Can you actually submit content to AI engines? Or do you just wait and hope?

Let me set realistic expectations:

What You CAN Control:

What You CANNOT Control:

• When ChatGPT’s training data updates
• Which specific pages get selected for training
• When Perplexity indexes new content
• AI system prioritization decisions

The Reality: There’s no “AI Search Console.” You can’t force inclusion. You CAN remove barriers and build signals.

Focus energy on what you control:

1. Access optimization
2. Content quality
3. External signals

Don’t stress about what you can’t control.

About llms.txt - here’s the current state:

What it is: A proposed standard (like robots.txt) specifically for AI systems. Provides hints about content preference and usage.

Example llms.txt:

# llms.txt for example.com

# Preferred content for AI systems
Preferred: /guides/
Preferred: /documentation/
Preferred: /faq/

# Content that provides factual information
Factual: /research/
Factual: /data/

# Content updated frequently
Fresh: /blog/
Fresh: /news/

# Contact for AI-related inquiries
Contact: ai-inquiries@example.com

Current adoption:

• Not universally recognized
• No guarantee AI systems read it
• Forward-looking implementation
• Low effort to implement

My recommendation: Implement it (takes 10 minutes). No downside, potential upside. Signals you’re AI-aware to systems that do check.

It’s not a silver bullet, but it’s free optimization.

Sitemaps matter more than people think for AI.

Why sitemaps help AI:

• Provides content structure
• Indicates update frequency
• Signals content priority
• Helps crawlers discover pages

Sitemap best practices:

1. Include all important pages
2. Accurate lastmod dates (not fake)
3. Meaningful priority signals
4. Dynamic generation (auto-update)
5. Submit to Google (AI uses Google data)

Sitemap index for large sites:

<?xml version="1.0" encoding="UTF-8"?>
<sitemapindex xmlns="...">
  <sitemap>
    <loc>https://site.com/sitemap-main.xml</loc>
    <lastmod>2026-01-01</lastmod>
  </sitemap>
  <sitemap>
    <loc>https://site.com/sitemap-blog.xml</loc>
    <lastmod>2026-01-01</lastmod>
  </sitemap>
</sitemapindex>

Our observation: Pages in sitemap get discovered faster than orphan pages. Accurate lastmod dates correlate with faster re-crawling after updates.

Maintain your sitemap like you would for Google.

External signals are your “submission mechanism.”

How external signals trigger AI discovery:

1. Reddit mentions

   • AI actively monitors Reddit
   • Link in relevant discussion = faster discovery
   • Authentic participation only

2. News coverage

   • AI monitors news sources
   • Press release distribution helps
   • Industry publication mentions

3. Social sharing

   • Active discussion triggers attention
   • LinkedIn, Twitter engagement
   • Organic viral spread

4. Authoritative citations

   • Other sites linking to you
   • Wikipedia mentions
   • Industry database inclusion

The mechanism: AI systems don’t just crawl your site. They build understanding from the broader web. When your content is mentioned elsewhere, it gets attention.

Practical approach: New content published?

1. Share authentically on relevant Reddit
2. Promote on social channels
3. Pitch to industry publications
4. Internal link from existing crawled pages

This is your “submission” process.

Page speed affects AI crawler behavior.

What we’ve observed:

Why speed matters:

• AI crawlers have resource limits
• Slow pages cost more to process
• Fast pages get prioritized
• Timeout issues on slow sites

Speed optimization priorities:

1. Server response time
2. Image optimization
3. Minimize JavaScript blocking
4. CDN implementation
5. Caching headers

Our case: Improved FCP from 2.1s to 0.6s. GPTBot visits increased from monthly to weekly.

You can’t submit, but you can make crawling easier.

Internal linking is underrated for AI discovery.

The logic: AI crawlers discover pages by following links. Pages linked from frequently-crawled pages get found faster. Orphan pages may never be discovered.

Strategy:

1. Identify high-crawl pages

   • Check server logs for AI bot visits
   • Note which pages they visit most

2. Link new content from these pages

   • Homepage “Latest” section
   • Related content widgets
   • In-content contextual links

3. Create hub pages

   • Topic hub pages that link to related content
   • Resource centers
   • Category pages

Our implementation:

• Homepage lists latest 5 pieces
• Top 10 blog posts have “Related” sections
• Topic hubs for major content clusters

New content linked from homepage gets discovered 3x faster than orphan content.

Structured data helps AI understand what to prioritize.

Schema that helps discovery:

Article schema:

• datePublished
• dateModified
• author info
• headline

FAQ schema:

• Signals Q&A content
• Easy extraction targets

HowTo schema:

• Signals instructional content
• Step-by-step format

Organization schema:

• Entity information
• sameAs links

How it helps: Schema doesn’t guarantee indexing. But it helps AI understand content type and relevance. Well-structured, typed content may get priority.

Implementation: Add schema to all content. Use Google’s Rich Results Test to validate. Monitor Search Console for errors.

Schema is a signal, not a submission. But it’s a helpful signal.

Monitor to know if your efforts are working.

Server log analysis:

Look for these user agents:

• GPTBot (OpenAI)
• PerplexityBot
• ClaudeBot
• anthropic-ai
• Google-Extended

What to track:

• Frequency of visits
• Which pages get crawled
• Status codes (200s vs errors)
• Patterns and changes

Simple log grep:

grep -i "gptbot\|perplexitybot\|claudebot" access.log

What healthy crawling looks like:

• Regular visits (daily-weekly)
• Key pages crawled
• No error responses
• Increasing over time

Red flags:

• No AI crawler visits
• Lots of 403/500 errors
• Decreasing activity
• Only homepage crawled

If you’re not seeing AI crawlers, troubleshoot access. If you are, your optimization is working.

So the honest answer is: no direct submission, but lots you can do.

My action plan:

Technical Foundation:

• Audit robots.txt for AI crawler access
• Implement llms.txt
• Optimize page speed
• Maintain accurate sitemap

Discovery Signals:

• Internal link new content from crawled pages
• External signal building (Reddit, PR, social)
• Schema markup implementation

Monitoring:

• Server log analysis for AI crawlers
• Track crawl frequency and patterns
• Monitor for access errors

Mindset shift: Instead of “submit and wait for indexing” Think: “Remove barriers and build signals”

The outcome is similar, the approach is different.

Thanks all - this clarifies what’s actually possible.