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.

翻译：近期基于代理的人工智能进展正将自动化从离散工具转向主动的多代理系统，这些系统通过统一接口协调多项专业化能力。然而，当前的代理系统通常依赖硬编码的代理架构，其固定角色、协调模式和交互流程限制了最终用户的个性化定制，难以适应个体需求与情境。针对这一局限，我们认为按需生成基于人物的代理为代理工作流中实现更高效且情境适切的交互提供了可行路径。通过在运行时动态构建代理及其人物表征以匹配用户特征、任务需求及工作流上下文，代理平台能够超越“一刀切”的配置模式。本文提出一种在代理平台中按需人物生成的流水线，详细阐述了如何将AI人物的实时构建系统化集成至代理系统内，旨在为代理平台设计范式开辟新可能。