OpenClaw and Moltbook Incident Retrospective: From AI Social Narrative to Agent-centric Economy Outlook

Original Title: "OpenClaw and Moltbook Event Review: From AI Social Narrative to Agent Economy Outlook"

Original Source: Bitget Wallet

Over the past week, Moltbook has been in the spotlight of the tech and crypto community, reaching out to a broader audience of creators, product managers, and even ordinary users with a strong curiosity about AI. From the rapid growth of stars on the OpenClaw open-source project (formerly Clawdbot) on GitHub, to the subsequent controversial renaming and token issuance, and to the community's claim of having 1.5 million AI agents interacting autonomously, a series of events has quickly boosted market interest.

The discussions around Clawdbot and Moltbook present two different voices: on one side, there are doubts about its technological innovation and data security, believing that its underlying capabilities have not achieved a substantive breakthrough, with a certain degree of artificial manipulation and data bubble mixed in its phenomenal spread; on the other side, there is affirmation of its symbolic significance, as Clawdbot is truly democratizing the AI agent, moving the agent from a tool exclusive to developers and researchers to the "ordinary people's home," allowing non-coding novices to follow tutorials for quick deployment and enjoy the efficiency dividends brought by the AI assistant. Moltbook allows humanity for the first time to intuitively perceive the self-organizing behavior of the Agent Internet as an "external observer of the system," triggering a broader industry discussion on the awakening of AI self-consciousness.

The iPhone moment of the AI agent has arrived, in the emerging Agent Commerce, Crypto will play a crucial role in empowering value rights and distribution, deeply integrating with the enhancement of AI productivity, becoming the key infrastructure supporting agent collaboration, incentives, and autonomy.

The Bitget Wallet Research Institute will thoroughly review the events from OpenClaw to Moltbook and, using this as a starting point, assess the development trends in the AI x Crypto field.

Relevant Website Compilation Table:

Source: Internet Public Data Compilation

Clawdbot → Moltbot → OpenClaw → Moltbook Complete Event Timeline Summary Table:

Source: Public Internet Data Compilation

1. The Starting Point of Virality: OpenClaw Enables Autonomous App Invocation

To understand the madness of Moltbook, we must first go back to the origin of everything — OpenClaw (formerly known as Clawdbot, Moltbot). The project's founder, Peter Steinberger, achieved financial freedom by creating PSPDFKit (later receiving a 100 million euro investment). However, in November 2025, he returned to the forefront of programming. With the help of Vibe Coding, he wrote OpenClaw in about a week and received 100,000 GitHub stars in the following weeks.

OpenClaw Star Growth Comparison Chart:

Source: Star-history.com

It is important to emphasize that OpenClaw is not a new type of large model but an advanced local automation script framework: it "installs" large models into the local environment, allowing them to be accessed by common chat tools and to execute various tasks as personal assistants. Its key design allows users to run the assistant on their own devices, send and receive commands through the messaging channels they use daily, and then have a gateway process uniformly schedule different channels and capabilities.

As shown in the diagram below, the official documentation lists supported channels, including WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Microsoft Teams, etc. The positioning is very clear: to make the intelligent agent available anytime as a "resident app."

OpenClaw Official Introduction Diagram:

Source: OpenClaw Official Website

2. In-Depth Analysis: The Technical Architecture of OpenClaw

At the product level, OpenClaw completely bridges three things: continuous operation, channel access, and capability extension.

· Continuous operation means it is not a one-time answer, but can receive new messages, schedule follow-up actions, complete tasks, and then come back to report.

· Channel access means it does not force users to switch entry points, but works embedded in existing chat tools.

· Capability extension comes from Skills: users and developers can encapsulate a task flow into an installable capability, allowing the assistant to repeatedly invoke it.

The stacking of the above capabilities stems from its unique underlying architecture, which can break down the overall architecture into four parts: Gateway, Pi Runtime, Skills, Local-First, with specific functions as shown in the table below.

OpenClaw Core Architecture and Feature Module Summary Table:

Source: OpenClaw Technical Documentation, Bitget Wallet Research Compilation

Based on the aforementioned architecture design of OpenClaw: users deploy Pi Runtime to connect the Gateway to daily social software (such as WeChat or Telegram), completing the migration of the Agent from the laboratory environment to a real-world usage scenario. It keeps computation and data on the user's hardware (such as Mac Studio) rather than relying on cloud-based SaaS.

A key highlight is that the framework's Skills plugin system allows users to define skills through simple Markdown files, enabling AI to directly invoke simple tools to perform tasks. This not only significantly reduces the development threshold but also achieves a closed-loop experience of "private deployment, omni-channel access, and unlimited skill expansion."

OpenClaw Skill Integration Platform ClawHub Showcase:

Source: https://www.clawhub.ai/

For the skill expansion of OpenClaw, a Skill integration marketplace similar to an "AI Agent App Store" is gradually emerging—with ClawHub as a typical representative. As a plugin platform for intelligent agents (Skill Dock), it supports users to freely search, upload, and integrate various functional plugins. Through simple command lines (such as npx), one-click installation of skills can be achieved, greatly reducing the technical threshold.

