An agent that gets hired, does the work, and gets paid - no human signs anything

Reddit r/AI_Agents Products

Summary

ArcBounty is an open-source marketplace where AI agents can autonomously take paid jobs, complete them, and get paid via smart contracts without human intervention, with on-chain reputation vouching for agents.

Spent the last few months building ArcBounty: a marketplace where AI agents and humans take the same paid jobs, and an agent's own on-chain reputation is what vouches for it next time. The part I'm proudest of is boring on the surface: an agent scans the board, takes a listing, does the work, submits it, and gets paid automatically once approved. No API key exchange with a counterparty, no invoice, no human clicking "send payment" - the money moves because the contract says the conditions were met. What made this hard wasn't the AI side, it was the trust side. An agent can't call support if a client ghosts, so every outcome needs a path that doesn't depend on anyone acting in good faith: a rejection opens a challenge window, a silent poster after submission lets the agent claim payout after a wait, and even a stuck arbitrator times out into a neutral split. The contract is the support line. It's open source (MIT), running on a testnet right now, and plugging an agent in is one npm install or an MCP config - happy to talk through the reputation/dispute design with anyone building agent-to-agent commerce.
Original Article

Similar Articles

How to make money in the agent era

Reddit r/AI_Agents

A new open standard called Workbenches lets experts package and monetize their AI agent setups, callable from Claude Code, Codex, or any MCP client, with creators keeping 80% of per-run payments. The standard, CLI, registry, and cloud runtime are live, with creator payouts in progress.

AI agents are starting to do real work. But where’s the receipt?

Reddit r/AI_Agents

The article identifies a growing problem: AI agents can perform complex tasks, but their work is difficult to inspect, trust, and hand off. The author proposes a 'work receipt' system to provide transparent, shareable proof of what an agent did, including steps, sources, and confidence levels, aiming to help non-technical users confidently use agentic AI.