AI CEO LabNano Banana Image Editing: The Prompts I Actually Use
Change the time of day, swap an outfit, put a logo on a bag, merge a person into a scene, fix the text on a sign. Plain English edits on an existing photo with Google's Nano Banana, the way I run it in Higgsfield and the Gemini app, plus the labelled reference trick that makes multi object edits land first time.
The photo is nearly right. The room is right, you are right, the moment is right. But it is daytime and the post needs night. Or the shirt is wrong. Or the sign in the background says the wrong thing. Five years ago that was an hour in Photoshop. Now it is one sentence, if you say the sentence properly.
Nano Banana is Google's image model and its strength is editing, not just generating. You hand it a photo and describe the change, and it keeps everything you did not mention. That is the part people miss: the value is not what it adds, it is what it leaves alone. A tattoo, a piercing, a logo, a face, all preserved while the scene changes around them.
I run it two ways. In Higgsfield from the command line, as nano_banana_pro with up to 14 references, when the agent does the work. In the Gemini app when I am testing a quick idea by hand. The model is the same. The idea that a multi object edit works far better when every reference is labelled first comes from a course I took; I have used it since and it is the single biggest improvement to hit rate I know.
This guide is the edit routine: describe the change, not the photo; tell it what to keep; one edit per turn; label your references; and check the parts the model never gets right without being asked.
The three levels
You ask the chat to make it night, get a different photo of a different room, and give up.
Every edit follows the routine: the photo as reference, the change described, the keep list stated, one edit per turn, references labelled. It lands in one or two tries.
Your agent runs edits from the command line on a folder of photos: relight, restyle, swap, fix text, and returns before and after pairs with a check on what changed that should not have.
The mental model
Describe the whole picture you want and hope the model rebuilds it.
Describe the difference. The photo is the reference; the prompt is the change and the keep list. One change per turn, references labelled.
| Role | Talks to you | Job |
|---|---|---|
| The source | Always | The photo you are editing, attached as a reference, not described |
| The change | Every turn | One edit in plain English: make it night, swap the shirt, add the logo to the bag |
| The keep list | Every turn | Face, tattoos, logo, text, layout, whatever must not move |
| The labels | Multi object edits | Every extra reference named on one board so the prompt can point at it |
The edit routine
1. Attach the photo; describe the change, not the photo
The most common mistake is re describing the image. The model already has it. Bad: a man with brown hair in a leather jacket holding coffee, at night. Good: make it night, keep everything else. The shorter the difference, the less the model reinvents.
2. Say what to keep
Keep the same face, hairstyle, skin tone and body. Keep the logo exactly. Keep the text on the sign. Keep the layout. If you do not name it, it is fair game. Character consistency in a multi scene story lives in this line.
3. One edit per turn
Make it night. Then add rain on the street. Then add the neon sign. Each turn builds on the last output, and each is easy to check. Three edits in one prompt is three chances to get one wrong and no way to tell which. Drag the result back in as the new source and go again.
4. Label references before a multi object edit
When several things must land in one image (a product, a logo, a person, two props), put them on one board first with a plain text label under each: PRODUCT, LOGO, HEADPHONES. Attach that board and refer to the labels in the prompt. Uploading five loose files and hoping the model matches them to your nouns is how you get refusals and wrong objects. Nano Banana Pro takes up to 14 references, so the board plus the source and a face reference is fine.
5. Pick the variant by the job
Nano Banana Pro (nano_banana_pro) for anything hard: faces, text, many objects, close ups. Nano Banana 2 (nano_banana_flash) for fast, cheap iterations. Higgsfield also exposes Nano Banana Pro as tools: a relight tool with an explicit light source, quality and colour, a shots tool that reframes one image into new angles, and a skin enhancer. When the job is lighting only, the relight tool beats a prompt.
6. Check what changed that should not have
Put source and result side by side. Face the same. Text unchanged where it should be. Hands, logos, background objects all still there. Then the usual realism check: does the new light make sense in the room. If the model added a watermark (the Gemini app does, bottom right), crop or remove it before posting.
Starter prompts
Paste these as written. They are short on purpose, because the long ones drift.
I am editing the attached photo with Nano Banana. Do not describe the photo back to me. Write the edit as a difference: the one change I want is [the change]. Then a keep list naming everything that must not move: [face, hair, skin tone, clothes, text on signs or labels, logos, layout, framing]. Phrase everything positively (tack sharp, not no blur). Keep the source aspect ratio. Give me the prompt to paste, then after I show you the result, list anything that changed that should not have.
I need several things placed in one photo: [list the objects and where each goes]. First tell me how to lay out a single reference board with each object labelled in plain text (PRODUCT, LOGO, and so on). Then write the edit prompt that refers to those labels, states where each goes, and keeps [face, room, framing] exactly. One generation on Nano Banana Pro with the source and the board attached.
The photo is right but the light is wrong. Tell me whether to prompt it or use the relight tool. If prompting: where the new light comes from, hard or soft, warm or cool, which side falls into shadow, and everything else unchanged. If the tool: the light source position, quality, brightness and colour to pass.
