GEO Framework
Defines how representation, evidence, measurement and governance are separated.
Books, research notes and source material on generative-engine visibility and the behaviour of AI agents, with explicit definitions, checks and limits.
The connected collection moves from GEO foundations and audit methods to AI-agent behaviour, recurring failures and a complete protocol for testing authority, evidence, stopping and recovery.
AUTHOR AND PUBLICATION RECORDView Kaan MURAZ ↗Defines how representation, evidence, measurement and governance are separated.
Maps 99 recurring failures in generative representation and the checks used to detect them.
Turns the framework into a versioned, inspectable audit procedure.
Answers 69 canonical questions with sources, practical actions and explicit limits.
Proposes a framework for agent identity, capability, eligibility, authority, rollback and human control.
99 fictional cases examine failures in agent identity, authority, tool use, delegation, stopping and governance. Each record includes detection signals, correct behaviour, a machine rule and an audit question.
A complete protocol for proving how an AI agent behaved, which authority applied, what evidence supports the judgement and whether stopping and recovery worked.
A proposed constitution for keeping human identity, consent, authority, challenge, exit and institutional responsibility intact when AI agents act.
A field guide to platform reports, controlled prompt samples and business outcomes—and to what each can and cannot establish.
Read the note ↗02EVIDENCE / INTERPRETATIONA rigorous method for separating entity mentions, attributed claims, linked and supporting citations, accurate portrayal, comparative inclusion, recommendations and commercial outcomes.
Read the note ↗03INTERNATIONAL / ENTITY GOVERNANCEA six-language operating standard for stable entity facts, native editorial quality, self-canonicals, reciprocal hreflang, RTL delivery, machine-data parity and market-level measurement.
Read the note ↗04METHOD / REPRODUCIBILITYA transparent workflow for fixed prompt panels, repeated observations, exact denominators, citation evidence and commercial outcome tracking.
Read the note ↗05DISCOVERY / EVIDENCE CHAINA seven-stage guide to AI-search discovery: crawling, indexing, query fan-out, retrieval, grounding, citation, recommendation and measurement.
Read the note ↗06SOURCES / CITATION READINESSA practical, evidence-led guide to source readiness for ChatGPT and generative search: access, original value, claim-level support, structured data and measurement.
Read the note ↗07FOUNDATIONS / GEOA practical definition of GEO, how AI-search discovery works, where it overlaps with SEO and how to measure it without invented certainty.
Read the note ↗08STRATEGY / SEO AND GEOA practical GEO and SEO comparison covering shared foundations, AI-search citations, technical discovery and the metrics that should remain separate.
Read the note ↗09TECHNICAL / CRAWLER POLICYA source-led guide to separating search discovery, user retrieval and model-training preferences.
Read the note ↗10MEASUREMENT / CITATION SHAREA fixed-query method for recording mentions, citations, accurate descriptions and recommendations without turning a sample into a ranking claim.
Read the note ↗11BUYER GUIDE / EUROPEA buyer's field guide to evaluating GEO expertise, multilingual delivery, evidence, scope and commercial accountability across Europe.
Read the note ↗12AUDIT / SEARCH AND ANSWER SYSTEMSA practical diagnostic sequence for crawlability, indexing, entity accuracy, source quality, AI retrieval and measured commercial demand.
Read the note ↗13TECHNICAL SEO / AI DISCOVERYThe technical eligibility layer behind Google AI features, ChatGPT Search and other answer systems, without invented AI-specific requirements.
Read the note ↗The library separates observable evidence from interpretation. It does not manufacture a universal GEO score or promise inclusion, citation or ranking.READ GEO ANSWERS ↗
Crawler access, indexing, retrieval, citation and recommendation are different events. Each must be checked independently.