This article explores a serious approach to AI agents, moving beyond simple search boxes and retry loops. The author tests an agent with eight tools, strict boundaries, and a contradiction gate on Azure. Results show reduced entity fragmentation and improved reasoning, but also reveal limitations.

The design emphasizes precise tool vocabulary and controlled iteration over open-ended exploration. The author shares honest findings, including where the agent fails, to provide practical insights for building reliable AI systems.