With Google, I can submit URLs via Search Console and get indexed within hours. With AI engines, it feels like throwing content into the void and hoping.
What I want to know:
I’d rather take action than hope. What’s actually possible here?
Let me set realistic expectations:
What You CAN Control:
| Action | Impact Level | Effort |
|---|---|---|
| Ensure crawler access (robots.txt) | High | Low |
| Optimize page speed | High | Medium |
| Proper HTML structure | Medium | Low |
| Sitemap maintenance | Medium | Low |
| llms.txt implementation | Low-Medium | Low |
| Internal linking from crawled pages | Medium | Low |
| External signal building | High | High |
What You CANNOT Control:
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:
Don’t stress about what you can’t control.
The crawler access part is non-negotiable.
Check your robots.txt for:
# AI Crawlers - Allow access
User-agent: GPTBot
Allow: /
User-agent: PerplexityBot
Allow: /
User-agent: ClaudeBot
Allow: /
User-agent: anthropic-ai
Allow: /
User-agent: Google-Extended
Allow: /
If you want to block (for opt-out):
User-agent: GPTBot
Disallow: /
Our discovery: Legacy robots.txt was blocking GPTBot due to wildcard rules from 2019.
Fixing this one issue led to first AI crawler visits within 48 hours.
Check robots.txt before anything else.
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:
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:
Sitemap best practices:
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:
Reddit mentions
News coverage
Social sharing
Authoritative citations
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?
This is your “submission” process.
Page speed affects AI crawler behavior.
What we’ve observed:
| FCP Speed | AI Crawler Behavior |
|---|---|
| Under 0.5s | Regular, frequent crawls |
| 0.5-1s | Normal crawling |
| 1-2s | Reduced crawl frequency |
| Over 2s | Often skipped or incomplete |
Why speed matters:
Speed optimization priorities:
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:
Identify high-crawl pages
Link new content from these pages
Create hub pages
Our implementation:
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:
FAQ schema:
HowTo schema:
Organization schema:
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:
What to track:
Simple log grep:
grep -i "gptbot\|perplexitybot\|claudebot" access.log
What healthy crawling looks like:
Red flags:
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:
Discovery Signals:
Monitoring:
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.
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