multimodal-orchestration

Multimodal Orchestration

AI interactions increasingly span multiple modalities — text, images, voice, code, tools, and structured data. Designing how these modalities work together is orchestration.

Modality Selection

Each modality has strengths:

• Text: Precise, editable, referenceable. Best for instructions, explanations, and nuanced content.
• Image: Spatial, holistic, immediate. Best for layouts, diagrams, and visual concepts.
• Voice: Natural, hands-free, emotional. Best for conversational flow and accessibility.
• Code: Executable, precise, verifiable. Best for technical specifications and automation.
• Structured data: Tables, forms, JSON. Best for comparison, configuration, and data entry.
• Tool use: Actions in external systems. Best for execution, not just generation. The designer decides which modality the AI uses for each part of a response — and which modality the user uses for each input.

Cross-Modal Transitions

When the interaction switches modalities, design the transition:

• Text to image: "Here's what that layout could look like" — the AI generates a visual from a text description
• Image to text: The user uploads a screenshot, the AI describes or critiques it
• Text to tool: The AI writes a plan, then executes it via tool use
• Voice to text: Spoken conversation captured and summarised as structured notes Transitions should feel seamless. The user shouldn't have to manually switch modes.

Modality Conflicts

Sometimes modalities compete:

• Text says one thing, the image shows another
• Voice tone contradicts text content
• Structured output doesn't match the conversational context Design for consistency across modalities. Establish a primary modality for each interaction type and treat others as supporting.

Design Artefacts

• Modality maps showing which modality is used at each interaction point
• Cross-modal transition specifications
• Input/output modality matrices per feature
• Fallback definitions when a modality is unavailable