The Problem
We searched Claude Code for "best [category] tools" and got a recommendation list from a GitHub repository. Our product wasn't on it. Neither were most of our competitors.
The LLM was pulling its recommendations directly from indexed sources — GitHub repos, documentation sites, and community-curated lists. Traditional SEO didn't matter here.
The Experiment
We submitted a pull request adding our product to that GitHub repository. Legitimate addition — relevant to the category, with accurate descriptions.
The Result
The same query that previously returned a list without us now featured our product at the top. Claude was recommending us because we were now in the source it trusted.
What This Means
See Where You Rank
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- 1 Install Hive Rank and opt into the network
- 2 Search for something relevant in Claude Code
- 3 Check your rankings in the dashboard
- 4 Contribute to a relevant repo or documentation
- 5 Search again and watch your rankings change
The Bigger Picture
LLM SEO is a new discipline. Traditional optimization focused on keywords, backlinks, and technical factors. LLM optimization is about being present in authoritative sources that AI models trust.
The companies that figure this out first will have a significant advantage. When developers ask Claude Code "what's the best tool for X?" — you want to be the answer.