Trusting AI agents: A reinsurance case study

This post details the implementation of a multi-agent AI system for reinsurance data processing using Temporal Workflows and Activities. It highlights the use of Temporal Signals for human-in-the-loop confirmation of tool executions and agent completions, and Temporal Workflows as a central router (Bridge Workflow) and inter-agent data store. The post also discusses principles for building AI agents, including designing for human-in-the-loop, using modular sub-agents, and keeping tool arguments simple, all within the context of Temporal's durable execution guarantees.