- Structure beats stream-of-consciousness. Layer seven elements in order: subject, action, setting, camera, lighting, style, and audio. Naming a camera move and giving the lighting a direction is the minimum bar for a prompt worth iterating on.
- Write the sound. LTX-2.5 generates audio in the same pass as the picture, so ambient noise, music, and dialogue all belong in the prompt. Put spoken lines in quotation marks and name the language or accent if it matters.
- Describe your cuts. A single generation can hold two to four connected shots. Name each transition in prose, re-establish the new framing, reuse the same identifiers for recurring subjects, and say whether the audio carries across.
An AI video prompt is a text instruction that tells a video generation model what to make, how it should look, and how it should move. Write a vague prompt and you get a vague clip. Write a structured one and you get a shot you can actually cut into a scene.
This guide covers what an AI video prompt is, how to structure one for any model, the vocabulary professional workflows lean on, and how to iterate without starting over. The specific examples use LTX-2.5, which generates video and synchronized audio from the same prompt, but the fundamentals carry across models.
What is an AI Video Prompt?
An AI video prompt is a text instruction that guides AI models to generate specific video content. Think of it as creative direction for an AI filmmaker. Your prompt tells the AI what to create, how it should look, how elements should move, and what atmosphere to establish.
At its most basic, a prompt might be as simple as "a cat walking through a garden." But effective prompting goes much deeper. Professional-level prompts specify camera angles, lighting conditions, motion patterns, composition details, and stylistic choices that shape every aspect of the generated video.
Modern AI video models have evolved from basic text-to-video generation to multi-modal prompting. Instead of relying solely on text, you can combine written prompts with reference images, audio tracks, and control signals like depth maps or pose skeletons. That means you can show the model exactly what you want while using text to describe how those elements should behave and evolve over time.
The evolution from pure text input to multi-modal prompting represents a significant leap in creative control. You're no longer limited by your ability to describe visual concepts with words.
How to Write AI Video Prompts
Structured prompts outperform stream-of-consciousness ones. The pattern most professional creators converge on layers six elements in a consistent order. Ordering matters because most models read left-to-right and weight the earliest tokens more heavily.
The Seven-Part Prompt Structure
Use this as your starting scaffold, then adjust:
Subject: The specific noun the shot is built around. "A woman in her 30s in a navy technical shell" beats "a person." Be specific about the main element viewers should notice.
Action: What the subject is doing, described with a specific verb. "Walking briskly" beats "walking." Describe movement and behavior clearly.
Setting: Where and when. "Tokyo backstreet at 6pm, wet asphalt after rain" gives the model a lighting cue for free. Environmental details establish context and atmosphere.
Camera: Shot size and movement. "Medium tracking shot from the left, handheld" tells the model what to render, not just what to depict. How should the camera behave?
Lighting: Quality and direction. "Warm sodium streetlights, soft rim light on the shoulder" carries more information than "atmospheric." This dramatically affects mood.
Style: A named aesthetic reference. "Shot on 35mm, muted grade, documentary" is stronger than "cinematic." Reference specific looks or artistic movements.
Audio: What the shot sounds like. Ambient sound, music, and speech all belong in the prompt, because LTX-2.5 generates audio in the same pass as the picture. Put spoken dialogue in quotation marks, and name the language or accent if it matters. Leave this out and the model picks the soundtrack for you.
A single well-structured sentence per element is enough. Concatenate them with commas. Models do not need bullet formatting, and long comma-separated prompts generally encode well through modern text encoders.
Balancing Specificity and Creative Freedom
One of the trickiest aspects of prompting is knowing when to be detailed and when to leave room for the AI's interpretation. Overly rigid prompts can produce stiff, unnatural results. Too vague, and you'll get unpredictable outputs that miss your vision.
Be specific about elements that are critical to your vision. If brand colors, specific products, or particular compositions are essential, describe them in detail. For supporting elements and atmospheric touches, broader descriptions often work better, allowing the AI to fill in natural details that enhance the overall scene.
Weak Prompts and Strong Prompts
Weak: "A product shot of a bottle."
Strong: "Close-up product shot of a brushed-steel water bottle on a bone-white marble surface, slow 20-degree camera arc from the left, soft key light from the top-left with a subtle fill, matte-black backdrop, high-end commercial aesthetic, shallow depth of field."
Strong: "Wide tracking shot of a young courier in a rain shell walking briskly through a Shibuya backstreet at 6pm, glancing at a paper map, warm sodium streetlights reflecting on wet asphalt, camera dollies alongside at hip height, shallow depth of field, documentary look on 35mm, rain on fabric and distant traffic under a low synth drone."
The strong prompts do four things the weak one does not. They name the exact subject, they specify a camera behavior the model can render, they give the lighting a direction, and they say what the shot sounds like. That's the minimum bar for a prompt worth iterating on.
