Tag
Docker Captain Karan Verma explains why AI governance must be enforced at runtime rather than relying on prompts, breaking down the execution, tool, and resource boundaries that build developer confidence in autonomous agents.
This paper identifies a silent failure mode in tool-using LLM agents where policy violations occur without tool errors or agent self-reporting. The authors propose and evaluate lightweight deterministic pre-execution gates that significantly reduce such failures in the τ²-bench airline domain.
A gateway that enforces instruction/data separation at runtime to protect agent systems from prompt injection attacks.
Introduces Faramesh, an open-source runtime enforcement layer for AI agent tool calls that checks policies before actions run, offering a solution beyond observability or LLM-as-judge.
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.