Summary
As enterprises adopt AI agents and agentic systems, they discover that these systems fail in unexpected and costly ways. These failures do not follow the patterns of traditional software bugs; they emerge from ambiguity, miscoordination, and unpredictable system dynamics. Fixes that focus only on prompts or tuning fall short. This report introduces a practical framework for understanding agentic failure modes and offers design and oversight strategies to help teams build more reliable, resilient agentic systems.
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