How to Direct Camera Movement
Camera vocabulary is where most prompts lose their grip. Models respond to standard cinematography terms because those terms are dense in the training data. Prefer named moves to vague adjectives.
Shot size: extreme close-up, close-up, medium close-up, medium, medium wide, wide, extreme wide.
Angle: low angle, high angle, eye-level, overhead, Dutch angle.
Movement: static, slow push-in, slow pull-back, dolly left, dolly right, handheld tracking, orbit, crane up, whip pan.
Depth: shallow depth of field, deep focus, rack focus from foreground to background.
Name the move first and describe intensity second. "Slow orbit, roughly 45 degrees over the shot length" is more legible than "the camera swings around a lot."
AI Video Prompt Examples
Brand Marketing
Sleek smartphone emerging from darkness into dramatic spotlight, rotating slowly to showcase all angles, premium metallic finish catching light, minimalist black background, smooth camera zoom toward product details, high-end commercial aesthetic with shallow depth of field.
Narrative Storytelling
Medium close-up of elderly craftsman carefully examining a wooden sculpture in his workshop, afternoon sunlight streaming through dust-filled air, warm golden hour lighting, slight camera push-in emphasizing focused expression, shallow focus on weathered hands and detailed wood grain, documentary-style naturalistic feel.
Social Media (Vertical Format)
Dynamic overhead shot of diverse hands reaching for colorful smoothie bowls on bright white table, vibrant tropical fruit toppings, natural daylight from above, quick energetic movements, vertical 9:16 format optimized for mobile viewing, trendy lifestyle content aesthetic.
Product Demonstration
Close-up sequence of hands demonstrating smartwatch features, tapping through interface with smooth transitions, clean modern workspace background slightly out of focus, soft professional lighting eliminating harsh shadows, slow methodical pacing allowing clear view of each action, Apple-style product demo aesthetic.
Common Prompting Pitfalls
These mistakes recur across creators and models:
Conflicting directions: "Fast-paced" and "meditative pacing" in the same prompt make the model pick one arbitrarily. Keep the tone coherent.
Camera contradictions: A "static wide" prompt with "sweeping motion" produces neither reliably.
Over-stuffed action: Three verbs in one prompt for a short clip guarantees at least one is dropped. Split into separate shots.
Vague qualifiers: "Nice," "good," and "beautiful" carry almost no signal. Replace with named references.
Missing motion information: Static descriptions without motion cues can produce flat, lifeless videos. Always specify how elements should move or how the camera should behave.
How to Iterate Without Starting Over
Iteration beats writing a perfect prompt on the first try. The failure mode is rewriting the whole prompt every time. The fix is changing one variable per generation and comparing.
A useful iteration order, from cheapest to most expensive change:
- Style keyword: swap "documentary" for "commercial" or "shot on 35mm" for "shot on Alexa."
- Lighting direction: swap "top-left key" for "back-lit rim."
- Camera move: swap "slow push-in" for "static wide."
- Action verb: swap "walks" for "strides" or "hesitates."
- Subject specificity: add age, dress, demeanor.
Only re-roll the seed after exhausting these. Changing model settings (guidance scale, steps) is the last resort — it changes everything at once, making A/B comparison harder.
Prompting LTX-2.5
LTX-2.5 responds best to cinematic, single-subject scenes with clear camera language, consistent lighting, and well-described audio. A few capabilities change how you write for it.
Writing Audio Into the Prompt
Because sound and picture come out of the same generation, audio direction belongs in the prompt rather than in post. Describe ambient sound, music, speech, or singing directly. Put dialogue in quotation marks, and specify language and accent where it matters: She whispers, "He's late." works; "she says something worried" does not.
Multi-Shot Prompts
LTX-2.5 can generate several distinct shots joined by explicit cuts inside a single prompt. Two to four shots per generation is the working range; more cuts need shorter, clearer beats per shot.
Write the whole scene as one chronological paragraph rather than a shot list or numbered beats, and at every cut do four things:
Name the transition in natural language. "A hard cut transitions to...", "The view cuts to a close-up of...", "The image dissolves into...".
Re-establish the new shot. Shot scale, camera angle, who or what is in frame, and lighting if it changed.
Keep identity consistent. Reuse the same visual identifiers for recurring people or objects: "the woman in the red coat, earlier at the table, now...".
State audio continuity. Say whether music, dialogue, or ambience continues or changes: "the piano score continues across the cut" or "the dialogue drops, only wind remains."
Give each shot a clear job, such as establish then detail then reaction, or wide then medium then close-up. Avoid conflicting geography or unexplained costume changes between cuts unless you say the cut jumps time or place.
When you want unbroken camera motion, intimate performance, or dialogue that stays lip-synced in one framing, stay with a single continuous take instead.
Single-Shot Structure
For one continuous take, write a single flowing paragraph in present tense, roughly four to eight descriptive sentences. Match the level of detail to the shot scale, since close-ups need more than wide shots. Express emotion through physical cues rather than abstract labels: "her jaw tightens" carries more than "she looks sad."
