How to make AI photos look real
The realism rules PixelPig writes into its own prompts, from pore-level skin to on-camera flash.
Prompt the camera and the moment, not the beauty. Ask for natural skin texture with visible pores and small imperfections, a phone-camera or amateur selfie look, one believable light source, and a real expression in an ordinary setting. Start from a sharp, real reference photo, generate three or four versions, and reject any with smoothed skin, broken hands or stray text.
Make your first photosTo make AI photos look real, prompt the camera and the moment instead of the beauty: natural skin with pores and small flaws, a phone-camera look, one believable light source, a real expression and an ordinary place. The result starts with the input, so a persona built from the right training or reference photos gives you a head start. Realistic does not mean hidden: Instagram has its own AI info label, and this guide assumes you disclose.
We have not run an image test for this page, and we will not pretend to. The proof below is the prompt method PixelPig already runs inside its own generators and teaches in its Academy, quoted from the code and the course.
Proof
PixelPig writes realism rules into three places. Each line below is quoted or paraphrased from the product itself.
| Where | What it says | Realism lever |
|---|---|---|
| Persona generator (builds a persona's portrait and body shots) | Every prompt includes "natural skin texture with realistic pores and fine imperfections, sharp focus" | Skin |
| Prompt expander behind the MCP connector | "Favor real-camera/smartphone looks, natural skin texture, believable lighting" | Camera, skin, light |
| Same expander, negative prompt | Excludes "cartoon/illustration/oversmoothed skin/distorted hands/extra fingers/watermark/text" | Common AI tells |
| Same expander, scene rotation | Rotates light setups such as "golden-hour outdoor setting, warm low sun" and "night-out setting with direct on-camera flash, digicam aesthetic" | Varied, motivated light |
| Same expander, identity rule | Never describes face, hair, skin tone or age; the reference photo carries identity | Consistency |
| Academy chapter 3 | Reference prompt: "Generate an amateur selfie and iPhone camera quality from the chest up", at 2K, 4:5 or 1:1, three or four versions | Camera feel, selection |
| Academy chapter 4 | Expression makes an image read "human-presenting rather than AI-presenting"; a flat mirror selfie kills it | Expression |
| Academy chapter 6 | Carousel standard: "High quality, high realism, iPhone-style amateur Instagram" | Camera feel |
Two points stand out. First, most of these rules ask for texture, imperfection and a believable camera. Second, the expander keeps identity out of the text prompt entirely. The face comes from the persona photo, and the prompt only owns the scene, pose, wardrobe, light and color. The same split applies when you generate persona photos from ChatGPT or Claude.
The method
Skin: ask for pores and small flaws
Image models drift toward smooth, poreless skin unless the prompt pulls the other way. Borrow the persona generator's phrasing: "natural skin texture with realistic pores and fine imperfections." Leave out words like flawless, perfect skin, glamour or airbrushed. If your model accepts a negative prompt, exclude oversmoothed skin.
Camera: name a real one, or a real style
"Amateur selfie, iPhone camera quality" does more than "8K ultra-detailed photo". Real social photos come from phones held at arm's length, a little off level, with ordinary depth of field. The Academy uses that exact framing for the reference image every later photo inherits from.
Light: one source, and say where it comes from
A kitchen lit like a fashion studio reads fake at a glance. Name one source the scene would have: window light from the left, warm lamps in the evening, low golden-hour sun, or a direct on-camera flash at night. PixelPig's expander rotates through setups like these so a batch of ten photos does not share one light.
Expression: give her something to do
The Academy's chapter on content at scale puts expression first: smiling, winking, a slight smile, looking annoyed, interacting with an object such as a strawberry or an iced matcha. A blank stare into a mirror is the pose people now associate with AI accounts.
Setting: keep it ordinary and in one world
The car, the parking garage, the living room, a café table. The Academy's "realism ceiling" makes the same point about the persona itself: stacking extra traits on a premise makes her less believable, and a more ordinary model reads more real. Keep her in one city and one life rather than a new country every post.
