# Critique of Agent Model

Published: 2026-06-24 · Updated: 2026-06-24 · Category: Research

Source page: https://www.sipply.dev/story/critique-of-agent-model-e4c8269c · 中文: https://www.sipply.dev/zh/story/critique-of-agent-model-e4c8269c

## Summary

A recent article on arXiv presents a critical examination of the agency concept in artificial intelligence, particularly in the context of Large Language Models (LLMs) that are often marketed as agents. The author argues that the current understanding of agency in AI is flawed and proposes a novel architecture for general-purpose agents that differentiates between 'agentic' systems, which possess some level of autonomy, and 'agentive' systems, which are more about the capacity to act. This distinction aims to clarify the capabilities and limitations of AI systems, potentially leading to more effective designs in the future.

## Key takeaways

- The critique highlights the shortcomings of current agent models in AI.
- A new architecture is proposed to better define and categorize AI agency.
- The distinction between 'agentic' and 'agentive' systems could influence future AI development.

## Why it matters

This critique is significant as it challenges existing paradigms in AI agency, which could lead to more robust and accurate AI systems in various applications.

- **Product managers:** For product managers, understanding these distinctions can inform the development of AI products that accurately reflect their capabilities and limitations, improving user trust and satisfaction.
- **Developers:** Developers can leverage the proposed architecture to create more nuanced AI systems that better align with user expectations and real-world applications.
- **Students and job seekers:** Students and job-seekers in AI should be aware of these evolving concepts of agency, as they represent critical discussions that could shape future job opportunities and research directions in the field.

## Sources

- [Critique of Agent Model](https://arxiv.org/abs/2606.23991) (arXiv cs.AI, 2026-06-24)

## 中文

### 代理模型的批判

最近在arXiv上发表的一篇文章对人工智能中的代理概念进行了批判性审视，特别是在大型语言模型（LLMs）通常被宣传为代理的背景下。作者认为，目前对AI中代理的理解存在缺陷，并提出了一种新的通用代理架构，区分“代理性”系统（具备一定自主性）和“代理行为”系统（更侧重于行动能力）。这一区分旨在澄清AI系统的能力和局限性，可能导致未来更有效的设计。

**要点：**

- 批判强调了当前AI代理模型的不足。
- 提出了一种新的架构，以更好地定义和分类AI代理。
- ‘代理性’和‘代理行为’系统之间的区分可能影响未来的AI发展。

**为什么重要：** 这一批判具有重要意义，因为它挑战了现有的AI代理范式，可能导致在各种应用中更强大和准确的AI系统。

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