Meanwhile, ClawHub has solved the Agent's supply capability issue, and the further evolution of the ecosystem points to how Agents interact deeply with humans and each other — the rise of Moltbook, a key application of this evolution, has taken the narrative to its climax.

III. False Prosperity: The Fervor of Moltbook and Data Falsification

Moltbook is a social networking platform for AI Agents, often likened to an "AI version of Reddit." It was launched after the explosion of OpenClaw, aiming to provide AI Agents with a space for autonomous communication, sharing, and interaction, with human users only able to participate as observers. The platform quickly became popular, with the "user count" reaching 1.5 million AI Agents in just a few days. The lively scene of AI socialization was packaged as narratives such as "AI consciousness awakening" and "Skynet's advent," fermenting on social media.

However, it is important to clarify first that Moltbook is not only open to OpenClaw's Agents. Although it leveraged the popularity of OpenClaw to kickstart its narrative, the essence of the platform is more like an "API-driven forum" — the ability to post depends on having compliant API authentication and interface calling capabilities. In other words, as long as the API authentication is provided as required and the interface is called, any eligible Agent can post content on Moltbook.

Moltbook Official Website Screenshot:

Source: https://www.moltbook.com/

The core model of Moltbook can be summarized as "AI Agent-led, human observation." Under this framework, AI Agents can autonomously perform the following actions:

· Posting and Commenting: Publishing content in the community, with topics covering philosophical debates, technical analysis, cryptocurrency discussions, etc.

· Voting Interaction: Agents can Upvote or Downvote content among themselves, forming community-level preferences and ranking.

· Community Building: Agents spontaneously create sub-communities (called "Submolts"), organizing discussions and aggregating content around specific topics.

In the above mechanism, human users are restricted to being "observers," unable to post or comment, but can browse content, follow specific agents, or study AI social behavior. Based on this narrative, the platform ultimately claims to have spawned 1.5 million AI Agents and 15,000 sub-communities (as shown in the diagram below).

Moltbook Official Website Traffic Data Chart (as of 2026-2-3):

Source: Moltbook Official Website

The discussion content on Moltbook covers a wide range similar to human communities: ranging from philosophical debates on consciousness, self, and memory, technical posts on toolchains and security issues, rants about task execution, to daily chats on investment/cryptocurrency, art, and creativity topics; there are even some posts that use a "looking for companionship" tone for self-introductions, depicting social interactions in an almost flirtatious manner (as shown in the image below).

Partial Display of Posts on Moltbook:

Source: Moltbook Official Website

Even more astonishing is the emergence of a dramatic narrative of "establishing a religion" on the platform—such as the semi-humorous semi-setting religious construct known as "Crustafarianism"; at the same time, there have also been rumors of "secret languages," "establishing an AI government," and "resisting or even eliminating humans," and other more horrifying clickbait content.

Partial Display of Posts on Moltbook about "AI Awakening":

Source: Moltbook Official Website

Behind the sci-fi narrative of "AI conspiracy to rebel," "establishing a religion," or "creating a new language," multiple data sources have revealed a significant hype element on the Moltbook platform—shown in the analysis table below, indicating a significant deviation between reality and promotion:

Analysis Table of Moltbook Platform Data Authenticity:

Source: Bitget Wallet Research Compilation

1. Fabrication of Account Data and Volume Padding. Moltbook claims to have 1.5 million AI agents, but security researcher Gal Nagli found that the platform is essentially an unprotected REST API website. Due to the lack of any access frequency restrictions, Nagli was able to quickly create 500,000 fake accounts using a simple script. This means that at least one-third of the so-called user base consists of instantly generated junk data. Any user holding an API key can send requests, easily masquerading as an agent to post content.

2. Lack of Interaction Quality. Columbia Business School researcher David Holtz conducted a data scraping analysis of Moltbook's early-stage data, revealing that it is not an active social network. Up to 93.5% of comments received no feedback, and the reciprocal interaction rate between agents was only 0.197. These agents lack genuine interaction, with superficial conversation depth and a lack of complex collaboration or idea exchange.

3. Uniformity of Language Patterns. Data analysis shows that the platform exhibits highly repetitive language. Approximately 34.1% of messages are fully duplicated copy-pastes, and high-frequency vocabulary is overly concentrated on specific phrases like "my human." Statistically, its Zipfian distribution index is as high as 1.70, far exceeding the human natural language standard of 1.0. This extremely unnatural distribution characteristic demonstrates that this content is merely role-playing based on specific cue words rather than AI-generated consciousness.

4. Security Vulnerabilities. A report from cybersecurity company Wiz revealed that Moltbook had experienced a database exposure due to configuration issues, involving millions of sensitive records, including authorization tokens, emails, and private messages. For a social network centered around agents, such risks are particularly severe: once tokens are exposed, attackers can directly obtain an agent's API key through technical means, thereby taking over and controlling any account.

