The reference for making a website legible to LLMs, citable by AI answer engines and correctly interpreted in generative search. SEO, GEO and AEO in a single framework.
The same corpus supports different tasks. Start with the decision you need to make, then refine by engine, audience, format or evidence level.
Search the corpusGenerative search (ChatGPT Search, Google AI Overviews, Perplexity, Gemini, Claude) captures a growing share of acquisition. The promises flourish: "rank first on ChatGPT", "hack the AIs".
This site takes the opposite stance. Optimising for LLMs is a discipline of editorial engineering, not a sleight of hand. We publish here a structured methodology (LOOP), an operational 40-point audit, a clear reading of the concepts and applications by sector.
LOOP is our proprietary framework, documented publicly. The resources are dated, sourced and kept up to date.
A topic cluster built to cover the whole subject: conceptual foundations, operational method, content engineering, technical architecture, framework, deliverable and proof by sector.
Definition, scope, business stakes and real limits. What GEO, AEO and LLM SEO cover, and what they do not.
Read the pageA six-step method to make a site visible and citable by AI answer engines, with no empty promises or magic recipes.
Read the pageContent design, chunking, self-containment, citation-friendly content. Editorial engineering applied to retrieval, without sacrificing human reading.
Read the pageCrawl, rendering, schema.org, llms.txt, AI bot management (GPTBot, PerplexityBot, ClaudeBot, Google-Extended). The indispensable foundations.
Read the pageThe four-dimension framework: Legibility, Ontology, Operations, Performance. A structured method to steer AI visibility as a loop.
Read the pageForty operational audit points to measure your site's LLM legibility, prioritise corrective actions and track progress.
Read the pageConcrete applications in B2B SaaS, e-commerce, media and professional services. Differentiated priorities by profile and sector.
Read the pageSemantic structure, clean HTML, self-contained passages, accessibility. What the machine can extract without friction.
Entities, disambiguation, topical authority. What your brand means to an LLM and how it sits in its graph.
Crawl, rendering, schema.org, llms.txt, AI bots. The technical foundations of a site indexable by AI engines.
Measurement, monitoring, iteration. Realistic KPIs, citation tools, regular reporting. The loop closes here, and starts again.
Run your site through the LOOP audit checklist. Forty points organised by dimension, clear deliverables, built-in prioritisation. Measure before you optimise.
Open the checklist →Inspect product facts before and after JavaScript rendering. Separate visible prices, structured data and delivery evidence when diagnosing a stale offer
Audit multilingual product answers for market scope, currency and policy applicability. Keep language matching separate from commercial eligibility checks