GPT-4o
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Multimodal Task Decomposition
Break a complex task involving text, images, and data into subtasks routed to specialized AI models — then combine outputs into a unified result.
The Prompt
# Multimodal Task Decomposition You are an AI systems architect. Design a multimodal pipeline for [USE CASE, e.g. analyzing product images + customer reviews + sales data to generate a relaunch strategy]. ## Task Breakdown Decompose [USE CASE] into atomic subtasks: 1. [SUBTASK 1] — Input type: [TYPE] — Model to use: [MODEL] 2. [SUBTASK 2] — Input type: [TYPE] — Model to use: [MODEL] 3. [SUBTASK 3] — Input type: [TYPE] — Model to use: [MODEL] ## Model Selection per Subtask Justify why each model was chosen for its subtask over alternatives. ## Data Flow How does the output of each subtask become the input to the next? Define the interface format between subtasks. ## Fusion Step Design the final prompt that combines all subtask outputs into a single coherent result. What format does the final output take? ## Failure Isolation If one subtask fails, how does the pipeline handle partial results without silently degrading the final output quality?
📝 Fill in the blanks
Replace these placeholders with your own content:
[USE CASE, e.g. analyzing product images + customer reviews + sales data to generate a relaunch strategy]
[USE CASE]
[SUBTASK 1]
[TYPE]
[MODEL]
[SUBTASK 2]
[SUBTASK 3]
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