AI Communication Library
Browse by Topic
- AI Communication Standards The technical standards, file formats, and protocols that allow websites and AI systems to communicate structured information.
- Knowledge Graphs for AI A knowledge graph connects named things to the relationships between them. That helps AI understand how the facts fit together. Start by naming the entities and connecting each fact to one canonical page.
- Agent-to-Agent Communication How autonomous AI agents exchange context, complete workflows, hand off tasks, and interact with tools and other agents.
- Dataset Publishing How businesses can publish structured information that AI systems can understand, cite, retrieve, and reuse.
- AI Infrastructure Vector search, retrieval systems, semantic indexing, embeddings, RAG, and the engineering behind AI visibility.
- AI Communication FAQ Frequently asked questions about AI communication standards, machine-readable websites, schema markup, and AI visibility.
Featured Articles
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What Is AI-to-AI Communication?
AI-to-AI communication is the exchange of information between AI systems and the websites, tools, data sources, or agents they use.
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What Is an AI-Ready Website?
An AI-ready website is structured so that AI systems can discover, read, interpret, and cite it accurately ... without relying on inference or guesswork.
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llms.txt vs llm.json: What Each File Actually Does
llms.txt gives AI a readable guide to a website. llm.json gives software a structured summary that code can check and reuse.
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What Is an AI Sitemap?
An AI sitemap is a site-defined JSON index that explains what a website contains and how its main resources connect. It can help an AI agent find useful information, but it does not replace sitemap.xml or guarantee retrieval.
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How Schema Markup Helps AI Understand a Website
Schema markup is structured data that tells AI systems exactly what each page is, who created it, and how it relates to real-world entities ... removing the need for inference.
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Knowledge Graphs for Website Owners
A knowledge graph is a structured map of entities and the relationships between them. For websites, it is the architecture that makes AI systems understand context, not just content.