Okay, I need to talk about llms.txt. If you haven't heard of it yet, congratulations — you've been living a blissfully unbothered life. For the rest of us who've been watching the AI optimisation space, llms.txt has been this year's must-have accessory. Every LinkedIn thought leader and their dog has been telling you to create one. It's a simple text file you drop onto your website that supposedly helps AI systems understand your content better.

Sounds great, right? Easy win? Just create a file and suddenly ChatGPT loves you?

Here's the thing. Google just had a very public disagreement with itself about whether this file matters — and the fallout tells us something much more important than the file itself.

In the space of a few days, two separate teams at Google published guidance that directly contradicted each other. Team One — Google's AI search team — told website owners they don't need llms.txt to appear in AI search results. Specifically named it as something you can stop worrying about. Team Two — the Chrome Lighthouse team (the people who build the tool that audits your website's performance) — shipped a new check that flags whether your site has an llms.txt file, noting that without one, AI agents might struggle to understand your site.

Same company. Same month. Completely opposite advice.

Naturally, the internet did what the internet does: panicked. Marketing forums lit up. LinkedIn went feral. Consultants started arguing with other consultants. It was beautiful, in a chaotic sort of way.

But here's what almost everyone missed in the confusion: both teams were actually right. They were just talking about two completely different problems.

When Google's John Mueller was asked about the contradiction directly, he gave what might be the most useful clarification anyone's offered on this topic all year. He split AI optimisation into two separate jobs: discovery and functionality.

Discovery is about getting found. It's about showing up when someone asks ChatGPT a question your website can answer, or appearing in Google's AI Overviews, or getting cited by Perplexity. This is the thing most business owners actually care about — being visible when AI is doing the answering.

Functionality is what happens after something has already arrived at your site. It's about whether an AI tool can navigate your pages, understand your structure, and actually do something useful once it's there.

Mueller compared llms.txt to a call-to-action button on a landing page. You don't add a "Buy Now" button to improve your Google rankings. You add it because once someone's already on your page, you want them to convert. Both matter to your business. They're just solving completely different problems.

This is the bit that unlocks the entire debate. llms.txt lives squarely on the functionality side. It was never designed to help you get found. Which is exactly why the search team can say "ignore it for rankings" while the browser team says "it helps agents navigate your site" — and both are telling the truth.

(Two teams at the same company accidentally creating an industry-wide panic because nobody bothered to check whether they were even answering the same question. If that isn't the most perfectly Google thing you've ever heard, I don't know what is.)

Now, if Mueller's distinction is the theory, the data is the bit that should really make you reconsider your to-do list.

A major study analysed roughly 300,000 websites and found no relationship between having an llms.txt file and how frequently a site appeared in AI-generated answers. None. Zero. When researchers removed llms.txt from their predictive model entirely, the model actually got more accurate — meaning the file was adding noise, not signal.

A separate study tracking AI crawler behaviour over ninety days found that out of more than half a billion bot visits, only a few hundred even looked at llms.txt files. To put that in perspective: that's like hosting the world's most elaborate house party and three people show up, two of whom are lost.

And here's the statistic that really puts the nail in it. Among the fifty most-cited websites in AI search — the ones actually winning the visibility game — llms.txt adoption sits at roughly six per cent. Among sites ranked 51st to 5,000th, adoption jumps to sixteen per cent. The sites creating the file the most enthusiastically are the ones it's helping the least. The sites dominating AI citations mostly aren't bothering.

People who've run controlled experiments — adding llms.txt to test sites and measuring against controls — report the same thing: no movement. No lift in AI citations. Nothing beyond statistical noise.

This doesn't mean the file is harmful. It costs almost nothing to create and it won't break anything. But if you've been told it'll help you show up more in ChatGPT or AI Overviews, the problem is the promise, not the implementation.

Following Mueller's logic, the answer is pretty narrow. If you publish technical documentation — API references, developer guides, that sort of thing — llms.txt serves a real purpose. AI coding tools do use it, it's cheap to maintain, and it genuinely helps those tools work with your documentation more efficiently.

If you're running any other kind of business — a services company, a consultancy, a local business, a publisher, a SaaS product, a shop — llms.txt is not where your energy should go. It's a "nice to have" at best. Worth knowing about. Not worth prioritising over the things that actually move the needle.

It's also worth noting that even Lighthouse itself marks the llms.txt check as "Not Applicable" when the file is missing, rather than flagging it as a failure. An audit checkbox is not a ranking signal. (Though I do understand the anxiety — when a Google tool puts a little amber warning next to something, the human instinct is to fix it immediately and ask questions later. We've all been there.)

Here's where I stop talking about what doesn't matter and start talking about what does. Because the llms.txt debate has been absorbing attention that would be much better spent elsewhere.

The llms.txt check is actually the least important item in Chrome's new audit category. The stuff that carries real weight is about whether AI tools can properly read and use your website — clean, well-structured code, stable page layouts that don't jump around, and semantic HTML that tells machines what your content actually means rather than just how it looks.

There's also a new standard emerging called WebMCP, which essentially lets your website expose its functions directly to AI agents rather than forcing them to guess from a screenshot. That's heading into public testing in Chrome soon, and it's the kind of infrastructure work that will genuinely separate sites AI can use from sites that merely exist near them.

But if we zoom out from the technical details, the interventions with the strongest evidence behind them are things you can act on right now.

Schema markup — the structured data that tells AI systems exactly what your content is about — remains the single highest-evidence thing you can do. Studies have found it associated with citation increases of 55 to 94 per cent. If you're going to spend time on one thing, it's this. (And yes, I know "implement schema markup" is less exciting than "drop a magic text file into your root directory." But the magic text file doesn't work, and this does. Sometimes the boring answer is the right one.)

Content freshness matters more than you'd think. The majority of pages cited by major AI platforms were updated within the previous thirty days. If your key pages haven't been touched in months, AI systems are quietly deprioritising them. A regular content review schedule isn't glamorous, but it's effective.

Your robots.txt strategy — the file that tells bots what they can and can't access — is more consequential than any new file you could add. The important move here is distinguishing between AI training crawlers (which you might want to block) and retrieval bots that are actively fetching your content to answer someone's question right now (which you almost certainly want to allow). Blocking everything because it feels safer might actually be costing you AI visibility.

Citation monitoring — tracking where and how AI systems mention your brand — gives you the measurement layer without which none of this can be evaluated. The tools are still imperfect, but having some visibility into how AI represents your business is better than flying completely blind.

None of this is glamorous. None of it generates the same excitement as a shiny new file format with a clever name. But this is where the evidence points, and evidence is what separates optimisation from superstition.

The llms.txt hype is a symptom of a totally understandable anxiety: AI is changing how people find businesses online, and we all want a clear lever to pull. A simple file you can drop into your website's root directory feels like a lever. The appeal is obvious.

But every piece of data available right now says llms.txt doesn't solve the problem most people think it solves. Its real utility is narrow and specific — helping AI tools that are already on your site work more efficiently. If that's your situation, ship it. If it's not, your time is better spent on the structural work that the data says actually matters: schema markup, fresh content, smart crawler access, and monitoring how AI systems are talking about you.

Don't chase the dream file. Prioritise the boring stuff that works.

Jo Lambadjieva is an entrepreneur and AI expert in the e-commerce industry. She is the founder and CEO of Amazing Wave, an agency specializing in AI-driven solutions for e-commerce businesses. With over 13 years of experience in digital marketing, agency work, and e-commerce, Joanna has established herself as a thought leader in integrating AI technologies for business growth.

😍It was great, all I needed

🙂Good, not great

🙄It sucked