Prompt Recipes That Keep AI Images Believable

Title and angle ? Prompt Recipes That Keep AI Images Believable delivers practical ai tools guidance with real-world steps, constraints, and checkpoints readers can apply immediately.

Prompt discipline ? Keep a prompt log with lens choice, lighting direction, material cues, and negative prompts. Small prompt tweaks make predictable changes when you have a record, and it keeps teams aligned on style language without reinventing every request.

Model selection ? Choose models by output purpose: photoreal for composites, stylized for concept boards, and lightweight models for iteration. Document version numbers so you can reproduce results months later, and run a quick bias and artifact check before approving a set.

Input quality ? Start with clean source plates. Denoise, balance exposure, and crop with intent before sending assets into an AI pipeline. High-quality inputs reduce the time you spend fixing warped edges, hands, and text later.

Sampling strategy ? Generate in low resolution to validate framing, then upscale successful takes. Use inpainting on localized defects instead of rerolling entire frames. Track seeds for each keeper so you can branch variations quickly.

Ethics and disclosure ? Credit datasets when required, avoid likeness use without consent, and add a visible note when AI is present in a final image. Clear disclosure protects trust with clients and platforms.

Quality bar ? Define non-negotiables: no extra fingers, no distorted typography, no smeared logos. Reject early and often. A short checklist before exporting saves retouch time.

Integration with retouch ? Blend AI passes with traditional dodge and burn, color matching, and grain overlays. Hand-finish faces and edges so the final piece matches natural optics instead of the telltale AI plastic look.

Performance and cost ? Batch similar prompts, reuse control images, and prune unused checkpoints. Monitor GPU minutes and store only approved checkpoints to keep infrastructure lean.

Version control ? Store prompts, seeds, and negative prompts beside exports. A simple JSON or CSV in each project folder lets collaborators reproduce or improve a shot without guesswork.

Compliance ? Review platform policies quarterly; many require labeling or restrict synthetic people. Build a lightweight review step so these checks happen before publishing, not after takedowns.

Delivery ? Export layered PSD/EXR or flattened TIFF depending on downstream needs. Include a text note describing where AI was used, what was retouched by hand, and any remaining limitations the client should know.