What Is Luma Boards and Agents? How to Build AI Storyboards with Thinking Image Models

From Prompt to Pre-Production: Inside Luma Boards and Agents

AI image generation has a consistency problem. Generate ten images of the same character across ten different prompts, and you’ll get ten different people. That’s fine for a mood board. It’s not fine for storyboards, character sheets, or any visual production workflow that requires coherent output across many frames.

Luma Boards and Agents is built to solve exactly that. It combines a canvas-based workspace with Uni1, Luma’s thinking image model, to produce visually consistent output across entire boards — not just single generations. The result is a new kind of tool for visual pre-production: one where the AI understands context across your whole project, not just the last prompt you typed.

This article covers what Luma Boards and Agents actually is, how Uni1 works, and how to use the canvas to build storyboards, character sheets, and video sequences from scratch.

What Is Luma Boards and Agents?

Luma AI — the company behind Dream Machine, their text-to-video model — introduced Boards and Agents as a canvas-based workspace for visual creation. It’s not a standard image generator. It’s closer to a collaborative visual planning tool where an AI agent works alongside you on a persistent canvas.

The core idea: instead of treating each image as a standalone generation, Boards and Agents uses the entire canvas as context. The agent reads everything on your board — reference images, character descriptions, style notes, previous generations — and uses that context to make new images that are consistent with what’s already there.

This makes Luma Boards and Agents well-suited for tasks that depend on visual consistency:

Building multi-panel storyboards for film, animation, or video
Creating character sheets that show a single character across multiple poses and scenarios
Developing visual style guides and mood boards
Planning shot sequences before moving to video generation

Think of it as giving the AI a persistent memory. Instead of re-describing your character in every single prompt, you establish them once on the canvas and the agent keeps that context active throughout your session.

Understanding Uni1: Luma’s Thinking Image Model

The engine behind Boards and Agents is Uni1, Luma’s thinking image model. The “thinking” part isn’t marketing language — it describes a real architectural difference from standard image generation models.

What “Thinking” Means for Image Generation

Most image models work like this: prompt in, image out. The generation process involves diffusion or autoregressive steps internally, but there’s no explicit reasoning phase before the image appears.

Uni1 works differently. Before generating an image, the model runs a reasoning pass — similar to how large language models like OpenAI’s o-series reason through a problem before giving an answer. During this thinking phase, Uni1 processes:

The text prompt
Visual references present on the board
Spatial context — where elements appear relative to each other
Style and character consistency cues from existing generations

This pre-generation reasoning is what allows Uni1 to produce outputs that are more coherent with their context. The model isn’t just pattern-matching to a prompt — it’s actively reasoning about what the output should look like given everything on the board.

How Uni1 Maintains Visual Consistency

Consistency in AI image generation is genuinely difficult because most models generate each image essentially from scratch. Approaches like LoRAs or DreamBooth help maintain character appearance, but they require training time, technical setup, and separate tooling.

Uni1 handles consistency through inference-time reasoning. The model uses existing images on the board as visual references when generating new ones. The results aren’t pixel-perfect, but they’re significantly more consistent than you’d get from running independent prompt-based generations.

This matters most for:

Character sheets — maintaining a character’s face, proportions, and design details across multiple poses
Scene continuity — preserving lighting, color palette, and environmental details across storyboard panels
Style consistency — ensuring a unified aesthetic across a whole board without manual style reference in every prompt

The Boards Interface: How the Canvas Works

The Boards interface is a drag-and-drop canvas that works more like a digital whiteboard than a chat window. That spatial, visual organization is central to how the system functions.

Setting Up a Board

When you create a new board, you start with a blank canvas. From there, you can:

Add text nodes — character descriptions, scene notes, or style directions
Upload reference images — photos, sketches, or existing art you want the AI to reference
Place generated images — images you’ve already created that serve as visual anchors for future generations

The spatial layout matters. Luma’s agent reads positional relationships on the canvas, so placing a character reference image near a scene prompt helps the agent understand the intended connection.

Working with the Agent

The agent is the active generation layer within the canvas. You prompt it to generate new images using the board’s existing content as context. Key capabilities include:

Generate from selection — select reference images and a prompt; the agent generates a new image that respects both
Fill panels — define a storyboard layout and have the agent generate each panel based on scene descriptions
Iterate in place — refine a generated image with additional instructions without losing context
Batch generation — produce multiple variants or panels in one pass

The difference from a standard text-to-image tool is significant. You’re not re-establishing context with every prompt — the board is the context. This makes iterating on a multi-panel storyboard far more practical than it would be with standalone image generation.

