This is the product category inside our awesome GPT Image 2 prompts hub. It focuses on examples, prompt structure, recommended aspect ratios, and the kind of writing that works best for this visual task.
Product prompts become useful when they describe the object, the environment, the selling context, and the visual hierarchy at the same time. That is why product detail pages and feature boards usually outperform simple floating-object prompts.
Inside this category, the most useful prompts usually answer three questions at once: what the main visual subject is, what the viewer should notice first, and what the image is ultimately meant to support. When those three layers are clear, product results in GPT Image 2 tend to become much more stable and much easier to refine.
Start with the hero object, then add material detail, lighting setup, price or feature modules, and the intended sales context. This helps the result feel closer to a real campaign or marketplace asset.
If you are working in a team, the cleanest workflow is to choose the example closest to your target, send it into the generator, and then change one variable at a time. That gives you a clearer way to discuss whether subject choice, light treatment, aspect ratio, or tone is moving the result in the right direction.
Examples
A commerce-oriented layout prompt for detail pages, feature modules, pricing blocks, and marketplace-style presentation.
Prompt
Generate image: Taobao product detail page of a T-800 robot, showing: front, side, and back three-view drawings of the robot, product price, product details, functions and usage scenarios.
Ideal for launch pages, e-commerce boards, feature explainers, product posters, and ad variations when you need to test multiple visual directions quickly.
If you are still unsure whether to pursue this direction, ask two simple questions: is this style closer to the channel or campaign you are building for, and does it leave enough space for later layout and brand information? If the answer is yes, this category is usually worth testing first.
Start from the example closest to your goal, then refine it around your own brand, subject, and channel. That is usually more efficient than writing from a blank box.