Selection: generate several, keep one
PixelPig's course generates three or four versions of every reference and picks one. Reject anything with a phone visible in the reference (it gets copied into later images), anything that looks dated, and anything with the tells in the table below. On the AI image generator, set resolution to 2K where the model offers it, since 1K is the default.
AI tells and their fixes
| Tell | What causes it | Fix in the prompt or workflow |
|---|---|---|
| Plastic, poreless skin | Beauty words, filtered reference | Natural skin texture, pores, fine imperfections; exclude oversmoothed skin |
| Studio light in a casual scene | No light source named | Name one source that fits the place |
| Blank, symmetrical face | No expression in the prompt | Add a specific expression or action |
| Extra fingers, warped hands | Hands doing something complex | Exclude distorted hands and extra fingers; keep the pose simple; regenerate |
| Garbled text on signs or shirts | Model inventing writing | Exclude text and watermarks unless you need a word |
| Same pose and room every post | One prompt reused | Vary the setting, light and outfit, keep the person |
| Overdone styling | Too many traits on one persona | Strip extras; ordinary reads real |
| Low-detail face | 1K output, distant framing | 2K, chest-up framing for close shots |
Common mistakes
Describing the face in every prompt. When a persona photo carries identity, adding hair color or eye color to the scene prompt gives the model two sources to reconcile. PixelPig's expander forbids identity words for this reason.
Starting from a weak reference. Every image inherits from the reference photo. A filtered, low-resolution or oddly angled reference produces the same problems in every output.
Chasing a perfect single image. The Academy's carousel standard accepts "relative body consistency, 80% or better" and warns against spending an hour on one post. Fix the visible tells and move on.
Ten selfies in a row. The Academy names three near-identical selfies in a row as the top failure. Variety comes from changing everything around the person.
Label it anyway
Realistic is the goal; deceptive is not. Meta says it adds an "AI info" label to images when it detects industry-standard signals or when people disclose, and it asks people to disclose photorealistic video and realistic audio (Meta's announcement). Many generated images also carry embedded provenance data, described by the C2PA standard. If you are building an account, growing an AI model on Instagram covers how realism and disclosure fit together in a feed.
Bottom line
Realism comes from asking for the things a real phone photo has: textured skin, one motivated light source, an expression, an ordinary place and a slightly imperfect camera. PixelPig writes those same rules into its own generators, keeps identity in the persona photo, and its Academy picks the best of several versions rather than trusting one. Start from a sharp reference, prompt the camera instead of the beauty, and label what you post.
Questions
- Why do AI photos look fake?
- The usual tells are skin with no pores, perfect studio light in an everyday scene, a blank expression, warped hands and garbled text. Most of them come from prompts that describe beauty instead of a camera and a moment.
- What prompt words make AI images more realistic?
- PixelPig's own persona prompts include "natural skin texture with realistic pores and fine imperfections". Add a camera feel, such as amateur selfie or iPhone camera quality, plus one named light source and a specific expression.
- How do I fix plastic-looking skin in AI photos?
- Ask for natural skin texture, pores and fine imperfections, and exclude oversmoothed skin. Remove beauty or glamour words from the prompt, and avoid starting from a filtered reference photo.
- Does a higher resolution make AI photos look more real?
- It shows more detail, including skin texture. The Academy builds reference images at 2K rather than the 1K default. Resolution cannot rescue a prompt that asks for studio-perfect skin, though.
- Which AI image model is the most realistic?
- We have not published a side-by-side test yet, so we will not rank them. PixelPig's Academy builds its reference image with Nano Banana Pro, and the studio also offers Nano Banana 2, GPT Image 2, Seedream and Wan models.
- Do I have to label realistic AI photos on Instagram?
- Meta requires disclosure for photorealistic AI video and realistic audio, and it adds an AI info label to images when it detects industry signals or the creator discloses. Labeling realistic AI photos yourself is the honest default.
- Can people tell my AI photos are AI?
- Some can, and platforms read embedded signals such as C2PA metadata. Aim for photos that look like a real phone camera, and disclose them where the platform asks.