Prompt engineering for AI images: 2026 guide

What is prompt engineering for images?

Prompt engineering means writing a request precise enough for an image model to produce exactly the visual you have in mind. With the same model, a vague prompt gives a generic image; a structured prompt gives a visual you can use in a campaign. The good news: it is not a secret language, just a simple method you learn in a few tries.

This guide gives you a structure that works on every model, before / after examples, each engine's specifics and the most common mistakes.

The structure of an effective image prompt

A good prompt answers six questions, in this order:

[Subject + action] · [Style] · [Light] · [Composition] · [Palette] · [Rendering details]

You do not have to fill everything every time, but the more precise the first three elements, the more predictable the result.

1. The subject: the most important part

Describe who or what, with two or three concrete details: age, outfit, material, expression, action.

❌ "a woman"
✅ "a 35-year-old architect in a burgundy jacket, confident smile, studying a scale model in a bright office"

2. Visual style

Realistic photo: "realistic photograph, DSLR, sharp focus"
Cinematic: "film still, anamorphic lens, light grain"
Illustration: "vector illustration, flat colours, flat design"
Painting: "oil painting, visible brushstrokes, impressionist style"
Product: "e-commerce packshot, plain background, soft shadow"

3. Light

This is often what separates an amateur image from a professional one.

Golden hour: "warm late-afternoon light, long shadows"
Studio: "softbox lighting, white background, product photography"
Dramatic: "chiaroscuro, single spotlight, deep shadows"
Neon: "night city mood, neon reflections on wet ground"

4. Composition

"close-up" for the details of a face or a product
"wide shot" to show the setting
"top view" for a flat lay
"rule of thirds, subject on the left, empty space on the right" to leave room for text

5. Palette

Give two or three colours, or a mood: "sand and cream tones", "pastel palette", "black and lime, strong contrast". For a brand, repeat its colours in every prompt.

6. Rendering details

Materials, depth of field, level of detail: "blurred background", "highly detailed textures", "matte surface". Do not stack ten quality adjectives: two are enough.

Before / after: three examples

Vague prompt	Structured prompt
A cup of coffee	White ceramic cup on a wooden table, latte with leaf art, soft morning light through the window, close-up, blurred background, warm tones
A sale poster	Summer sale poster for a clothing brand, large "-30%" text at the top, model in a light dress, bright yellow background, modern graphic style
A landscape	Sand dunes at sunrise, a single hiker in the distance, wide shot, light haze, orange and pink palette, realistic photograph

Model specifics

GPT Image 2

It understands full sentences and precise instructions very well, including text to write in the image. Put the text in quotes and say where it goes. On iafetch, pick Fast (2 credits) to explore, then Pro (4) or Creative HD (6) for the final version.

Flux (Schnell, Dev, 1.1 Pro)

Flux responds better to natural-language descriptions than to keyword lists. Write sentences and describe the scene as you would to a photographer. Flux Schnell (1 credit) is for testing an idea, Flux 1.1 Pro (4 credits) for a very fine photographic result.

Ideogram v2 and Recraft v3

Ideogram excels at typography: logos, posters, covers. Recraft is built for design: vector illustrations, icons, consistent brand visuals. In both cases, specify the graphic style and the colours.

Flux Kontext: editing an existing image

To edit a photo, describe only the change: "replace the background with a beach at sunset, keep the product and the lighting". The shorter and more precise the instruction, the better the rest of the image is preserved.

Midjourney and Stable Diffusion

Midjourney uses parameters at the end of the prompt (for example --ar 4:5 for the format). Stable Diffusion accepts a negative prompt to exclude defects ("blurry, deformed, watermark"). These tools are not built into iafetch, but the six-step method works there too.

Iterate smartly

Generate 3 or 4 quick variations with an affordable model
Keep the best one and note what is missing (light, framing, colour)
Change only one thing at a time in the prompt
Switch to a high-end model for the final version
Adapt the format: square for a feed, portrait for a story, landscape for a banner

10 mistakes to avoid

Being too vague ("a nice image")
Forgetting the light
Not specifying the format
Asking for too many elements in one image
Changing several things at once between two tries
Stacking quality adjectives without describing the scene
Using the names of real people
Reproducing a protected brand or logo
Generating once and giving up
Using the most expensive model to test ideas

Let AI write the prompt for you

On iafetch, the "Improve with AI" button turns a short idea into a detailed prompt with Claude: subject, style, light and composition are filled in automatically. The Prompts module goes further and writes prompts tailored to the target tool (image, video, voice). It is a good way to learn: compare your starting idea with the prompt you get.

Frequently asked questions

Do prompts have to be in English?

No. Recent models understand French, Spanish, German and many other languages very well. English is still handy for some photography terms, which you can mix into your own language.

What is the ideal prompt length?

One to four sentences. Beyond that, the model may ignore part of the instructions; below that, it invents the details for you.

Can I keep the same character across several images?

Start from a first successful image and use Flux Kontext to adapt it: a new outfit, setting or pose, while keeping the face.