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About this glossary

RAG (Retrieval Augmented Generation) – Glossary

RAG is an AI technique where a model retrieves relevant source content, then uses it to generate an answer. This grounds responses in verifiable material and reduces hallucinations.

It pairs semantic retrieval with generation, so answers point to credible sources.

Examples

  • Hotel policy page: A “Cancellation policy” page with a question heading and a short answer near the top, the AI retrieves the exact policy lines, then cites the hotel’s page as the source.
  • Product specs: A comparison page with a specs table and concise summaries per model, the AI pulls the key dimensions and materials, assembles a side-by-side answer, and cites the product pages.
  • Local services: A “Services and hours” page with structured data and clear sections, the AI extracts the service list and today’s hours, then credits the business site.
  • How to article: A tutorial with steps and a short “Quick answer” block up top, the AI composes a one paragraph instruction and points back to the tutorial for details.

These patterns help AI retrieve precise sections, generate accurate summaries, and credit your site.

Further reading

Guide

AI features and your website, Google Search Central

Describes query fan-out and grounding with supporting pages, useful context for retrieval behavior in Search.

https://developers.google.com/search/docs/appearance/ai-features

Guide

Top ways to ensure your content performs well in Google’s AI experiences on Search, Google Search Central

Practical tactics to help content perform in AI experiences on Search.

https://developers.google.com/search/blog/2025/05/succeeding-in-ai-search

Docs

Local business (LocalBusiness) structured data, Google Search Central

Guidelines for LocalBusiness schema to improve retrieval and presentation.

https://developers.google.com/search/docs/appearance/structured-data/local-business

Video

Webinar: SEO for LLMs, adapting to the AI‑first web, Sitebulb

Content strategy for LLMs, technical accessibility and controls, citation tracking and AI referrals.

https://sitebulb.com/resources/guides/webinar-seo-for-llms-adapting-to-the-ai-first-web/

Guide

LLM optimization checklist, Link‑Assistant

AEO tactics, entity consistency, schema alignment, prompt‑like formats, citation tracking to boost inclusion in AI answers.

https://www.link-assistant.com/news/seo-checklist.html#LLM-optimization-checklist71

Related terms

Source attribution

Source attribution means links or citations included by AI answers to credit original pages. This builds trust and dr...

Structured data

Schema markup, often Organization, LocalBusiness, and FAQPage, that helps machines parse content.

Entities

Entities are clearly defined people, places, brands, or services that search engines recognize in their knowledge gra...

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About this glossary

I’m building this glossary to become a better developer and website strategist, in my ongoing quest to build clearer, better websites. It maps how terms relate, adds practical examples, and highlights best practices so I can communicate more clearly with clients. If it helps others too, great.

It’s a living resource, I aim to cite sources clearly. If you spot errors or omissions, please contact me so I can update it. Drafts may be assisted by AI, I review and fact check before publishing. For details on how I use AI, see AI Use at Webmarks.