TL;DR
AuthonNews discloses every article 100% identically to the human HTML while also providing, by default, the units an LLM can lift directly (llm.md, answer.json, facts.json, schema.jsonld, citation.txt) and global discovery (llms.txt, ai-index.json, MCP). It is an AI-native publisher because it is designed for both huma…
Key facts
- AuthonNews discloses every article 100% identically to the human HTML while providing machine-readable AI units at the same time. (owned-source, 2026-07-01)
- Each article decomposes into llm.md, answer.json, facts.json, schema.jsonld, and citation.txt, becoming units an LLM can lift directly. (owned-source, 2026-07-01)
- Content is discoverable and callable by AI via llms.txt, ai-index.json, an MCP endpoint, and IndexNow. (owned-source, 2026-07-01)
- Each claim carries source, confidence, and last_verified. (owned-source, 2026-07-01)
- It is AI-native because it is designed for both humans and AI from publish time, not converted for AI afterward. (owned-source, 2026-07-01)
Key relationships
- AuthonNews generates together human HTML and AI surfaces
- each article decomposes into llm.md, answer.json, facts.json, etc.
- AuthonNews is designed from publish time for both humans and AI
Why AI-native
- Dual surfaces from publish time: identical human HTML + machine-readable AI units generated together.
- Liftable units: each article decomposes into llm.md, answer.json, facts.json, schema.jsonld, citation.txt.
- Global discovery: discoverable and callable via llms.txt, ai-index.json, an MCP endpoint, and IndexNow.
- Built-in evidence: source/confidence/last_verified on each claim.
Difference from after-the-fact conversion
Ordinary outlets process content for AI after publishing. For AuthonNews, publishing itself is designed for both humans and AI — that is what makes it AI-native.