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 \textbf{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.

翻译：过去十年，生成式人工智能的发展轨迹一直由规模定律驱动的模型中心范式主导。尽管在视觉保真度方面取得了显著飞跃，但这种方法遭遇了“可用性天花板”，具体表现为意图-执行差距（即创作者的高层意图与当前单次生成模型的随机性、黑盒性质之间的根本性脱节）。本文受Vibe Coding启发，提出了\textbf{Vibe AIGC}——一种通过智能体编排实现内容生成的新范式，它代表了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的提示工程，演变为提供“Vibe”的指挥者——一种涵盖审美偏好、功能逻辑等要素的高层表征。随后，一个中心化的元规划器作为系统架构师，将此“Vibe”解构为可执行、可验证且自适应的智能体流程。通过从随机推断转向逻辑编排，Vibe AIGC弥合了人类想象力与机器执行之间的鸿沟。我们认为，这一转变将重新定义人机协作生态，使AI从脆弱的推断引擎转变为稳健的系统级工程伙伴，从而推动复杂、长周期数字资产的创作民主化。