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

TL;DR

The paper argues that the current model-centric trajectory of generative AI hits a usability ceiling due to the Intent-Execution Gap. It proposes Vibe AIGC, a paradigm of agentic orchestration where users act as Commanders providing a Vibe, and a Meta Planner converts this into executable, verifiable multi-agent workflows. By shifting from stochastic inference to logical orchestration, the approach aims to enable robust, long-horizon content creation and to democratize the production of complex digital assets. The work lays out the top-level architecture, key components, and preliminary attempts across text, image, and video, highlighting both the potential benefits and the limitations of architecting an orchestrated AIGC ecosystem for professional use.

Abstract

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.

Figures (5)

• Figure 1: Content generation advancing toward the Vibe AIGC era: A systemic leap driven by structural combination.
• Figure 2: A collaborative multi-agent pipeline in AutoPR.
• Figure 3: A collaborative multi-agent pipeline in Poster Copilot.
• Figure 4: A collaborative multi-agent pipeline in AutoMV.
• Figure 5: Schematic diagram of Vibe AIGC architecture.