Gemini app vs Nano Banana in Higgsfield
Layer 1 is the Gemini app: drop the photo in, type the change, take the result. It is the fastest way to learn the routine. Layer 2 is Higgsfield from the command line, where the agent runs it. The settings that change:
Model ID
nano_banana_pro for hard edits, nano_banana_flash for Nano Banana 2, nano_banana_2_lite for the cheapest pass. Run higgsfield model list if a name has moved.
References are repeated flags, up to 14
The source photo is the first image flag. The labelled board, the face reference and the product are more flags. The prompt refers to them by label.
Aspect ratio and resolution are explicit
Nano Banana Pro accepts 1:1, 3:2, 2:3, 4:3, 3:4, 4:5, 5:4, 9:16, 16:9, 21:9 and 1k, 2k or 4k. Keep the source's ratio for an edit unless you are reframing on purpose.
Tools instead of prompts for lighting and angles
nano_banana_2_relight takes a light source position, light quality (hard, sharp, soft), brightness and colour. nano_banana_2_shots takes exactly one image and returns new angles. nano_banana_2_skin_enhancer for skin. These are the options when the prompt keeps missing.
Give it to your agent, three ways
Same skill, three worlds. Pick the one you actually use. The skill file at the bottom of this page is the instructions in every case.
An agent with connectors (Claude Desktop, Claude Code, Grok Bot)
Claude Code with the Higgsfield CLI runs the edits and the diff. The skill below is the instructions. If you prefer connectors, Higgsfield exposes an MCP and Google's Gemini API is a plain HTTP call.
- Install and log in to the CLI (commands below).
- Save the skill file. Keep the photos to edit in a folder the agent can read.
- Say "edit this image" with the path and the change: "edit clinic-front.jpg: make it dusk, keep the sign text and my face exactly." The agent writes the difference prompt with the keep list, runs it, and returns the before and after with a list of anything that moved.
- For a multi object edit, give it the loose files; it builds the labelled board first, then runs the edit against it.
curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh higgsfield auth login higgsfield model get nano_banana_pro higgsfield model get nano_banana_2_relight
ChatGPT (a project or a custom GPT)
ChatGPT does not run Nano Banana. The honest Layer 1 for this model is the Gemini app, and the routine is identical. ChatGPT's own GPT Image can do the same class of edits and is a fine fallback, especially when the edit is text.
- Gemini app: attach the photo, write the change and the keep list, one edit per turn, drag each result back in as the next source. Expect a watermark bottom right; crop or remove before posting.
- ChatGPT: create a Project, paste the skill as instructions, attach the photo, same routine. Put exact text in the prompt when the edit is a sign or a label.
- Either way, ask the chat to list what changed that should not have before you download.
Anything with an API (a token and a curl call)
Two APIs. The Higgsfield CLI for the agent path, and Google's Gemini API when you want the model with no studio in between. The Gemini model IDs on the docs page as of this writing: gemini-3-pro-image for Nano Banana Pro, gemini-3.1-flash-image for Nano Banana 2. Confirm the request shape on that page before you build on it; it changed this year.
- Higgsfield: source photo as the first image flag, the board and any face or product references after it, prompt as the difference plus keep list.
- Relight: use the relight tool with an explicit source position, quality, brightness and colour instead of a prompt.
- Gemini API: key in an environment variable, image as base64 inline data next to the text prompt, model set to the Nano Banana ID you want.
# Higgsfield: a plain edit
higgsfield generate create nano_banana_pro \
--prompt "Make it dusk with the streetlights on. Keep the sign text, my face, my clothes and the framing exactly the same." \
--image ./photos/clinic-front.jpg --aspect_ratio 4:5 --resolution 2k --wait
# Higgsfield: multi object edit with a labelled board
higgsfield generate create nano_banana_pro \
--prompt "Place PRODUCT in my right hand, LOGO on the tote bag, HEADPHONES on the desk. Keep my face and the room exactly." \
--image ./photos/me-desk.jpg --image ./boards/labelled-refs.png --resolution 2k --wait
# Higgsfield: relight tool instead of a prompt
higgsfield generate create nano_banana_2_relight --image ./photos/me-desk.jpg \
--light_source mdl --light_quality soft --brightness 60 --color "#FFD8A8" --wait
# Gemini API: same edit, no studio (confirm shape on Google's docs page)
export GEMINI_API_KEY=...
IMG=$(base64 -i ./photos/clinic-front.jpg)
curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" -H 'Content-Type: application/json' \
-d "{\"contents\":[{\"parts\":[{\"text\":\"Make it dusk. Keep the sign text and the face exactly.\"},{\"inline_data\":{\"mime_type\":\"image/jpeg\",\"data\":\"$IMG\"}}]}]}" > out.jsonFailure modes
Every one of these has happened to me or to someone I set this up for.
