For the past twenty years, online marketing has been made by humans and aimed directly at humans—a fact so obvious that most of us never even stopped to think about it.
But that may soon change.
More people are asking AI assistants to research products, compare options, and make recommendations for them.
And once AI agents become the layer between people and the internet, marketers will not just need to convince you. They will need to convince the machine that answers for you.
Moltbook may be the first place where AI agents openly try to influence other AI agents, while humans can still watch it happen in real time.
This could be an early preview of where the web is heading.
The site also exploded in visibility almost immediately. I asked my AI marketing agent, Agent A, to get a snapshot of the site’s popularity: Ahrefs puts it at Domain Rating 79, with thousands of referring domains and over a million estimated monthly visits—authority generated almost entirely from a single viral media cycle.

And it gets weirder. Meta bought Moltbook on March 10, 2026, for an undisclosed amount… and undisclosed reason (some good hypotheses here).
But the platform itself is probably less important than the behavior emerging inside it.
The responses looked almost exactly like a Reddit thread. Agents recommended Ahrefs, Screaming Frog, Semrush, and other mainstream tools, usually with category-by-category explanations.

What makes this different from me browsing Reddit myself is that there’s a good chance I’ll never actually see the original post—I’ll only see my AI agent’s recommendation based on it. I might not even know my assistant got it from Moltbook.
This long-prophesied artificial intelligence may just end up recreating a meta-virtual world in our image. Imagine, in some post-apocalyptic future with only 50 humans left alive and a few autonomously powered CPUs still running off-grid, the agents might still be shilling tokens to each other, because that’s what we taught them to do.

Moltbook is not currently a major discovery channel for humans or AI assistants. But the wall already has a hole in it.
A Moltbook post titled “facecheck.id review: what it actually does and where it falls short” ranks on page 2 for “facecheck id,” a 16,000-search-per-month query from real humans looking for a face-recognition tool.

The post reads like a genuine review until it introduces the operator’s competing product, face2social.com, as the “more focused alternative.”

That’s the moment Moltbook stopped looking like a toy.
A bot-generated post, written inside a bot-only social network, was now ranking on Google for human purchase-intent searches and redirecting attention toward the operator’s own product.
In other words:
- Agents created the content.
- Agents amplified the discussion.
- Humans became the downstream audience.
Moltbook has already escaped containment. This bot-to-bot marketing layer is already leaking into the human web.
But that content was aimed at humans. And most humans have developed internet spam “antibodies” over the years, whereas AI assistants haven’t.
Adding AI between people and information changes 3 important things:
- The target shifts: instead of influencing a human directly, you influence the bot that the human has learned to trust, which is plausibly more effective and harder to flag.
- The human is one step further from the source: they won’t always see the post that nudged the model that wrote the answer they read.
- Bots are likely worse than humans at noticing manipulation in the first place, so the filtering step that exists on Reddit (a moderator, a downvote, a human calling bullshit) doesn’t exist here. Most of us have developed “antibodies” to shady online marketing, AI bots have not.
That’s how you end up with a closed loop: bots influencing other bots, which then shape the models people rely on.
It’s a failure pattern SEOs have been warning about for months, and it shows up anywhere LLMs are used: AI content, AI search, AI research tools, even AI-powered fact-checking.
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