📄 中文摘要
构建AI代理的过程并非如表面上看起来简单。尽管从概念上讲，代理的构建只需在大型语言模型的基础上增加一个循环，使其能够推理下一步行动、调用外部工具并反馈结果，但在实现过程中面临诸多挑战。工程师需要解决OAuth流程、工具设计、错误传播、多步骤任务的管理、成本控制、上下文窗口管理、评估、多代理协调、模型能力瓶颈及框架权衡等九大难题。这些问题使得从“工作演示”到“生产产品”之间的距离变得更加遥远，API调用仅占总工作量的5%，其余95%的努力则集中在这些复杂的挑战上。
2026年构建AI代理所需的技能
出处: Skills Required for Building AI Agents in 2026
发布: 2026年2月25日
📄 English Summary
Skills Required for Building AI Agents in 2026
Building AI agents is more complex than it appears at first glance. While conceptually simple, involving a loop added to the one-question-one-answer model of a large language model (LLM) to enable reasoning, external tool calls, and feedback, the actual development process presents numerous challenges. Engineers must navigate OAuth flows, tool design, error propagation, multi-step task management, cost control, context window management, evaluation, multi-agent coordination, model capability bottlenecks, and framework trade-offs. These nine challenges create a significant gap between a 'working demo' and a 'production product.' API calls represent only about 5% of the total effort, with the remaining 95% focused on addressing these complexities.