Realistic AI Prompts Are Subtractive, Not Additive

Everybody searching for realistic ai prompts is looking for the same thing, which is a string of words that produces a picture nobody questions. The results are a Reddit thread with one mega prompt, a Facebook post about ultra realism, a couple of collections, and an OpenAI forum question about photos of people.

The direct answer is unsatisfying and it's the only one I've found to be true. Realistic ai prompts don't add realism, they remove errors. A picture reads as real when nothing in it contradicts physics, and it reads as generated when one thing does, no matter how good the rest is. So the useful work is knowing where the contradictions happen and writing to prevent them, rather than stacking words like ultra realistic, 8K, hyperdetailed, which point at the most rendered corner of the training data and make things worse.

The failures fall into categories. Here they are, in the order a viewer finds them.

Where People Actually Look, In Order

Watch somebody look at an image they suspect is generated and the sequence is consistent. This is my own observation from showing people work rather than any study, so treat it as a working model.

The first four are cheap fixes and the last four aren't, which is the practical takeaway. Most of what you can do with words is at the top of that list, and it's still worth doing because the top of the list is where people look first.

OpenAI is fairly direct about two of these in their own documentation. On text, they say the model "can still struggle with precise text placement and clarity". On layout, that it "may have difficulty placing elements precisely in structured or layout-sensitive compositions". Both of those are the vendor telling you which battles to avoid picking.

The Physics Errors, Sorted

This is the part I'd want somebody to hand me. These are the categories of implausibility, roughly in order of how often they're what's wrong.

Light without a source. The scene is lit from somewhere that isn't in the picture and isn't implied by anything in it. Fixable, and the fix is naming one source and its direction and then not naming a second.

Shadows that disagree with each other. Two objects casting in different directions because the model averaged two lighting conventions. Partly fixable through the same discipline.

Materials without weight. Fabric that doesn't drape, metal that doesn't have thickness at its edges, liquid sitting at an impossible angle. Somewhat fixable by naming the material's behaviour rather than its name, so "heavy wool coat, drape gathering at the elbow" rather than "wool coat".

Scale drift. A chair that's slightly too big for the table, a doorway slightly too small for a person. Very hard to fix with words and it's the one that produces an uneasy feeling nobody can name.

Structural impossibility. A building whose upper floor doesn't sit on the lower one, a staircase that returns to itself. Sometimes charming and rarely intentional.

Depth of field that doesn't follow a plane. Parts of the image blurred that sit at the same distance as parts that are sharp. Hard to fix, easy to spot once you know.

Reflections and refraction. Mirrors showing content that isn't in the scene, glass that bends nothing. Best avoided, because I've never found a prompt that reliably fixes it.

Notice how many of those say hard or rarely. Realism above a certain level isn't a prompting problem, it's a model capability problem, and the honest move is to design around it rather than write harder.

Imperfection Is A Vocabulary, Not A Mood

Every guide says add imperfections. Almost none say which, so here's the working list, sorted by what part of the image it addresses.

For the optics, chromatic fringing at high-contrast edges, slight barrel distortion, a small lens flare, vignetting at the corners, focus falling slightly in front of or behind the intended plane.

For the capture, motion blur on a moving element, handheld framing, a blown highlight, shadows lifted with visible noise, slightly underexposed.

For the medium, film grain, halation around bright areas, dust and small scratches, colour cast from mixed lighting.

For the subject, wear on surfaces, fingerprints on glass, dust on a matte surface, uneven wear on painted metal, a garment creased where it's been sat in.

Two or three of these, chosen from different rows, does more than ten from one row. Stack five optical defects and you get something that looks like a filter rather than a photograph.

The subject row is the one people skip and it's my favourite, because wear implies time and time implies the object existed before the photograph. A pristine object in a photograph is a product shot. A worn one is a life.

The photographic side of this, meaning grain and stock and why clean renders read as fake, is worked through in ai photo prompt. Skin specifically is in ai portrait prompts.

Video Breaks In Time, Not In Texture

This is where I think most people are unprepared, because everything above is about a single frame and video adds an axis where the models are much weaker.

