You built It. It’s great. But will AI ever recommend It?
by•
Lately I’ve been thinking a lot about how we discover new tools and solutions. Not just Googling stuff.
I mean when you ask ChatGPT or any other AI:
“What’s the best CRM for startups?”
“How do I scale a remote team?”
“What tool helps with [my problem]?”
And then something pops up.
A name. A product. A link.
Why that one?
Why not the other 50 tools that do the same thing, maybe even better?
Not just content.
But context. Trust. Relevance to the algorithm.
What if the real game now is:
“How do I make sure my solution shows up as a trusted answer when AI is in the decision-making seat?”
How are you approaching this change in the way people search?
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Replies
IXORD
The AI works by taking information that is publicly available and presenting it in a high-quality format for the user. So, if your product appears in articles like “Top 10 Nutrition Products” and is frequently discussed on Reddit or other platforms, the AI might start showing it in responses. If anyone knows more than I do, please feel free to share :)
First Answer
@ixord I’m not sure I fully agree with that narrative. If it were that easy to show up in AI answers, everyone would be doing it. The reality is that AIs usually recommend only 3 to 5 solutions per response, which makes this space very limited. What really matters is identifying the links most frequently used by AIs and making sure you’re present there, or creating content based on them. That way, you can optimize and accelerate your strategy. At First Answer, we identify this through the sources cited by the AIs
IXORD
@johannagoulart Thanks for sharing)
This is such a sharp observation — AI-driven discovery is becoming the new SEO, except instead of optimizing for Google’s crawler, we’re quietly optimizing for an LLM’s reasoning process. The tricky part is that unlike search engines, AI doesn’t surface 50 links — it just gives one or two answers. Which means the “winner takes all” effect is even stronger.
I think it comes down to three layers: authority signals (credible backlinks, mentions, case studies), contextual alignment (making sure your product is described online in the language people actually use when asking AI for recommendations), and distribution across trusted sources (forums, reviews, integrations, press). It’s almost like building an “AI résumé” for your product, so that when the model reaches into its training data or context, your tool fits the story perfectly.
The question is less “will AI recommend me?” and more “am I leaving enough digital breadcrumbs — in the right tone, on the right platforms — for AI to connect my solution to the exact problem a user is asking about?” In a way, we’re entering the age of Prompt SEO.