https://page2pod.com - Agentic commerce, llms.txt, and markdown for AI: Yoast principal SEO Alex Moss explains how brands get selected by AI agents — not just clicked.
Alex Moss, principal SEO at Yoast and co-founder of FireCask, joins Jon Clark and Joe DeVita to unpack what it takes to be chosen by an AI agent: concise, quotable content, clear entity relationships, structured data, and a single machine-readable source of truth on your own domain. He calls the discipline "token optimization" — making information load faster for models the way Core Web Vitals made pages load faster for people.
Alex also breaks down the standards war behind Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) — llms.txt, agents.md, Google's UCP and OKF, OpenAI's ACP — and why the tech for agentic commerce is ready even if consumers aren't. His advice is refreshingly practical: experiment, follow the engineers building these systems, and adopt one standard at a time.
🤖 In This Episode
- How Yoast decides which SEO defaults ship on — and why schema stays gated behind an API
- Why markdown beats HTML for LLM ingestion (an 80% token reduction on one real example)
- What does it actually mean to be "selected" by an AI agent instead of clicked?
- Is llms.txt worth adopting now? Alex's insurance-policy framework for unproven standards
- The Walmart–ChatGPT experiment and Alex's timeline for real agentic commerce adoption
- AI information pages, entity maps, and building a source of truth machines can trust
- The team you'd hire to launch an agentic-commerce-ready eCommerce brand today
Whether you're placing bets on llms.txt or ignoring the acronyms entirely, this conversation gives you a working framework for which AI-search standards deserve your time.
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💬 Would you buy anything through a ChatGPT session today — and what's the biggest purchase you'd trust an AI agent with? Tell us in the comments.
Guest links:
Sponsored by Moving Traffic Media → https://www.movingtrafficmedia.com
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