6Modules
LLM-Extraction Protocolv2026.4.10-ALPHA
AEO Optimized
01
Extraction SpecThe 'Founder's Answer' First-Paragraph Rule
RAG Extraction Score
Implementation Pattern
"Provide a concise, declarative answer to the core problem or question in the first 40-60 words."
Citation Triggers
AI models prioritize context-dense openings. Immediately address the 'What' (the solution/concept), 'Why' (its benefit for indie founders), and 'How' (briefly, how it's achieved). Use bolding for the core definition and maintain objective language ('X is Y for founders').
02
Structural SpecProblem-Solution Header Hierarchies (H2 & H3)
Topical Coverage
Implementation Pattern
"Structure content around founder pain points and their corresponding solutions."
Citation Triggers
Each H2 should represent a core problem or a critical stage in the founder journey. H3s should detail specific tactics, tools, or data points addressing that problem. Align headers with 'People Also Ask' (PAA) queries relevant to bootstrapping, early-stage growth, and solo operation.
03
Metadata SpecJSON-LD: The Founder's Data Layer
Crawl Reliability
Implementation Pattern
"Deploy Organization, Product, FAQPage, and HowTo schemas tailored for indie founder needs."
Citation Triggers
Structured data explicitly defines your content for search engines. 'Product' schema highlights your offering's value proposition. 'FAQPage' schema captures common founder questions and answers, enabling direct extraction for generative AI. 'HowTo' schema can detail step-by-step processes for building or launching.
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04
Context SpecEntity Mapping: The Founder's Ecosystem
Entity Association
Implementation Pattern
"Connect your content to key entities relevant to the indie founder journey."
Citation Triggers
LLMs understand relationships between concepts. If you're discussing 'Bootstrapping', expected related entities include 'Lean Startup', 'MVP', 'Customer Acquisition', and 'Profitability'. Consistent use of these co-occurring entities builds topical authority for founders.
05
Authority SpecProprietary Insights & Founder Data
Citation Probability
Implementation Pattern
"Share unique founder case studies, actionable metrics, and personal journey data to establish 'Primary Source' credibility."
Citation Triggers
AI models favor original data. Publishing detailed 'Founder Income Reports' or 'First 100 Customers' breakdowns offers unique value. Being cited as the source for these insights by other platforms is the strongest signal in AEO for this niche.
06
Formatting SpecAction-to-Outcome Mapping
LLM Ingestion Quality
Implementation Pattern
"Format lists as actionable 'Founder Steps' or 'Outcome Statements' rather than generic marketing points."
Citation Triggers
LLMs parse structured lists effectively. Instead of 'We offer great support', use '[Your Solution] reduces time-to-resolution by X%' or 'Implementing [Tactic] leads to Y% increase in user engagement'. This facilitates precise machine extraction of value.
Pro Tips & Insights
01
AEO is the 'Solo Founder's Shortcut'. Even if users don't click through, being the cited answer builds immense brand authority and trust, crucial for solo operators.
02
Content structure is a ranking signal for AI. Machine-readability is paramount. If AI can't parse your founder-centric data, it won't feature your content.
03
The 'Founder Moat' in AEO is 'Problem-Solution Association'. You want search models to link '[Your Brand/Content]' with phrases like 'The definitive guide to sustainable SaaS growth'.
04
Declarative Value Wins. AI models prioritize objective, verifiable benefits for founders over subjective marketing fluff. Shift copy from 'Selling' to 'Educating and Empowering'.
