Vercel 實戰經驗：為什麼我們刪除了 AI Agent 80% 的工具？
Original: We removed 80% of our agent’s tools
When building AI applications, developers often fall into the trap of "more tools equals a smarter Agent." In early versions of Vercel's AI…
Vercel 在建構生產級 AI Agent 時發現，給予過多工具會導致模型混淆、延遲飆升與成本暴增。他們透過「動態工具載入」、「多 Agent 架構」與「程式碼硬編碼路由」等策略，成功精簡了 80% 的工具。這項優化不僅讓 Agent 的任務成功率顯著提升，更大幅改善了用戶體驗，證明了在 AI 應用開發中「少即是多」的硬道理。
When building AI applications, developers often fall into the trap of "more tools equals a smarter Agent." In early versions of Vercel's AI assistants and Agents, they were equipped with dozens or even hundreds of tiny tools (such as querying a specific API, modifying a specific setting, etc.). However, this "Tool Bloat" caused serious side effects in real production environments: LLMs faced with enormous tool descriptions (Tool Schemas) consumed context extremely quickly, frequently hallucinated by choosing the wrong tool, and saw both reasoning latency before each generation and Token costs skyrocket.
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