The SEO and GEO Series: from the Fundamentals to AI Visibility

I have been optimising websites for search engines for over 25 years — and since AI answers became the new stage for visibility, a second discipline has joined in: GEO (Generative Engine Optimization). In this series I worked through both from the ground up: the classic SEO foundation, the fundamentals of GEO, the practice of AI optimisation, and the question of how you even measure success. This page is the entry point and the table of contents for the series — from here you can jump into every part.

Why SEO and GEO belong together

SEO and GEO are not opposites but two layers of the same task: getting found and getting cited. If you rank in classic search results, you deliver exactly the clean, structured and trustworthy content that AI systems build their answers from. The technical foundation — fast loading, clear structure, structured data — carries both worlds. GEO is not a replacement for SEO but its extension: the same content additionally has to be citable, unambiguous and machine-readable. That is precisely why this series starts with the SEO foundation and builds step by step towards AI visibility.

The series

SEO foundation

SEO in 2026: What Actually Matters — what really counts after a good 25 years of SEO, put in honest context instead of checklist folklore.
Technical SEO: The Foundation — HTTPS, canonicals, sitemap, hreflang, structured data, and the traps I have been seeing for 25 years.
On-Page & Content: What Makes Pages Rank — title, meta description, H1 hierarchy, readability, and "lead with the answer".
Link Strategy: Internal and External — descriptive anchor text, internal linking, rel attributes, shallow link depth, and backlinks by quality.
Core Web Vitals & Performance — thresholds for LCP, INP and CLS, what each metric measures, plus concrete optimisation and measurement tools.

GEO fundamentals

GEO: Visibility in AI Answers — why being citable in AI answers is becoming a new discipline alongside SEO, and what that means in practice.
Google's AI Optimization Guide, in Context — Google's position: SEO and GEO are the same discipline — but only for Google AI Search. What that means in practice.

GEO practice

Writing for AI: The GEO Writing Playbook — lead with the answer, mini-definitions, quantitative evidence and FAQ patterns so AI systems cite you.
Multi-Turn & Query Fan-Out — AI search is a dialogue: anticipate follow-up questions, serve query fan-out, build topic authority through topic clusters.
Structured Data & Technical GEO — JSON-LD schemas, llms.txt, AI crawler management, and the Markdown mirror as this site's lived experiment.
E-E-A-T & Brand Authority — why AI systems cite verifiable authority, and how you make experience, expertise and trust visible.
Multimodal & Search Everywhere — search is more than text: image, video, audio and voice count, and AI aggregates visibility across many platforms.
Content Signals & C2PA: Controlling AI Usage — with the content-signal directive and C2PA you control how AI systems may use your content.

Measurement & outlook

Measuring GEO — and the Outlook on Agents — measuring GEO success without standard tools: a question catalogue, KPIs like brand-mention rate and citation quality, plus a look at autonomous AI agents.

Bonus: workshop report

Making-of: My SEO and GEO Tool — how 25 years of practice turned into a fast, free SEO/GEO analysis tool, with real code examples of how the score and checks actually compute.

Where to start

New to SEO? SEO in 2026 and Technical SEO lay the foundation. Mainly after visibility in AI answers? Start with the GEO fundamentals in What is GEO? and go straight to Writing for AI — that is the practical core. If you have been at this a while, the practice parts hold the current building blocks of 2026.