Multimodal generation is a powerful but nuanced process. To maximize speed and avoid factual errors (known as visual hallucinations), content teams must adhere to strict best practices that align the image and the text description.
Best Practice: After generation, check that the copy accurately reflects the image. If the text mentions 'a red button,' but the image shows a blue button, the AI has hallucinated. The human verification step is crucial here.
Do not rely on the AI to generate accurate descriptions for highly abstract images (e.g., a stylized gradient or an abstract concept). Focus the AI on concrete elements (logos, product features, specific UI components).
Use a high-quality, high-resolution source image for the AI's analysis, but ensure the resulting product description copy is optimized for web speed. A good workflow means using a clean, well-lit image for the AI, even if you publish a compressed version.
Always dedicate a section of your prompt to SEO. Mandate that the description follows a clear, scannable structure: a persuasive headline, a bulleted feature list, and a strong conclusion.
Use the AI for macro-creation (the entire draft) and the human for micro-editing (polishing flow, fixing punctuation, and injecting the final brand voice). The process should be 90% AI creation and $10%$ human refinement, not $100%$ AI deployment.
Continuously track the conversion rate of AI-generated descriptions. Use the data to refine your core prompts (e.g., 'If Version B copy converts higher, emphasize urgency in all future prompts').