llms.txt explained.
A robots.txt for the answer engines. Adoption is uneven, the spec is in flux, and an hour spent on it pays back inside a quarter.
llms.txt is a proposed convention, akin to robots.txt, for telling LLM-powered crawlers which pages on a site are canonical sources, which are duplicates, and which to skip. Adoption inside the major engines is uneven in 2026, but the cost of shipping one is small and the upside is real: a clean llms.txt that points the answer engines at primary-source pages, like our case studies and our reports, materially improves citation quality. Our own llms.txt is the worked example, and the longform with the per-section template ships in June 2026.
Coming online in 2026. The roadmap below is committed, the writing is queued.
Related reading
- 01
What is GEO.
A working definition. The patterns the answer engines actually weight.
- 02
How to rank in ChatGPT.
What the SearchGPT crawler weights and where llms.txt fits.
- 03
How to rank in Perplexity.
Why Perplexity behaves more like classical search.