How to start making AI videos: a beginner workflow

Selecting the Right AI Video Platform

1:34 to 2:41 in the video, about 1 minute

Starting out in AI video creation requires picking an environment that will not quickly become obsolete. Because AI models evolve rapidly, relying on a platform tied to only a single model can leave creators stuck behind the curve.

A flexible platform offering a variety of state-of-the-art tools—such as Seedance 2.5, Kling, MiniMax H3 Max, FLUX, and dedicated motion transfer tools—ensures you can always switch to whichever engine delivers the best results for your specific project.

• Avoid long-term subscriptions tied exclusively to a single video model.
• Look for all-in-one platforms featuring unified image and video creation tools.

The Core Production Workflow and Asset Creation

2:42 to 12:22 in the video, about 10 minutes

Creating coherent AI videos involves a structured four-stage process: ideation, asset generation, video generation, and editing. Jumping straight into generating video clips from text usually results in inconsistencies and wasted credits.

Assets serve as reference anchors for your project. By preparing detailed multi-angle character sheets, location backgrounds, and prop images in advance, you give the video model the precise visual references it needs to keep elements identical from shot to shot.

• Generate images first because they cost a fraction of video generation credits.
• Prepare character sheets showing front, profile, back, and close-up views on neutral gray backgrounds.
• Produce dedicated location and prop sheets to keep environments and key objects stable.

Mastering the Multi-Part Video Prompt Format

12:23 to 14:22 in the video, about 2 minutes

High-quality video prompts require much more detail than a single descriptive sentence. To produce predictable motion, cinematic visuals, and timed audio, prompts must be organized into clear technical blocks.

A comprehensive prompt framework should define the overarching scene goal, specific asset references (using tag assignments like image tags), background lighting, timed stage-by-stage camera motions, audio/dialogue cues, and strict consistency instructions.

• Goal: A high-level description summarizing the action and duration.
• References: Tagged links linking characters, locations, and props to the prompt.
• Stages: Chronological second-by-second breakdowns of cuts, camera movements, and subject actions.
• Style and Audio: Specific film styles, color palettes, dialogue text, and ambient sound effects.

Automating Prompts with Custom LLM Skills

14:23 to 19:33 in the video, about 5 minutes

Writing detailed multi-part prompts manually for every shot can be overwhelming. Creators can streamline the workflow by uploading pre-built prompt skill templates into conversational LLMs such as ChatGPT.

By voice-dictating a rough narrative or scene concept into the LLM, the configured skill automatically expands the raw concept into a formatted, production-ready video prompt containing all necessary shot stages and camera instructions.

• Use speech-to-text tools to quickly describe narrative ideas without manual typing.
• Iterate with the LLM through multiple revisions to adjust comedic timing, actions, or camera distances before generating the clip.

Generating Videos: Drafts, References, and Audio Matching

19:34 to 23:25 in the video, about 4 minutes

Once prompts and asset tags are assembled, videos can be generated using either text-to-video or reference-to-video workflows. Reference-to-video provides far greater creative control because every character, location, and object is mapped directly to corresponding reference files.

To manage production budgets, start by generating short clips in low-resolution draft modes. This allows you to evaluate action timing and character behavior cheaply before committing larger credit pools to 1080p upscaling.

For realistic dialogue and character voices, creators can record their own voice lines and import the resulting audio as an MP4 reference. Linking specific voice files to individual characters in the prompt produces accurately synchronized line deliveries.

• Assign reference numbers directly to characters and scenes in the prompt settings.
• Use draft modes (e.g., 480p) to test shot logic before rendering full 1080p clips.
• Provide audio as black-screen MP4 files to help video engines match speech cadence and voice timbre.

Motion Transfer and Viral Formats

23:26 to 26:41 in the video, about 3 minutes

Another powerful AI video method involves motion transfer tools. Instead of relying purely on text-based motion instructions, motion transfer extracts physical movements from a real video and applies them to custom AI characters.

While this technique is often used to recreate viral social clips, the creator recommends recording original base footage yourself rather than copying others' content. Performing the action on camera and swapping in your character asset creates original, engaging videos with natural physical motion.

• Extract motion data directly from source footage.
• Apply custom character sheets to map your character onto human movement.
• Film original performances to maintain originality and comedic authenticity.

Final Thoughts

Producing professional AI video content requires moving past single-sentence prompting. By adopting a structured workflow—building reference sheets, organizing scene prompts into timed stages, and using draft modes to test motion—creators can achieve cinematic, consistent results without burning through resources.

As video models continue to advance, mastering foundational skills like asset referencing, LLM prompt structuring, and performance-based motion transfer ensures you can adapt seamlessly to any new generative tool that arrives.