Prompting Image Models for AI Headshots That Keep Your Likeness

If you have tried turning a casual photo into a professional headshot with an image-editing model such as Gemini's image model (often called Nano Banana), you have probably seen the failure mode: the result looks polished, but it no longer quite looks like the person. The jaw is a little narrower, the skin is airbrushed, the hairline is fuller, and the person looks five years younger.

This post is a practical guide to avoiding that. It covers how to structure the prompt, which constraints do the most to preserve facial features, what to check in the input photo, and a simple checklist for evaluating the output. Nothing here depends on a specific tool; it applies to any model that takes a reference image plus a text instruction.

Why likeness drifts

An image-to-image model treats your photo as a reference, not as a fixed asset. Everything in the frame is open to reinterpretation unless the prompt says otherwise. For headshots, the model's idea of "professional" tends to lean toward retouched studio photography, so small edits to the face are a common side effect of asking for a "professional headshot".

The common drift patterns are:

• Skin smoothing: pores, freckles and fine lines disappear.
• Face reshaping: slimmer jaw, larger eyes, more symmetrical features.
• De-ageing: softened under-eye lines and wrinkles.
• Skin tone shifts: brighter studio lighting quietly lightens the skin.
• Hairline tidying: receding or uneven hairlines get "fixed".

Each change on its own can be subtle. Together, they produce someone who looks like a relative.

A prompt structure that works

A useful pattern is to split the prompt into four blocks, in this order:

1. Reference role: tell the model what the image is.
2. Preserve: list what must not change.
3. Change: list what should change.
4. Prohibit: explicit negatives for the drift patterns above.

Putting the preserve block before the style words matters. If the prompt opens with "professional studio headshot, flawless lighting", the model has already been pulled toward the retouched look before it reads your constraints.

Here is a template:

[Reference]
The uploaded photo is the reference and shows the person to portray.

[Preserve]
Keep the person exactly recognizable: face shape, features, eye shape,
age, skin tone and hairline stay as in the photo. Keep real skin texture
and pores. The number of people stays the same.

[Change]
Clothing becomes a navy blazer over a white shirt. Background becomes a
softly blurred light-grey wall. Head-and-shoulders framing, facing the
camera, even soft studio light, crisp focus on the eyes, natural
friendly expression.

[Prohibit]
Do not smooth the skin, slim the face, lighten or change the skin tone,
or make the person look younger or older. Do not add text, logos or
watermarks.

The bracketed labels are just for readability; you can remove them before sending.

Constraints that do the most work

In practice, a few specific instructions carry most of the weight:

• Name features, not just "the face". "Keep the face the same" is vague. "Face shape, eye shape, nose, jawline, hairline" gives the model concrete targets.
• Say "real skin texture and pores". Without it, smoothing is the default for anything described as professional.
• Rule out skin tone changes explicitly. Lighting instructions can shift skin tone as a side effect. A direct "do not lighten or change the skin tone" line counters that.
• Pin the age. "Do not make the person look younger or older" stops gradual de-ageing.
• Add personal specifics. If someone has a scar, a mole, freckles or a gap in their teeth, name it: "keep the small scar above the left eyebrow". Specific constraints are followed more reliably than general ones.
• Change one thing per pass when iterating. If the first result needs a different jacket, ask only for the jacket in the next edit, and use the previous output as the new reference. Stacking several changes in one follow-up prompt invites drift.

If you want to see a full working example of this structure, the professional headshot prompt on Mona Lisa Studio is published on the page, including its preserve and no-smoothing lines, and is a reasonable starting point to adapt.

Input photo checklist

The prompt protects likeness, but the photo supplies it. Before generating, check:

• [ ] Sharp focus on the face, especially the eyes.
• [ ] Front-facing or slightly turned, looking at the lens.
• [ ] Head and shoulders in frame, so the model does not have to invent your build or where the new outfit sits.
• [ ] Even daylight, such as a window to one side. Avoid harsh overhead light that hides eye shape.
• [ ] No beauty filters. A filtered photo has already altered the face before the model sees it.
• [ ] One person only, cropped if necessary, so faces do not blend.
• [ ] Recent photo, so the result matches how you look now.

Evaluation checklist

Do not judge the output at thumbnail size. Open it full screen next to the original and go through:

• [ ] Eye spacing and eye shape match.
• [ ] Nose and jawline match.
• [ ] Hairline and hair colour match.
• [ ] Skin texture is still visible; it is not plastic.
• [ ] Skin tone matches the original under comparable light.
• [ ] Apparent age is unchanged.
• [ ] Personal details (scars, moles, freckles) are still there.
• [ ] Hands, if visible, have five natural fingers.
• [ ] No stray text, logos or artifacts.

A quick sanity test: show the result to someone who knows the person, without explanation, and ask whether anything looks off. If something has drifted, add a targeted constraint for that feature and regenerate, rather than rewriting the whole prompt.

Scope and ethics

AI headshots are fine for professional profiles, resumes and team pages. They are not suitable for passports, visas or official ID, which usually require unedited photos. Changing clothing and background is a reasonable presentation choice; changing someone's face is a misrepresentation. And only generate headshots of yourself, or of people who have explicitly agreed.

Summary

• Structure the prompt as reference, preserve, change, prohibit.
• Name specific features and rule out smoothing, reshaping, de-ageing and skin tone shifts.
• Start from a sharp, unfiltered, front-facing photo with shoulders in frame.
• Iterate one change at a time.
• Evaluate at full size against the original.

Disclosure: I'm part of the Mona Lisa Studio team; this post was drafted with AI assistance and edited by me.