Making My Website AI-Ready: llms.txt, Schema.org, and What Actually Changed

#webdev #ai #seo #javascript

Hey DEV community! A few months ago I shared how I built a car rental platform in Moldova. Since then, I've been thinking about something that didn't exist as a concern when I started: how do AI assistants discover and describe my site?

If someone asks Gemini "what's a good car rental in Moldova?", or "sober driver chisinau" will it mention my business? If Claude cites a source about sober driver services in Chișinău, will it be my page?

Traditional SEO assumes humans read your site. AI-era SEO needs to assume both humans AND AI agents do. Here's what I actually did — and what changed.

The Problem Nobody Warned Me About

In 2024, I noticed something weird. My site ranked well on Google, but when I asked Claude or Perplexity about car rental in Chișinău, my business either wasn't mentioned, or was described with outdated info from training data.

The issue: AI crawlers work differently from Googlebot.

GPTBot, ClaudeBot, PerplexityBot, Claude-SearchBot — these are real, active crawlers
They respect robots.txt, but most sites don't explicitly address them
They parse structured data, but rely heavily on clear, semantic content
Without explicit signals, your site gets ignored or misrepresented

Traditional SEO focuses on Googlebot. AI-era SEO needs to think about a dozen different crawlers, each with different priorities.

Meet llms.txt

Enter llms.txt — a proposed standard (think robots.txt but for AI). It's a markdown file that tells AI systems:

Who you are
What your site is about
Key URLs they should know
What's the most important information

It's not a W3C standard yet, but Anthropic, OpenAI, and others are increasingly looking at it. The cost to implement is 15 minutes. The upside is significant.

Here's a simplified version of mine:

# PlusRent.md

> Car rental and designated sober driver service in Chișinău, Moldova. 
> Operating since 2022, 20+ vehicles, 24/7 support, 27 Google reviews (5.0 stars).

## Services

- **Car Rental**: Economy (€15/day), Standard (€31/day), Premium BMW/Mercedes (€61/day)
- **Sober Driver (Șofer Treaz)**: From 150 MDL/hour. Available 24/7 in Chișinău (30 km radius).
- **Airport Delivery**: Free to Chișinău Airport (business hours), available for Iași Airport.

## Key Pages

- [Main](https://plusrent.md/ro/): Service overview
- [Car Catalog](https://plusrent.md/ro/cars): 20 vehicles with pricing
- [Sober Driver](https://plusrent.md/ro/sofer-treaz): Designated driver service
- [Contact](https://plusrent.md/ro/contact): +373 60 000 500, 24/7

## Key Facts

- 3 languages: Romanian, Russian, English
- 439+ completed orders
- Address: Meșterul Manole 20, MD-2044, Chișinău
- Coordinates: 47.013737, 28.886408

Available at plusrent.md/llms.txt if you want a real example.

Schema.org: Still Essential, Now Also for AI

I already had basic Schema.org markup from the first iteration. But I went deeper, adding multiple interconnected types:

// AutoRental — primary business schema
{
  "@context": "https://schema.org",
  "@type": "AutoRental",
  "name": "PlusRent",
  "priceRange": "€15-€120",
  "areaServed": [
    {"@type": "City", "name": "Chișinău"},
    {"@type": "Country", "name": "Moldova"}
  ],
  "makesOffer": [
    {
      "@type": "Offer",
      "name": "Economy Car Rental",
      "price": "15",
      "priceCurrency": "EUR"
    }
    // ...
  ]
}

The key insight: AI systems parse multiple schema blocks. Having separate schemas for Organization, AutoRental, FAQPage, BreadcrumbList, and LocalBusiness gives AI systems multiple signals confirming what your site is about.

One mistake I made initially: using @type: "Product" for services. Google and SEMrush both flagged this, requiring e-commerce fields like shippingDetails and hasMerchantReturnPolicy. For a service business, use Service or domain-specific types like AutoRental, Vehicle, or LodgingBusiness.

Robots.txt for the AI Era

Most robots.txt files are written for one crawler: Googlebot. Here's a snippet from mine, explicitly addressing AI bots:

# Default rules apply to everyone
User-agent: *
Allow: /
Disallow: /admin
Disallow: /api/

# AI Crawlers — explicitly allowed with same restrictions
User-agent: GPTBot
User-agent: ClaudeBot
User-agent: anthropic-ai
User-agent: PerplexityBot
User-agent: Google-Extended
User-agent: Applebot-Extended
Disallow: /admin
Disallow: /api/

# Point them to machine-readable summary
Sitemap: https://plusrent.md/sitemap.xml

Being explicit matters. Some AI companies treat "no rules for my bot = assume disallowed" as default behavior. Being explicit about what's allowed prevents accidental exclusion.

Testing Actual Results

I tested the same question before and after on Claude, ChatGPT, and Perplexity: "What car rental services are available in Chișinău, Moldova?"

Before:

Generic answers mentioning "various international companies"
Outdated info
My business rarely mentioned

After (2-3 weeks post-implementation):

Specific mentions of PlusRent with accurate service descriptions
Correct pricing quoted
Sober driver service mentioned (an unusual service AI systems wouldn't typically know about)

The effect isn't instant — AI systems rebuild their indices on their own schedules — but over weeks, the quality of AI-generated responses about my business improved substantially.

What Actually Moved the Needle

Ranking these by impact from my experience:

Schema.org done right — biggest impact. AI systems parse structured data carefully.
llms.txt — cheap win, clear signal.
Explicit AI bot rules in robots.txt — marginal but easy.
Clear semantic HTML — no divs-with-classes when <article>, <section>, <nav> exist.
Unique meta descriptions per page — AI uses these as summaries.

The underrated factor: having multiple external sources mentioning your business. AI systems use citations to validate claims. If your site says "24/7 service" but three independent blogs and review platforms also say it, AI trusts it more.

Key Takeaways

AI-ready SEO is just good SEO, but more explicit. You're not gaming AI — you're helping it understand you.
llms.txt is cheap — 15 minutes of work for potentially significant upside.
Schema.org types matter. Don't force Product on a service business.
Multiple schemas > one giant schema. Give AI multiple validation signals.
External citations build trust. No amount of on-site optimization replaces real third-party mentions.

The wild part? None of this is revolutionary. It's the same SEO principles — clarity, semantic correctness, helpful markup — applied to a broader audience of readers that now includes AI agents.