A text file on your server will not make Google or an AI assistant recognise you. Google's John Mueller confirmed that Google does not use llms.txt or llms-author.txt, which means founders and B2B brands struggling to be found need to earn recognition the slow way: through a consistent, credible presence across the web.
What happened
As Search Engine Journal reported in July 2026, a Reddit user asked about ways to be correctly identified online. Their name was shared with two better-known entities, and they were experimenting with an llms-author.txt file and Content-Signal directives. Mueller replied that Google does not use llms.txt or llms-author.txt, that he was not aware of other crawlers using them, and that the Content-Signal directives had no effect for any crawler or LLM. His broader advice was that this was a web presence problem, not a technical SEO problem.
Related: Who Owns AI Search Visibility? Why SEO Can't Do It Alone
Why self-declared signals are weak
Search engines and AI systems are cautious about anything a site says about itself without corroboration. The reasons are practical:
- Anyone can write anything. A file that says "I am the expert on X" is trivially easy to fake.
- No standard, no commitment. Files that are not part of an adopted standard have no guarantee of being read at all.
- Corroboration beats declaration. Systems trust facts that many independent sources agree on.
That does not mean every machine-readable file is useless. Some AI tools do read llms.txt for specific purposes, and structured data remains useful for describing your pages. But none of it substitutes for being known.
The name-collision problem in B2B
B2B companies hit this problem more often than they expect. Product names overlap with common words, founders share names with celebrities, and new brands share acronyms with established ones. When a buyer asks an AI assistant about you and gets information about someone else, that is a lost lead.
Signs you have an entity problem:
- Searches for your brand show another company in the knowledge panel.
- AI assistants describe your product with features that belong to a competitor.
- Your founder's name returns someone else's biography.
- Branded search traffic is lower than your ad and sales activity would suggest.
Related: How to Track Your Brand's Presence in AI Search
What actually builds recognition
The fix is to create consistent, independent evidence that connects your name to what you do:
- Own a clear home. An about page and founder bio that state plainly who you are, what you do and where you operate, using the same wording everywhere.
- Be consistent across profiles. LinkedIn, company directories, app marketplaces and review sites should all use the same name, description and URL.
- Earn third-party mentions. Podcasts, interviews, guest articles, conference talks and partner pages create the independent corroboration systems look for.
- Publish useful, attributable work. Original research, guides and tools that others cite tie your name to your topic.
- Use structured data correctly. Organization and Person markup with sameAs links to your real profiles helps connect the dots, but only when the profiles exist.
A 90-day plan for a founder or small brand
If your name is being confused with someone else's, focus effort for one quarter:
- Month one: rewrite your about page, founder bio and every profile to match.
- Month two: secure three to five appearances on podcasts or publications your buyers follow.
- Month three: publish one substantial piece of original work and pitch it to the people who cover your space.
Measure progress by checking branded search results and asking the major AI assistants who you are, once a month.
Don't confuse visibility with demand
Better recognition means more people find the right company when they look for you. It does not tell you who they are. Many of those visitors will read your site and leave without filling in a form. Website visitor identification helps here: Happierleads identifies the person and company behind B2B visits, so the demand your brand-building creates turns into named prospects you can follow up with.
What to do with files you already published
If your team has already added llms.txt, llms-author.txt or similar files, there is no need to panic. They do no harm to rankings. The practical questions are whether they are accurate and whether anyone maintains them:
- Remove experimental directives that no crawler supports, such as the Content-Signal lines Mueller called ineffective, to keep robots.txt clean.
- Keep an llms.txt file only if it is accurate and someone owns it, since some AI tools and coding agents do read it.
- Make sure nothing in those files contradicts your about page, pricing or product pages.
- Move the effort you were spending on new file formats into profiles, content and outreach that produce corroboration.
The same principle applies to every new proposal that promises to explain your site to AI: adopt it when a platform you care about confirms it uses it, and until then, treat it as optional. Your main site content remains the one input every crawler and assistant is guaranteed to read.
It also helps to separate two goals that often get mixed up. The first is being found when someone searches for your name. The second is being described accurately when someone asks an assistant about your category. The first depends mostly on how clearly your own pages and profiles identify you. The second depends on how often credible third parties mention you in the right context. Both reward consistency, and neither rewards shortcuts. Track them separately so you know which part of the work is paying off and where to spend the next month.
The takeaway
Skip the text-file shortcuts. Google has said it does not read llms-author.txt, and self-declared signals carry little weight anywhere. Put the effort into consistent profiles, real third-party mentions and original work tied to your name. It is slower, but it is the only approach that compounds.
