Vibe AIGC：基于智能体编排的内容生成新范式

摘要

过去十年间，生成式人工智能的发展轨迹始终由模型中心化范式主导，这一范式受规模效应定律驱动。尽管在视觉保真度方面取得了显著突破，但该方法仍遭遇了"可用性天花板"，具体表现为意图-执行鸿沟（即创作者的高层意图与当前单次生成模型的随机性、黑箱特性之间的根本性脱节）。本文受氛围编码启发，提出氛围AIGC这一通过智能体编排实现内容生成的新范式，其核心在于分层多智能体工作流的自主合成。在此范式下，用户的角色超越了传统提示词工程，升级为通过"氛围"提供高层表征的指挥官——该表征涵盖审美偏好、功能逻辑等要素。中心化元规划器则作为系统架构师，将"氛围"解构为可执行、可验证且自适应的智能体流水线。通过从随机推理转向逻辑化编排，氛围AIGC在人类想象力与机器执行力之间架设了桥梁。我们认为，这一转变将重塑人机协作生态，使AI从脆弱的推理引擎蜕变为稳健的系统级工程伙伴，从而推动复杂长期数字资产的民主化创作。

English

For the past decade, the trajectory of generative artificial intelligence (AI) has been dominated by a model-centric paradigm driven by scaling laws. Despite significant leaps in visual fidelity, this approach has encountered a ``usability ceiling'' manifested as the Intent-Execution Gap (i.e., the fundamental disparity between a creator's high-level intent and the stochastic, black-box nature of current single-shot models). In this paper, inspired by the Vibe Coding, we introduce the Vibe AIGC, a new paradigm for content generation via agentic orchestration, which represents the autonomous synthesis of hierarchical multi-agent workflows. Under this paradigm, the user's role transcends traditional prompt engineering, evolving into a Commander who provides a Vibe, a high-level representation encompassing aesthetic preferences, functional logic, and etc. A centralized Meta-Planner then functions as a system architect, deconstructing this ``Vibe'' into executable, verifiable, and adaptive agentic pipelines. By transitioning from stochastic inference to logical orchestration, Vibe AIGC bridges the gap between human imagination and machine execution. We contend that this shift will redefine the human-AI collaborative economy, transforming AI from a fragile inference engine into a robust system-level engineering partner that democratizes the creation of complex, long-horizon digital assets.

Vibe AIGC：基于智能体编排的内容生成新范式

Vibe AIGC: A New Paradigm for Content Generation via Agentic Orchestration

摘要

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