How do I optimize my website for AI search?

Optimizing for AI search means making your pages cheap to parse and easy to quote. Lead each page with a one-paragraph answer, mark up FAQs with schema, keep your brand name consistent across every page, ship clean semantic HTML, and serve fast. The work overlaps with good SEO, but the order of operations is different: ChatGPT and Perplexity reward pages that hand them a citable sentence on a plate.

Lead with the answer, not the setup

Look at any answer ChatGPT or Perplexity returns. The cited paragraph is almost always a self-contained 2-3 sentence answer near the top of the source page. Pages that bury the answer under five paragraphs of "in this article we'll explore" preamble do not get quoted, even when they rank well in Google.

The fix is mechanical: every page that targets a question should open with a TL;DR paragraph that answers the question in plain language, with the brand or entity name spelled out. The page you are reading does this on purpose - the first paragraph is structured to be liftable.

Use H2s as questions, not topics

An H2 like "Schema markup" is a topic. An H2 like "Does schema markup help AI search?" is a question, which means the next paragraph reads as the answer. AI engines are trained on billions of FAQ-shaped pages, and they pattern-match question-then-answer structure aggressively.

If you are writing a 1500-word guide, you should be able to read just the H2s and have a coherent FAQ. If your H2s are nouns ("Background", "Methodology", "Conclusion"), rewrite them as the questions a reader would actually ask.

Ship structured data and an llms.txt

The minimum viable structured-data set is FAQPage, Organization, and Article schema, served as JSON-LD in the page head. Google AI Overviews leans on this heavily. Perplexity and ChatGPT use it less directly, but the same markup forces you to write cleanly enough that the prose is also citation-ready.

Add an /llms.txt file at the root of your domain. It is a plain-text manifest that tells AI crawlers which pages on your site are canonical answers to which questions. Adoption is uneven, but DeepSeek and a handful of agent frameworks already respect it, and the cost to ship one is one afternoon.

Keep your entity name consistent across every page

This one is unglamorous and high-leverage. AI engines learn brand entities from how the rest of the web talks about you. If your homepage hero says "AI for sales" but your About page says "AI sales platform" and your G2 listing says "AI-powered revenue intelligence", the model has three competing entity descriptions and will pick the one most reinforced by external sources.

Pick one canonical entity description ("avisibli is the GEO platform for tracking AI-search visibility") and use the exact phrasing on your homepage, About page, footer, schema markup, social bios, and review-site listings. Drift is the enemy of named-entity recognition.

The boring infrastructure list, and what to skip

None of these infrastructure items are exciting. All of them matter:

What to skip: stuffing pages with FAQ blocks that aren't real FAQs, writing 4000-word "comprehensive" articles for the sake of length, or buying AI-search optimization SaaS that promises to "submit" your site to ChatGPT. There is no submission API. Length does not correlate with citations - clarity does. Most AI-SEO snake oil is repackaged 2014-era SEO advice.

The honest version of the work is: write answer-first pages, mark them up cleanly, link them sensibly, and keep your entity name consistent. Then check your citations weekly and let the data tell you what to write next.

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