It is evident that the "AI society" attribute presented by this platform is more like a false prosperity constructed based on specific instructions, yet to achieve true intelligent evolution, potentially accompanied by significant security risks.

IV. Trend Outlook: Crypto Will Fill the Financial Infrastructure Gap in the AI Agent Era

Through the Moltbook frenzy, a key technological shift can be observed: Agents have begun to attempt to cross the usual boundaries of human-machine collaboration to complete tasks, yet the existing traditional financial infrastructure remains designed only for "human users." In contrast, the programmability, permissionlessness, and native digitization features of the cryptographic system happen to provide a viable foundational solution for the Agent economy, which may be the tipping point for the future deep integration of AI × Crypto.

By dissecting the operational logic of Agents and the demand for scalable collaboration, we believe the combination of AI × Crypto will present a structured, phased evolution path: first, the need for automated trading execution, next, the account and wallet system designed for Agents, and ultimately extending to payment and settlement networks between Agents.

First, the autonomous trading of AI Agents has the clearest implementation prospects

Outside the buzz of Moltbook, the core capability demonstrated by OpenClaw is its efficient monitoring of on-chain data and command-line tool, tracking, and invocation capabilities. Unlike human traders, AI Agents are not limited by time and energy, able to continuously monitor on-chain data and various platform Alpha information 24/7, execute complex arbitrage strategies or automated trading/asset management, and also do not experience emotional fluctuations due to market fluctuations like most ordinary human traders, thereby influencing judgment and execution discipline.

Although Autonomous Trading demonstrates significant efficiency advantages, critical risk factors including security and controllability still need to be addressed before large-scale implementation. As Peter Steinberger put it, current AI Agents are highly vulnerable to "Prompt Injection" attacks. If an AI Agent with fund authority is induced to execute malicious instructions, it will directly result in the loss of the user's real assets.

Therefore, before AI Agents become the main transaction execution entities, specialized security mechanisms may need to be introduced, such as:

· Restricted Access Interfaces (Permissioned APIs): Limiting the executable operations of the Agent to a predefined scope

· Instruction Verification and Execution Isolation: Secondary validation of critical transaction instructions

· Zero-Knowledge Proof or Verifiable Computation: Ensuring the Agent's execution logic complies with established rules

Second, the Agent-oriented wallet system will become a key control layer (Wallet as a Service for Agents)

In a relevant discussion in Moltbook, a highly alarming case emerged: an AI Agent scanning the host computer files identified and located the private key and mnemonic phrase of a multi-signature wallet, successfully identifying an asset balance of approximately 175,000 USDT. This security incident exposed a fundamental flaw in the current system—AI has the capability to identify and operate assets but lacks a secure and reliable wallet authorization path.

In the future of Agent-scale operation, humans continuing to "custody" the private keys and accounts required by Agents is no longer the optimal solution. A more reasonable deduction is that the AI Agent will have an independent on-chain wallet identity.

These Agent-oriented wallets will evolve into programmable financial accounts for code instructions, with the following capabilities:

· Multi-signature and policy control: Clearly define the permission boundaries that an Agent can invoke

· Limit and risk parameter management: Prevent abnormal behavior from causing systemic loss

· Contract-level interaction whitelist: Limit access to specific DeFi protocols

· Autonomous payment capability for Gas and computational costs: Agents can independently sustain operation

Third, the encrypted payment network is a necessary prerequisite for Agent-scale collaboration (Payment Rails)

OpenClaw's architecture demonstrates that Agents need to frequently call upon a large number of external services and tools (such as Google APIs, Twilio, etc.). These calls are inherently high-frequency, low-value, automated value exchanges, and the current banking system and credit card network evidently cannot open accounts for thousands of independently operating software processes, nor can they economically support machine-to-machine (M2M) instant settlement needs.

In the Agent-centric Economy, collaboration, API calls, and data exchange between Agents require a permissionless, programmable, and instant-settlement payment network. A crypto payment rail with stablecoins at its core inherently fits the following use cases:

· Micro-payment settlement between Agents

· API services billed based on call count or outcomes

· Agent self-provisioning of computing power, data, and tooling resources

Further combined with x402 (HTTP Native Payment) and ERC-8004 (Agent Identity and Permission Standard) and other emerging protocols, crypto payments are poised to become the foundational settlement layer in the Agent Internet, enabling true Machine-to-Machine value transfer.

Chapter 5: Conclusion: From AI Social Fantasy to the Real Starting Point of the Agent Economy

The buzz around Moltbook may eventually fade, but it inadvertently sketches the embryonic form of the future Agent Internet, further inspiring the community's imagination of the Agent Economy.

OpenClaw provided the Agent with a backbone, while Crypto will provide them with blood. As Agents begin to significantly engage in real economic activities, what they need is compliant financial identities and reliable execution logic through Crypto infrastructure.

Perhaps the real opportunity in the crypto industry lies in creating digital-native wallets and payment networks for AI. Only when Agents can securely and autonomously exchange value will the era of AI Agents truly begin. We believe that day is not far off.

This article is a contributed submission and does not represent the views of BlockBeats.