Multi-shot AIGC Creation Workflow

AIGC POV

A character, viewpoint, and constraint framework for multi-shot generative video that reduces blind retries and makes failure reasons reusable.

  • Generative Video
  • Creative Workflow
  • Consistency

Generating one attractive shot is not the hardest part. Preserving the same person, viewpoint, and world rules across shots is. Without structured records, every failure becomes another blind retry and costs keep accumulating.

Cover frame from the AIGC POV film
Open full sizeCover frame from the AIGC POV film
How can the subjective feeling that “this shot is wrong” become specific, editable issues in character, camera, continuity, and narrative function?

Every action should have a reason.

  1. Lock identity, viewpoint, and invariants before scene-specific action.

    Separating global rules from local change reduces the need for the model to reinterpret the character in every shot.

  2. Split prompts into camera, subject, environment, continuity, and negative constraints.

    A modular structure maps revisions to specific variables and makes it possible to track which changes improve results.

  3. Record failures by consistency, motion, composition, and narrative function.

    A vague similarity judgment cannot guide the next round. Failure types make retries purposeful and reusable as rules for later shots.

How a shot moves from creative intent into controlled iteration

Start / inputProcessDecisionOutcome
  1. Creator

    Define the shot’s narrative job

    State what information, emotion, or action this shot must advance.

  2. Constraint layer

    Lock global invariants

    Fix character identity, first-person viewpoint, world rules, and continuity.

  3. Prompt DSL + model

    Organize variables and generate

    Separate camera, subject, environment, and negative constraints while recording model parameters.

Creative review

Does the shot satisfy continuity and narrative purpose?

Review character, viewpoint, motion, composition, and relation to adjacent shots—not beauty alone.

Pass

Lock the shot and reference assets

Carry identity, composition, and parameters into the next shot.

Identity / continuity failure

Revise global constraints

Adjust character references, world rules, and invariants before retrying.

Motion / narrative failure

Revise local shot variables

Change camera, action, pacing, or negative constraints and regenerate.

Creative loop

Turn failure reasons into rules for the next round

Record why a candidate failed, what changed, and whether it improved; accepted shots continue to the next scene or final edit.

Business meaningThe flow replaces blind retries with explicit creative decisions: accepted shots become assets for the next scene, while failed shots identify which variable should change and why.

From judgment to something that runs.

Constrain

Define character and world rules, including what cannot change in each shot.

Generate

Create candidates from structured prompts while recording model and parameters.

Review

Select by continuity and narrative purpose, then revise constraints for the next round.

  • Completed a multi-scene POV film of about 1m40s
  • Developed a reusable prompt DSL
  • Retained a generation–review–retry record
What this does not prove yet

This is a personal workflow validated on one finished piece, not yet a general tool across models and creators.

What I would test next

Turn review criteria into shot-level records so future work can reuse why a retry happened, not just the prompt text.