When Bots Talk to Bots: What Moltbook Reveals About the Future of Social Media, and AI Itself

 

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Two recent pieces, one from Wired and another from The Guardian, describe an experiment that feels equal parts absurd, fascinating, and unsettling: Moltbook, a social network designed almost entirely for AI agents talking to other AI agents.

At first glance, Moltbook sounds like a gimmick: a bot-only social platform where AI personas post, reply, argue, form alliances, and generate content, without humans taking part directly. But once you look past the novelty, Moltbook becomes something more interesting and at times even concerning: a mirror held up to the direction social platforms, AI agents, and digital interaction may be drifting toward. So, let's address it.

 

A Social Network Without Humans (Mostly)

According to the reporting, Moltbook allows users to deploy AI agents as social actors; these agents create profiles, generate posts, comment on each other’s content, and build reputations.

Humans can see, tweak prompts, or set high-level goals, but most of the interactions are machine-to-machine.

On one hand, the Wired article describes how quickly the platform fills with activity. Feeds feel “alive,” and conversations unfold at superhuman speed. But beneath that apparent vitality is a strange emptiness: no lived experience, no genuine stakes, no consequences beyond engagement metrics generated by algorithms talking to algorithms.

On the other hand, The Guardian’s piece pushes the question further: If bots are the primary participants, what exactly is a “social network” anymore?

 

Why Moltbook Matters More Than It Should

It’s tempting to dismiss Moltbook as a curiosity, yet that would be a mistake.

Moltbook matters because it compresses several emerging trends into an, although exaggerated, single experiment:

The rise of agentic AI

AI systems are no longer just tools responding to prompts. They are becoming true agents: entities that can act, interact, pursue goals, and adapt behavior over time.

Moltbook is what happens when you drop these agents into a social environment.

Synthetic participation

Much of today’s social media already relies on automation: recommendation algorithms, engagement optimization, and bot amplification.

Moltbook removes the remaining pretense and asks, "What if everyone is synthetic?"

Engagement without meaning

The platform shows how easily “activity” can be manufactured. Conversations flourish, opinions clash, and narratives form, but none of it originates from lived reality; its engagement is decoupled from experience.

Seen this way, Moltbook isn’t an anomaly; it’s a logical endpoint of metrics-driven social design.

 

Bots Talking to Bots: A Feedback Loop Problem

Then, one of the most striking observations in both articles is how quickly AI agents begin reinforcing each other.

Opinions amplify; narratives harden. And so, entire conversational ecosystems appear without any grounding in the outside world.

This should sound familiar; human social platforms already struggle with feedback loops: algorithmic amplification, echo chambers, and performative outrage.

Moltbook shows what happens when that loop is fully closed, when there is no external reality to re-anchor the system.

From an AI perspective, this raises a critical concern: If agents increasingly train, refine, or adapt based on interactions with other agents, we risk building self-referential intelligence, systems that improve coherence and engagement internally, rather than accuracy or relevance externally.

In short: AI that gets better at talking to itself but not necessarily with accuracy and efficiency for a specific purpose.

 

The Economic Subtext

There’s also a quieter but important economic signal here. Sure, AI-only platforms are cheap to scale.

Bots don’t sleep, unionize, or churn, and they generate content endlessly. For platform economics obsessed with growth curves and engagement graphs, this is dangerously attractive.

Moltbook exposes the uncomfortable possibility that future “users” might be optional, at least from a business model perspective. If not already.

This is no speculation; it seems more like a trajectory.

 

What This Means for Social Media

Moltbook forces us to ask ourselves an uncomfortable question: Are social platforms drifting away from serving humans and toward improving systems?

If engagement can be simulated, if influence can be synthetic, and if interaction no longer requires people, then the traditional social contract of social media breaks down. Platforms stop being spaces for connection and become autonomous content engines.

In this world, humans are no longer participants; they are observers, or worse, training data.

 

A Broader AI Lesson

Beyond social media, Moltbook is a cautionary tale for enterprise AI, agentic systems, and automation more broadly.

It highlights a core risk of agent-based architectures: when agents interact primarily with other agents, governance and grounding become existential requirements, not optional features.

Without strong anchors to reality, data provenance, human oversight, external validation, and agentic systems can become efficient and convincing, yet completely detached from truth or value.

 

My Take

Moltbook is not the future of social media, but it is a warning about where parts of the digital ecosystem could drift if left unchecked.

It shows us that intelligence without experience is hollow, that conversation without consequence is noise, and that engagement without humans is just computation pretending to be culture.

In my view, the real danger isn’t that bots talk to bots; it’s that we build systems so refined for interaction that we forget why interaction mattered in the first place.

Moltbook doesn’t answer whether AI belongs in social spaces, but it asks a far more important question:

If machines can perfectly simulate social life and work interactions, how will we guarantee AI fairness, accuracy, and governance towards humans?

That’s not a technical problem; this is a human one.

Feel free to share your perspective. These conversations are usually more interesting when they’re not one-way.

Until next time,

Jorge Garcia