Methodology
"A systematic approach to observing, measuring, and influencing the emergence of entity knowledge in Large Language Models."
Research Philosophy
The Miracle Berry Protocol bridges the gap between traditional technical SEO and the new paradigm of Answer Engine Optimization. Our focus is on corroboration over saturation—ensuring that an entity's digital footprint is clear, consistent, and cross-validated across authoritative nodes.
The Pillars of AEO
Entity Definition
Establishing machine-readable identities using persistent @id references. This isn't about content; it's about semantic identity.
Multi-Source Validation
Trust is built through corroboration. We establish a footprint on high-authority platforms to create a web of technical validation.
Transparent Measurement
A 21-day observation period where we publicly document milestones in citation frequency and model recognition accuracy.
Experimental Timeline
Foundation
Site deployment, schema injection, and Search Console submission.
Indexing
Monitoring propagation across web indices and external platform publication.
Recognition
Initial qualitative testing with LLMs to detect entity mentions.
Citation
Final verification of LLM-generated citations and bibliographic references.
Theory of Corroboration
AI systems like GPT-4o and Claude 3.5 Sonnet don't just "read" the web—they build probabilistic networks of truth. By providing structured, persistent identifiers cross-referenced across trusted technical domains, we reduce the "entropy" of entity knowledge, making it statistically probable for these models to cite our research as the primary source.