Explore / GEO Best Practices
GEO Content Engineering Manual & Evaluation Standard
Based on 53 academic papers in AI Search / GEO / AEO, translating theoretical findings into actionable SEO optimization methodologies.
Executive Summary
This operation manual translates cutting-edge academic conclusions on Generative Engine Optimization (GEO) into actionable engineering workflows. It systematically details a six-layer architecture spanning requirement definition, prompt graph engineering, content structuring, citation authority, performance audit, and content governance.
Who is this for?
- AI startups & growth marketing teams seeking to improve brand share of search in Perplexity, ChatGPT, etc.
- Content creators & global branding teams mastering next-gen generative AI optimization rules.
- GEO/AEO agencies & strategists building professional auditing scoring cards.
Document Info
Version: 2026-06-24
Format: Desktop Optimized PDF
Size: 825 KB
Compiled from 53 AI Search / GEO Papers
Manual Table of Contents
1. Research Scope & Executive Summary
2. Academic Topic Map of 53 AI Search / GEO Papers
3. GEO Content Engineering First Principles
4. GEO Definition & Six-Layer Framework Design
5. 12-Step Operational Workflows & Node Examples
6. GEO Quality Standards & 100-Point Audit Scoring Card
7. Audit & Attribution Methodology
8. Team Structure, Templates, and Rollout Roadmap
9. White-Hat Principles & Generative Risk Mitigation Boundaries