The Short Answer
To get found by AI search engines, ensure your content is indexed by Bing and Google, structure it in clear chunks of 75-225 words, provide direct answers to questions, and use schema markup. AI search engines don't crawl the web directly—they pull from existing search indexes and process the content through language models.
How AI Search Engines Work
AI-powered search engines like ChatGPT, Perplexity, and Claude work differently than traditional search. When you ask a question, they retrieve relevant content from search indexes (ChatGPT uses Bing, Perplexity uses its own crawler plus Google), then synthesize an answer using that content as context.
This means two things matter: First, your content must be in the search index. If Bing hasn't crawled your site, ChatGPT will never see it. Second, your content must be structured in a way that LLMs can easily extract and cite. Dense paragraphs and buried information get overlooked.
The Technical Foundation
1. Allow AI Crawlers
Your robots.txt file controls which bots can access your site. Make sure you're not blocking AI crawlers. The key user agents to allow are: GPTBot (OpenAI), ClaudeBot (Anthropic), PerplexityBot, and Google-Extended. A simple "User-agent: * Allow: /" permits all crawlers.
2. Create an XML Sitemap
Submit an XML sitemap to Bing Webmaster Tools and Google Search Console. This helps search engines discover all your pages quickly. For AI search visibility, being in Bing's index is especially important since ChatGPT relies on it.
3. Implement llms.txt
The llms.txt file is an emerging standard that provides AI systems with a curated map of your most important content. Place it at your domain root (example.com/llms.txt) with links to your key pages. Think of it as a sitemap designed specifically for language models.
4. Add Schema Markup
JSON-LD structured data helps AI systems understand your content's context. Use Article schema for blog posts, FAQ schema for Q&A content, and HowTo schema for tutorials. This markup signals what type of content you're providing and makes it easier for LLMs to extract relevant information.
Content Structure for LLM Visibility
LLMs process content in chunks. Research suggests optimal chunk sizes of 75-225 words—long enough to contain complete ideas but short enough to be easily processed. Structure your content accordingly:
- Lead with the answer. Put your main point in the first sentence or paragraph. LLMs often cite the most direct, clear statement they find.
- Use the Short Answer + Deep Dive format. Start with a concise answer, then expand with details. This mirrors how AI search presents information.
- Create clear sections. Use descriptive headings (H2, H3) that signal what each section covers. LLMs use these to navigate content.
- Keep paragraphs focused. One idea per paragraph. Dense, multi-topic paragraphs are harder for LLMs to parse and cite accurately.
Frequently Asked Questions
How do AI search engines find content?
AI search engines like ChatGPT use Bing's index, while Perplexity maintains its own crawler. They pull content from traditional search indexes and process it through large language models to generate answers. If your content isn't indexed by Bing or Google, it won't appear in AI search results.
What is llms.txt?
llms.txt is an emerging standard that helps AI systems understand your website's key content. Similar to robots.txt but designed for LLMs, it provides a curated map of your most important pages in a format that's easy for language models to process.
How should I structure content for AI search?
Use a Short Answer + Deep Dive format: Start with a clear, direct answer in 1-2 sentences, then provide detailed explanation. Keep paragraphs to 75-225 words (chunked for LLM processing). Use clear headings and include structured data markup.