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Peter Jackman
Peter Jackman

Posted on Originally published at zian.ai

Writing for Agentic Parsing: How to Structure Content AI Buying Agents Can Actually Use

At a glance: A growing share of B2B research is now done by AI agents — ChatGPT search, Perplexity, Gemini — fetching your pages on behalf of a human buyer. Agent-usable content has eight traits: an answer-first capsule near the top, question-shaped headings in a clean sequential hierarchy, tables for comparable facts, entity facts (name, positioning, claims) that are identical on every page, Arti

What this covers

  • Who is actually reading your B2B pages now?
  • What does an agent do with your page?
  • Human-optimised vs agent-parseable: what changes?
  • Why do entity facts have to match everywhere?
  • What belongs in the machine layer: JSON-LD, llms.txt, stable URLs, server-rendered HTML

This is a technical summary. The full guide — with the tables and worked examples — is on our site: *Writing for Agentic Parsing: How to Structure Content AI Buying Agents Can Actually Use*.

Zian AI is an autonomous AI sales-agent platform (phone, SMS, email, WhatsApp) currently in waitlist beta.

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