How to Build a Continuous AI Video Sequence
A practical framework inspired by the “Rabbit March” project
AI tools can now generate stunning visuals and soundscapes, but creating a piece that feels continuous across multiple clips still demands human direction.
During the Rabbit March experiment, we developed a workflow that connects individually generated scenes into one seamless motion piece — synchronized to music, rhythm, and atmosphere.
Tools used in the process:
- ChatGPT — to translate musical structure and timing into visual scene prompts
- Suno — to compose the underlying music track
- getimg.ai — to generate still and moving visual scenes based on those prompts
- VEED.com — to edit, align, and finalize the video sequence
Together, these tools form a hybrid creative system: human-guided storytelling amplified by AI.
1. Start with a Core Motif
Begin with a single recurring subject that defines your sequence — a motif.
This could be a marching group, a lone traveler, a drifting balloon, or any image that can visually evolve without breaking identity.
The motif serves as your continuity anchor, appearing in every clip as the world changes around it.
Example: In Rabbit March, a line of rabbits was present in every shot, even as the environment shifted from meadow to glowing forest to sunrise parade.
2. Outline the Narrative Arc
Think in terms of progression, not plot.
Describe the flow as emotional, visual, or rhythmic — for instance:
calm → curiosity → wonder → climax → resolution.
Sketch a short arc of five to ten stages. Each will become a separate scene prompt.
Example arc:
- Meadow morning
- Into the forest
- Lights appear among trees
- Parade begins
- Sunrise and celebration
3. Write Scene Prompts Sequentially
Each segment should be a self-contained description that also connects to what came before it.
| Element | Description | Example |
|---|---|---|
| Setting | Time, place, and visual tone | “A misty forest with faint golden light filtering through the trees.” |
| Action | What the motif or camera is doing | “The rabbits continue marching, their shadows stretching ahead.” |
| Transition cue | Hint linking to the next scene | “As the mist begins to glow with color…” |
These cues help AI systems maintain directional flow and light consistency between clips.
4. Maintain Stylistic Continuity
Decide on a visual language early — realism, painterly, clay animation, etc.
Keep it constant across prompts. Reinforce coherence by matching:
- Lighting (e.g., soft dawn light that slowly brightens)
- Camera perspective (side view, dolly forward, or aerial pan)
- Motion direction (left-to-right)
- Color palette (e.g., pastel tones gradually warming)
Small repeated details — such as wind direction or shadow length — make the viewer feel an unbroken world.
5. Generate, Review, and Adjust
Render each clip individually in getimg.ai, then compare adjacent scenes:
- Do they match in tone and lighting?
- Does motion continue logically?
- Does the motif stay recognizable?
A key practical technique is to feed the final still frame of each generated clip back into the next prompt as its starting image.
This ensures that the opening frame of the new segment matches the ending of the previous one, maintaining continuity in composition, lighting, and motion direction.
It effectively gives the AI a “memory” of the prior scene, allowing smoother transitions even when generating clips separately.
Re-use phrasing like “in the same golden light” or “continuing along the path” to reinforce linkage.
A few careful re-renders — plus the still-frame carryover method — often turn jump cuts into seamless visual flow.
6. Assemble and Polish
Combine the finished clips in sequence.
Use simple crossfades or match cuts to bridge small mismatches.
Add a consistent soundtrack or ambient loop to bind the sequence rhythmically.
Rabbit March was edited in VEED.com, which made it easy to trim, synchronize, and color-match clips directly in the browser.
7. Why This Method Works
This approach balances AI spontaneity with human direction.
By treating each prompt as a frame in a larger motion, you guide the generator toward temporal coherence — something most models can’t yet ensure automatically.
The result feels designed rather than assembled: a continuous journey through individually generated moments.
8. Align Scenes to a Musical Timeline
When the visuals follow a soundtrack, synchronization turns the project into a unified audiovisual story.
In Rabbit March, we began with a time-stamped musical index of the Suno track — noting every change in mood, tempo, or instrumentation.
That timeline was fed into ChatGPT, which divided it into 8-second sections (matching getimg.ai’s current clip length).
For each section, ChatGPT generated a detailed prompt describing scene, lighting, motion, and tone.
Example input to ChatGPT
0:00–0:20 soft intro (90 BPM, piano and strings); 0:20–0:40 light percussion begins; 0:40–1:00 tempo increases and horns enter.
Instruction: Divide into 8-second sections and create prompts that visually express each moment in continuity.
Example output
- 0:00–0:08 – Misty meadow at dawn, rabbits awakening to the first notes of piano.
- 0:08–0:16 – March begins in rhythm with soft drums; camera tracks left to right.
- 0:16–0:24 – Light pierces the treetops as strings swell.
This makes ChatGPT an intermediary between sound and sight — translating tempo and structure into cinematic instruction.
Step 1 – Measure the BPM
We measured the Beats Per Minute with a metronome and DAW tap tool.
Knowing the exact tempo allowed us to describe motion precisely:
“The camera pans right in time with a 90 BPM rhythm; each step matches one beat.”
Step 2 – Incorporate Rhythm into Prompts
Once BPM and timestamps were defined, rhythm was written into the visual language:
“Lanterns rise on every second beat as the melody swells.”
“The forest glows in pulses that follow the drumline.”
This doesn’t make the AI hear the music, but it gives it contextual rhythm, creating visuals that feel naturally synchronized when edited to the soundtrack.
9. Tools Used
| Tool | Purpose | Role in Workflow |
|---|---|---|
| ChatGPT | Scene generation | Divided the musical timeline into 8-second segments and generated coherent prompts for each clip. |
| Suno | Music creation | Produced the original track whose BPM and structure guided all visual timing. |
| getimg.ai | Image / Video generation | Created each 8-second AI video clip from the ChatGPT prompts, using the last still frame of one clip as the first frame of the next. |
| VEED.com | Video editing | Assembled, synchronized, and finalized the full sequence into a single narrative flow. |
Each tool handled a different layer — text, sound, image, and video — yet together they created a tightly synchronized, human-guided AI composition.
Final Thoughts
Rabbit March showed that continuity and rhythm come from intentional design, not coincidence.
By combining a structured musical map, BPM awareness, AI-assisted scene writing, the still-frame carryover technique, and careful editing, you can turn separate AI clips into a unified cinematic experience — one where image and sound move together as if born from the same creative breath.