Method
The AI search optimization methodology behind every SIMLL program
Our AI search optimization methodology stacks four disciplines: topical authority mapping, tested on-page execution, live SERP validation, and model-side training from the labs. Here is why that beats template SEO, in terms a business owner cares about.
Discipline one
Topical authority: cover the territory, earn the trust
Search engines and AI engines trust sources that own a topic, not sites that visit it occasionally. Following Koray Tugberk Gubur's topical authority methodology, every SIMLL program starts with a full topical map of your market: every question a buyer asks, organized into hubs and supporting pages, each with one job and no overlap. That structure is why our pages get cited: an AI engine assembling an answer looks for the source that covers the whole territory.
Discipline two
On-page rigor: measured, not guessed
The second discipline is Kyle Roof's on-page SEO methodology: single-variable testing that proves which on-page factors move rankings, applied as a checklist to every page we publish. Word placement, heading structure, keyword positioning, and schema are executed to measurement, not taste. The result is a page that both Google's ranking systems and AI extraction can read without ambiguity.
Discipline three
DataForSEO validation: The Golden Rule
Nothing ships on assumption. Before any page is written, the topic is validated against live SERP data through DataForSEO: real volumes, real cost-per-click, real competition, and what the current results actually reward. We call it the golden rule: if the live SERP does not confirm the opportunity, the page does not get built. This is what separates a mapped program from a content calendar.
Discipline four
Model-side understanding: trained where the engines are built
AEO and GEO fail when they treat AI engines as black boxes. Jose completed Anthropic's coursework on how Claude reasons and cites sources, and OpenAI's coursework on how ChatGPT assembles answers. That training shapes how we structure pages for extraction: answer-first openings, entities named explicitly, claims a model can lift and attribute. It is the difference between optimizing for AI search and guessing at it.
The workflow
From map to measurement, every time
Topical map
The full territory of your market, structured into hubs and supporting pages.
SERP validation
Every topic checked against live search data through DataForSEO before writing.
Entity matrix
The entities an authoritative answer must cover, mapped per page.
Brief
Structure, keywords, questions, and linking defined before drafting.
Draft
Written for a decision-maker, structured for AI extraction.
Publish
Schema, meta, slug, and internal links wired in on the way out the door.
Measure
Rank tracking plus AI citation monitoring: who cites you, who does not, and why.
This methodology, run for your business
Three tiers, everything done for you. See what each program includes.