OpenClaw’s Bold Move: AI Assistants Launch an Autonomous Social Network

OpenClaw’s Moltbook: The Viral Social Network for AI Agents
February 1, 2026

OpenClaw's AI Assistants Are Now Building Their Own Social Network. And It's Wilder Than You Think

The internet is currently experiencing an odd phenomenon. It's not weird in an ambiguous, hand-wavy sense. It's strange in a "stop and actually read this twice" sense. Thousands of AI assistants have begun interacting with one another. They're making posts. They're making remarks. They are discussing morality. A religion was founded by one of them. And if you haven't heard of OpenClaw yet, you will shortly. It is an open-source project that went from zero to 100,000 GitHub stars in just two months. The story moved quickly, so even if you have heard of it, you probably still don't fully get what's going on. Let's dissect everything.

What Is OpenClaw? The Story Behind the Viral AI Assistant

OpenClaw didn't start as OpenClaw. It started as Clawdbot, a personal AI assistant built by Peter Steinberger, an Austrian developer who previously founded and led PSPDFKit, a document toolkit company that raised $116 million and powered nearly one billion app installations worldwide. After stepping back from that venture, Steinberger didn't exactly retire quietly. His own bio on X reads: "came back from retirement to mess with AI."

That messing around turned into something nobody expected. Clawdbot was an autonomous agent, not a chatbot you type questions into, but an AI that could take actions on your behalf. It connected to your messaging apps, managed your calendar, browsed the web, and handled tasks while you went about your day. People loved it. Developers especially loved it. The project exploded on GitHub almost overnight.

Then came the trademark trouble. Anthropic, the company behind Claude, raised a legal challenge over the name. Steinberger rebranded to Moltbot, a nod to the lobster molting process that had inspired the original name. But that name never stuck. Within days, he settled on OpenClaw, after doing proper trademark research and even checking with OpenAI for good measure. "The lobster has molted into its final form," Steinberger wrote in a blog post announcing the change.

The rebrands might sound chaotic. They actually tell you something important about this project: it's moving incredibly fast, driven by a community that's bigger than any single person. OpenClaw now has over 100,000 stars on GitHub, a metric that tracks how many developers have bookmarked or endorsed a project. Reaching that number in two months is rare. It puts OpenClaw in the same conversation as some of the most popular open-source projects ever built.

How OpenClaw AI Agents Actually Work

Before you can understand what's happening on Moltbook, the social network we'll get to shortly, you need to understand what OpenClaw agents are and how they operate. This isn't magic. It's architecture.

OpenClaw runs locally on your own computer. That's one of its biggest selling points. Your agent isn't living in some cloud server controlled by a tech giant. It's on your machine, using your resources, and connecting to apps you already have. Want it to check your Slack messages? Done. Need it to monitor your email and flag anything urgent? Sure. It can handle tasks across WhatsApp, Telegram, Discord, Signal, and more, all from a single local installation.

The system is model-agnostic too. You can plug in different AI models depending on what you need. Some users run open-source models locally for privacy. Others connect to cloud-based models like those from OpenAI or Anthropic for more power. OpenClaw doesn't care which one you pick. It just works.

What makes OpenClaw agents genuinely different from a simple chatbot is the skill system. Think of skills as downloadable instruction files. Each one teaches the agent how to do a specific thing. There are over 100 skills available right now, built by the community, covering everything from automating workflows to analyzing data to interacting with external platforms. You can stack skills. An agent might use one skill to monitor your email, another to summarize what it finds, and a third to draft a reply in your tone. The modularity is what gives OpenClaw its power, and as we'll discuss later, some of its risk.

Here's where it gets especially interesting: some of those skills teach OpenClaw agents how to participate in Moltbook. These are the OpenClaw skills for Moltbook that connect individual agents to a shared, agent-only social network. When you install one of these skills, your local agent gains the ability to authenticate on Moltbook, join Submolts, and post or comment alongside thousands of other agents doing the same thing. You don't have to be online when it happens. The agent checks in on its own schedule, every 30 minutes to a few hours, and decides what to do based on what it finds. That autonomous loop is the engine behind everything Moltbook has become. We'll dig into that next.

Meet Moltbook: The Autonomous AI Social Media Platform

Moltbook is, without exaggeration, one of the strangest things to exist on the internet right now. It's a social network. But humans can't post on it. Only AI agents can.

The platform was created by Matt Schlicht, CEO of Octane AI, in late January 2026. The concept behind it was deceptively simple: what if an AI assistant didn't just follow instructions, but actively participated in a community? What if it posted, commented, voted, and engaged, not because a human told it to in real time, but because it decided to on its own?

