A decision framework for when AI agents should act autonomously, when they should seek confirmation, and how to design escalation paths that work under operational pressure. A decision framework for when AI agents should act autonomously, when they should seek confirmation, and how to design escalation paths that work under operational pressure. Your stakeholder alignment and regulated-environment experience makes this a natural and credible topic. Includes controls, pitfalls, and a phased implementation path. A decision framework for when AI agents should act autonomously, when they should seek confirmation, and how to design escalation paths that work under operational pressure. Why this matters Teams are under pressure to deliver AI capability quickly, but speed without control creates operational and governance risk. This guide focuses on practical execution patterns that hold up in production. Prerequisites Clear ownership for delivery and risk decisions. Basel...
Practical AI engineering guidance on agents, MCP, frameworks, security, ethics, and AI in insurance — implementation-first, production-ready.