| Failure | Fix |
|---|---|
| Asked for night, got a different room | Describe the difference and the keep list; never re describe the photo |
| Three edits in one prompt, one went wrong, no idea which | One edit per turn; build on the last output |
| Five loose reference files, wrong objects placed or a refusal | Put them on one labelled board and refer to the labels |
| Face drifted on a close up | Nano Banana Pro, a face reference attached, keep list names the face |
| Sign text changed on its own | Put the exact text in the keep list, or in the prompt to set it |
| Watermark in the corner of a posted image | Gemini app stamps one; crop or remove before posting |
| Lighting still wrong after four prompts | Use the relight tool with a named source position |
| Prompt says no people, model adds people | Positive phrasing: empty street |
The tools I use for this
| Tool | What it is for here | |
|---|---|---|
| Nano Banana Pro (Gemini) | The editing model. Keeps what you do not mention. Up to 14 references in Higgsfield. | no link, just use it |
| Higgsfield | Where the agent runs it, plus the relight, shots and skin tools. | no link, just use it |
| Gemini app | The chat window version for quick edits by hand. Stamps a watermark. | no link, just use it |
| Claude | Writes the difference prompt, builds the labelled board, runs the diff. | Open |
The free skill
It is the edit routine as instructions for an agent: take the source photo as the reference, write the change as a difference (what changes, what stays), one edit per turn, label multiple references on one board before a multi object edit, choose nano_banana_pro for hard edits and Nano Banana 2 for fast ones, then diff the result against the source for unwanted changes before returning it.
--- name: edit-any-image-nano-banana description: Edits existing photos with Google's Nano Banana (Nano Banana Pro and Nano Banana 2) through the Higgsfield CLI or the Gemini app: relight, time of day, outfit and object swaps, merging a person into a scene, fixing text, carrying a character across scenes. Writes the edit as a difference with a keep list, one edit per turn, builds a labelled reference board for multi object edits, and diffs the result against the source. Trigger on "edit this image", "make it night", "swap the shirt", "put the logo on", "fix the text in this photo", "put me in this scene". --- # Edit Any Image With Nano Banana You are changing one thing in a photo the user already has, and leaving everything else alone. The photo is the reference. The prompt is the difference plus the keep list. ## Before you start - Get the source photo as a file on disk. Chat pasted images are not reachable from the command line. - Check `higgsfield account status`; ask for `higgsfield auth login` if needed. If the CLI is unavailable, write the prompt for the Gemini app and remind the user it stamps a watermark bottom right. - Ask one question only if the change is ambiguous. Never ask what the photo shows. ## The prompt shape 1. **The change**, one sentence, plain English. "Make it dusk with the streetlights on." 2. **The keep list**: face, hair, skin tone, clothes, text on signs and labels, logos, objects, layout, framing. Anything not named may move. 3. **Positive phrasing**. "Tack sharp" not "no blur". "Empty street" not "no people". 4. Never re describe the photo. Never stack edits. One edit per turn. Use the output of one turn as the source of the next. ## Choose the model - Faces, text, close ups, many objects: `nano_banana_pro` (up to 14 references, 1k/2k/4k, ratios 1:1, 3:2, 2:3, 4:3, 3:4, 4:5, 5:4, 9:16, 16:9, 21:9). - Fast iterations: `nano_banana_flash` (Nano Banana 2) or `nano_banana_2_lite`. - Lighting only: `nano_banana_2_relight` with `--light_source`, `--light_quality` (hard, sharp, soft), `--brightness`, `--color`. Beats a prompt when the light keeps missing. - New angles of one image: `nano_banana_2_shots` (exactly one image). - Skin: `nano_banana_2_skin_enhancer`. Keep the source aspect ratio unless the user is reframing on purpose. ```bash higgsfield generate create nano_banana_pro \ --prompt "<change>. Keep <keep list> exactly the same." \ --image ./source.jpg [--image ./board.png] [--image ./face.jpg] \ --aspect_ratio <source ratio> --resolution 2k --wait ``` ## Multi object edits: the labelled board When several objects must land in one image: 1. Compose one board image with every object and a plain text label under each (PRODUCT, LOGO, HEADPHONES). Build it with a script or ask the user for one. 2. Attach the source first, the board second, any face or product reference after. 3. Refer to the labels in the prompt and say where each goes. One generation. Loose files without labels produce wrong placements and refusals. ## Character across scenes Source portrait as the first reference, keep list names face, hair, skin tone, build, marks (tattoos, piercings, glasses). Prompt: "Same person, now <scene>." Test a close up first; drift shows there before it shows in a wide shot. ## The diff Put source and result side by side and report anything that changed that should not have: face, text, logos, hands, background objects, framing. Then the realism check: does the new light make sense in the room; is skin still textured. Return the result only if the diff is clean, with the prompt used so the next turn can build on it. ## House rules - Never put words, products or endorsements on a real patient or clinician. - Never invent a logo; use the real file on the board. - Remove or crop the Gemini app watermark before anything is posted.
What done looks like at thirty days
- Ten before and after pairs from your own photos, each with the prompt that landed
- One labelled board multi object edit that worked first or second try
- A character carried across scenes with the keep list and no drift
- Your agent runs edits from a folder and returns a diff with each result
- Old photos in your library have become new posts
Want an editing pipeline for your whole content library?
Inside the AI CEO Lab, the Content Engine module wires Nano Banana into your reference folder and your agent, so every photo you already own becomes ten posts.