08 = Newsletter Individual #10

Issue #10

Jul 9, 2026

8 min read

The 4-Step AI Pre-Production System That Saves 6 Hours Per Project.

My complete AI-assisted pre-production workflow: script analysis, reference frames, storyboard generation, and edit structure locked before the timeline opens or the camera rolls.

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Analyse

Storyboard

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Pre-production is where most production time is actually lost. Not in the edit. Not on location. In the planning stage, where decisions get made slowly, visuals get communicated badly, and structural problems in the script survive long enough to become expensive problems on set. The traditional pre-production process is slow because every step involves a handoff: the writer to the director, the director to the storyboard artist, the artist back to the director, the director to the crew. Each handoff introduces delay, misinterpretation, and revision. An AI-assisted pre-production workflow does not eliminate these decisions. It compresses the time between them.

“The most expensive decision in any production is the one that gets made on set because it was not made in pre-production. AI does not remove that decision. It moves it earlier.”

I’ve been running a four-step AI pre-production system across every project for the past six months. The time saving per project is consistently between four and six hours, depending on the complexity. Script analysis in fifteen minutes instead of two hours of notes sessions. Reference frames built in thirty minutes instead of half a day of mood board assembly. A Kling multi-shot storyboard pass in forty-five minutes instead of outsourced illustration turnaround. Edit structure mapped before the timeline exists. The camera rolls into a production that is already decided. I like that considerably.

The 4-Step Workflow

Step 1

Run the Script Through a 3-Prompt Analysis Loop

Find structural problems before they become location problems.

Before any visual work begins, run your script through three sequential prompts using Claude or ChatGPT. Prompt one identifies structural weaknesses in the narrative arc. Prompt two flags scenes that will be difficult or expensive to shoot as written. Prompt three suggests specific rewrite targets with reasons. This analysis pass takes fifteen minutes and consistently surfaces problems that would have taken two hours of notes sessions to identify. The goal is not to rewrite the script with AI. The goal is to know exactly which scenes need a director’s decision before pre-production moves forward.

Blind production → Structural problems found early

Step 2

Build the Reference Frame Library in Midjourney or Flux

Locked reference images are the visual bible. Everything generates from them.

Generate character reference frames, location establishing images, and key object references in Midjourney or Flux before opening any video generation tool. Use a consistent character seed or prompt structure across every character image so they look the same across the library. Lock these frames once they are approved. This library is the visual input for every subsequent generation in the project. Without locked references, every video generation tool invents the character appearance from scratch. With them, you have a single source of truth that keeps Kling storyboards and Gen-4.5 character clips visually consistent from the first frame to the last.

Inconsistent generations → Locked visual bible

Step 3

Build the Storyboard Pass in Kling 3.0 Multi-Shot Mode

Six shots per generation pass, consistent world, directorial control per cut.

With reference frames locked and script analysis complete, open Kling 3.0 Custom Storyboard mode. Upload your character reference images. Write the shot list using the structure from Issue 6: shot type, camera movement, duration, and audio for each of the six cuts. Generate in Draft Mode first to validate pacing and scene logic before committing to full quality credits. A complete scene storyboard from a six-shot Kling pass takes forty-five minutes including draft iterations. The output is a moving reference, not a static frame, which means every stakeholder responds to it faster than they would to a hand-drawn board.

Static storyboard → Animated pre-visualization

Step 4

Map the Edit Structure Before the Timeline Opens

Lock scene order, cut points, and B-roll slots before production begins.

After the storyboard pass is approved, map the edit structure in a simple document before a single clip is generated or shot. Write each scene in order, note the intended cut point between shots, flag every B-roll slot that needs to be filled, and mark which shots are generation versus camera versus Aleph 2.0 editorial fix. This document becomes the production brief that every tool and crew member works from. When the camera rolls, or when generation begins, the edit structure already exists. You are filling slots in a pre-approved plan, not making decisions under deadline pressure.

Open-ended production → Slot-filling execution

Tool of the Week

featured

Kling 3.0

Multi-shot AI storyboard generator with per-shot directorial control

The reason Kling earns its slot in the pre-production stage rather than the production stage is Draft Mode. Full-quality generation for a storyboard pass is an unnecessary credit spend when the goal is scene logic validation, not deliverable footage. Draft Mode generates the same six-shot sequence at a fraction of the cost and fast enough to iterate three or four storyboard directions in a single working session. The storyboard becomes a decision-making tool rather than a polished output, which is exactly the right job for it at this stage.

Try it yourself

Prompt Recipe

Copy & Use

You are a professional script editor and production supervisor with 15 years of experience

preparing screenplays for independent film and branded content production.

— PROMPT 1: STRUCTURAL ANALYSIS —

Context: Here is the script or scene outline for analysis: [PASTE SCRIPT OR SCENE OUTLINE]

Task: Identify the three most significant structural weaknesses in this script. For each weakness, state: what is wrong, where it occurs (act, scene, or page), and why it will cause a problem in production or audience engagement.

Format: Three numbered findings. Maximum 60 words per finding. Be specific.

— PROMPT 2: PRODUCTION RISK FLAGS —

Context: Using the same script above.

Task: Identify the three scenes that will be most difficult or expensive to produce as currently written. For each scene, state: what makes it difficult, what the production cost implication is, and one specific rewrite direction that would reduce the difficulty without changing the story intent.

Format: Three numbered flags. Maximum 60 words per flag.

— PROMPT 3: REWRITE TARGETS —

Context: Using the structural weaknesses and production risk flags identified above.

Task: List the five most important rewrite targets in order of priority. For each target, state: the specific change needed, the scene or section it applies to, and the expected benefit in one sentence.

Format: Five numbered targets. Maximum 40 words per target. No explanatory preamble.

Constraints: Do not rewrite the script. Identify problems and targets only. Do not suggest AI generation as a solution to production challenges.

Pro Tips:

Mini Case Study

Real Results

Script notes sessions, outsourced storyboard illustration, mood board assembly, and edit planning all handled sequentially across multiple days.

After: 4-Step AI Pre-Production System

Script analysis, reference frames, Kling storyboard pass, and edit structure map completed in a single working session. Stakeholders respond to moving storyboards faster than static frames.

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AI Pre-Production Workflow Checklist

Step-by-step checklist to run the complete 4-step AI pre-production system on any project.

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Vani Aggarwal

Filmmaker & Head of Content Strategy exploring the edge where Al meets
story.

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