按需生成角色化智能体，让多智能体协作更贴合用户需求。
Building Persona-Based Agents On Demand: Tailoring Multi-Agent Workflows to User Needs
- 运行时动态创建带角色的智能体，匹配用户特征与任务场景。
- 打破固定角色限制，实现灵活自适应的多智能体协作流程。
- 适合需要高度个性化的智能助手、客服或工作流平台设计者。
当前代理型AI正从独立工具转向由多个专业化能力协同的主动式多智能体系统，通过统一接口提供服务。然而，现有系统通常采用硬编码的智能体架构，角色、协作模式和交互流程固定，难以满足用户的个性化需求和情境变化。为此，我们提出一种按需生成角色化智能体的路径，通过在运行时动态构建匹配用户特征、任务要求和工作流上下文的智能体与角色，使智能体平台摆脱“一刀切”配置，实现更高效、更贴切的交互。本文提出一套在智能体平台中集成实时角色生成的流水线，系统性地阐述了这一方法的实现方式，旨在开启智能体平台设计范式的全新可能。
原文摘要 · Abstract (English)
Recent advances in agentic AI are shifting automation from discrete tools to proactive multi-agent systems that coordinate multi-specialized capabilities behind unified interfaces. However, today's agent systems typically rely on hard-coded agent architectures with fixed roles, coordination patterns, and interaction flows that limit end-user personalization and make adaptation to individual needs and contexts difficult. Given this limitation, we argue that on-demand persona-based agent generation offers a promising path towards more efficient and contextually appropriate interaction within agentic workflows. By dynamically crafting agents and personas at run-time to match user characteristics, task demands, and workflow context, agentic platforms can move beyond one-size-fits-all configurations. We present a pipeline for on-demand persona generation in agentic platforms, detailing how real-time crafting of AI personas can be systematically integrated within agent systems, aiming to open new possibilities in agentic platform design paradigms.
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