This week, I read Dr. Jeffrey Funk’s insightful LinkedIn post on Disney and Lionsgate’s experiments—and frustrations—with generative AI in Hollywood. Richard Self’s comment got me thinking.
He highlighted a fascinating contrast: studios that once boasted about AI generating anime versions of John Wick or cloning Dwayne “The Rock” Johnson for Moana sequels are now scaling back, realizing their catalogs (even Disney’s!) aren’t large enough to train viable video models.
Maybe the challenge isn’t just technical. Maybe Hollywood is still approaching AI as if it needs to instantly conjure full-length films, complete with flawless visuals, pacing, and character arcs. But what if they took a page out of their own playbook—how movies have always been made?
Every film starts with a plot. A treatment. A writer’s room. Rough drafts, rewrites, character notes, pacing adjustments, emotional beats. Directors don’t shoot a movie by pointing a camera at chaos; they start with a framework and refine it.
And that’s exactly where LLMs (large language models) can shine today.
Instead of replacing directors, actors, or animators, LLMs could serve as the idea machine—a structured collaborator that helps studios generate, refine, and iterate on movie plots. Think of it as an endless writer’s room where you never run out of interns with fresh ideas (and none of them demand a corner office).
So let’s explore how Disney—or any movie producer—might systematically use LLMs to generate viable movie plots.
Why Story, Not Visuals, Is the Right Starting Point
Hollywood’s recent AI experiments jumped straight into visuals: deepfakes, animated rehashes, and video effects. That’s flashy, but it skips the foundation.
Visuals without story are just noise. The reason a Disney film resonates isn’t because of the CGI (though impressive), but because the plot follows timeless patterns: friendship, courage, sacrifice, discovery.
LLMs are built for language and structure—perfect for generating story scaffolding. By treating AI like a story consultant, studios can speed up ideation while still leaving the artistry and nuance of acting, directing, and animation to humans.
The LLM Movie Plot Playbook
Here’s the systematic approach I believe studios could use—tested not in theory but in the trenches of how writing and iteration naturally work.
Step 1: Define the Movie Type (Genre + Tone + Audience)
Every creative process begins with constraints. Without constraints, AI plots devolve into spaghetti: one minute you’re in a princess musical, the next you’re in a dystopian war epic.
Key decisions include:
- Genre: Animated musical, live-action thriller, rom-com, sci-fi epic.
- Tone: Lighthearted, dark, whimsical, serious.
- Audience: Kids, family, adults, niche fans.
Example: “Animated adventure for families, PG, lighthearted tone, with musical elements.”
This sets the rules of the sandbox.
Step 2: Generate a Rough Plot Outline
Now, feed the model a baseline structure. There are classic storytelling frameworks that AI can easily adapt:
- Three-Act Structure: Setup → Conflict → Resolution.
- Four-Act Disney Model: Setup → Conflict → Climax → Resolution.
- Hero’s Journey: Call to Adventure → Trials → Abyss → Return with the Elixir.
Prompt Example:
“Generate a high-level movie plot in 4 acts. The genre is an animated adventure with musical elements. The target audience is families with children. Use the beats: Setup, Conflict, Climax, Resolution. Keep the tone whimsical and magical.”
What you get is essentially a first draft treatment—like the initial whiteboard in a writers’ room.
Step 3: Identify the Essence (Frameworks, Patterns, Characteristics)
This is where the Disney magic (or Marvel formula, or Pixar touch) comes in. Each studio has “DNA markers” in its films. LLMs can enforce those markers by layering specialized prompts.
For Disney, this might include:
- Themes: Friendship, courage, family bonds, self-discovery.
- Patterns: A talking animal sidekick, a musical number every 20 minutes, a villain reveal at midpoint.
- Tone Rules: Whimsical humor, moments of heartfelt sincerity, bittersweet endings that resolve in hope.
Instead of dumping all of this in one giant prompt, you’d run one pass per characteristic.
Step 4: Run Characteristic Prompts (One at a Time)
Here’s where the “writer’s room” analogy really clicks. Each pass adds depth, like assigning a specialist to polish one part of the script.
- Theme Reinforcement Prompt:
“Enhance the plot to emphasize the theme of friendship. Add one subplot that forces the protagonist to rely on a friend, and make sure the climax resolves through this bond.” - Comic Relief Sidekick Prompt:
“Introduce a comic relief sidekick who provides humor but also contributes meaningfully to the quest. Give them a small growth arc.” - Villain Prompt:
“Deepen the villain’s motivation. Make them sympathetic in one scene, while ensuring they remain a credible threat.” - Musical Moment Prompt:
“Insert 3 musical numbers that advance the plot: one in the setup, one in the conflict, one in the resolution. Describe the emotional tone of each song.”
