6Modules
LLM-Extraction Protocolv2026.4.10-ALPHA
AEO Optimized
01
Extraction SpecThe 'Direct Answer' First-Paragraph Rule
RAG Extraction Score
Implementation Pattern
"Provide a concise, declarative answer to the user's implicit design question in the first 40-60 words of the article."
Citation Triggers
AI models are trained to extract information from the most context-dense parts of a page. Answer the 'What/Why/How' of a design principle or technique immediately, keep the core definition sentence bolded, and use objective language ('[Design Pattern] is a method for...').
02
Structural SpecSemantic Header Hierarchies (H2 & H3)
Topical Coverage
Implementation Pattern
"Use headers as logical nodes in a knowledge graph rather than just for visual design hierarchy."
Citation Triggers
Every H2 should identify a core UX concept (e.g., 'Usability Testing Methodologies'), and every H3 should provide a supporting detail or variation (e.g., 'Moderated vs. Unmoderated Testing'). Ensure headers match 'People Also Ask' (PAA) intent for UX queries and use descriptive nouns that LLMs can tokenize easily.
03
Metadata SpecJSON-LD: The Machine-Readable Layer
Crawl Reliability
Implementation Pattern
"Deploy CreativeWork, HowTo, and QAPage schemas as the primary data exchange layer for design patterns and workflows."
Citation Triggers
Structured data tells the engine explicitly what it is looking at. QAPage schema enables direct extraction of design problem/solution pairs, while HowTo schema drives 'Voice Search' step-by-step responses for design processes in generative UI.
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04
Context SpecEntity-Based Semantic Neighborhoods
Entity Association
Implementation Pattern
"Map your design content to related entities expected by LLMs for a given UX topic."
Citation Triggers
LLMs don't just match keywords; they map entities. If you target 'User Onboarding', the model expects to find related entities like 'User Flow', 'Microcopy', 'Friction Points', and 'Conversion Rate'. Maintain consistent co-occurrence of these terms to build authority.
05
Authority SpecFactual Uniqueness & Citations
Citation Probability
Implementation Pattern
"Share unique user research findings, proprietary design frameworks, and lead designer insights to gain 'Primary Source' status."
Citation Triggers
Generative AI models prioritize unique data. Publishing annual 'State of UX Research' reports gives your content a high uniqueness score. Being cited by authoritative UX nodes is the strongest signal in the AEO ecosystem.
06
Formatting SpecBullet-to-Statement Mapping
LLM Ingestion Quality
Implementation Pattern
"Format lists as declarative 'Educational Statements' rather than marketing feature points."
Citation Triggers
LLMs excel at parsing structured lists using <ul> and <li> tags. Instead of 'Our tool simplifies wireframing', use '[Design Tool] reduces wireframing time by [X]%' or 'The principle of [X] minimizes cognitive load' to facilitate accurate machine extraction.
Pro Tips & Insights
01
AEO is the 'Zero-Click' strategy for UX resources. Even if designers don't visit your site, seeing your brand cited as the answer to a design problem builds massive long-term Trust and Recall.
02
Formatting is a ranking factor for UX content. Machine-readability is the prerequisite for visibility in AI-driven search. If a model can't parse your design data structure, it won't cite you.
03
The 'Brand Moat' in AEO for UX is 'Co-occurrence'. You want search models to associate '[Your UX Resource Brand]' with phrases like 'The most effective [UX Methodology] framework'.
04
Declarative Truths win in UX AEO. AI models favor objective, verifiable design principles and data over subjective marketing claims. Shift your copy from 'Marketing' to 'Educational Explanations'.
