Type a beautiful landscape into any image generator and you will get something competent, generic and immediately recognisable as AI output. Type six carefully chosen clauses instead and the same model produces something you would actually use.
Nothing about the model changed. What changed is how much of the decision making you handed over. Every detail you leave out is a detail the model fills with its statistical default, and those defaults are what make AI images look like AI images.
The Seven Parts of a Working Prompt
Think of a prompt as a shot list rather than a description. Each of these parts answers a question the model would otherwise answer for you.
1. Subject. Who or what, with the specific details that matter. Not a woman but a woman in her sixties with close cropped grey hair and reading glasses.
2. Action or pose. What they are doing, or how the object is oriented. Static prompts produce static, catalogue looking images.
3. Setting. Where, and when. A kitchen at 7am with steam on the window is a scene. A kitchen is a set.
4. Composition and shot. Close up, medium shot, wide establishing shot, overhead flat lay, low angle, shot from behind. This is the single most underused control and often the one that transforms an image.
5. Lighting. Soft window light, hard midday sun, golden hour backlight, single overhead lamp, neon spill, overcast diffuse. Lighting determines mood more than colour does.
6. Style or medium. Oil painting, 35mm film photograph, flat vector illustration, watercolour, 3D render, charcoal sketch. Be specific about medium before reaching for artist names.
7. Colour and mood. A limited palette instruction such as muted earth tones or high contrast teal and amber does more work than any adjective about atmosphere.
You will not need all seven every time. You should know which ones you are deliberately leaving out.
The same idea at three levels of detail
| Attempt | Prompt | Result |
|---|---|---|
| Weak | A cat in a house | Centred cat, flat light, generic room |
| Better | An orange tabby cat sleeping on a windowsill in a sunlit room | Recognisable scene, still a stock photo feel |
| Strong | Close up of an orange tabby cat asleep on a wooden windowsill, warm late afternoon sun through dusty glass, shallow depth of field, 35mm film photograph, muted warm palette | Specific image with intent |
The third prompt is not longer for the sake of it. Every clause removed a decision from the model.
Modifiers That Reliably Change the Output
Some terms consistently move an image. Others are decoration that people copy from prompt lists without noticing they do nothing.
| Category | Terms that work | Notes |
|---|---|---|
| Shot | close up, medium shot, wide shot, overhead, low angle, dutch angle | Strongest single lever |
| Lens | 35mm, 85mm portrait, macro, wide angle, shallow depth of field, bokeh | Only meaningful for photographic styles |
| Light | golden hour, backlit, rim lighting, softbox, harsh flash, candlelit, overcast | Second strongest lever |
| Medium | oil on canvas, gouache, linocut, 3D render, pencil sketch, screen print | Changes the image more than any style word |
| Era | 1970s Kodachrome, Victorian engraving, 1990s camcorder, Bauhaus poster | Carries palette and texture at once |
| Palette | monochrome, limited palette, pastel, high contrast, desaturated | Prevents the default oversaturated look |
Two terms worth retiring. Masterpiece and highly detailed were useful signals to older Stable Diffusion checkpoints trained on tagged aesthetic scores. On modern models they mostly add nothing and can push output towards an overprocessed style. Trending on ArtStation belongs to the same era.
Artist names are a separate matter. They are powerful shortcuts, but naming a living artist to imitate their style is contested ethically and increasingly restricted by the tools themselves. Naming the technique rather than the person gets you most of the way there and does not build your work on someone else's name.
Four Things Image Models Still Get Wrong
Knowing the failure modes saves more time than any prompt trick.
Negation. Writing without a hat frequently produces a hat, because the concept is in the prompt either way. Only a dedicated negative prompt field handles exclusion reliably. Otherwise, describe the positive alternative.
Counting. Ask for exactly five apples and you will get four, six or seven. Small counts up to about three are usually fine. Beyond that, generate and check rather than trusting the number.
Text. Better than it was, still unreliable past a couple of short words. Plan to add real typography yourself.
Precise spatial relationships. A red cube to the left of a blue sphere and behind a green cone is the kind of instruction models scramble. Keep spatial requirements simple, or compose multiple elements in an editor.
Hands, once the running joke of the genre, have largely been fixed in current models. Fingers still go wrong at small scale or in complex poses, which makes hands worth checking rather than worth fearing.
Iterate on One Variable at a Time
The most common mistake after a mediocre result is rewriting the entire prompt. You then have no idea which change helped.
