Why your AI images aren't turning out the way you want
It's not just about learning to see through the camera lens. It's about understanding how AI understands you.
Give the model a clear visual priority.
Image models interpret your words through learned visual associations. If you ask for a close-up selfie and also describe an elaborate skyline, furniture, and background activity, the model may widen the shot to accommodate those competing details.
Every instruction must support the intended photograph, not compete with it.
Tell AI what it doesn't already know.
“High-end nightclub lounge” already carries learned associations with low lighting, upscale furniture, and a social atmosphere. You don't always need to list every fixture or specify lighting technicalities. Add detail when it controls something essential or corrects an actual test result.
Think like the camera.
Describe what should be visible in the frame, not everything that could exist in the world beyond it. Prioritize subject, pose, and camera distance. Keep the environment subordinate when the subject is the point.
Test the interpretation.
A beautiful image can still miss your intended composition. Compare the result with your goal, identify the most important mismatch, and change only the instructions that caused it. Different generators may interpret the same words differently.
Practical guidance developed from extensive image-generation experimentation. Results vary by generator, model version, and settings.
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