The Prompt Enhancer
LTX-2.5 ships an optional prompt enhancer that expands a short prompt with visual, cinematic, and temporal detail before it reaches the text encoder. It's on by default in the standard templates.
Leave it on when you're working from terse prompts and want the model to fill in the cinematic language. Turn it off when your prompt is already precise and you want your exact wording preserved, which is usually the case once you're iterating on a specific shot.
Anchoring With Images and Keyframes
Text has limits. Supplying a first frame anchors the subject and composition, and the strength of that conditioning is adjustable, so you can hold tightly to the reference or leave the model room to move.
You can also supply a first frame and a last frame and let the model generate the motion between them. That turns a hard-to-describe camera move into two fixed points, which is far more reliable than writing the movement in prose.
Motion and Structure Control
For work where prose isn't precise enough, LTX-2.5 accepts control signals through IC-LoRA adapters: pose skeletons to anchor body structure, depth maps for spatial layout, edge maps for composition, and drawn motion trajectories for camera and subject paths. These sit alongside the text prompt rather than replacing it, and the guidance for prompting alongside them is to describe visual style rather than the control signal itself.
Best Practices for Prompting LTX-2.5
Write the audio. It is generated with the picture, so leaving it out means leaving it to chance.
Combine text and visual references. Text describes action, timing, and motion. Images define style, composition, and visual specifics.
Use Retake for targeted refinement. If a generation is mostly right but one moment is off, regenerate just that segment rather than the whole clip, preserving the surrounding footage.
Use a negative prompt. The standard templates apply one by default. It is the cleanest way to steer away from a recurring artifact without cluttering the positive prompt.
Start simple, add complexity. Begin with the core shot, then layer detail as you iterate.
Use shot types and angles in the text even when using references. Specifying "low angle" or "over-the-shoulder" helps the model understand spatial relationships and framing intent.
AI Video Prompt Tips
1. Master Camera Angle Vocabulary
Familiarize yourself with standard cinematography terms. Using "Dutch angle," "bird’s eye view," "eye-level tracking shot," or "low angle hero shot" communicates instantly recognizable framing. This technical vocabulary produces more predictable, professional results than vague descriptions like "interesting angle."
2. Use Lighting Descriptors Strategically
Terms like "golden hour," "overcast softbox," "harsh midday sun," "neon-lit," or "rim-lit silhouette" give the AI clear direction on both technical setup and emotional atmosphere. Don’t leave lighting to chance.
3. Specify Motion Direction and Speed
Instead of just "moving," describe how things move: "drifting slowly left to right," "rapid vertical ascent," "gentle swaying motion," or "sharp whip pan." Direction and speed details ensure the AI generates motion that matches your intended energy and pacing.
4. Reference Established Artistic Styles
Mentioning recognized styles helps the AI understand your aesthetic goals. References like "Wes Anderson symmetry," "noir cinematography," "documentary realism," or "music video energy" tap into visual conventions the model recognizes.
5. Iterate Systematically
Keep successful prompt elements and adjust one variable at a time. This systematic approach helps you identify which changes improve results and builds your understanding of how specific prompts affect output.
6. Leverage Visual References When Possible
Text has limits. When your vision is highly specific visually, use reference images alongside text prompts. A single reference image can communicate more about desired style, composition, or mood than paragraphs of description.
7. Consider Frame-by-Frame Planning
For complex shots, think through the progression of frames. Planning how your scene evolves from beginning to end helps you write prompts that account for timing, transitions, and narrative progression rather than just describing a static moment.
8. Understand your model's strengths.
LTX-2.5 is strong on synchronized audio in a single pass, multi-shot sequences that hold continuity across cuts, and adherence to complex prompts through its Gemma 4 text encoder. Writing prompts that lean on those, rather than fighting them, is most of the skill.
9. Avoid Over-Prompting
More detail isn’t always better. Extremely long, complex prompts can confuse models or produce overworked results. Focus on the most important elements and trust the AI to fill in supporting details naturally.
10. Manage Expectations Realistically
Two things the model still handles unevenly. On-screen text has improved but exact spelling and frame-to-frame consistency are not guaranteed, so keep any text short and prominent, check it across the whole clip, and add critical titles or logos in post. Highly chaotic motion can still introduce artifacts, while simpler, plausible movement is more reliable. Everyday motion like dancing is fine.
Conclusion
Effective AI video prompting combines clear text instructions, strategic visual references, and control signals when text alone isn't precise enough. It's both an art and a science, requiring creativity, technical understanding, and systematic experimentation.
The most important takeaway is that AI video prompting is a learnable skill that improves dramatically with practice. Pay attention to what works, refine what doesn't, and gradually build a personal library of effective prompting techniques.
Start with the seven-part structure (subject, action, setting, camera, lighting, style, audio), iterate one variable at a time, and describe your cuts explicitly when a scene needs more than one shot.
