Building Persona-Based Agents On Demand: Tailoring Multi-Agent Workflows to User Needs
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866915970930442240 |
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| author | Arbore, Giuseppe Sillano, Andrea De Russis, Luigi |
| author_facet | Arbore, Giuseppe Sillano, Andrea De Russis, Luigi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_27882 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Building Persona-Based Agents On Demand: Tailoring Multi-Agent Workflows to User Needs Arbore, Giuseppe Sillano, Andrea De Russis, Luigi Artificial Intelligence Human-Computer Interaction 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. |
| title | Building Persona-Based Agents On Demand: Tailoring Multi-Agent Workflows to User Needs |
| topic | Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.27882 |