People say AI images are “luck”—repeatable quality is clear intent + clean structure + explicit constraints + small iterations. Make GPT Image 2 understand you the first time, more often.
Series：(I) Model selection & parameters · (III) Advanced prompt techniques · (IV) Generation use cases · (V) Editing use cases · (VI) Character consistency
Mantra: Scene → Subject → Details → Constraints
State the goal, describe the look, then lock what must not drift.
Standard prompt structure
Keep a fixed order—and name the deliverable (ad, UI, infographic, poster, photo, etc.) so the model locks the right mode:
- Purpose: what is this image for?
- Scene: where; environment; context
- Subject: the hero object/person
- Details: materials, palette, motion, lettering, mood
- Constraints: forbidden changes; must-preserve list
Skeleton blockquote
Generate a [purpose] image. Scene: [background]. Subject: [hero]. Show [key details]. Composition: [framing]. Avoid [no-go list]. Preserve [invariants].
Specificity + quality cues
- Name materials, shapes, textures, medium (photo / watercolor / 3D render)
- For realism, say
photorealistic/ photographic - Camera language steers mood—you do not need perfect optical jargon
Composition controls
- Shot scale: macro / bust / full body / wide
- Angle: eye-level / low / high / aerial
- Light: soft daylight / golden hour / noir contrast / dim interior
- If layout matters, place elements: “logo top-right”, “subject centered, left negative space”—especially for neon / cinematic scenes.
Latency vs fidelity
Speed-first: quality="low"; dense information or micro-detail: medium or high.
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