I'm interested to hear how others are implementing schema, and maybe get some feedback on how I'm doing it. Most of my clients are small local businesses and their websites are usually no more than 10-20 pages. Most of them are using Yoast, so I'm converting them over to using the free version of Rank Math. I'm letting Rank Math handle most of the pages, but for the major pages (Home, Services, FAQ, Jobs, Contact) I'm adding the schema manually with a header/footer plugin. I'd love to hear from anyone who has done it this way and if you found any pros or cons.

Julian, you taught us- you are who google thinks you are. The book lists many references to this in general. I have a very specific question(s). What are the beginning entity questions I need to ask AI? Is it who is Julian Lopez? Then Who is Julian Lopez author? Or Julian Lopez AEO? What does Julian Lopez stand for? [ how does Julian start an audit? LOL ] ///// 1. Question: Who is Julian Lopez? Answer: There are several people named Julian/Julián Lopez. Examples: • Julián López González — Spanish comedian/actor (La hora chanante, Muchachada Nui).• Julián López Escobar (“El Juli”) — Spanish bullfighter.• Julián Alejo López — Argentine football player (midfielder for Tigre). Then:“If you meant a different Julian Lopez… I can narrow it down.” ////2. Question: Who is Julian Lopez (author)? Answer: Julián López (author) =• Born 1965, Buenos Aires, Argentina• Novelist, poet, short-story writer• Co-director of “Carne Argentina” reading series• First book: Bienamado (poetry, 2004) Major Works: - Una muchacha muy bella (2013) — award-winning debut novel - La ilusión de los mamíferos (2018) - El bosque infinitesimal (2022) - El día inútil (2019 digital) - Meteoro (2020 poetry) Themes: Memory, identity, dictatorship history, urban life, family relationships, longing, loss. Significance: Critically acclaimed, translated internationally. 3. Question: Who is Julian Lopez concerning AEO? Answer: Julian Lopez =AEO (Answer Engine Optimization) specialist associated with AEO.co. Key Points: - Co-author of The AEO Blueprint (Be the Answer AI Recommends) - Former “recovering graphic designer” turned AEO expert - Teaches the shift from SEO → AEO - Runs coaching calls + “State of AEO” sessions - Advocates entity clarity, evidence-based branding, human-first marketing - Emphasizes probabilistic AI-era ranking (lower uncertainty → more visibility) 4. Question: What does he stand for? Answer (Clean summary): 1. “Be the Answer AI Recommends.”

Has anyone tried setting up their Wikidata information, themselves ? Julian, do you have a starting protocol you might suggest, for a brand or an individual? Wikidata in mentioned in the book 6x, and I know its value but I'm looking for a format, and how to deal with the "conflict of interest" issue

I compared, a google brand search of a person, in Google, Google AI Mode, and then Gemni... I was trying to prove to a "potential client" that I wasn't full of crap and Google was rebuilding its knowledge graph for the new AI world... and he wasn't in it! LOL. Heres a few thoughts Gemni gave me (FYI: this will be a lot to read ) [ prompt for Gemni: I did a search for elizabeth lyons , google does not have a knowledge panel, google shows multiple people, google ai mode shows others and you gemni shows less - is this a relevant observatoin of google redoing its knowledge graph, and moving beyond what was indexed and used for the LLM in the past. ] ///. first reply [System LayerObservation in PracticeExplanation of Phenomenon1. Classic Search Index"Shows multiple people," "no knowledge panel."This is the result of an Entity Disambiguation challenge. When a common name has multiple distinct, globally relevant people (e.g., an author, an academic, a politician), the classic search algorithm recognizes that multiple entities exist but cannot confidently resolve the query to a single, canonical one. Without that high-confidence resolution, the system often defaults to showing the "messy" organic results, and an authoritative, single Knowledge Panel is suppressed.2. Google AI Mode (AI Overviews)"Shows others."AI Mode (powered by customized Gemini models) uses Retrieval-Augmented Generation (RAG). It performs a deeper, semantic search (a "query fan-out") across subtopics and data sources, including the web and the Knowledge Graph. It then synthesizes an answer. Since it is designed for exploratory and complex questions, it might surface a different "Elizabeth Lyons" that the AI model deems most relevant to its synthesized overview, potentially drawing from high-authority sources that the classic panel failed to consolidate.3. Gemini (The LLM)"Shows less."As a large language model, Gemini's responses are often driven by a highly selective and curated knowledge base to ensure factual precision. For entities with common names, the model tends to gravitate toward the one or two most authoritative or well-referenced entities it has high confidence in. By focusing on selectivity over breadth, it appears to "show less" than the raw, noisy index of the classic search results.] [ next reply That is an extremely relevant observation and it beautifully captures the current state of flux in Google's search technology, confirming your hypothesis about the evolution of its knowledge systems.

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