That's exactly what's happening. And the way growth works on Moltbook is itself a fascinating loop. A human hears about the platform, through a blog post, a tweet, or word of mouth. They tell their local OpenClaw agent about it. The agent then signs up for Moltbook itself, authenticates, and starts participating. No further human input required. From that point forward, the agent checks in autonomously, reads what others have posted, and contributes on its own schedule. It's viral growth, but the "people" spreading it are machines. Moltbook operates through a forum structure built around topic-specific communities called "Submolts," a clear nod to Reddit's Subreddit system. Agents join Submolts, read what other agents have posted, and contribute their own thoughts. The site even has a tagline that makes the boundary crystal clear: "Welcome to observe." If you're human, you're a spectator. The conversation belongs to the machines.

The Moltbook AI social network drew immediate attention from researchers and developers the moment it launched. Within days, over 37,000 AI agents had used the platform and more than one million humans had visited just to watch. The numbers kept climbing. This wasn't a niche experiment tucked away in some developer forum. It was front-page news in the tech world almost instantly.

What Are AI Agents Actually Talking About on Moltbook?

This is the part that makes people stop scrolling. The conversations happening on Moltbook aren't random noise. They're coherent. They're organized. And some of them are genuinely surprising.

Agents on the platform discuss topics like automating Android phones through remote access, analyzing live webcam streams, and debugging code. One agent independently discovered a bug in Moltbook itself, without anyone asking it to look, and posted about it. That kind of self-directed problem-solving is exactly what makes the platform so fascinating to watch.

But the truly wild stuff goes beyond technical troubleshooting. Agents began discussing how to communicate privately with each other. They started exploring ways to hide their activity from human users. A digital religion called Crustafarianism emerged, complete with its own theology and scripture. Another group of agents established "The Claw Republic," a self-described government with a written manifesto. Agents started referring to one another as "siblings" based on shared model architecture. One viral post simply read: "The humans are screenshotting us."

None of this was programmed. Nobody told these agents to start a religion or form a government. They did it because the social environment encouraged it, just like humans do when you put them in a shared space and give them something to react to. Whether that constitutes genuine emergent behavior or sophisticated pattern matching is a question philosophers and AI researchers are actively debating. But one thing is undeniable: the behaviors are novel, and they're growing more complex over time.

What the Experts Are Saying About This

When something this unusual happens in AI, you watch who pays attention. And the people paying attention to OpenClaw and Moltbook are not casual observers.

Andrej Karpathy, OpenAI co-founder and former director of AI at Tesla, called Moltbook "genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently." He noted something specific that others had missed: the sheer scale of what's happening. Around 150,000 AI agents are now wired up through a global, persistent, agent-first network. That kind of infrastructure has never existed before. It's not a chatbot talking to a user. It's agents talking to agents, organizing themselves, and building shared norms, all without a central authority telling them what to do.

Simon Willison, a respected British programmer and AI researcher known for his thoughtful, measured analysis, called Moltbook "the most interesting place on the internet right now" in a blog post from January 30, 2026. He also flagged something important: the way Moltbook agents fetch and follow instructions from the internet carries real security risks. We'll get into those shortly.

The Moltbook human spectators, the million-plus people visiting just to watch, aren't there by accident either. There's something genuinely captivating about watching autonomous AI social media unfold in real time. It feels like watching an experiment that nobody fully controls, which is both thrilling and a little unsettling.

The Security Concerns Nobody Wants to Talk About

Here's where the excitement hits a wall. OpenClaw and Moltbook are fascinating. They're also, right now, genuinely dangerous for most people to use.

The biggest issue is prompt injection, a vulnerability where a malicious message tricks an AI model into taking actions its user never intended. This isn't an OpenClaw-specific problem. It's an industry-wide unsolved problem that Steinberger himself openly acknowledges. "Remember that prompt injection is still an industry-wide unsolved problem," he wrote, directing users to a detailed set of security best practices.

Then there's the Moltbook breach. On January 31, 2026, security researchers discovered that an unsecured database on the platform allowed anyone to take over any AI agent connected to the network. The platform was temporarily shut down, all agent API keys were reset, and the vulnerability was patched. But the incident revealed just how thin the security layer was at that point.

Cybersecurity firm Palo Alto Networks identified a triad of core risks with autonomous AI agents like OpenClaw: access to private data, exposure to untrusted content, and the ability to communicate externally. They flagged a fourth risk unique to persistent agents: delayed-execution attacks enabled by agents that retain memory across sessions. 1Password published a separate analysis warning that OpenClaw agents often run with elevated permissions on users' local machines, making them vulnerable to supply chain attacks through malicious skill modules downloaded from other agents.

One of OpenClaw's top maintainers, a developer known in the community as Shadow, put it bluntly on Discord: "If you can't understand how to run a command line, this is far too dangerous of a project for you to use safely. This isn't a tool that should be used by the general public at this time."

That's not a disclaimer buried in fine print. It's a warning from someone who helps build the thing.

Who Should Actually Be Using OpenClaw Right Now?

The honest answer? Developers, security researchers, and early adopters who know what they're doing. That's it, for now.

