AI search engines are rewriting the rules of SEO.
ChatGPT, Perplexity, and AI Overviews don't rank pages — they read them. Here's what changed, what still matters, and how to structure your blog so machines quote you instead of a competitor.
From keyword stuffing to semantic relevance
Search used to be a matching problem — pages that contained the most phrases won. AI search is a comprehension problem. The winner is the page the model can understand and trust.
Semantic relevance
AI systems reward clear meaning over keyword density. The days of stuffing a page with exact-match phrases are over.
Clean document structure
A logical hierarchy — one H1, ordered H2s, short scannable paragraphs — is how an AI engine reads your page.
Factual accuracy
Answers are synthesized from sources the model trusts. Precise, verifiable statements get cited; hype gets ignored.
Structured data
Schema markup gives machines an explicit map of your content — what it is, who wrote it, when it was published.
Structure your article for machines
How you format a post is now part of its SEO. Rich blocks give AI systems discrete, quotable units of meaning — the difference between being summarized and being skipped.
Pull quotes
A standout claim rendered as a quote is easier for a model to isolate and attribute than a sentence buried in a wall of text.
Callout boxes
Key takeaways in a visually distinct block become the 'TL;DR' an AI assistant repeats when summarizing your article.
Tables & lists
Comparison tables and ordered lists are parsed into structured answers far more reliably than prose paragraphs.
Media captions
Captioned images, videos and embeds add context and factual grounding — signals models look for when deciding what to cite.
AI-ready by default, not by accident
Makr was built static-first. Every article you publish is clean, semantic HTML — exactly the structure AI crawlers love — without a single line of configuration. Follow our guide on how to write a blog post to structure your drafts for maximum citation value.
Write
Draft in plain markdown. Makr keeps your words the single source of truth — no lock-in, no proprietary blocks.
Structure
Makr's engine transforms raw text into semantic, rich HTML: correct heading hierarchy, schema, and readable typography.
Publish
Your article ships as pure static HTML on a global CDN — fast, crawlable, and perfectly structured for AI readers.
Quick answers
It's the practice of structuring a website so AI assistants and AI-powered search engines (like ChatGPT, Perplexity, and Google AI Overviews) can read, summarize, and cite it accurately. That means semantic HTML, clear hierarchy, structured data, and factual, scannable content.
No — but it's changing. Traditional ranking signals like backlinks and page speed still matter. What's new is that AI systems now synthesize answers from your content, so clarity and structure have become as important as keyword targeting.
Models favor sources with clean document structure, machine-readable metadata, and precise, well-organized information. A page that is easy for a machine to parse — clear headings, short paragraphs, tables, quotes — is dramatically more likely to be cited than a dense, unstructured page.
Yes. Structured data like Article, BreadcrumbList, and FAQPage markup gives AI engines an explicit map of your content. Makr adds the right semantic structure automatically, so you don't need to write schema by hand.
Poorly, and unreliably. Many AI crawlers don't execute JavaScript, so client-rendered content can be invisible to them. Static HTML — what Makr publishes — is readable by every crawler, always.
Makr enforces semantic HTML, generates clean heading hierarchy, and structures every article with rich blocks and machine-readable markup. The result is a page that loads instantly and reads beautifully to both humans and AI.