Organizing a Storyboard Layout

For storyboard work specifically, Boards lets you structure the canvas around your narrative:

Create a dedicated section for character references
Define scenes as individual cells, laid out in sequence
Add brief scene descriptions to each cell
Ask the agent to generate images for each scene
Review, iterate on individual panels, then export the sequence

A rough storyboard that might take a week to sketch manually can be approximated in hours. That’s not a replacement for professional storyboard artists in full production — it’s a tool for rapidly testing narrative ideas before committing resources.

Key Use Cases for Luma Boards and Agents

Storyboarding for Film and Video

Production teams use storyboards to pre-visualize shot sequences. Traditionally, this means hiring storyboard artists, creating clear briefs, and going through multiple revision rounds before a frame is drawn.

Boards and Agents gives directors, producers, and creative leads the ability to generate a rough visual sequence quickly — establishing shots, character staging, camera angles — and share a working reference with the full team. It’s particularly useful for pitching ideas or aligning a team’s visual understanding early in development.

Character Development and Character Sheets

Character designers produce multiple views of a character — front, side, three-quarter, expressions — for handoff to animators or production teams. Uni1’s consistency features make it practical to generate a character’s core design and then produce variations without the appearance drifting significantly between panels.

Applications extend beyond animation: game developers, graphic novelists, and illustrators can use this workflow to establish and reference character visuals without the overhead of traditional production.

Visual Development and Mood Boards

Early creative work involves a lot of visual exploration — finding the right tone, palette, and aesthetic before committing to a direction. Boards lets you rapidly generate and compare visual directions side by side on the same canvas.

Because everything lives in one board, you can show different lighting setups, color grading styles, or character design directions and compare them directly — without switching between tabs or tools.

Pre-Visualization for Video Generation

Luma’s broader platform includes Dream Machine for video generation. Boards and Agents can serve as a pre-visualization layer before you move to video. Generate a storyboard sequence, refine it until the narrative arc works, then use those images as keyframe references for video generation.

This pipeline — from storyboard to video — is one of the more useful applications for short-form content creators and indie filmmakers who need fast iteration without a large production team.

How to Build Your First AI Storyboard in Luma Boards

Here’s a step-by-step walkthrough for building a basic storyboard.

Step 1: Define Your Character

Before generating scenes, establish your main character. Create a dedicated section of the board:

Upload any visual references you have — sketches, photos, or existing character art
Write a detailed character description covering physical appearance, clothing, and distinctive features
Generate 2–3 reference images using Uni1 to establish the AI’s visual understanding of the character

Label this section clearly. It becomes the character anchor for all subsequent generations.

Step 2: Outline Your Scene Sequence

Write scene descriptions as text nodes in sequence. Keep them brief and visual — describe what the camera sees, not backstory:

Scene 1: Character walks through a crowded market at dusk, looking anxious
Scene 2: Close-up on character’s face as they spot something across the crowd
Scene 3: POV shot of a figure disappearing into an alleyway

Step 3: Generate Each Panel

Select your character references and the first scene description, then prompt the agent to generate a panel. Review the output, iterate if needed, and move to the next scene. The board context carries forward — you shouldn’t need to repeat character details in every prompt.

Step 4: Refine and Iterate

Review the full storyboard as a sequence. Look for character drift between panels, lighting inconsistencies, or framing issues that break the visual flow. Use the agent’s edit-in-place tools to revise specific panels without regenerating the entire board.

Step 5: Export and Use

Export the sequence for use as a rough animatic, video generation reference, a visual brief for artists, or a client presentation. The output from Luma Boards is flexible — it can feed into multiple downstream workflows.

Where MindStudio Fits Into AI Media Workflows

If you’re using Luma Boards and Agents as part of a broader production workflow, you’ll quickly find that different tasks pull you toward different tools: storyboarding in one place, image editing in another, video generation somewhere else, asset management elsewhere. It fragments fast.

MindStudio’s AI Media Workbench is built for exactly this problem. It gives you access to all major image and video generation models — including FLUX, Veo, Sora, and more — in a single workspace, without separate accounts or API keys. More importantly, it lets you chain these generation steps into automated, repeatable workflows.

