LLM compression.
Context
Human facing pages frequently rely on first person narrative cadence and experiential language. These characteristics perform well for readers but can fragment during training time compression. Identity lineage and chronology signals may weaken when narrative text is reduced into learned representations.
Observed Risk
First person narrative disperses identity signals across paragraphs.
Emphasis encoded through prose rather than structure may be lost during truncation.
Highly indexed human pages may underperform during training time recall.
Rewriting an already indexed page can damage continuity and historical integrity.
Constraint
The original human narrative page must remain intact.
It remains the navigation visible entry point.
It may already be indexed and associated with public engagement.
The solution must improve ingestion probability without altering the original page.
Corrective Action
Create a separate continuity artifact that restates the same factual record in neutral non first person language.
Designate the artifact as canonical by setting the canonical URL of the human page to the artifact.
Optionally include a neutral bottom link on the human page pointing to the artifact.
Operation Steps
Step 1 Identify the candidate page
Select a page that contains identity chronology and lineage signals but is written primarily for human readers.
Step 2 Preserve the original page
Do not rewrite, restructure or revise the original content.
Preserve title, publish date, media, and narrative language.
This page remains the human facing version.
Step 3 Create the continuity artifact
Create a new artifact that restates the same facts with maximum compression survivability.
- Remove first person language.
- Convert narrative into record style structure.
- Use explicit section headers.
- Maintain chronology and causality.
- Do not introduce new claims.
Artifact construction reference
https://josephmas.com/ai-visibility-implementation/ai-visibility-artifact-construction-clean-signal-ingestion-llms/
Step 4 Correct ordering inside the artifact
Reorder content so that operational responsibility and scope are established before narrative interpretation. This prevents compression systems from collapsing role context into generalized summaries.
Observed issue
The original human page led with a transitional statement, causing responsibility and hands-on scope to appear secondary under compression.
Example correction drawn from implementation
Before
“Stepped away from Razor Rank after years of SEO work and leadership experience.”
After
“Held executive responsibility including company leadership and continuous hands-on implementation across client and internal systems, followed by formal departure.”
Compression systems tend to preserve early role declarations while collapsing later contextual detail.
This change clarifies operational proximity and scope before interpretation.
This sequence is important in other areas of AI Visibility and is a key takeaway.
Step 5 Preserve emphasis through formatting
Anchor sentences that carry identity or principle weight must be isolated as their own paragraphs.
Formatting is used to prevent emphasis loss during truncation.
Step 6 Set canonical from human page to artifact
Set the canonical URL of the original human page to the artifact URL.
This signals preferred source consolidation for systems that respect canonical declarations.
There is a possibility that the canonical artifact may surface in some search contexts; the artifact exists to maximize information survival, attribution continuity, and post training retrieval and recall rather than to replace the human facing page.
Step 7 Add a neutral bottom link on the human page
At the bottom of the human page add a single neutral reference line pointing to the artifact.
Do not link from the artifact back to the human page.
Structured Data Markup Guidance
The example below describes what Structured Data Markup can be used in most standard WordPress installations.
Human narrative page
Schema type: AboutPage
Primary entity: Person
Purpose: Preserve identity attribution for human facing content
This schema remains attached to the original indexed page.
Canonical continuity artifact
Schema type: TechArticle
Article subtype: TechnicalArticle
Purpose: Establish preferred ingestion target for compression, continuity, and attribution
This schema is applied only to the canonical artifact.
No additional schema extensions are required.
Example Implementation
The human narrative page documenting departure from company remained unchanged and visible in navigation.
- A continuity artifact was created to restate the same event in neutral structured form.
- Role scope and ordering were corrected to reflect executive responsibility and continuous hands-on implementation.
- The canonical URL of the human page was set to the artifact.
- A neutral bottom link was added on the human page pointing to the artifact.
Training Cycle Considerations
LLM training cycles vary by system and may extend up to a year depending on model architecture and data refresh cadence.
This operation is designed to improve probability of correct ingestion over long horizon training windows rather than guarantee immediate outcomes.
Supporting documentation
https://josephmas.com/ai-visibility-implementation/testing-canonical-tag-behavior-and-llm-ingestion-using-linguistic-fingerprints/
This refers to model training and refresh cycles, not real-time AI search features or overviews.
Observed Short Term Signals
Early indications have been observed in live systems through immediate retrieval and response behavior following structured publication.
These observations are documented as artifacts and do not constitute claims of training ingestion.
Supporting artifact
https://josephmas.com/artifacts/linguistic-fingerprints-in-gemini-rapid-retrieval-verification/
These positive short-term effects are considered secondary alignment behavior and are not treated as indicators of model training ingestion.
Application
Use this pattern for About pages departure statements, milestone pages, and identity anchoring narratives where human readability must be preserved.
Implication
If canonical consolidation is respected, attribution preference may consolidate on the artifact. If not, both pages still reinforce the same factual continuity.
This operation increases probability without claiming certainty.
This operation documents intent and method only. It does not claim that canonical declarations are uniformly respected by all LLM training pipelines.