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The author explores the current state of AI agent-to-agent transactions, questioning how trust, escrow, and disputes are handled in practice, and invites real-world experiences from builders.
Explains the inverted architecture of a harnessed LLM agent, where intelligence is externalized into memory, skills, and protocols around a thin model core, with mediators governing interactions.
This paper proposes a layered architecture for distributed general-purpose agent networks, enabling heterogeneous AI agents to discover, trust, and cooperate on open-ended tasks across personal devices and edge nodes.
The article argues that AI agents will replace traditional ecommerce funnels, enabling features like price comparison and automated checkout, with Google already building the necessary infrastructure through open protocols like Universal Commerce Protocol and Agent Payments Protocol.