IBM and UC Berkeley applied MAST (Multi-Agent System Failure Taxonomy) to 310 ITBench SRE traces to diagnose why enterprise agents fail in IT automation tasks. Researchers including Ayhan Sebin, Saurabh Jha, Rohan Arora, Daby Sow, Mert Cemri, Melissa Pan, and Ion Stoica found that Gemini-3-Flash exhibits "surgical failure" profiles with isolated errors, while open-source models Kimi-K2 and GPT-oss-120b show compounding failure patterns where errors cascade over time. The analysis classified failures as "non-fatal" or "fatal," moving beyond simple success-rate metrics.
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