Doc // Methodology ReferenceClassification // ProprietaryUSPTO // App. 4592722Status // Patent Pending

The Stage30™ Methodology Reference

Stage30™ is the resolution methodology for AI search. The theory in brief, and the corpus the score is read against. A measurement, not an opinion.

AuthorsJ. Barbush, L. Ramirez
Maintained byCast Iron LA
EntityCast Iron LA, CA S Corp
Canon versionv24
ModelThree Pillars → Resolution
Scale0 to 100, banded
§ 01

The Theory, in Brief

An AI search system does not rank. It resolves. It retrieves a small set of candidate sources for a question, then composes one answer by eliminating the candidates it cannot trust. A brand is selected when its signal holds together across the page, across the wider web, and across the structure a model parses before it reads a word of prose.

Stage30 scores that on three pillars. The detailed criteria are proprietary. The frame is public.

PillarIsGoverned by
AuthorshipThe writing. A citable position in a verifiable human voice.Stage for Writing™
EntityThe graph. One resolvable entity across every surface a model reads.Stage for Surfaces™
Code RefinementThe structure. Markup and schema that lower a model's inference cost.Stage for Developers + HTML™

The three pillars roll into one Resolution Score from 0 to 100, banded from Terminal at the top to Entropic at the bottom. The number answers one question: why is a model not resolving to this brand? Terms are defined in the Lexicon; the argument is in the methodology.

§ 02

The Source Corpus

The methodology is written down. It is versioned, cross-referenced, and tested on real brands before it is published. This is the record of what the score is read against.

Foundational specification
DocumentFunctionExtent
Stage30™ Methodology, Complete IPThe full specification. USPTO Application 4592722.108 pp
The Stage30™ CanonThe living master reference, with relational-identity and outbound addenda.v21–v24
Stage30™ Complete ArchitectureThe end-to-end system, on-page through off-page.13 pp
The Stage for X family, one reference per pillar
DocumentGovernsExtent
Stage for Writing™ (v1.1a)Authorship.47 pp
Stage for Surfaces™Entity. The entity network and cross-surface audit.Entity Network
Stage for HTML™Code Refinement. The page-level structural reference.44 pp
Stage for Developers™Code Refinement. Schema, JSON-LD, entity chains.21 pp
Stage30™ HTML BlueprintCode Refinement. The condensed production blueprint.12 pp
System, vocabulary, and tooling
DocumentFunctionExtent
Search Graph OptimizationThe on-page and off-page node model.System
Stage30™ Entity RunBookThe procedure for building the entity graph.7 pp
Glossary + The LexiconThe canonical vocabulary, defined once.Reference
Brand Entropy Audit + Collapse ReferenceThe diagnostic instruments and failure taxonomy.Diagnostic
Generation Prompt + google_ai_guide_vs_stage30The controlled application system, benchmarked against Google's AI guidance.Tooling
Applied implementations

The method is built and measured on live client sites before it is published. It is currently in additional testing across other brands.

SiteRecordStatus
nocompromisegaming.comProof of concept. Documented +34% lift in AI conversion from a single page.Implemented
milksandwich.comReference implementation.Implemented
Additional brandsDiagnosis and staged rebuild.In testing
CORPUS SUMMARY
> More than 240 pages of formal specification across the core references.
> Plus the living Canon and the diagnostic instruments.
> Plus live client implementations, with additional testing in progress.

The corpus is proprietary and maintained internally. Excerpts are shared under engagement.

§ 03

Attribution and External Sources

The methodology is original IP developed by John Barbush and Cast Iron LA. The market data the model is calibrated against is third-party and cited directly.

SourceFinding used
GetPassionFruit / The Digital Bloom (2025)Position 1 organic citation probability in AI Overviews is approximately 33%.
Ahrefs (Mar 2026)Across 863,000 keywords and 4M+ AI citations, over 62% of AI citations come from outside the top 10.
Industry CTR analysis (2025–2026)Organic CTR drops 58 to 61% when AI Overviews appear. Cited pages see 35%+ CTR lift.
Google Search data (Q1 2026)Approximately 48% of queries now trigger an AI Overview.
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Stage30™ // Cast Iron LA // Proprietary // Patent Pending // USPTO App. 4592722