Can one phone photo become a full Amazon image stack & A+ Content? Learn an AI prompt framework, review-based market intel, live demos, and split-testing tips.

Shivali Patel kicks off this AI-themed AM/PM podcast episode with a simple question: What if a few camera-phone shots of your product could turn into a full, high-converting Amazon image stack, plus A+ Content, in minutes, without a photoshoot? She frames the problem sellers constantly face: creative assets are expensive, and even after you invest, you still need fast updates when dimensions change, bundles get added, or customers misunderstand what’s included (like the Project X coffin products, where many shoppers didn’t realize a gift box was part of the offer).

Kamaljit Singh from AMZ One Step and ListingOptimization AI explains that AI isn’t the magic; systems are. AI can speed up and scale production, but conversion comes from knowing what an image needs to communicate and how to direct the model. He breaks down his “Image Framework” approach for structuring prompts (intent, main subject, aesthetics, guidelines, and emphasis) and emphasizes the difference between AI “lazy users” and “power users,” especially for more complex products where details, angles, and visual references require tighter control.

From there, the episode shifts into live demos that show the workflow in action: generating market intelligence by analyzing your reviews and competitor reviews, turning that into a brief, and then producing multiple main images, secondary infographics, and even A+ Content modules quickly using templates and different image models. They also show how edits can be made with direct commands, and they close with the practical next step: don’t guess, use Helium 10 Audience and Manage Your Experiments to split test, ideally changing one element at a time so you can clearly measure what actually improves conversions.

In episode 487 of the AM/PM Podcast, Shivali and Kamaljit discuss: