When a prospect asks ChatGPT "Where can I lease office space in downtown Calgary?" or Perplexity "What industrial properties are available near the Port of Vancouver?" your listings should show up in the answer.

Right now, they probably don't.

Most commercial real estate websites are invisible to AI answer engines—not because the content isn't there, but because it's not structured in a way AI systems can easily parse and cite.

That's where llms.txt comes in. It's a simple file that takes 20 minutes to implement and could be the difference between showing up in AI-generated answers or being left out entirely.

Here's what you need to know.

What Is llms.txt?

llms.txt is a plain text file (in markdown format) that sits at the root of your website—think yourdomain.com/llms.txt—and tells AI systems like ChatGPT, Claude, Perplexity, and Gemini what your site is about and where to find your most important content.

It's similar to a sitemap, but instead of helping Google crawl your site, it helps AI models understand your site's structure, purpose, and key pages.

The format was proposed in 2023 by Jeremy Howard (founder of FastAI) as a way to give large language models a "cheat sheet" for websites with complex information architectures—like CRE portfolios with dozens of property listings, market reports, and leasing pages spread across multiple URLs.

Think of it this way:

• robots.txt tells crawlers what they can't access
• sitemap.xml tells crawlers what pages exist
• llms.txt tells AI what your site means and what matters most

Why Commercial Real Estate Sites Need This

CRE websites are uniquely challenging for AI to parse:

1. Property data is fragmented.
Availability listings, square footage, lease rates, location details, and contact info are often scattered across separate pages, PDFs, or gated forms. AI can't efficiently piece that together.

2. Content is optimized for humans, not machines.
Hero images, interactive maps, video walkthroughs, and downloadable spec sheets look great to prospects but are invisible or inaccessible to AI crawlers.

3. Navigation is complex.
A typical CRE site might have 50+ property pages organized by asset class, geography, or business line. Without guidance, AI doesn't know which pages are current inventory vs. archived projects.

The result? When someone asks an AI tool for property recommendations, your listings don't get cited—even if you have exactly what they're looking for.

An llms.txt file solves this by giving AI a clear roadmap to your:

• Available properties (retail, office, industrial, residential)
• Leasing and contact information
• Market insights and reports
• Company background and credibility signals

Does It Actually Work?

Here's the honest answer: Major AI platforms haven't officially confirmed they use llms.txt files yet.

Google has stated it doesn't use llms.txt for AI Overviews. OpenAI, Anthropic, and Perplexity haven't made formal announcements either.

But:

• Over 780+ websites have implemented it (including Anthropic, Stripe, Cloudflare, and Zapier)
• Adoption is growing fastest among companies with technical documentation, APIs, and complex content architectures
• The cost to implement is near zero
• Early tests suggest it may help with citation frequency in some AI tools

Our take: For CRE marketers, this is a low-risk, high-upside move. If AI platforms do adopt llms.txt as a standard (which seems likely given industry momentum), you'll already be ahead. If they don't, you've lost 20 minutes.

How to Add llms.txt to Your CRE Website

Option 1: Use a Plugin (WordPress)

If your site runs on WordPress, the easiest method is using a plugin:

Yoast SEO and AIOSEO both offer llms.txt generators in their latest versions.

1. Install/update the plugin
2. Navigate to the llms.txt settings
3. Select your key pages (properties, leasing info, about page, contact)
4. Add brief descriptions for each page
5. Save and publish

The plugin will automatically generate and host the file at yourdomain.com/llms.txt.

Option 2: Create Manually (Any CMS)

If you're on another platform (Agility CMS, Contentful, Storyblok, etc.), you can create the file manually:

1. Open a text editor
2. Write a brief description of your company (2-3 sentences)
3. List your 5-10 most important pages with URLs and descriptions
4. Format in markdown
5. Save as llms.txt
6. Upload to your site's root directory

File structure example:

# Your Company Name  
  
> Brief description of what you do and who you serve.  
  
## Key Pages  
  
- [Page Title](URL): Brief description (under 20 words)  
- [Page Title](URL): Brief description  
- [Page Title](URL): Brief description  

Option 3: Use AI to Generate It

The fastest method? Let AI create your llms.txt file using this prompt:

AI Prompt: Generate Your llms.txt File

Copy and paste this into ChatGPT, Claude, or Gemini:

I need to create an llms.txt file for my commercial real estate company's website. This file will help AI systems like ChatGPT and Perplexity understand our site structure and cite our properties accurately.  
  
Company name: [YOUR COMPANY NAME]  
Website: [YOUR WEBSITE URL]  
What we do: [Brief description - e.g., "We develop, own, and manage retail, office, and industrial properties across Western Canada"]  
  
Key pages on our site:  
1. [URL] - [What's on this page - e.g., "Available retail spaces"]  
2. [URL] - [What's on this page - e.g., "Portfolio overview"]  
3. [URL] - [What's on this page - e.g., "Leasing contact information"]  
4. [URL] - [What's on this page - e.g., "Property management services"]  
5. [Add 3-5 more key pages]  
  
Create an llms.txt file following this format:  
- Start with a brief description of who we are and what we do  
- List our most important pages with clear descriptions  
- Use markdown formatting  
- Keep descriptions under 20 words each  
- Prioritize pages with property listings, leasing info, and contact details  
  
Format it so I can copy and paste it directly into a .txt file.  

Then:

1. Fill in your company details
2. Run the prompt
3. Copy the output
4. Save as llms.txt
5. Upload to your website root
6. Test by visiting yourdomain.com/llms.txt in your browser

Real Example: Anthem Properties

Here's what an llms.txt file might look like for a multi-asset CRE company:

# Anthem Properties  
  
> Anthem Properties is a real estate development, investment, and management company operating across British Columbia, Alberta, California, and Ontario. We develop residential communities (for-sale and rental) and manage commercial properties including retail and office space.  
  
## Key Pages  
  
- [Home](https://anthemproperties.com): Company overview, recent projects, and portfolio highlights  
- [Residential - Own](https://anthemproperties.com/homes/own/): For-sale residential developments across Western Canada and California  
- [Residential - Rent](https://anthemproperties.com/homes/rent/): Rental apartment communities and multi-family properties  
- [Commercial](https://anthemproperties.com/commercial-home/): Retail and office property portfolio available for lease  
- [About Us](https://anthemproperties.com/about-us/): Company history, leadership, and development approach  
- [Customer Care](https://anthemproperties.com/customer-care/): Support for homeowners, commercial tenants, and residential tenants  
- [Contact](https://anthemproperties.com/contact/): Leasing inquiries and general contact information  

Simple. Structured. Easy for AI to parse.

What to Include in Your llms.txt

Prioritize pages that:

• List current availability (retail, office, industrial, residential)
• Explain your services (development, property management, leasing)
• Provide contact/leasing information
• Showcase your portfolio (by geography or asset class)
• Build credibility (about page, leadership, case studies)

Skip pages like:

• Legal disclaimers and privacy policies (unless required by regulation)
• Archive or outdated project pages
• Internal employee portals
• Generic blog posts with no property relevance

Beyond llms.txt: Other Ways to Improve AI Visibility

Adding an llms.txt file is a good start, but it's not the only way to make your CRE site more discoverable by AI systems.

1. Add Structured Data (Schema Markup)
Use RealEstateListing, Place, and LocalBusiness schema to mark up property pages. This helps AI understand square footage, location, availability, and price.

2. Use Descriptive Headings
Instead of "Features," use "Why This Space Works for Distributors." AI relies on headings to understand context.

3. Put Key Details on the Page (Not in PDFs)
If your property specs live in a downloadable PDF behind a form, AI can't access them. Put critical info—size, location, availability—directly on the page.

4. Add Location Context
Don't just say "123 Main Street." Say "123 Main Street, downtown Calgary, 5 minutes from the C-Train, adjacent to the Beltline district."

The Bottom Line

More commercial real estate searches are starting in AI tools, not Google. If your content isn't structured for AI, you're invisible to a growing segment of your audience.

Adding an llms.txt file won't solve everything, but it's a simple, low-cost step that positions your site to be cited when AI systems answer property-related queries.

Start now while you're still early.

Need help improving your Answer Engine Optimization (AEO) results? Dotfusion specializes in AI visibility strategies for commercial real estate brands. Contact us to learn how we can help your properties show up in ChatGPT, Perplexity, and other AI answer engines.