LLMS.TXT REVIEW

Suggestions for Improving Warren Laine-Naida’s LLMS.txt

After publishing my article about how websites become visible in AI search systems, Warren asked me for feedback on his own llms.txt file. Below are my observations and improvement suggestions.

Why I Looked at This File

My interest in this topic comes from my article about how websites can become visible in AI-driven systems like ChatGPT, Gemini, or Perplexity. When Warren asked for feedback, I reviewed his llms.txt from the perspective of structure, clarity, and machine readability.

The good news is that the file already has a strong structure. My suggestions focus mainly on improving clarity and prioritization for LLM systems.

Short version: The foundation is good. A few structural improvements could make the file even clearer for AI systems.

Key Suggestions

  1. Remove YAML front matter
    The title, slug and date fields at the top are not part of the llms.txt concept and could confuse parsers.
  2. Expand the summary
    A short description of Warren's services would help models understand the context of the file faster.
  3. Add short descriptions to links
    Short explanations help models interpret relevance and context.
  4. Curate instead of collecting
    Long lists of blog posts could move into an optional section.
  5. Fix encoding artifacts
    Some characters suggest a UTF-8 encoding issue.
  6. Consider Markdown versions
    Clean Markdown versions of key pages can be easier for LLM systems to process.

Overall Impression

Warren's llms.txt already provides a solid foundation. The suggestions above focus on improving structure, readability and prioritization so that AI systems can interpret the content more efficiently.