You stop the generic look by controlling four specific variables — reference images, style parameters, prompt structure, and aspect ratio — instead of typing a longer description and hoping for the best.
Most people who complain that AI images all look alike are using the same short prompt with no reference material and default settings, which pushes the model toward its most statistically average output. Fix those four inputs and the sameness problem mostly disappears.
The mechanism matters here. Image models like Midjourney learn a compressed map of what images tend to look like, and a vague prompt lands you near the crowded center of that map — the visual equivalent of an average face. According to our AI tool database, Midjourney's V7 release added Draft Mode, Omni Reference, Personalization v2, and a Niji 7 anime model, and those features exist precisely because the center of the map is boring.
Omni Reference lets you feed in a specific subject and carry its identity across generations, while Personalization v2 learns from your own ratings so the model drifts toward your taste rather than the average. Draft Mode is the practical companion: it renders fast, cheap-looking versions so you can test composition before committing to a full render.
The workflow that actually kills sameness is draft, compare, refine, then final render — not generate once and accept whatever appears.
Here is a concrete worked example. Say you want a product photo of a ceramic coffee mug on a wooden table. The generic version — "a coffee mug on a table, photorealistic" — will give you soft lighting, a blurred background, and that familiar glossy sheen.
Instead, write the prompt as a list of physical facts: "matte stoneware mug, unglazed rim, sitting on reclaimed oak, hard afternoon window light from the left, visible dust in the air, 85mm lens, shallow depth of field." Then attach a reference image of the actual mug via Omni Reference so the shape and color stay consistent across every shot.
Set the aspect ratio to match your final placement — square for an Instagram grid, wide for a website banner. The result is a set of images that look like they came from one photographer on one afternoon, which is exactly what a brand needs. On pricing, our database lists Midjourney at Basic $10/mo, Standard $30/mo, and Pro $60/mo, with a Mega tier at $120/mo for the V7 listing; the higher tiers matter mainly if you need more fast-render hours or stealth mode, not because image quality changes.
Now the limits, because this approach is not free of trade-offs. Reference images can over-constrain a model — if your reference is low resolution or oddly lit, that flaw gets baked into every output, and you may spend more time cleaning references than writing prompts. Personalization only works if you actually rate images, so it is a slow-burn feature rather than an instant fix.
Draft Mode trades fidelity for speed, so never judge color accuracy from a draft. And none of this helps if your underlying creative direction is vague; a model cannot invent a visual identity you have not decided on. One more honest caveat: pricing and feature names in this space change often, so treat any figure as a snapshot and confirm on the vendor's own page before subscribing.
If you are working with a different tool, the same four levers apply, but I cannot quote its plans — check the vendor directly. For the writing side of the same problem, see How do I stop AI from writing content that sounds like a robot wrote it?.