From Script to Finished Film: What a Standard Film and TV Project Workflow Looks Like

When many people start making a film, they tend to begin by "trying to generate a shot first." This is natural, but it is often why a project gets abandoned halfway through—because whether a shot is good only has meaning within the context of the entire workflow. Mature film and TV production has a relatively fixed workflow. Understanding it is not just about following steps, but about knowing what each stage "should produce" and avoiding rework.

The Six Stages of the Workflow

From idea to finished film, a piece usually goes through six stages. Their order is not an arbitrary rule, but is determined by dependencies—the input of a later stage is precisely the output of the previous stage.

1. Project Creation: Build the Container First

Before starting a first film, the easiest thing to overlook is the concept of the "project" itself. In traditional production, a project is a folder that holds the script, assets, personnel, and schedule. AI production likewise needs a container that brings all subsequent outputs together; otherwise, halfway through, they will be scattered everywhere and lose their version relationships. NadouPro's workspace is this container: it is a structured film and TV creation model centered on scripts, subjects, storyboards, and shot production. When creating a new project, you can enter a project name, or start from a blank project and set the aspect ratio and dimensions—the aspect ratio step is critical, because it determines the frame baseline for all later materials.

2. Script Import and Episode Splitting: Cut Long Text into Segments

Once there is a container, the first thing to do is put the story into it. Upload the script file directly, and the system parses the text and outputs an episode structure. The value of this step is establishing hierarchy: a long piece of content is cut into multiple independently processable units, each with its own characters, scenes, and progress. Episodes themselves can continue to be operated on—adding, editing, and deleting are all supported. This is important in practice because script structures often change, such as when one episode is too long and needs to be split, or when the content of two episodes needs to be merged.

3. Subject Extraction: Turn "Text" into "Entities"

This is a very critical step in the AI film and TV workflow, yet it is the one most easily underestimated. If the script says "a middle-aged man in a gray trench coat walks into a café," that only describes attributes. But to generate dozens of shots later, there must be a definite image that remains consistent throughout: what exactly this person looks like, and what exactly that café looks like. So the purpose of subject extraction is to consolidate scattered descriptions in the script into definite subjects—characters, scenes, props, as well as their basic states and script-related substates. Note that this says "subjects," not "characters," because it includes three types of objects, not just people. If this stage is done roughly, every shot later will have to be described again, and consistency will inevitably collapse; if it is done in detail, what follows is reference and reuse.

4. Character Image Generation and Adjustment: Turn Entities into Assets

After subjects are determined, the next step is to generate visual images. Based on the character settings, character images can be generated with one click, producing images of the basic state and substates. After that, you can continue adjusting states and views, including perspective, shot scale, lighting, generating multiple angles or expressions through grids, or editing local details. The output of this step has two uses: first, to confirm whether the image meets expectations; second, to become the reference baseline for all subsequent shots. The generated character images are stored in the character asset library and can be filtered and reused by name, tag, gender, age range, skin tone, hair color, body type, and other conditions. At this point, "certainty" is truly established.

5. Storyboard Planning: Break the Story into Shots

At this point in the workflow, the story has structure and the subjects have images. The next problem to solve is "how to shoot it." The essence of a storyboard is to break the narrative down into shots. After the script and subject settings are determined, a shot-level shot list can be generated automatically, avoiding manual entry line by line. The resulting list is not the final version, but a draft: storyboards can be added, deleted, and edited, the order can be adjusted, subject references can be modified, and parameters such as shot dimensions, depth of field, and camera angle can be adjusted through field configuration. This step is the hub of the entire workflow. The previous steps solve "what it is," and the later steps solve "how to present it"; the storyboard is exactly the interface between the two.

6. Shot Asset Generation and Finished Film

After the storyboard is determined, production of assets begins. Shot assets are generated one by one according to the storyboard; images can be generated, and videos can also be generated. After the assets are produced, they enter the subsequent production and finished-film stage—in this stage, boundary integration, cutting, and editing can be completed within the project, without first exporting and then processing in other software. It should be noted that this step is not "completed in one go." In real projects, asset generation is often iterative: first produce a low-cost version to see the overall effect, then raise the specifications for key shots after confirmation.

Why the Workflow Matters More Than the Steps Themselves

After looking at these six stages, there is an observation that is easily overlooked: every stage has clear inputs and outputs. - Project creation: outputs the container and frame baseline - Script import: outputs the episode structure - Subject extraction: outputs a definite subject list - Character image generation: outputs visual images and assets - Storyboard planning: outputs the shot list - Asset generation: outputs shot assets and enters finished-film production. The benefit of this "clear input and output" design is that it allows rollback. If a certain shot is unsatisfactory, there is no need to overturn the entire project; simply return to the corresponding stage to correct the settings, then regenerate the affected assets. Conversely, if a stage is skipped—for example, starting shot generation directly without subject extraction—then every shot is independent. Once inconsistency is found between earlier and later shots, there is no option to "correct the settings"; each one can only be redone individually.

Common Workflow Misconceptions

Misconception 1: Treating the workflow as a fixed order. The order above is a logical dependency, not an operational rule. In practice, it is often necessary to roll back: if you are halfway through storyboarding and discover that a certain scene setting has a problem, you should return to the subject stage to supplement it, rather than force a textual description into the storyboard. Misconception 2: Skipping the subject stage and generating images directly. This is the biggest cause of failure in AI projects. The time saved will be paid back many times over in later shot consistency. Misconception 3: Making the storyboard too rough. If you only write descriptions like "he walks into the room," you will find during execution that countless details have not been determined. The granularity of the storyboard should be detailed enough to "execute directly." Misconception 4: Treating asset generation as the endpoint. Assets are only raw materials; a finished film still needs editing, color grading, sound, and other stages. Including these in the plan prevents chaos at the final stage.

Finally

The value of a workflow is not that it makes people operate step by step, but that it lets people clearly understand at every step what should be produced now and what the next step depends on. Film and TV production has never taken shape all at once through inspiration; it is accumulated through a series of verifiable intermediate outputs. What AI changes is only the speed and implementation method of each stage; it does not change this chain itself.

Contains AI-generated information that may be incorrect. Please verify independently.