What Is AI Discovery Readiness?
A practical definition of AI discovery readiness: crawler access, retrievable content, clear business information, evidence, and honest limits.
Concept library
Understand the foundations of AI discovery readiness
Definitions and decision frameworks for crawler access, initial HTML, business clarity, evidence, and the limits of automated testing.
AI discovery foundations
Start with the core ideas behind discoverability, readiness, and answer engine optimization.
What Is AI Discovery?
AI discovery is the process through which search engines, answer systems, and agents find, retrieve, interpret, cite, and use information from websites.
What Is Answer Engine Optimization (AEO)?
Answer Engine Optimization helps make website information accessible, understandable, verifiable, and useful to search engines and AI answer systems.
How systems interpret websites
Understand retrieval, website signals, entities, and how sources can become useful in generated answers.
What Makes a Website Understandable to AI?
How retrieval, initial HTML, semantic structure, entity clarity, evidence, and consistent metadata make a website easier to interpret.
What Is an AI Citation?
An AI citation is a visible source reference attached to a generated answer, but citation is only one stage between discovery and business impact.
What Is Retrieval-Augmented Generation?
Retrieval-augmented generation combines a language model with external documents selected at answer time, helping systems use fresher, more specific, and attributable information.
Crawler access and policy
Separate search-discovery crawlers, training crawlers, and the controls that apply to each purpose.
AI Search Crawlers vs Training Crawlers
Why AI search, model training, user-triggered retrieval, and data-use controls are separate website-policy decisions.