开发人员正在探索管理AI代理成本和确保人工监督的方法，尤其是在《第14条》等法规出台的背景下。一种方法是构建具有强大成本跟踪和硬性限制的多租户LLM网关，并使用Python进行实现。另一个关键考虑因素是，代理的提示不应被误认为是权限系统，尤其是在处理意外操作时，这一点已由Anthropic的报告强调。此外，通过为AI代理提供广泛的工具集并实施用于工具选择的决策模型来控制令牌成本，可以提高其效率。 AI
影响 开发人员可以通过实施更好的工具选择、成本跟踪以及理解提示在人工监督方面的局限性来提高AI代理的成本效益和可靠性。
排序理由 该集群讨论了AI代理的实际实现细节和最佳实践，包括成本管理、工具选择和提示工程，而不是新的发布或研究突破。
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