Make your site readable by AI engines

A practical checklist for making a WordPress site readable to AI engines, covering schema, headings, crawlability, and the machine-readable layer.

A checklist for keeping AI engines able to read and find your pages through a site migration or redesign, so you do not go invisible the day you relaunch.

A step by step guide to adding Article schema to WordPress blog posts so AI engines can read who wrote what, when, and about what.

A step by step guide to adding author schema in WordPress so AI engines can read who wrote a page and what makes them credible.

A step by step way to add Breadcrumb schema so an AI engine understands where a page sits in your site and how your content is organized.

A step by step way to add FAQ schema to a WordPress page so an AI engine can read your questions and answers as facts, not as decorative text.

A step by step way to add HowTo schema to a procedure page so an AI engine reads your steps in order instead of guessing them from formatting.

A step by step way to add Organization schema so an AI engine reads who your business is, what it is called, and how to reach it as facts, not guesses.

A step by step way to add Product schema to a WordPress page so an AI engine reads your price, availability, and product name as facts instead of guessing from layout.

The current user-agent tokens for the major AI crawlers, how to allow or block each one in robots.txt, and the honest tradeoff of blocking, with every name sourced to the vendor's own documentation.

A dated user-agent reference table for the major AI crawlers with every name sourced to the vendor's own docs, the grep and awk commands to pull them out of an access log, and an honest read of what a crawl hit does and does not prove.

A step by step way to find and fix the crawlability problems that stop AI engines from reaching and reading your pages in the first place.

How to find and fix thin pages that AI engines cannot answer from, by adding the specifics and structure a machine needs to read and use the page.

How to keep your structured data valid and matching the page as you edit, with a watch and re-prove loop that catches the schema you quietly broke.

A step by step way to structure an About page so an AI engine can extract who your company is, who runs it, and how to reach it, instead of inferring from a brand story.

A step by step guide to making your homepage readable to AI engines, so a machine can tell what you do, who you serve, and why to recommend you.

A step by step way to structure and label your pricing page so an AI engine reads your plans and prices as facts instead of guessing from a styled table.

How to measure whether AI engines name and cite your pages, set a baseline across four engines, and re-prove it over time as content and engines drift.

A step by step guide to writing headings that AI engines can parse, so the right section of your page answers the right question.

Where AI assistant visits show up in Google Analytics 4 now that there is a native AI Assistants channel, how to break them down by source and landing page, and an honest account of what GA4 cannot see.

A step by step way to structure a page with clear headings, real text, and labeled meaning so an AI engine can extract a clean answer from it.

The small-merchant version: which of the three product-data paths you control, what OpenAI says about merchant ranking, and the catalog hygiene that decides it.

A step by step way to structure an ecommerce product page so an AI engine reads the price, availability, specs, and reviews as facts instead of guessing from a styled layout.

Location pages are the most abused pattern in local marketing, and Google names the abuse. How to state where you work so machines can use it, without clones.

A step by step guide to checking whether ChatGPT and other AI engines can actually fetch, parse, and understand a given page on your site.

A step by step guide to keeping Yoast and adding the machine-readable layer AI engines need, into one clean schema graph, without a collision.

The extractable-answer pattern: where the capsule goes, how long it runs, why one fact per sentence matters, and what a 15-domain Search Engine Land audit actually found about capsules and ChatGPT citations.

A step by step way to write an llms.txt file that points AI engines at the pages on your site that actually answer questions, and where to put it.

A step by step way to structure an X versus Y comparison page with named criteria, a real table, honest tradeoffs, and an FAQ, so an engine can extract the comparison instead of inferring it.

How to write and structure FAQ content so AI engines can read and lift a clean answer, with real questions, direct answers, and valid FAQ markup.

How to use internal links so AI engines can find and read your deeper pages, with a practical pattern for hubs, descriptive anchors, and orphan pages.

A step by step guide to keeping Rank Math and adding the machine-readable layer AI engines need, merged into one clean schema graph.

What a Shopify store owner can actually control for AI readiness through the theme, structured data, metafields and robots.txt.liquid, what Shopify holds and you do not, and where the honest platform limits are.

A dated, sourced account of the agent-readiness levers each platform exposes: the robots.txt Squarespace locks, the JSON-LD editor Wix ships, and more.

How to add structured data to a local business page so AI engines can read your name, location, hours, and services, and how to check whether it is present and correct.

How to mark up a service page so AI engines can read what the service is, who it is for, and what it costs, and how to check the markup matches the page.