Technical fixes to help AI find and use your content
May 29, 2025
Triin Uustalu
If you want your content to be found by AI tools like ChatGPT, Gemini or Perplexity, it’s not enough to write well. You also need to build well. LLMs don’t rank pages—they reuse structured chunks. To show up in AI search results, your content must be readable, retrievable, and trustworthy at the code level. These aren’t hacks. Their infrastructure. And they’re quickly becoming table stakes.
Machines don’t see your site—they interpret it
A human reader might appreciate your design, layout, and branding. A language model sees your <html> and asks: Where is the useful content?
When LLMs scan a page—either through browsing, APIs, or structured datasets—they look for clean, fast-loading, semantically organised blocks of information. If your site is cluttered with scripts, overloaded with CSS, or hides key details behind interactions, you’re at risk of being ignored.
Crawlers from tools like ChatGPT’s browsing plugin or Perplexity’s sourcing engine don’t behave like Googlebot. They have short timeouts, limited context windows, and no tolerance for ambiguity. You have seconds to make your content extractable.
Fix 1: Semantic HTML is your baseline
If your content is wrapped in the right tags, models can quickly identify what’s relevant. That starts with semantic HTML.
- Use
<article>or<main>to group meaningful content. - Headings should be nested logically:
<h1>for the title, followed by<h2>,<h3>as needed. - Break content into clearly sectioned paragraphs, ideally using
<section>where appropriate.
This isn’t about SEO trickery. It’s about legibility. A model needs to recognise where one idea ends and another begins. When that’s hard to parse, your content risks being skipped entirely.
We break this down further in The rise of AI search: from pages to paragraphs.
Fix 2: Answer-first formatting
Language models don't read your page from start to finish. They skim. They summarise. If you bury your insight halfway down the page, you’ll be overlooked.
Lead with value. If your article answers a question, make that answer clear in the opening lines. Then use the rest of the section to explain, expand, and contextualise. This formatting doesn’t just help machines—it improves usability for humans too.
AI models tend to favour content that reads like FAQs or explainers: short declarative blocks, front-loaded with relevance, cleanly structured with subheadings.
Fix 3: Add schema markup (with restraint)
Structured data helps models interpret your intent. Marking your content with schema.org elements like FAQPage, Article, or HowTo gives LLMs cues on how to classify and summarise what you’ve written.
But don’t over-mark or misapply. Only use schema types that reflect what’s actually on the page. If you add FAQPage to a sales pitch, you’re likely to get penalised by search engines—and ignored by LLMs.
Used properly, schema becomes a contract: Here’s what this content is about. Feel free to summarise it.
You can find examples of this in SEO is evolving—AIO is what’s next.
Fix 4: Prioritise crawl performance
Most LLM crawlers operate on tight deadlines. Some will give your page 2–3 seconds before deciding whether to move on. That means your content needs to be available fast and visible immediately.
To help:
- Avoid heavy client-side JavaScript rendering
- Don’t hide key content behind expandable menus or scroll triggers
- Use clean HTML instead of overly styled templates
Also, consider adding a llms.txt file to your domain. It’s an emerging convention, similar to robots.txt, that signals which pages are intended for AI indexing. This file isn’t yet standardised, but it’s already being adopted by a handful of forward-looking platforms.
Fix 5: Make trust explicit
AI models infer credibility from signals. Some are content-based: clarity, accuracy, citation. Others are structural—author attribution, publish date, and external references.
Pages with real authors, visible timestamps, and outbound links to credible sources are far more likely to be quoted. Not just because they appear more trustworthy, but because they’re easier to validate during summarisation.
This also helps differentiate your content from the growing flood of auto-generated fluff. If a model sees clear provenance and fresh data, it’s more likely to choose your paragraph as the answer.
Making your website LLM-friendly doesn’t require a rebuild. But it does require a rethink.
Visibility in AI search now depends on how your site communicates—not just to people, but to systems that are deciding what people see. That’s not just a content problem. It’s a structural one.
At Glafos, we help teams build content that’s readable by people and usable by machines. If you’re ready to make your site part of the answer, join the beta. Because being findable in the age of AI starts long before anyone hits “search.”
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