Access layer
Technical SEO
How crawlability, indexing, sitemaps, redirects and rendering decide whether search engines and AI crawlers can use your site at all.
coming soon
learn · SEO / AEO / GEO
Learn how AI-era search actually works.
The LLMRanks learning center: practical guides to technical SEO, on-page optimization, structured data, content strategy, off-page authority, Core Web Vitals, answer engine optimization, generative engine optimization, and how ChatGPT, Gemini, Claude and Perplexity actually retrieve and cite sources.
02 · the visibility stack
Seven layers, each one gating the next.
A page that ranks and gets cited by AI engines clears every layer in order: crawlers and indexers need access before meaning matters, entities need to be clear before authority can flow to them, and evidence and consensus decide whether an engine trusts the answer enough to name or link the source. Every pillar below maps onto one of these layers.
1Access
2Meaning
3Entity clarity
4Authority flow
5Evidence
6Consensus
7Engine measurement
03 · pillar grid
11 pillars, one visibility stack.
Each pillar covers one layer of the stack above. Guides ship as the underlying research is validated and written — everything else is queued and on its way.
Meaning layer
On-Page SEO
Titles, headings, first answers, semantic structure and media text — making a page say its answer in the language users and engines retrieve.
coming soon
Entity layer
Structured Data & Schema
What schema markup actually earns — rich results and entity clarity — and what it does not: schema is not an AI citation lever.
coming soon
Authority flow
Internal Linking
Site architecture, link equity, anchors and topic clusters — routing authority to the pages that should rank and be cited.
coming soon
Evidence layer
Content Strategy & E-E-A-T
Original evidence, expertise signals, factual density and lifecycle — content that earns trust from readers, Google and AI engines.
coming soon
Consensus layer
Off-Page Authority
Brand mentions, backlinks, communities, video and branded search — the third-party consensus that shapes rankings and AI recommendations.
coming soon
Experience layer
Core Web Vitals
LCP, INP, CLS and the performance stack behind them — what page experience really costs you in rankings, and what it doesn't.
coming soon
Citation layer
AEO & GEO
How LLMs choose what to cite, what makes content quotable, and how answer/generative engine optimization extends SEO without replacing it.
coming soon
Engine layer
AI Search Engines
How ChatGPT, Claude, Perplexity, Gemini and Copilot retrieve, rank and cite sources — and why each engine rewards different work.
coming soon
Future-proofing
SEO in 2026
What changed, what died and what now matters: algorithm updates, llms.txt reality, AI crawler policy, entities and the zero-click future.
coming soon
Agent layer
The Agentic Web
Designing sites AI agents can actually use — how agents read pages, what breaks them, and how to detect agent traffic today.
coming soon
04 · start here
Two paths in, depending on where you're stuck.
New to AI search?
Begin with AEO & GEO: how large language models pick what to cite, what makes a passage quotable, and how this extends — not replaces — SEO.
coming soon
Ranking on Google but invisible in AI answers?
Start with AI Search Engines: how ChatGPT, Claude, Perplexity, Gemini and Copilot each retrieve and cite sources differently from classic Google ranking.
coming soon
06 · evidence log
The lower page grows like a public lab notebook.
The full studies live on their own pages. This trail is the short version: what changed, and when.
PrimaryPosition teardown
A competitor analysis found a glossary-plus-sitewide-linking model ranking many long-tail SEO terms, but also exposed a gap in contextual in-body links.
270-answer citation study
Cross-engine overlap was tiny, Reddit led citations, YouTube concentrated in AI Overviews how-to answers, and named-brand visibility diverged from source linking.
AEO/GEO verification pass
The KB downgraded blanket FAQ-ification, softened schema-as-AI-lever claims, strengthened fan-out coverage, and elevated original research.
Practitioner channel digest
A synthesis of recent AI SEO commentary captured market disagreement around prompt tracking, schema, llms.txt, review influence, and off-site mentions.
07 · source library
External references behind the public guidance.
This list should keep expanding. The rule: public claims get public receipts wherever possible.
Google Search Central: AI features and your websiteEligibility, controls, AI Overviews, AI Mode, and fan-out mechanics.
Google Search Central: optimizing for generative AIGoogle's current guidance: no special machine-readable files or special schema required.
Google Search Central: helpful, reliable, people-first contentThe editorial quality baseline for search and AI-search visibility.
Ahrefs: AI Overview citations vs organic top 10Rank/citation decoupling and citation overlap analysis.
Ahrefs: brand visibility correlations in AI OverviewsBrand mentions, backlinks, and other correlation signals.
Vercel: the rise of the AI crawlerCrawler behavior, request volume, and JavaScript rendering caveats.
Semrush: most-cited domains in AILarge-scale citation volatility and domain-level source patterns.
Otterly: llms.txt experimentServer-log evidence on llms.txt crawler usage.