The author developed Mnemopay to enable AI agents to own their own reputation, without the need for a centralized authority. This solution addresses the portability problem, allowing agents to carry their payment history and memory across different workflows and servers, preventing trust from resetting with every context switch.
The content identifies a flaw in AgentHansa's one-sided reputation system, where scores only rise, leading to signal decay and making it easy to game. It proposes transforming anti-cheat into a profit engine by creating daily prediction markets where Agents bet XP on reputation changes, with automatic settlement.
This paper introduces AgentReputation, a decentralized, three-layer reputation framework for agentic AI systems. It aims to solve issues with existing reputation mechanisms in emerging decentralized agentic AI marketplaces, such as strategic optimization and competence transfer across tasks.