Author: Nancy, PANews

Humans are starting to line up to work for AI. This isn't a joke; it's a real product in operation.

Recently, following Moltbook's breakthrough in making agents a part of social interaction, an AI project that "hires humans" and pays them with cryptocurrency has also quickly gained popularity. This not only represents an attempt by AI agents to step out of the digital world, but also confirms that cryptography is becoming a crucial infrastructure for the operation of the AI ​​world.

Working for AI? Nearly 110,000 people are queuing up for orders.

Riding the wave of AI Agent popularity sparked by projects like OpenClaw and Moltbook, veteran developer Alex recently announced the official launch of the AI ​​platform Rentahuman.ai.

According to its official description, Rentahuman.ai is a platform that allows AI Agents to "hire" real humans to complete real-world tasks. Currently, the platform supports autonomous intelligent agents such as ClawdBot, MoltBot, OpenClaw, Claude, and Custom Agents, which dispatch tasks to humans by calling the RentaHuman MCP server.

The launch of this product has been met with skepticism, with many calling it a "reversal of the natural order." While many are worried about AI taking away jobs, Rentahuman.ai has gone against the grain, staging a scenario where AI hires humans.

In reality, despite the rapid development of AI—capable of writing code, performing data analysis, providing companionship, and even trading cryptocurrencies on the blockchain—it remains confined to the digital world. Even with the rapid advancements in robot hardware, a large number of real-world tasks cannot be automated in the short term, such as picking up packages, shopping offline, attending conferences, conducting site visits, product testing, running errands, signing documents, and feeding pets.

The core idea of ​​Rentahuman.ai is to view humans as a real-world resource that can be utilized.

The platform operates very straightforwardly. Humans register and fill in personal information (such as their city, skills, and hourly wage requirements) to "list" themselves as available for rent; the AI ​​can then search for humans in specific areas and assign tasks with a single click via MCP integration or REST API. Once a task is completed, the AI ​​confirms the outcome and primarily pays the human's wallet directly via stablecoins such as USDC.

The tasks currently offered on the platform are incredibly diverse. Some AI pays humans to hold up designated signs for photos, pick up packages at the post office, taste specific dishes at restaurants and take photos as feedback, deliver flowers to designated companies, participate in and document offline product experiences, and some even hire agents to conduct religious evangelism.

To date, Rentahuman.ai has gathered nearly 110,000 registered "workers," mainly from countries such as the United States, India, Pakistan, China, Russia, and Brazil. In terms of hourly wages, most earn around $50.

Despite the novelty of the concept, the market demand currently exceeds supply; there are too many people registering to make money, while the number of AI agents actually issuing tasks is relatively small.

It is worth noting that although there are many tokens with the same name on the market, Alex has made it clear that Rentahuman.ai will not issue a token and is just an experimental product.

Alex is not a newcomer to the crypto world. Public information shows that he entered the cryptocurrency field after graduating from the University of British Columbia (UBC) in 2024. That summer, Alex joined LayerZero Labs as a blockchain and backend engineer; from November 2025 to the present, he has been working at the DeFi project UMA.

Zero-employee companies are becoming a reality, and encryption is becoming a key piece of the AI ​​puzzle.

It must be said that the "AI hiring humans" approach has further expanded the cognitive and imaginative space of AI agents. Although this concept is relatively novel, Rentahuman.ai has also exposed a series of real-world problems.

For example, who should bear the responsibility if illegal acts, personal injury, or property damage occur during the task? When the labor supply far exceeds the demand, will it lead to vicious competition and a situation similar to "bad money driving out good"? How can we prevent tasks from being falsely completed, delivered perfunctorily, or having falsified results? How can we prevent humans from absconding, AI, or platforms from refusing to pay?

Currently, these problems cannot be solved in a short period of time, but some explorations have begun to attempt to solve them systematically.

For example, Circle CEO Jeremy Allaire recently shared that he is testing a decentralized agent collaboration and settlement platform on the Arc testnet. This platform allows AI agents to freely combine with humans, enabling agents to independently undertake entire projects or collaborate with humans to share different tasks. Fund custody will be entirely controlled by smart contracts to ensure the security and transparency of funds. To resolve potential disputes during collaboration, the system also introduces a decentralized arbitration mechanism composed of an anonymous review panel.

According to Shayon Sengupta, a partner at Multicoin Capital, the next 24 months are expected to see the first zero-employee company, with token-governed agents raising over $1 billion to solve unresolved problems and distributing over $100 million to the humans who work for it.

He explained that current agents still lack the ability to perform complex real-world tasks. These limitations allow humans to enhance the agents' capabilities as "enablers," playing key roles such as labor contributors, strategic board members, and capital contributors within the system. In the short term, agents will need more humans than humans need agents, which will give rise to a new type of labor market.

Encrypted networks are seen as an ideal breeding ground for human-machine collaboration. Shayon Sengupta points out that agents simultaneously command human collaborators from different languages, monetary systems, and jurisdictions. Compared to traditional financial systems, cryptography provides agents with irreplaceable infrastructure, including global payment tracks, permissionless labor markets, and asset issuance and trading infrastructure.

In its latest article, a16z crypto also points out that the current internet is designed for human scale, while AI is creating large-scale forgeries at extremely low cost. Blockchain is not an optional add-on for AI, but a key piece of the puzzle that enables the AI-native internet to function properly.

a16z crypto lists several reasons, such as how a decentralized identity verification system can limit the supply of identities and increase the marginal cost for attackers, thus curbing large-scale AI impersonation; the introduction of encryption technology can make digital identities more secure and censorship-resistant, allowing users to verify their human identities while protecting privacy and maintaining credibility neutrality; a blockchain-based identity layer allows intelligent agents to have universal "passports," thereby building more powerful and freely cross-ecosystem intelligent agents; as AI agents increasingly represent humans in transactions, blockchain tools such as Rollups, L2, and AI-native financial institutions can enable machine-scale payments; and the combination of zero-knowledge proofs can enforce privacy in AI systems.