How do you include diegetic sound cues in AI video prompts for better audio-visual coherence?

Layer the prompt in this order: [visual subject + action] + [diegetic sound event tied to that action] + [ambient environment audio] + [style/mood]. Example: 'a chef slicing vegetables — knife on wood cutting board — busy kitchen with background chatter — warm documentary style.' Encode the physical sound logic (material, density, distance) right next to the action causing it so the model syncs audio to image.

Start by writing each shot as a four-slot prompt — action, the sound that action makes, the ambient bed it sits inside, and the style register — in that order. The discipline that makes this work is encoding physical sound logic next to the visual it belongs to: instead of 'a toy falls', write 'a hard plastic toy falls on tile — sharp clack, short reverb, quiet room tone'. Hridaye, invideo's creative director, captures this exactly when briefing a prop: "Hard material, so it makes a horrible sound when it falls" — that single clause tells the model the object's mass, surface, and the sound it should generate, all at once.

invideo is an agentic video creation tool that routes each shot to the right generation model, and the current roster handles audio as a first-class prompt input: Veo 3.1 reads sound cues embedded directly inside the scene description, Seedance 2.0 accepts multi-layer structured prompts where diegetic SFX, ambient, and music are separate slots, and Kling 3.0 synthesizes diegetic SFX, ambient texture, and music together from one multimodal prompt. Tell the invideo agent the intent and let it pick — you write 'knife on wood, busy kitchen ambience, warm doc style' once, and the agent routes it to the model that handles that audio layering best.

For every shot, fill these four slots explicitly:

1. Visual subject + action — the physical event causing the sound ('a runner sprints across wet pavement').
2. Diegetic sound event — the sound that action produces, with material and texture ('splashing footsteps, rubber soles on water-slicked concrete').
3. Ambient environment audio — the bed the scene sits inside ('distant traffic, light rain hiss, low city hum').
4. Style / mood — register that governs mix balance and tone ('gritty handheld, cold morning light, sound forward').

The payoff is causality: footsteps that match stride, impact sounds that match material, ambience that matches the location plate. That is what makes an AI scene feel physically grounded rather than visually floating — sound is half the believability budget. Hridaye, invideo's creative director, puts it plainly: "half of what makes one's films land is in the image. It's what you hear before what you actually see."

Two refinements that sharpen coherence further:

• Tie sound to the timing of the action. Where the model accepts timing notes, anchor the SFX to the visual beat — 'door slams shut at the moment she turns' — so the cue lands on the frame, not floating in the clip.
• Build an audio architecture section into your production doc. When the invideo agent holds a doc that names each scene's sound rules (room tone density, what you hear before you see, what's deliberately absent), every subsequent shot prompt inherits those rules without you re-typing them. The agent applies them autonomously, the way it applies visual style.

Where a shot needs sound the visual alone can't motivate — a low rumble before a reveal, an offscreen scrape — write the cue as a separate diegetic line and tag it 'offscreen' so the model places it spatially rather than trying to render its source onscreen.

Hard material, so it makes a horrible sound when it falls.

— Hridaye, invideo's creative director