We analyzed the top domains cited across all LLMs in Rankfender. The results change how you should think about AI visibility.

The data (Rankfender, Juin 2026):

The Product Hunt playbook has changed. Here is what the data says actually works.

The Old Playbook (2025 and earlier)

You built a "Notify me" page. You set up an email sequence. You posted on launch day. You hoped.

That still works, but it is no longer enough. Product Hunt is no longer a transactional "launch and vanish" platform. It has become a community, and the real conversations now start in forum threads .

There is a point in every product's life where it crosses a threshold. The person who built it can still explain it. But the person who just joined cannot.

The complexity is not in the code. It is in the context. The decisions that were made. The compromises that were accepted. The edge cases that were built around. The technical debt that was deferred.

No one writes those down. They just become the way things are.

The threshold is crossed when the product can no longer be fully understood by one person. Not because the person is less capable. Because the product has absorbed too many decisions that no one remembers making.

Ahrefs just dropped a study that changes how we think about SEO. They analyzed 863,000 keywords and 4 million AI Overview URLs. The findings are clear: the old playbook is broken.

In July 2025, 76% of URLs cited in AI Overviews also ranked in Google's top 10 for the same query. Today, that number has collapsed to 38%. The drop is real. The overlap has been cut in half in less than a year.

Where are the citations coming from now? The remaining citations are split almost evenly: 31.2% come from positions 11 100, and 31.0% come from outside the top 100 entirely. A huge chunk of AI citations are coming from pages you wouldn t even see on page one.

Why is this happening? Query fan out. When a user searches, Google splits the query into multiple related sub-queries and pulls sources from all of them. The pages that appear most often across those sub-queries get cited in the AI Overview, even if they don t rank for the original keyword. The AI answer is not a summary of the SERP below it.

I'll go first.

I still reply to every comment manually. Reddit, LinkedIn, Product Hunt, forums, Twitter, Discord. Every single one.

AI could do this. There are tools that generate replies, post on schedule, analyze sentiment, even mimic your brand voice. But I don't use them. Here's why.

A 2024 study on community engagement across 500 brands found that personalized responses drive 3.2x higher retention and 4.7x more repeat interactions than automated replies. People can tell when a response is copy-pasted. They can feel when no one actually read their comment. The average user only needs 2-3 automated interactions before they disengage entirely.

The biggest AI companies are hiring senior SEO talent.
OpenAI brought in a search leader from Netflix. Anthropic is offering $320k for an SEO Lead. Meta has roles at $300k

The same companies building the tools that were supposed to "kill" search are now investing in understanding it.

This is not a coincidence. When the companies that build LLMs pay top dollar for search expertise, they are telling you something: Organic visibility is becoming a strategic moat . The companies that win will be the ones that understand how search and AI discovery work together

AI is not replacing SEO. It is redefining it. The discipline is shifting from rankings to citations, from click-through rates to answer engine optimization. The fundamentals have not changed. The skills have evolved.

Backlinks are still one of the strongest signals Google uses to judge whether a page deserves to rank . But the math changed. Google's December 2024 and October 2025 spam updates devalued link networks, paid placements, and AI-generated guest-post farms . The old volume play is dead. The new play is about quality, relevance, and context.

In the age of AI search, backlinks influence visibility differently. They act on the retrieval layer the live search index that grounds AI answers rather than the model's frozen training weights . A domain's Authority Score correlated with AI mentions at Pearson 0.65, according to a Semrush study of 1,000 domains tracked across five AI surfaces . Raw backlink volume correlated far more weakly.

Two insights from the data:

I have been looking at what is actually getting traction on Product Hunt right now. The pattern is clear.

In March, OpenClaw products dominated the leaderboard. Anything with "Claw" in the name got votes. That was a land grab new space, everyone rushing in to claim a spot .

In April, that stopped. The "just build an agent" strategy stopped working. What replaced it? Products that do specific tasks inside workflows you already have .

Here is what the data shows.

We analyzed 6.8 million AI citations across ChatGPT, Gemini, and Perplexity . The finding changed how we think about AI visibility.

The breakdown

• First-party websites: 44% of citations

• Business listings: 42%

• Reviews and social content: 8%

• Forums like Reddit: Just 2%

The most impactful sources are the ones you already control . This directly challenges the perception that Reddit and user-generated content dominate AI answers .

I spent the last two months analyzing Product Hunt launches.
Not the upvotes. The patterns behind them.

Here is what the data says.

The first hour is not the most important hour.

The top 10% did not have more upvotes in the first hour. They had more comments in the first hour. Comments signal engagement. Upvotes signal approval. Engagement carries more weight.