How to prepare your blog and RSS feed for AI Search?

RSS is back in favor, this time with AI algorithms in mind. Why? To understand this, we need to refer to the definition of RSS. It is a simplified data format based on XML tags, used, among other things, for the simple processing of articles on websites, making them easier to subscribe to and obtain up-to-date data. It is a kind of “data channel” that provides articles in clean, structured data, with minimal noise (no ads or layout elements).

What does this mean for AI accessibility? Models prefer sources that don’t require too much computing power to understand the content’s context. A well-defined feed makes it easy to aggregate and update such articles – this can be your advantage! RSS delivers content in a consistent, straightforward layout, without unnecessary elements, which improves AI bots’ page processing and makes it easier to extract data from your content.

We’ll talk more about RSS in the context of a blog in a moment, but first, let’s start with the basics. Before you implement an RSS system, ensure the technical elements of your website are in order. Extensive content and nice graphics are not enough if your website’s code is a mess. Remember that bots, both Google and AI tools, do not see a website the way a human does – they look at it based on the code and search for a logical structure and markings for the most critical elements. What should you pay attention to?

• Use semantic HTML5. Clearly mark sections such as <header>, <footer>, <article>, <section>, and <author> in the code. AI models use these tags first to extract relevant units.
• Ensure clean canonical links and meta tags conform to the Open Graph standard, e.g., og:title, og:description, article:published_time. This structure will help AI identify the target page version, along with its title, meta description, and publication time. Simply including information about the publication date in the article is not enough – AI may not be able to extract it from the text.
• A schema is essential for LLM model bots to understand your website well. I have written a comprehensive guide on this topic, which I recommend reading: Structured data and AI Search – which schemas support visibility in AI responses? In the context of a blog, the most critical structured data will be Article, BlogPosting, Author, and Organization.

If RSS is to be used by AI models, don’t treat it as a tool for shortened versions of posts. Models will prefer a detailed feed with the entire content of the article, rather than just excerpts (previews), for example. What data should be included in the RSS feed for your blog?

• Correctly used MIME type, which informs bots what kind of file or data they are dealing with (e.g., application/rss+xml or application/atom+xml)
• Include parameters such as:
  • Dc:creator – designation of the author of the post
  • Content:encoded – this will be the full content of the article in HTML format
  • Updated – the date of the last update of the post
  • Category – helps AI bots understand the topic of the post to facilitate semantic content grouping

Thanks to these elements, AI can easily determine not only the article’s topic but also its context, source, date of creation, and links to other publications.

AI-based search engines and LLM models not only analyze the content itself, but also assess its freshness. AI algorithms are designed to provide the most likely answer possible. The timeliness of an article will therefore be an essential factor. If the article is new, AI believes it is more likely to contain accurate, up-to-date information. 

A regularly updated RSS feed will be a helpful signal that the blog is maintained systematically and worth quoting. Some tools, such as Perplexity, are sensitive to so-called temporal signals. This refers to information about when content was added or changed. The more such signals there are, the greater the chance that the AI model will use the page in its responses.

To enable bots to access such signals, it is worth introducing HTTP Last-Modified and ETag headers in RSS feeds. This will allow for better content caching and provide a signal of content freshness.

Finally, here are a few helpful tips from me, backed by my experience working on projects for various industries! Below are my top 5 technical tips to make AI models eager to use your blog as their source of information.

What to do to get regular mentions in AI Search?

• Keep your URLs consistent – frequent changes to permalinks, even if you handle redirects, are not recommended. Embeddings rely on stable addresses, so remember to be consistent across your entire website.
• Take care of internal linking – both Google and AI bots use internal linking to create so-called “context maps,” which make it easier for them to understand the thematic clusters on your blog and the entire site.
• Publish RSS in your sitemap, e.g., /sitemap.xml with a link to the feed.
• Take an API-first approach – treat RSS as a public API for your blog.
• Finally, one content tip – use clear language! Just like the RSS structure itself, your texts should be simple, readable, and clearly structured. Shorter sentences and bullet points will help LLM models understand the context.