Brief

Microsoft researchers have updated their taxonomy of failure modes in agentic AI systems, drawing insights from a year of red-teaming efforts. The updated classification aims to better understand and categorize the ways these advanced AI systems can go wrong. This work is part of ongoing efforts to improve the safety and reliability of AI technologies. AI

This article explores eleven fundamental patterns that underpin all production-ready agentic AI systems. It emphasizes the critical role of structured data, particularly JSON schemas, in ensuring reliable handoffs and communication within these complex workflows. The author argues that mastering these patterns is essential for developing robust and scalable AI applications. AI