Korean AI Video Site Automated by Short Drama Team, Prompt and Workflow Leaked
A South Korean AI video aggregation service website has been exploited by a Chinese short drama team using automated scripts, involving amounts of around hundreds of thousands of RMB. The automation led to the sharing of prompts, reference images, and generated results within the community, exposing frontline AI automation experiences in short dramas.
The core approach does not pursue high-quality individual works but rather factory-style automated operations. Each generation aims for about 90% consistency, with prompt structures focused on minimizing re-drawing costs and post-editing time, achieving automated scene transitions. Even short shot prompts are meticulously crafted, with prompts in the over 80-episode short drama rarely undergoing major changes: storyboard actions are described in short narrative sentences, dialogues are directly copied from the original work, and the starting and ending states are defined in just one line.
The team intentionally damaged the facial areas of reference images, pairing them with faceless full-body images and facial close-ups to prevent the model from mechanically replicating entire faces while enhancing close-up performance. Lighting and material were defined as the highest priority for maintaining visual consistency, with these two items alone accounting for about 1/5 of the prompt budget, precisely specifying material ratios (e.g., long knife metal highlights ×1.5, skin ×0.5, fabric ×0.3) to ensure stable hierarchical relationships after multiple generations.
The starting and ending visual states rely solely on text locking, without depending on reference images as frames, with some prompts explicitly stating the connection to the next episode's content and transition states, achieving a chain-like automatic transfer that eliminates manual alignment bottlenecks. Narrative and pacing are driven by voiceovers, with minimal resources spent on shot scheduling, marking tonal characteristics as constants for characters and state intonations as variables for storyboards, with actions strictly aligned with dialogue timing.
In market mechanisms, event-driven factors lead to the abuse of AI video tools and the publicization of workflows. Funding flows towards automated scripts and prompt optimization, benefiting short drama teams that master factory-style processes, while unprotected aggregation service providers bear the pressure. The leakage of prompts and reference images may accelerate the standardization and replication of low-cost mass-produced short dramas in the industry.
Source: Public Information
ABAB AI Insight
This case shows that AI video generation has shifted from single-shot creation to industrialized assembly lines. Prompts are designed as reusable templates, prioritizing the compression of re-drawing and editing costs over artistic consistency. Intentionally damaging reference images, locking lighting and material ratios, and fixing text for starting and ending states all serve the goal of "usable in one generation, with automatic shot transitions."
In terms of capital pathways, short drama teams automate the invocation of paid services, shifting costs to platforms while accumulating transferable prompt assets. Similar to early content farms' large-scale use of generation tools, the key lies in transforming model invocation into predictable output. We are currently in the practical verification stage of AI short dramas transitioning from manual to factory models.
This is analogous to a digital version of storyboard and continuity management in traditional film industries, but further removes the manual editing phase.
Essentially, this is a technological substitution. The mechanism is: through structured prompts and state transmission, video generation is compressed from a creative process into a scriptable production line, making the marginal cost of a single work close to zero, thereby changing the economics of short drama supply.
ABAB News · Cognitive Laws
- The goal of factory-style prompts is not perfection, but minimal re-drawing and editing.
- Intentionally damaging reference images often controls model behavior better than complete references.
- When narration is driven by voiceover, visuals only need to serve the timing of the dialogue.