Interested in how to create AI-generated video that looks cinematic, not cheap? Do you want to have a repeatable workflow for turning a simple concept into polished AI video content using tools like Seedance? In this article, you will learn a step-by-step process for creating professional-quality AI video, from concept development and building key visuals to generating clips with Seedance and assembling them into a finished product.
The biggest misconception about AI video is that it’s easy. Entering a prompt into a video model yields a result, but its quality is entirely dependent on the creator’s ability to communicate with the tool. Ross Symons notes that most people who dismiss AI video as “low quality” are seeing the result of vague prompts, not the limits of the technology itself.
Understanding Models: LLMs vs. Diffusion Models
The first thing to understand is the difference between how Large Language Models (LLMs) and diffusion models process instructions. LLMs, such as ChatGPT, Claude, or Gemini, understand conversational intent. A diffusion model, the underlying technology behind most AI image and video generators, including Midjourney and Seedance, does not.
- Diffusion models extract visual keywords from a prompt and ignore conversational “fluff.”
- The phrase “create me an image of a cat walking on a beach wearing a cowboy hat” works in Midjourney, but the model doesn’t parse that sentence the way a chatbot would. It looks for visual keywords: cat, beach, cowboy hat.
Prompting strategies that work well in chat do not directly translate to image and video generation. Each model has its own prompting structure, and learning that structure is what separates a polished result from an ordinary one. Ross notes that certain tools excel at specific tasks.
“Midjourney, for example, remains the preferred tool among creatives for art direction, ideation, and creative exploration,” — Ross Symons.
ChatGPT’s image generation has the advantage of a reasoning layer that interprets intent, but many professionals still prefer the aesthetic output of a specialized image model.
For those who don’t know how to write structured prompts for a tool like Midjourney, there’s a practical life hack. Instead of learning the syntax, tell ChatGPT what you want the desired image to look like and ask it to write a prompt in Midjourney format. ChatGPT converts conversational descriptions into a structured, keyword-based format that diffusion models respond to, leading to significantly better results.
Pro Tip: Image generation is the foundation for AI video. Mastering the creation and refinement of static images first leads to a much higher success rate when transitioning to video, because the same principles of prompting, composition, and visual direction apply.
1. Developing the AI Video Concept
The concept is the underlying idea of what the video is trying to convey. It doesn’t have to be complex or deeply artistic. It can be as simple as “I want to show my product in an unexpected environment” or “I want to explain this technique with a visual metaphor.” The point is to have an intention before touching a tool.
Ross illustrates this with a project he originally created as a stop-motion animation many years ago. The concept: a can of Red Bull sits on a table. A piece of paper slides, folds into an origami bull, bumps into the can, opens it, drinks the liquid, grows wings, and flies away. The whole work is a play on the words “Red Bull gives you wings.” This concept has transitioned across different mediums. He recently recreated it using Seedance, feeding the sequence into an AI video model with a couple of image references, and the concept held up because the idea was strong regardless of the production tool.
Ross recommends using LLMs to further develop the concept. Even a basic idea can be expanded by asking ChatGPT to help extrapolate the narrative, suggest visual sequences, or variations. The goal is to have a clear understanding of the story before moving on to visual development.
2. Creating Key Visual Elements
Once the concept exists, the next step is to develop the key visual elements that will anchor the video. Ross divides this into three components:
- Subject (or hero): This is the focus of the story. It can be a product, a person, or any object that drives the narrative. For the perfume ad Ross created, the hero was the bottle itself. He generated a product image mockup with Midjourney, establishing the look of the bottle before doing anything else. Creating product mockups with ChatGPT, Midjourney, or Gemini is a valid starting point when professional product photography is not available.
Pro Tip: When using a personal photo as a character, isolate the subject on a solid background. Do not use a photo with a busy environment or other people. Provide multiple photos taken from different angles, all showing the subject in the same clothing. This gives the model clear data to work with when placing the character in new environments, poses, and scenarios.
Using Camera Angles for Visual Storytelling
Camera perspective is one of the quickest ways to elevate AI-generated visuals beyond the flat, centered composition most models produce. A few basic cinematography principles go a long way.
- Low angles make a character powerful and dominant.
- High angles can make a character appear submissive or vulnerable.
- Close-ups create intensity.
- Wide, pulled-back shots with empty space around the subject suggest isolation or vulnerability.
A practical tip for those without a cinematography background: use ChatGPT to analyze a film still. Upload an image and ask the model to explain what creates a certain emotional effect. Is it the camera angle? Dramatic lighting? Soft bokeh? Contrast? ChatGPT will break it down using the correct cinematic terminology, which can then be directly used in image and video prompts.
Ross tested this approach by asking ChatGPT to generate “Guy Ritchie’s six most commonly used shots” in a single image. The result included close-ups, high-angle shots, and several techniques Ross hadn’t encountered before, each usable as a reference for future prompts. Creators can reference specific directors or films without knowing the technical vocabulary. Phrases like “make this character look like Aladdin in this scene” or “show me a Guy Ritchie-style shot with this character in this environment” yield results that differ from the generic, centered output most people receive.
3. Creating an AI Video Storyboard Using Keyframes
A keyframe in the context of AI video is an image used as a reference point for the model. A storyboard is a sequence of 6-12 keyframes that outline the main moments of the video, establishing the angle, lighting, and composition for each moment.