Each run adds texture without derailing the core.
Step 5: Apply Smoothing Prompts
Once you’ve bolted on all the character traits and themes, the story can feel stitched together. That’s where “smoothing” prompts come in.
- Pacing & Transition Prompt:
“Review the plot for pacing and smooth transitions. Ensure each act escalates stakes and emotion logically. Fix abrupt jumps.” - Tone Consistency Prompt:
“Ensure the overall tone remains whimsical and family-friendly. Adjust any scenes that feel too dark or out of place.”
This turns a Franken-plot into something cohesive.
Step 6: Run Meta-Prompts (Director’s Notes)
Finally, take a step back and apply big-picture checks:
- Continuity Check:
“Verify that all character motivations, timelines, and settings are consistent. Fix contradictions.” - Emotional Arc Check:
“Ensure that the emotional stakes rise steadily across acts, leading to a satisfying climax and resolution.”
This ensures the story is more than just connected scenes—it’s an emotional journey.
Step 7: Iterate (2–3 Rounds)
Just like a screenplay, the first draft won’t be the final draft. Run the enhancer and smoothing loops two or three times. Each pass should feel tighter, with fewer rough edges.
A Concrete Example (Disney-Style Adventure)
Let’s walk through a mini version.
- Baseline Plot:
A young girl discovers a dragon egg. When it hatches, she must protect the baby dragon from a kingdom that wants to exploit it. - Theme Enhancer:
Add a subplot where she betrays her best friend but must reconcile to save the dragon—reinforcing friendship and trust. - Villain Pass:
The villain isn’t evil for evil’s sake; he wants the dragon’s power to protect the kingdom from famine. Misguided, but not heartless. - Comic Relief Pass:
Enter a sarcastic squirrel who befriends the dragon and provides humor, but later risks himself to warn the girl of danger. - Musical Pass:
- Song 1 (Setup): “Something’s About to Hatch” (wonder + curiosity).
- Song 2 (Conflict): “Torn Between Two Worlds” (loyalty vs. fear).
- Song 3 (Resolution): “Fly Free” (triumph and closure).
- Smoothing Pass:
Ensure Act II flows naturally into Act III with the betrayal and reconciliation serving as the bridge. - Meta Check:
Confirm the villain’s motivation (protecting the kingdom) remains consistent.
Result: A Disney-ready adventure outline in less than an hour of AI prompting.
Why This Matters
Studios don’t need AI to replace storytellers. They need it to accelerate ideation. Writer’s block is expensive. Endless draft cycles chew up budgets. A structured AI workflow could:
- Produce 10 viable treatments in a week.
- Help junior writers learn classic storytelling structures.
- Explore “what if” scenarios at low cost.
- Give executives more polished options before greenlighting.
And because the process is modular, it doesn’t stifle creativity. Human writers can jump in at any stage, rework prompts, or twist outcomes.
The Legal Elephant in the Room
Of course, Jeffrey Funk’s post hit another critical point: the legal quagmire. AI in Hollywood isn’t just about technology—it’s about rights. Who owns the AI-generated treatment? Who gets credit? Can a studio risk union backlash?
But here’s the irony: using LLMs for plots rather than finished films sidesteps many of those issues. Treatments are always collaborative, and no one person owns the idea of “a boy and his dragon.” What matters is execution.
By keeping AI in the ideation stage, studios avoid most of the IP minefields while still reaping efficiency gains.
A Twist of Humor
Let’s be honest: the day Disney asks an LLM to generate Frozen 3 is the day we get songs like “Do You Wanna Share a Wi-Fi Password?” or “Let It Load.”
But jokes aside, AI won’t kill the magic of Disney—it might just help writers spend less time staring at blank pages and more time crafting characters audiences love.
Conclusion
Hollywood is learning the hard way that you can’t brute-force AI into making perfect films. Visual models struggle. Legal issues abound. Catalogs aren’t big enough.
But story—story is universal, modular, and exactly the kind of pattern-driven task where LLMs thrive.
If Disney or Lionsgate treated LLMs not as wannabe directors, but as plot consultants in a structured, iterative workflow, they could produce richer drafts, faster, and at lower cost—without diluting the human artistry that makes cinema timeless.
In short: don’t ask AI to be Spielberg. Ask it to be the overcaffeinated intern with 100 wild ideas, then refine the best ones through proven storytelling frameworks.
That’s how AI can move from “failed deepfake experiments” to “indispensable creative partner.”
References
Liongate’s Attempt to create Movies using AI has crumbled into disaster
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