A generated clip can have flawless texture in every frame and still be obviously fake, because the failure is in how things change between frames. Cloth that moves without inertia. A walk cycle where the feet slide slightly. Liquid that pours without splashing. Objects that morph at the edges as the camera moves. Faces that subtly rearrange between one second and the next.

None of those are visible in a still. All of them are visible in motion within about a second and a half, which is roughly how long it takes a viewer to decide.

What I've found helps, and I want to be clear this is mitigation rather than solution.

Google's Veo documentation frames a video prompt around five components, subject, action, style, camera positioning, and composition, with clips running 4, 6, or 8 seconds. The constraint that helps here is the clip length, oddly. Eight seconds isn't long enough for most physics failures to accumulate badly, provided you've only asked for one thing to happen. Ask for three things and the clip will find a way to be wrong about at least one. The full motion treatment is in ai video prompts.

How Real Does It Need To Be

Not every use needs the same standard, and matching the standard to the job saves an enormous amount of rerolling.

The row that catches people is print. An image that's convincing on a phone falls apart at A4, because the failures I listed earlier are all detail-scale and detail scales with size. I've had covers that looked fine everywhere until I saw one physically, at which point the hand in the background became the only thing I could see.

The Escape Route Is Stylisation

Something worth considering before you spend forty renders chasing photorealism, which is that you may not need it, and that a stylised image cannot fail a realism test because it never made a realism claim in the first place.

An illustration with a hand that's slightly wrong is an illustration. A photograph with a hand that's slightly wrong is a fake. Same error, completely different reception, and the difference is entirely about what the image promised the viewer at first glance.

I've moved work into stylisation more than once for exactly this reason, usually after failing to get a photographic version past my own thumbnail check, and the stylised version was frequently better anyway because it forced simplification. Fewer objects, clearer silhouette, one idea. The photographic attempt had been hiding a weak composition under texture.

The rule I'd offer is that if a subject involves hands doing something specific, several people at a distance, text, or a mirror, and you don't have a strong reason for it to be a photograph, make it not a photograph. You'll spend a quarter of the attempts and you'll get something more distinctive at the end of it.

Where this doesn't apply is anything that has to look like documentation of a real event, or product photography, where the whole point is that the thing exists. There's no stylistic escape from a product shot. That's the case where you either get the render right or you photograph the actual object, and photographing the actual object is a genuinely underrated option that nobody in this field ever mentions.

The vocabulary for going stylised is a different set of controls entirely, sorted by axis in ai art style prompts.

Quality Words Are Actively Counterproductive

Brief, because I've said versions of this elsewhere and it's worth repeating anyway.

Ultra realistic, photorealistic, 8K, hyperdetailed, masterpiece, award winning. These select for the region of training data where those captions appear, which is rendered art, wallpaper sites, and stock. So the words meant to buy realism buy the opposite.

What buys realism is the boring stuff. A named light source with a direction. A real lens behaviour. One or two physical defects. A subject that has clearly been used. None of it sounds impressive written down, which is presumably why the prompt collections are full of the other kind.

Realism Questions

Is there one prompt that produces realistic images? No, and any collection selling one is selling a subject as well as a style, so it works for their picture and not yours.

Why do faces look wrong even when everything else is fine? Because we process faces with dedicated machinery and the tolerance is tiny. A chair being five percent wrong is invisible. A face being five percent wrong is unsettling.

Does a higher resolution help realism? It helps fidelity and it exposes errors, so it can make things look worse. I draft at the cheapest tier and only render up once the composition and the content are settled.

How do I know if my image will pass? Show it to somebody at the size it'll actually be seen, and watch where their eyes go. That's crude and it's the best test I've found.

Are the realism prompt collections useless? As vocabulary, no. As a shortcut, mostly, since the load-bearing parts are the physical constraints and those don't copy across to a different subject.

Is video realism getting closer? The texture side has moved fast. The physics side has moved slower, at least on what I've been able to run, and physics is the half that gives it away.

What I'd Change First

Remove every quality adjective from your prompt, then add one light source with a direction and one physical defect.

That's usually a net reduction in words and a net increase in believability, which is the whole argument of this piece compressed into one edit. The class-by-class view of what steers each type of image is in ai image prompt, and the wider prompting framework is in chatgpt prompts.