Most disappointing images come from prompts that are vague in exactly the ways that matter to the model. Five specific changes fix most of it.
1. Brief it like a photographer, not a search engine
“A dog” gives the model almost nothing. “A golden retriever running through shallow water at sunset, low angle, motion blur on the legs” gives it a subject, lighting, camera position, and effect. Camera angle, lighting, mood, and composition matter as much as the subject itself.
2. Use a reference image when style matters
Most current tools, including Meta’s Muse Image, accept a reference photo alongside your prompt. For a specific art style or palette, a reference image communicates it more precisely than any amount of description.
3. Know the specific things models still get wrong
Text in images, hands and complex physical interactions, exact object counts, and consistency across multiple generations of the same character remain genuinely unreliable. Expect to regenerate for any of these.
4. Iterate instead of rewriting
“Same composition, warmer lighting” beats a longer new prompt trying to fix everything at once, the same principle covered in our prompt engineering guide for text.
5. Treat the first result as a draft
Not a final answer. Budget for two or three passes on anything you actually plan to use, rather than expecting the first generation to be it.
Read Meta’s own announcement of Muse Image for more detail.
