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Compact finite-state machines can predict LLM agent failures with up to 94% accuracy, revealing that deployment harnesses shape behavior more than the models themselves.
AgentRoom slashes task abandonment rates in multi-agent coding by emphasizing coordination over mere parallel execution.
