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This paper introduces Base Sequence Analysis, a framework that encodes LLM agent runtime behavior into compact sequences, revealing high-risk patterns like the 'P-X-P' trigram and a verification deficit. It presents Governor, a runtime intervention system that improves task success by 6.2% and reduces token consumption by 44%.
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.
The article argues that companies are overinvested in AI intelligence (model capability) while neglecting crucial runtime layers for authority, accountability, and reality representation, leading to potential failures when AI acts within institutions.
The article discusses the need for runtime governance in AI agents to balance autonomy with compliance, introducing SAFi, an open-source framework that enforces policies in real-time and audits actions.
The article argues that prompt-based alignment methods face an architectural ceiling, proposing a 'Runtime Governance Layer' with hard constraints between generation and execution, drawing parallels to biological self-preservation and Terror Management Theory.