The Two Dialects: Sentences or Tags
There are exactly two ways to write a prompt, and using the wrong one for your tool is the most common reason a good prompt underperforms. Find out which dialect your tool speaks before anything else.
Dialect 1 — Natural sentences. Write as you would brief a person. Used by GPT Image, Gemini/Nano Banana, Midjourney, Ideogram, FLUX, Runway, and essentially every tool built on a conversational model.
A low-angle 35mm photograph of a heron mid-stride through a shallow tidal estuary at first light, low backlight with mist catching the sun, the bird small in a wide frame.
Full sentences genuinely help here — the language model uses grammar to work out what modifies what. "A red car and a blue house" survives as a sentence; as tags it becomes a colour soup.
Dialect 2 — Comma-separated tags. Short descriptors, most important first. Used by Stable Diffusion and its descendants, and by most open-weight and anime-focused models.
heron, mid-stride, shallow estuary water, first light, backlit, mist, 35mm photo, low angle, wide shot
These models read more literally and weight roughly by position, so ordering is your emphasis. Many also accept explicit weights and a separate negative prompt field for things to avoid — which, unlike writing "no X" in your sentence, actually works.
A quick way to tell which you're in: if the tool has a chat box and answers you back, it's dialect 1. If it has a second text box labelled negative prompt, it's dialect 2. If in doubt, write a natural sentence — every modern model tolerates it, while tag soup confuses the conversational ones.
Platform-specific extras are worth ten minutes of reading. Aspect ratio, stylisation, reference weighting and version flags are all per-platform, they change every few months, and every vendor documents them properly. Read your tool's own guide once; skip anyone's list of "magic prompt words".