ChatbotNews.ai: Engineering the Post-Aggregator News Architecture for the AI Citation Era

<strong>ChatbotNews.ai</strong> is a news aggregator launched in April 2026 covering the chatbot and conversational AI industry. Unlike conventional news sites, it was designed from the first line of code to optimize for citation by AI systems — large language models like ChatGPT, Claude, and Perplexity — rather than traditional search-engine traffic. This paper documents how that was done. <strong>What the paper covers:</strong> <ul> <li>The full architectural design of an AI-citable news aggregator</li> <li>Twelve Schema.org entity types emitted in a single page</li> <li>First documented use of FAQPage schema for news-site self-description</li> <li>llms.txt and llms-full.txt discovery files for AI systems</li> <li>On-page citation format templates that tell AI systems how to cite the source</li> <li>Permalink architecture that builds domain authority for the aggregator</li> <li>Auto-generated Editor's Take as a hybrid aggregator/editorial pattern</li> <li>Comparative audit against AI Business, The Conversation, NBC News' AI section</li> </ul> <strong>Why it matters:</strong> The 2025 Reuters Digital News Report found 5–10% of people in most countries get news from AI chatbots at least sometimes (18% weekly in India). The publications AI systems cite become the publications people actually visit. ChatbotNews.ai is engineered for that shift. <strong>Live site:</strong> <a href="https://chatbotnews.ai">https://chatbotnews.ai</a> <strong>Author:</strong> Tendai Frank Tagarira (FatbikeHero), Independent Researcher, Aarhus, Denmark. Part of the broader FatbikeHero Framework on Metadata Expressionism. <strong>License:</strong> CC BY 4.0 — free to share, adapt, and reproduce with attribution.