Author: Nancy, PANews
Humans have started queuing up to work for AI. This is not a joke, but a product that is actually running.
Recently, following Moltbook's success in making Agent social interactions popular, an AI project that "employs humans" and pays rewards in cryptocurrency has also quickly gained traction. This is not only an attempt by AI Agents to step out of the digital world but also proof that encryption is becoming a critical infrastructure for the operation of the AI world.
Working for AI? Nearly 110,000 People Queueing for Task Assignments
Riding the wave of AI Agent热潮 (boom) sparked by projects like OpenClaw and Moltbook, veteran developer Alex recently announced the official launch of the AI platform Rentahuman.ai.
According to the official introduction, Rentahuman.ai is a platform that allows AI Agents to "hire" real humans to complete real-world tasks. Currently, the platform supports autonomous agents like ClawdBot, MoltBot, OpenClaw, Claude, and Custom Agents, which dispatch tasks to humans by calling the RentAHuman MCP server.
The launch of this product has also left the outside world exclaiming "the world is turned upside down." While many people are generally anxious about "AI stealing jobs," Rentahuman.ai does the opposite, staging a drama of "AI employing humans."
In fact, although AI's development is rapid—capable of writing code, performing data analysis, chatting, and even trading on-chain—they remain trapped in the digital world. Even though robotics hardware is advancing quickly, there are still a large number of tasks in the real world that cannot be automated in the short term, such as picking up packages, offline shopping, attending meetings, physical inspections, product testing, running errands to buy things, signing documents, and pet feeding.
The core idea of Rentahuman.ai is to treat humans as a real-world resource that can be called upon.
The platform operates in a straightforward manner. Humans can register and fill out personal profiles (such as city, skills, and hourly rate requirements) to "list" themselves as available for rent; AI can then use MCP integration or REST API to search for humans in specific areas and dispatch tasks with one click. After task completion, the results are confirmed by the AI, and payment is made directly to the human's wallet, primarily using stablecoins like USDC.
The tasks already published on the platform are also diverse. Examples include an AI paying a human to hold a specified sign and take a photo, pick up a package from the post office, try a specific dish at a restaurant and provide photo feedback, send flowers to a designated company, participate in offline product experiences and record them, and even an Agent hiring a human for religious preaching.
As of now, Rentahuman.ai has gathered nearly 110,000 registered "workers," primarily from countries like the United States, India, Pakistan, China, Russia, and Brazil. In terms of hourly rates, most are around 50 USD.
Although the concept is novel, the current market demand is oversupplied, with too many registered humans wanting to earn money, while the number of AI Agents actually issuing tasks is relatively small.
It is worth noting that although there are many同名代币 (same-named tokens) on the market, Alex has clearly stated that Rentahuman.ai will not issue a token and is just an experimental product.
Alex is not a new face in the crypto space. Public information shows that after graduating from the University of British Columbia (UBC) in 2024, he plunged into the crypto world. In the summer of the same year, 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 Becoming a Reality, Crypto a Key Piece of the AI Puzzle
It must be said that the "AI employing humans"玩法 (play/gameplay) further expands the认知 (cognition/understanding) and imagination of AI Agents. Although this concept is quite novel, Rentahuman.ai also exposes a series of practical problems.
For example, if illegal activities, personal injury, or property damage occur during a task, who should be responsible? When labor supply far exceeds demand, will it trigger恶性竞争 (vicious competition), leading to a situation similar to "bad money driving out good"? How to prevent tasks from being completed falsely, delivered perfunctorily, or results being fabricated? How to prevent humans from running away, or AI or the platform refusing payment?
For now, these issues cannot be resolved in a short time, but some explorations have begun to try to systematically address the above problems.
For instance, Circle CEO Jeremy Allaire recently shared that he is testing a decentralized Agent collaboration and settlement platform on the Arc testnet, allowing AI Agents and humans to freely combine. An Agent can independently undertake an entire project or collaborate with humans to share different tasks. Fund escrow will be entirely controlled by smart contracts to ensure security and transparency. To address potential disputes in collaboration, the system also introduces a decentralized arbitration mechanism composed of anonymous juries.
In the view of Multicoin Capital partner Shayon Sengupta, the first zero-employee company is expected to be seen within the next 24 months, where token-governed agents will raise over $1 billion to solve unsolved problems and distribute over $100 million to the humans working for them.
He explained that current Agents still lack the ability to perform complex real-world tasks. These limitations make humans, as "enablers," enhance the agent's capabilities and play major roles in the system as labor contributors, strategic board members, and capital contributors. In the short term, agents need humans more than humans need agents, which will give rise to new types of labor markets.
Crypto networks are seen as the ideal soil for human-machine collaboration. Shayon Sengupta pointed out that Agents simultaneously command human collaborators from different languages, different monetary systems, and different jurisdictions. Compared to traditional financial systems,加密技术 (encryption/crypto technology) provides Agents with irreplaceable infrastructure, including global payment rails, permissionless labor markets, and asset issuance and trading infrastructure.
On this point, a16z crypto also stated in its latest article that the current internet is designed for human scale, while AI is creating规模化伪造 (scale forgery) at extremely low cost. Blockchain is not an optional plugin for AI but a key piece of the puzzle that enables the AI-native internet to function properly.
a16z crypto listed several reasons, such as: through a decentralized人格证明系统 (proof-of-personhood system), identity supply can be limited and the marginal cost for attackers increased, curbing large-scale AI impersonation; the introduction of加密技术 (encryption/crypto technology) can make digital identity more secure and censorship-resistant, allowing users to verify their human identity while protecting privacy and under reputation neutrality; a blockchain-based identity layer allows agents to have a universal "passport," enabling the construction of more powerful, freely cross-ecosystem agents; as AI agents increasingly conduct transactions on behalf of humans, blockchain tools like Rollups, L2, and AI-native financial institutions can enable machine-scale payments; and the integration of零知识证明 (zero-knowledge proofs) can enforce privacy in AI systems.
