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LLMs are surprisingly bad at automating the creation of executable visual workflows from natural language, highlighting a significant gap in their ability to translate intent into reliable, deployable code.
A stark capability cliff reveals that even leading AI models falter on complex workflows, achieving less than 15% success despite advancements in tool-use benchmarks.
AI agents can now learn durable skills instead of constantly "reinventing the wheel," thanks to SkillNet's infrastructure for creating, evaluating, and connecting AI skills at scale.
