The article argues that current AI agent development is hampered by reliance on frameworks like CrewAI and LangGraph. It suggests a shift towards a "harness" approach, where developers build custom solutions rather than adapting pre-built frameworks. This new paradigm emphasizes upstream integration and flexibility, moving away from the rigid structures of traditional frameworks. AI
影响 Suggests a move towards more flexible and custom AI agent architectures, potentially improving development efficiency and capability.
排序理由 The article discusses a conceptual shift in AI agent development, offering an opinion on best practices rather than announcing a new product or research.
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