Google’s Mueller: LLM-Only Markdown Pages Unnecessary
▼ Summary
– Google’s John Mueller opposes creating separate Markdown or JSON pages for LLMs, stating they can parse standard HTML effectively.
– Mueller argues that if specific file formats improved LLM performance, AI companies would openly recommend them.
– He acknowledges some pages work better for AI systems but attributes this to content quality rather than file format.
– The discussion highlights that structured data formats like JSON are only necessary when explicitly required by platforms like OpenAI.
– The key takeaway is to focus on improving existing HTML content and implementing schema where platforms provide clear guidance.
Google’s Search Advocate John Mueller has clarified that creating separate Markdown or JSON pages specifically for large language models is unnecessary, emphasizing that LLMs are fully capable of parsing standard HTML web pages. This perspective offers valuable guidance for webmasters and SEO professionals navigating the evolving relationship between content creation and AI systems.
The discussion originated when Lily Ray raised a question on Bluesky regarding the growing practice of developing distinct markdown or JSON pages intended solely for LLMs, inquiring whether Google had an official stance on the matter. Ray highlighted that this topic has gained significant traction, with companies actively promoting such services.
In his response, Mueller expressed skepticism about the need for this approach. He pointed out that from the very beginning, large language models have been trained on and have processed conventional web pages. He questioned the logic behind presenting LLMs with content formats that are invisible to human visitors, adding that if equivalence between formats is a concern, HTML remains the logical choice.
When Ray probed further, suggesting that alternative formats might help convey key information more efficiently to AI systems, Mueller countered that if file types genuinely enhanced performance, the companies operating these AI platforms would likely be the first to advocate for them. He remarked that AI firms are not typically reserved about sharing technical requirements that could improve their systems.
Mueller acknowledged that certain pages might perform better with AI than others, but he attributed this more to content quality and structure rather than the underlying file format. He specifically mentioned that complex JavaScript can still pose challenges for many AI systems, but overall, the distinction between HTML and Markdown is not a decisive factor.
These comments collectively suggest that, according to Google’s view, web publishers do not need to invest in creating duplicate “shadow” content in specialized formats just to accommodate LLMs.
The conversation also touched upon the role of structured data, drawing a clear distinction between speculative format changes and situations where AI platforms provide explicit specifications. For instance, Matt Wright referenced OpenAI’s eCommerce product feeds, which utilize defined JSON schemas. This demonstrates that structured data becomes crucial when a platform formally requests a specific format, such as in the case of product listings designed for integration with tools like ChatGPT.
Chris Long further noted on LinkedIn that editorial websites implementing product schemas frequently appear in ChatGPT citations, reinforcing the value of structured data where clear guidelines exist.
For anyone considering whether to develop “LLM-optimized” content in Markdown or JSON, this discussion serves as a reminder to focus on foundational best practices. Mueller’s insights confirm that LLMs are well-equipped to handle standard HTML. Rather than creating separate content streams, webmasters are better served by enhancing page speed, improving readability, and refining content architecture on their existing sites, while implementing schema markup in line with platform-specific documentation.
The Bluesky thread illustrates that while AI-specific formats are emerging in niche applications like product data feeds, these are tied to particular integrations and do not represent a universal rule that markdown outperforms HTML for LLMs.
This exchange underscores how rapidly advancements in AI-driven search are translating into technical demands for SEO and development teams, often in the absence of comprehensive official documentation. Until LLM providers issue more detailed guidelines, the practical takeaway is to concentrate on justifiable improvements: maintaining clean HTML, minimizing obstructive JavaScript, and adopting structured data only where platforms have clearly outlined its use.
(Source: Search Engine Journal)