For example, you could build a MindStudio workflow that:

Takes a script or scene description as input
Generates character reference images using a selected image model
Produces storyboard panels in sequence
Runs each image through an upscaler or background removal tool
Outputs an organized visual package into a connected project management tool like Notion or Airtable

MindStudio’s image generation capabilities span 200+ models, and its video generation tools cover the major models — all accessible from the same no-code workflow builder. You can also connect media generation steps to 1,000+ business tool integrations, so assets move automatically into the systems your team already uses.

Building a basic media workflow takes less than an hour using the visual builder. If you’re already experimenting with Luma Boards, MindStudio is a practical way to connect those outputs into an automated production pipeline. You can start free at mindstudio.ai.

How Luma Boards Compares to Other AI Storyboarding Tools

Several other tools operate in a similar space. Here’s how they differ.

Midjourney — Excellent image quality, especially for cinematic and stylized output. But Midjourney generates images independently. There’s no shared canvas, no board-level context, and maintaining character consistency requires significant prompt engineering workarounds. It’s a generation tool, not a production planning tool.

Adobe Firefly + Frame.io — Adobe’s AI integrations fit naturally into existing creative workflows. The integration depth with Premiere Pro and After Effects is a genuine strength. But Adobe’s tools are designed for professionals already embedded in that ecosystem, and they’re not purpose-built for rapid storyboard creation from scratch.

Runway — Strong for video generation and has some image generation capabilities. Runway and Luma overlap in the video space, but Runway doesn’t have a dedicated storyboard canvas workflow like Boards.

Kling AI and Pika — Both produce solid video generation results but don’t offer a dedicated storyboard canvas or agent-based generation environment.

What distinguishes Luma Boards is the specific combination: canvas interface, agentic generation, and a thinking image model built around reasoning through visual context. It’s the most purpose-built tool currently available for this pre-production workflow.

Frequently Asked Questions

What is Luma Boards and Agents?

Luma Boards and Agents is a canvas-based AI workspace from Luma AI. It uses their Uni1 thinking image model alongside an agentic interface to help users build storyboards, character sheets, mood boards, and visual sequences. The agent reads the entire canvas as context, which allows it to generate new images that stay visually consistent with what’s already on the board.

What is Uni1 and how is it different from other image models?

Uni1 is Luma AI’s thinking image model. Unlike standard diffusion models that generate images directly from a prompt, Uni1 runs a reasoning pass before generating output. This lets it process visual references, style context, and spatial information from the board before producing an image — resulting in better coherence and consistency across multiple generations on the same canvas.

How does Luma Boards maintain character consistency?

Luma Boards uses inference-time reasoning rather than fine-tuning. When you have character reference images on your board, Uni1 reads those as visual context when generating new panels. It’s not pixel-perfect, but it’s significantly more consistent than independently prompting a standard image model for each storyboard frame.

Is Luma Boards free to use?

Luma AI offers access to Boards and Agents through their platform, which has both free and paid tiers. Free users typically receive a limited number of daily generations, while paid plans unlock higher usage limits and faster generation speeds. Current pricing details are available directly on Luma AI’s website.

Can Luma Boards output feed into video production?

Yes. Images generated in Boards can serve as keyframe references for video generation in Luma’s Dream Machine or other video models. Storyboard panels can also be exported as a visual brief for animators or production teams, or used directly as input frames in video generation pipelines.

How is Luma Boards different from Midjourney for storyboarding?

Midjourney generates high-quality images from text prompts, but it treats each generation independently — no shared canvas, no board-level context, no persistent character memory. Luma Boards is purpose-built for production workflows that require consistency across many images. For standalone image generation, Midjourney remains excellent. For building a coherent storyboard or character sheet, Luma Boards is substantially better suited to that task.

Key Takeaways

Luma Boards and Agents is a canvas-based AI workspace designed for visual pre-production — storyboarding, character sheets, mood boards, and video sequences.
Uni1, the model behind Boards, uses a reasoning phase before generating images, which produces more contextually consistent output than standard diffusion models.
The canvas gives the agent persistent context — character references, scene descriptions, and previous generations all inform new outputs without re-prompting.
Primary use cases are film storyboarding, character development, visual development, and pre-visualization before video generation.
Tools like MindStudio’s AI Media Workbench can extend these workflows — connecting image generation, video creation, and asset management into automated pipelines across tools.

If you’re building visual production workflows that combine multiple AI tools, MindStudio is worth a look. Start free and build your first workflow in under an hour.