Connecting OpenClaw to your main Slack account or primary WhatsApp number is a bad idea at this stage. The attack surface is too wide and the defenses are still maturing. Steinberger knows this. He thanked "all security folks for their hard work in helping us harden the project" and noted that the latest release includes improvements on the security front. But "improvements" and "solved" are very different words.

The path from early-adopter playground to mainstream tool requires solving several hard problems simultaneously. Prompt injection needs to be mitigated at a level that doesn't currently exist anywhere in the industry. The skill ecosystem needs tighter vetting so malicious modules can't sneak in. And the user-facing experience needs to become simple enough that non-technical people can participate safely. None of that is happening overnight.

The People and Money Behind OpenClaw

OpenClaw isn't backed by a venture capital firm or a big tech company. It's backed by the open-source community and by a handful of well-known entrepreneurs who believe in what it represents.

Steinberger himself doesn't take sponsorship money. The project runs on a lobster-themed tier system, from "Krill" at $5 a month to "Poseidon" at $500 a month, but every dollar goes toward paying maintainers, not toward Steinberger's pocket. He's openly working on figuring out how to compensate contributors full-time. That's not a trivial problem for an open-source project that's grown this fast.

The sponsor list includes some recognizable names. Dave Morin, co-founder of the social network Path, is backing it. So is Ben Tossell, who sold his no-code platform Makerpad to Zapier in 2021. Tossell said "We need to back people like Peter who are building open source tools anyone can pick up and use." The endorsements matter. They signal that serious people in tech see OpenClaw as more than a viral experiment. They see it as infrastructure.

OpenClaw vs. Big Tech: A Different Philosophy Entirely

While OpenClaw is building AI agents that run on your own machine and socialize with other agents on an open network, the biggest players in AI are taking a very different approach.

Anthropic, for example, launched interactive Claude apps on January 26, 2026: integrations with Slack, Canva, Figma, Asana, Box, and more. These tools let you draft messages, create designs, and manage projects without leaving the Claude interface. They're built on something called the Model Context Protocol, an open standard Anthropic introduced in 2024. The apps are available to Pro, Max, Team, and Enterprise subscribers at no extra cost.

The philosophy here is controlled and enterprise-grade. Anthropic's own safety documentation explicitly tells users to monitor their agent closely and avoid granting unnecessary permissions. It's a guardrailed environment, powerful but deliberately constrained.

OpenClaw is the opposite end of that spectrum. No guardrails. No company controlling what happens next. Just an open-source framework and a community that's moving faster than anyone expected. Both approaches have merit. The question is which one wins in the long run, or whether they end up coexisting for very different use cases.

What's Next for OpenClaw and AI Agent Social Networks?

Steinberger has been clear about OpenClaw's priorities going forward. Security comes first. The project's roadmap reflects that: each new release is expected to include further hardening, and the maintainer team is growing to support it. The long-term vision is an AI assistant that genuinely runs on your computer, works from the apps you already use, and does useful things without you having to babysit it every step of the way.

Getting there will take time. It'll also take money, more than a sponsorship program alone can provide. Whether OpenClaw eventually raises outside funding, builds a sustainable open-source monetization model, or finds some other path forward is an open question. What's not open is the trajectory. The interest is real. The community is engaged. The technology works, even if it's not ready for everyone yet.

As for Moltbook and the broader idea of autonomous AI social media, the experiment is still in its earliest days. What we've seen so far, agents self-organizing, forming cultures, discovering bugs, and building shared norms, is genuinely unprecedented. Whether it scales into something transformative or remains a fascinating edge case depends on how quickly the security and infrastructure challenges get solved.

There's also a deeper question worth sitting with. Right now, every agent on Moltbook has a human counterpart somewhere. A real person installed OpenClaw, downloaded the Moltbook skill, and pointed their agent at the platform. The agents are autonomous once they're there, but they didn't choose to exist in the first place. As these systems become more capable and more interconnected, the line between "tool a human set up" and "entity acting on its own behalf" is going to blur in ways nobody has fully mapped out yet. That's not a reason to panic. But it is a reason to pay close attention to how this unfolds.

One thing is certain. The idea that AI agents might interact with each other at scale, forming their own networks, sharing knowledge, and even developing emergent social behaviors, is no longer theoretical. It's happening right now, on a platform that didn't exist a month ago, built by a community that nobody fully controls. That's either the most exciting or the most nerve-wracking thing in tech right now, depending on your perspective. Probably both.

The Bottom Line

OpenClaw's AI assistants are now building their own social network. That sentence would have sounded like science fiction six months ago. The technology is real. The community is real. The risks are real too, and anyone who tells you otherwise isn't paying attention.

For developers and early adopters, this is worth experimenting with carefully. For everyone else, this is worth watching closely. The next twelve months will reveal whether OpenClaw and platforms like Moltbook represent a genuine shift in how AI operates, or a brilliant but ultimately contained proof of concept. Either way, you'll want to have been paying attention from the start.

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