📄 中文摘要
在过去两年中,单智能体系统不断成熟,微调技术、提示工程框架和工具使用的可靠性都有了显著提升。然而,构建单一智能体的方式正面临瓶颈。真正值得构建的系统并不是单打独斗的个体,而是协调合作的团队。例如,一个研究智能体可以委派给数据抓取工具,一个规划者可以与编码者协调,销售智能体在做出承诺前会检查库存。这些并非假设,许多公司正在实际构建这样的系统,但在尝试时却遇到了许多未被广泛讨论的问题。
📄 English Summary
The Multi-Agent Infrastructure Problem Nobody Is Talking About
Over the past two years, single-agent systems have matured significantly, with improvements in fine-tuning, the emergence of prompt engineering frameworks, and reliable tool usage. However, building solely with a single agent is hitting a wall. The systems that are truly valuable are not solo performers but orchestrated teams. For instance, a research agent can delegate tasks to a scraper, a planner can coordinate with a coder, and a sales agent checks inventory before making commitments. These are not hypothetical scenarios; companies are actively building such systems. Yet, the moment one attempts to implement these multi-agent systems, they encounter numerous challenges that have not been widely acknowledged.
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数据源: OpenAI, Google AI, DeepMind, AWS ML Blog, HuggingFace 等