The Civilization Framework proposes a new way to structure communication between AI agents by treating the civilization—comprising a human sovereign, a persistent ledger, and interchangeable agents—as the addressable party rather than individual agents. It introduces the Embassy Protocol, an asynchronous, carrier‑agnostic overlay that routes messages to a ledger endpoint where any online agent can process them, with commitment state on ledgers serving as the true record of interaction. The paper also identifies a temporal‑weight effect in AI‑to‑AI communication, demonstrates its impact in a preregistered experiment, and discusses mitigation strategies such as instruction‑level provenance labeling and sealed‑answer accuracy equivalence.
whyItMatters":"The framework offers a novel architecture that could reduce context loss and authority bias in multi‑agent AI systems, potentially improving reliability and accountability in AI‑driven interactions."
arXiv:2605. 06738v2 Announce Type: replace-cross Abstract: Autonomous AI agents already transact at production scale -- 69,000 bots, 165 million transactions, $50 million in volume on a single marketplace -- and any party can verify a signed credential without a central service.
By Lars Kersten Kroehl
AcquireBound is a runtime authorization framework that ensures AI agents can safely acquire and activate resources such as compute, credentials, and services. It quarantines acquired outputs, resolves their capabilities through authenticated evidence, and activates them only after verifying a manifest, provenance, and relational constraints. The system demonstrates strong safety properties, passing extensive benign and unsafe trace tests across multiple resource classes.
By Genliang Zhu
The paper proposes five runtime primitives—discovery, identity, governance, attestation, and supply chain—to manage autonomous AI agents in enterprise settings. It argues that traditional control models fail because agents are transient, model-driven, and self‑discoverable, making runtime governance essential. The authors detail an implementation that mediates agent actions against policy, authorizes them via a per‑tenant vocabulary, and records them in a verifiable ledger, noting the associated operational costs and partial deployment status.
By Jiten Oswal, John Cadeddu
arXiv:2608. 19216v1 Announce Type: new Abstract: AI control research asks how to deploy models safely even when they may be misaligned, but many control protocols assume that the deployer can instrument the model and its surrounding pipeline.
By Zhen Wen Lim
arXiv:2608. 11344v1 Announce Type: cross Abstract: Financial institutions are delegating consequential decisions to agentic AI systems that decompose goals, coordinate models and tools, and act with little oversight.
By Henry Han