Foundation Protocol: A Coordination Layer for Agentic Society
Quick Answer
This paper shows that The Foundation Protocol (FP) introduces a graph-first coordination layer for autonomous agents, enabling reliable relationships and multi-agent collaboration in a human-AI society.
Quick Take
The Foundation Protocol (FP) introduces a graph-first coordination layer for autonomous agents, enabling reliable relationships and collaboration in a human-AI society. It focuses on economic primitives, accountability, and integration with existing protocols to foster a pluralistic and governable AI economy.
Key Points
- FP unifies agents, tools, resources, and humans for enhanced collaboration.
- It provides economic primitives for metering, receipts, and settlement.
- The protocol supports multi-party organization and event-based collaboration.
- FP aims to maintain accountability while enabling composable agency.
- Designed for incremental adoption, it reduces integration and governance overhead.
Paper Resources
Article Content
From source RSS / original summaryarXiv:2605. 23218v1 Announce Type: new Abstract: Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. As these systems scale, the bottleneck shifts away from raw model capability toward coordination. Agents need to form reliable relationships, organize work, exchange value, support an AI economy, and stay safe and accountable under real-world oversight.
This paper introduces the Foundation Protocol (FP), a graph-first coordination layer for an emerging human-AI society. FP unifies heterogeneous entities, including agents, tools, resources, humans, institutions, and organizations, and supports native multi-party organization and event-based collaboration. It also provides economic primitives for metering, receipts, and settlement, and treats policy, provenance, and audit as first-class concerns.
FP is designed to wrap and bridge existing protocols rather than replace them, enabling incremental adoption while reducing integration and governance overhead. The aim is to keep autonomous agency composable while keeping accountability non-negotiable, so that coordination itself can become shared infrastructure for a human-AI society that is open, pluralistic, and governable.
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