A better loop:
1. Get a rough composition you like, ignoring style.
2. Lock the subject and setting wording. Do not touch them again.
3. Change only the lighting clause. Generate. Compare.
4. Change only the medium or style clause. Generate. Compare.
5. Adjust the palette last, since it is the least destructive change.
Save the prompts that worked. A personal library of six reliable structures beats any list of a thousand prompts you found online, because yours are tuned to the tool you actually use.
Aspect ratio is worth setting deliberately too. Most tools default to square, and a square frame quietly kills any composition that wanted to be a landscape or a portrait.
18 Prompt Starters by Use Case
Copy these, then swap the subject. The structure is the reusable part.
| Use case | Prompt |
|---|---|
| Profile picture | Head and shoulders portrait of a person with short dark hair, soft window light from the left, plain warm grey backdrop, 85mm lens, shallow depth of field, natural colour |
| Blog header | Wide overhead flat lay of a wooden desk with a notebook, coffee cup and pen, soft diffuse daylight, muted earth tones, plenty of empty space on the right for text |
| App icon concept | Flat vector illustration of a folded paper aeroplane, bold single colour on a solid background, thick even strokes, no gradients, centred, generous margin |
| Product shot | Studio photograph of a matte ceramic mug on a seamless light grey backdrop, single softbox from above left, soft shadow, sharp focus, neutral colour |
| Fantasy landscape | Wide establishing shot of a valley of terraced fields under low mist, distant mountain ridge, cool blue hour light, oil painting with visible brushwork, limited palette |
| Character concept | Full body character sheet of a desert traveller in layered linen robes, neutral standing pose, flat lighting, plain background, ink and watercolour |
| Food photo | Close up of a bowl of noodle soup with steam rising, dark wooden table, single warm overhead light, shallow depth of field, rich contrast |
| Architecture | Low angle photograph of a brutalist concrete stairwell, hard midday sun casting sharp diagonal shadows, monochrome, high contrast |
| Retro poster | 1960s travel poster of a coastal town, flat shapes, limited four colour palette, screen printed texture, bold simplified forms |
| Children's book | Gouache illustration of a small fox looking up at a lantern in a snowy forest, soft edges, warm limited palette, gentle mood |
| Cyberpunk street | Medium shot of a rain slicked alley at night, neon signs reflecting in puddles, backlit figure with umbrella, teal and magenta palette, 35mm film grain |
| Minimal wallpaper | Abstract composition of soft overlapping gradients in deep indigo and violet, subtle grain, vertical format, no subject, plenty of negative space |
| Nature macro | Macro photograph of a dew covered fern frond, morning light, extremely shallow depth of field, green and gold palette, sharp focus on the near edge |
| Portrait painting | Three quarter view portrait in the manner of Dutch golden age painting, single candle light source, dark background, warm skin tones, oil on canvas |
| Isometric scene | Isometric 3D render of a tiny cafe interior, soft ambient occlusion, pastel palette, clean edges, white background |
| Editorial illustration | Conceptual illustration of a person carrying an oversized clock up a staircase, flat shapes, limited palette of ochre and slate, subtle paper texture |
| Sticker | Die cut sticker illustration of a smiling cactus, thick white outline, bold flat colours, simple shading, white background |
| Logo exploration | Simple geometric mark combining a leaf and a droplet, single weight line art, black on white, centred, no text |
Where This Runs on a Phone
You do not need a desktop workflow for any of this. Generai puts text to image generation and an AI chat assistant in one iPhone app, which is a practical combination for prompt work: you can draft and refine the prompt in chat, then generate from it without switching apps and losing the thread.
Two honest limits. Every consumer generator inherits the failure modes above, so no app will reliably spell a sentence or count seven objects, and any listing that suggests otherwise is overselling. And phone generation is tuned for speed and convenience rather than the fine grained control of a desktop pipeline with model weights and samplers, which is the right trade for most people and the wrong one if you need reproducible seeds.
If you are comparing options first, AI art generator apps for iPhone covers the landscape, and best AI chatbot apps for iPhone covers the text side.
The Bottom Line
A prompt is a set of decisions. Make them yourself, in this order: subject, action, setting, shot, lighting, medium, palette. Anything you skip, the model decides, and its defaults are the reason so much AI art looks the same.
Then change one clause at a time, keep the versions that worked, and stop expecting the model to spell, count or arrange objects in precise space. Those are your job, or your editor's. For the rest of what these tools are genuinely good at, how to use AI for productivity covers the workflows worth building.