Getting a great AI-generated image starts with being specific about what you want the viewer to notice first, then layering in the details that control style, lighting, and composition. A good approach is to describe the subject, the scene, and the “camera” choices in a single, clear request—then refine based on what the first result gets wrong.
Lead with the main subject and what the image is for. Example: “A minimalist product photo of a matte black insulated water bottle on a light gray background.” This anchors the model on the primary object and the overall vibe.
Specify materials, colors, age, facial expression, wardrobe, environment, and key props. Replace vague words like “nice” or “beautiful” with observable traits: “soft morning window light,” “shallow depth of field,” “subtle condensation droplets,” or “brushed aluminum texture.”
Choose an art direction (e.g., “studio photography,” “watercolor illustration,” “retro 1970s ad”), then define lighting and framing. Useful composition cues include “centered,” “rule of thirds,” “wide shot,” “close-up,” “top-down flat lay,” and “negative space for text on the right.”
Request an aspect ratio and resolution-friendly framing: “square 1:1,” “vertical 4:5,” or “banner 16:9.” If your image needs clean edges for a product page, ask for “simple background, crisp outline, no motion blur.”
Add a short “avoid” list to reduce mistakes: “no extra fingers, no warped logos, no unreadable text, no cluttered background.” Keep exclusions limited so they don’t overpower the main description.
After the first generation, adjust one variable at a time (lighting, angle, background, or style) so improvements are predictable. For a practical way to review details and catch errors before downloading or publishing assets, use the checklist in this guide.
Avoid relying on generated text; request “no text” and add typography later in design software. For logos, describe the brand mark conceptually and use a real logo overlay afterward to ensure accuracy.
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