LLMs.txt: Guiding AI Models to Your Website’s Best Content
The article delves into llms.txt, a proposed plain-text file designed to instruct AI models on which website pages to prioritize during crawling, processing, and citation. Despite a lack of official adoption by major AI platforms, including Google, some site owners are implementing it, anticipating a future where AI becomes a primary traffic source, akin to the evolution of robots.txt.
LLMs.txt serves a distinct purpose from robots.txt; while the latter controls crawler access, llms.txt merely suggests priority pages to AI, offering a curated, human-readable markdown list. This aims to present AI systems with a clean, structured view of a site's most valuable content, free from typical web page clutter. Examples like Yoast SEO, BX3 Interactive, and Hugging Face showcase varied complexities, from simple page listings to intricate documentation with code snippets. Notably, Anthropic, the company behind Claude, also maintains an llms.txt file, hinting at potential future relevance.
Potential benefits include enhanced control over AI citations, simplified content parsing for AI, improved AI performance, and quicker site analysis. However, significant limitations exist: no major AI platforms officially support it, it's a suggestion rather than a rule, it's vulnerable to “keyword stuffing” for AI, and it could expose valuable site structure to competitors.
Creating an llms.txt file involves selecting high-priority pages, formatting them in markdown (potentially using AI or generators), uploading it to the site's root directory, and regularly updating it. The article concludes that while it's a low-risk experiment that might offer a future advantage, it shouldn't overshadow established SEO fundamentals.
(Source: https://backlinko.com/llms-txt)
