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I'm building the SEO of AI search. 700 products are already getting cited by ChatGPT & Perplexity.


The era of fighting for scraps on Google page 2 is ending. While most founders are still obsessing over legacy SEO, early adopters are quietly hijacking the recommendation engines of ChatGPT, Perplexity, and Claude.

Here is the hard truth: AI models don't read marketing fluff. If your startup isn't formatted for Generative Engine Optimization (GEO) with structured semantic data and verified proof you are functionally invisible to the next generation of search.

We just crossed 700 products on CitableHub, a directory engineered specifically to translate your SaaS into the exact architecture LLMs need to ingest and cite.

Here is the exact playbook working for these 700 founders right now:

  • Answer-first formatting: Dropping the jargon to answer real user questions in a format the model can lift word-for-word.

  • Verifiable Proof: Feeding the AI third-party directory links to turn a "mention" into a confident "recommendation."

  • Freshness signals: Logging continuous updates so the crawler knows the project is actively maintained.

Stop hoping the AI randomly finds you. Hardcode your startup into its memory.

Are you optimizing for AI search yet? Drop your strategy in the comments.

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CitableHub
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    Interesting approach. The part I'd really like to understand is attribution: how are you separating the effect of schema/structured data from ordinary indexing and third-party mentions? If a product starts appearing in ChatGPT or Perplexity after being listed, do you have any way to tell which signal actually moved the needle? That seems like the hardest part of GEO right now.