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Despite advances in agentic systems, they still lag far behind human performance in complex tasks, achieving only 19.1% success on a new benchmark designed to probe their limitations.
Text embeddings might be leading you astray: they're substantially less reliable than human experts in capturing semantic nuances critical for policy analysis and AI use case understanding.
