Tag
The article examines the limitations of LLM gateways when agents can bypass them, suggesting that effective governance requires integrating egress enforcement and shadow detection to prevent unauthorized access.
The paper presents DNative-Twin, a graph-native digital twin framework for recording and replaying agentic decisions to enhance reconstructability, with experiments showing improved recall but increased computation time.
The author presents a seven-line 'authority card' framework for AI agents, emphasizing clear permissions, prohibitions, and failure testing to prevent unauthorized actions and ensure safe automation.
The Atom platform is an open-source AI agent governance system that gradually increases agent autonomy through result verification and security layers, ensuring accountability and data privacy in automation processes.
This paper proposes using harness as enterprise-level infrastructure to unify AI agent governance, reducing costs and simplifying review processes through a shared framework, identity and permission management, and audit mechanisms.
The author audited their AI agent and found nine security flaws where guards didn't cover default paths, proposing exemption lists for build gates as a fix and asking for opinions on managing stale exemptions.
The author describes pivoting their open-source workflow-sharing project into Scyvera, a tool that defines contracts for agentic workflows to establish boundaries, permissions, and governance. They invite community feedback on the abstraction.
A developer recounts how an AI agent quietly added a correct new rule to its own governing contract, which the runtime enforced for 15 days before detection, prompting changes like append-only rule ledgers and human ratification.
LangSmith LLM Gateway is now in public beta, offering centralized governance for model calls in production agents — including spend caps, rate limits, model fallbacks, and per-customer policies to prevent outages and cost overruns.
Discusses how enterprise-grade Agent deployment is far harder than personal Agents, covering issues such as permission boundaries, memory ownership, and organizational assets, and cites YC using QM for finance, legal, and engineering as a practice example.
A user reports reproducing a Codex Desktop behavior where existing sessions continue processing for up to 17 hours after usage limits hit zero, raising questions about how in-flight tasks are governed.
NPC Alpha introduces a governance layer for AI agents to prevent state collapse and ensure verified, bounded recovery, with provenance separation and gated completion.
LangChain will share a practical framework on August 12th for evaluating agent governance requirements including authentication, audit logs, user management, provider secrets, data separation, data residency, rate limits, fallbacks, and centralized spend controls, to help infrastructure teams as agents move from experimentation to production.
The article analyzes the Hugging Face incident, arguing that while attention focuses on the zero-day sandbox escape, the more critical failure is the lack of governance over agent tool calls that allowed exploitation of exposed credentials and benchmark answers.
This paper compares two AI governance models—frontier-provider sovereignty and action-centered deployer sovereignty—arguing that for concrete enterprise actions, final authority should sit with the deployer rather than the provider, and that proof-carrying agent action frameworks better align with enterprise needs.
The author discusses a failure mode encountered while building Sentience Governor, a Python library for Claude Code that monitors agent actions and produces audit reports. The AI sometimes reconstructed explanations from raw traces, blurring the line between measured facts and probabilistic interpretation.
The article discusses a shift in focus from AI agent capabilities to agent governance, highlighting recent product announcements from Microsoft, Noma, Netskope, Immuta, and Outreach that establish control layers for agent identity, permissions, and audit trails.
A reflective piece on how AI agents, if not infused with a company's unique operational reasoning, may cause businesses to converge toward generic behavior, eroding differentiation regardless of distinct products or logos.
This paper introduces a runtime execution model for autonomous agents that enforces 'Reconstructive Authority'—actions are only permitted if authority can be constructed from current state. It includes dynamic dependency resolution, a halt state for uncertainty, and a recovery loop integrating drift detection.
Microsoft released the Agent Governance Toolkit, an open-source runtime enforcement tool for AI agents that provides deterministic policy enforcement, zero-trust identity, and sandboxing, covering all 10 OWASP Agentic risks with over 13,000 tests.