The storyboard serves the creator more than the model. It provides structure, prevents overloading a single clip with too much action, and establishes a clear sequence of events before video generation begins. Ross emphasizes that the storyboard doesn’t need to be professional. It’s a planning tool, and rough images are perfectly adequate if they convey how each moment should look and feel.
There are two main approaches to using keyframes with AI video models:
- Start Frame + End Frame + Prompt: This method provides the model with an image to start the video, an image for its end, and a text prompt describing what happens in between. For example, the start frame is an empty surface. The end frame shows a Red Bull can centered in the shot. The prompt reads: “A Red Bull can slides in from the right at a slow speed and stops directly in the center.” The combination of visual anchors and text instruction gives the model clear constraints.
- Start Frame + Prompt Only: This method uses only a starting image and allows the prompt to guide the action without a fixed endpoint. It offers more creative freedom. For a 10-second clip, the start frame could be an empty surface, and the prompt could read: “A Red Bull can slides in from the left, a paper airplane flies in from above, lands next to the can, unfolds into a flat sheet of paper.” The model fills in the motion and timing.
Pro Tip: To create a longer video, stitch clips together by extracting the last frame from the previous clip and using it as the start frame for the next. This creates visual continuity across a multi-clip sequence without having to regenerate consistent elements from scratch.
Common Mistakes When Creating Keyframe Sequences
The most common mistake Ross sees is people cramming too much action into a short clip. A 5-second clip can only accommodate one or two actions. Writing a long paragraph describing a sliding can, flying paper, a bull forming, and an explosion, all within five seconds, overloads the model. The result is distorted limbs, warped perspectives, and visual artifacts. The solution is to match the complexity of the prompt to the duration of the clip.
Ross also distinguishes between using images as keyframes and using them as references. Keyframes require precise reproduction at specific points in the video, often leading to awkward transitions and unnatural camera movements as the model is forced to move between two rigid endpoints. References give the model an idea of the desired look without requiring pixel-perfect accuracy, and they tend to produce smoother, more natural results. Ross recommends using references instead of keyframes in most cases.
4. Video Generation with Seedance and Assembling the Final Product
Seedance, developed by ByteDance (the company behind TikTok), stands out for its adherence to prompts and the accuracy of reference images. Ross describes it as almost flawless in both areas, which is a significant step forward compared to video models even two years ago.
Seedance is not a standalone application. It is a model accessed through aggregator platforms. Ross recommends Luma AI (lumalabs.ai) as the preferred platform, along with Flora, Figma Weave, Artlist, Imagine Art, Open Art, and Krea. These platforms provide access to Seedance alongside other video models such as Kling 3.0, Veo 3, and others, all connected via API.
Google Veo 3 (available via Gemini) offers free video generation and was considered cutting-edge before the advent of Seedance and Kling 3.0. Ross notes that while Veo is useful, skills learned on one model do not automatically transfer to another. Each video model has its own prompting structure. Practice with Veo builds general familiarity with AI video, but getting the best results on Seedance requires learning how Seedance specifically responds to prompts, timing instructions, and reference images.
How to Effectively Use Prompts in Seedance
Seedance supports time-segmented prompting, which allows creators to specify what happens at certain intervals within a single clip. For a 15-second clip, the prompt might be structured as: “Between 0 and 4 seconds, this happens. Between 4 and 8 seconds, this happens. Between 8 and 12 seconds, this happens.” The model adheres to these timing instructions, allowing for the choreography of multi-step sequences in a single generation rather than stitching together multiple short clips.
Seedance Cost and Scaling Workaround
Seedance offers a choice of durations from 5 to 30 seconds per clip. Ross advises beginners to start with shorter, low-resolution clips to get familiar with the workflow. Generating a 30-second high-resolution clip without experience often leads to wasted money and unsatisfactory results. A 30-second Seedance clip at 720p resolution costs approximately $14. Increasing the resolution to 1080p roughly doubles the cost to $28-32. These prices are significantly higher than earlier AI video models, where 5-second clips cost less than $0.20, but the quality difference is also significant.
A cost-effective alternative is to generate at a lower resolution and then upscale. Ross generated a 480p clip for approximately $6, then upscaled it twice using the platform’s built-in tools to near-4K quality for an additional $3. The total cost of $9 yielded quality comparable to a native high-resolution render, at about a third of the price. The two leading upscaling tools are Topaz Labs and Magnific, both of which are integrated into most aggregator platforms.
Conclusion
Mastering AI video isn’t just about mastering tools; it’s about developing a director’s mindset. By applying principles of concept, visual development, and storyboarding, you can create high-quality AI video content that looks professional and engaging. Start with a clear idea, use LLMs to develop it, create strong visuals, and meticulously plan your sequences. Then you can scale your video productions to levels previously impossible, and now possible.
Frequently Asked Questions
What is Seedance and how does it work?
Seedance is an AI model for video generation developed by ByteDance. It allows you to create videos based on text prompts and reference images, while ensuring high accuracy and quality. It is accessed through aggregator platforms such as Luma AI.
How much does it cost to create a video using Seedance?
The cost of a 30-second clip at 720p resolution is about $14, and at 1080p it’s $28-32. However, you can save money by