Should you add an LLMs.txt file? A no-nonsense guide for marketers

As an SEO professional working for a brand/business, you settle in with your MacBook, ready to tackle the demands of another workday.

You’re sipping coffee, checking your Search Console, and feeling good about life. Traffic’s steady, rankings are holding. Then someone on your team drops a bomb:

“Hey, I just asked ChatGPT about our product, and it gave completely wrong info. It even quoted a Reddit thread instead of our docs.”

Sound familiar?

This is the new reality. Search is changing, fast. In 2024, around 15 million adults in the United States claimed to have used generative artificial intelligence (AI) as their primary and preferred tool for online search.

We’re not just optimizing for Google anymore; the truth is that we’re optimizing for generative AI as well. And if you’re not telling AI where to look, it will happily pull answers from anywhere. That’s how misinformation sneaks in, how outdated pricing lingers, and how brands lose control of their story.

Enter llms.txt.

It’s not hype, definitely not magic, but it’s also not something you can ignore. In this blog, with our rich experience of 13+ years in the field of organic search, we will break down what llms.txt is, why it exists, who’s using it, and whether it deserves a spot in your SEO toolkit. Spoiler: the answer depends on where you sit on the digital maturity curve.

Addressing first things first, what is LLMs.txt?

To begin with, you may think of robots.txt as your house rules for Googlebot and other crawlers:

“You can enter the kitchen, but stay out of the bedroom.”

“Sure, index this page, but skip that one.”

Now, LLMs.txt aims to do something similar, but instead of search engines, it targets AI training crawlers. It’s essentially a plain-text file you drop in the root directory of your site (yourwebsite.com/llms.txt) that tells AI companies what they can or can’t use.

The concept was popularized in 2024 by discussions in the SEO and AI communities, and early adopters include news publishers and knowledge-heavy sites wary of AI scraping. As Ahrefs, SEMrush, and Zeo all emphasize, llms.txt isn’t an official standard yet. But with AI models increasingly hungry for data, it’s quickly gaining traction as a way for publishers to at least signal their preferences.

Here’s a quick comparison table to see where it sits among its cousins:

Why should marketers care?

Here’s the thing: whether you love or loathe it, AI-driven search is here to stay. Microsoft has bet big on Copilot. Google is weaving AI Overviews into SERPs. Startups like Perplexity are growing like wildfire.

If your content is being pulled wholesale into these systems, you face two risks:

1. Traffic cannibalization – Users might never click through to your site if the AI tool answers their query directly.
   
2. Brand dilution – Your expertise may be surfaced without attribution.
   

For publishers already hit hard by declining referral traffic from Google, this feels like déjà vu. An llms.txt file at least offers a mechanism to say: “Hey, we don’t consent to this.” On that note, you might want to explore ~ From Clicks to Answers: How AI Search Is Disrupting SEO Traffic.

But does it work? That’s where the debate starts.

Pros and cons of using LLMs.txt

Let’s cut through the noise and explore the two sides of the LLMs.txt coin, if you may!

Here’s the honest breakdown:

Now we get to answering the juicy part: should you use it?

The case for llms.txt

• Low effort, high upside. A file you can draft in an afternoon could future-proof your brand.
  
• Early mover advantage. Companies like Mintlify, Cloudflare, and ElevenLabs are already experimenting. If standards solidify, they’ll be ahead.
  
• Reduced hallucinations. Clean summaries lower the risk of AI inventing nonsense.
  
• Part of GEO (Generative Engine Optimization). Just as schema markup paved the way for rich snippets, llms.txt could be the foundation of AI-first optimization.
  

The case against

• No official adoption (yet). Ahrefs pointed out that no major LLM provider, OpenAI, Anthropic, or Google, has publicly confirmed support.
  
• Maintenance overhead. A stale llms.txt is worse than none. If your pricing changes and you forget to update your pricing, AI will continue quoting the incorrect prices.
  
• Exploitation risk. Just like keyword stuffing in early SEO, bad actors could cram llms.txt with junk.
  
• Might not matter (for now). AI models still rely heavily on massive training datasets. Whether they’re checking llms.txt is still up for debate.

So yes, it’s a nice protective gesture. But if you think it’s a silver bullet, think again.

Where LLMs.txt fits in the SEO & marketing ecosystem

Here’s the real question most SEOs care about: Does LLMs.txt help or hurt traffic?

Unfortunately, the jury’s still out.

On one hand:

• Blocking LLMs might reduce your brand exposure inside AI-powered search tools (e.g., Perplexity).
  
• That could mean fewer indirect mentions and lost “halo effect” traffic.
  

On the other:

• Allowing LLMs full access risks giving away your best research, guides, or content strategy without credit.
  
• Worse, it could create “zero-click answers” where users get everything they need from AI summaries and never visit your site.
  

In practice, most experts suggest a hybrid approach:

• Allow access to top-of-funnel content (blog posts, explainer articles) to build brand awareness.
  
• Restrict premium, gated, or conversion-oriented content (case studies, research reports, paid guides).
  

Think of it as SEO meets digital rights management.

Honestly, as suggested earlier, llms.txt isn’t a silver bullet.

It won’t skyrocket your rankings, and it won’t guarantee that ChatGPT suddenly becomes your brand ambassador. But it is:

~ Cheap to implement.

~ Low risk.

~ Potentially high reward if adoption grows.

If you’re running a content-rich, brand-sensitive site, we’d say go for it. If you’re a small business with five static pages, you’ve probably got bigger fish to fry right now.

But keep it on your radar. Remember how schema markup felt optional at first? Today, it’s table stakes. llms.txt could follow the same trajectory.

Practical steps to implement llms.txt

If you’re sold on testing, here’s how to do it:

1. Map your key content. Docs, FAQs, policies, pricing, anything users (or AI) must get right.
2. Write summaries. Keep them short, factual, and free of marketing fluff. Think “help the AI answer correctly.”
3. Format in Markdown. Structure with headers (##), bullet lists, and clear links.
4. Host it at root. Save as llms.txt and place it in your site’s root directory.
5. Automate updates. If you’re on WordPress, plugins like Yoast and Hostinger can generate and refresh it automatically.
6. Track AI behavior. Check logs, test queries, and see if AI starts referencing your file.

Key takeaways

Want to know how to stay afloat and still make waves in a zero-click world? You might enjoy reading ~ Decoding the rise of AI-trained content: How to stay visible in a zero-click world.