What kind of AI image prompt is this?

This is a GPT Image 2 AI image prompt for Brand Name Color Absolute Rule Read Before Product GPT Image 2 Prompt. It is designed as a ready-to-copy example so you can study the wording, match the visual style, and regenerate a similar result. The example focuses on Product & Brand direction. Keep the composition cues that matter most—subject, lighting, materials, and camera language—then swap only the parts that should change for your own brief.

How do I use this prompt?

Copy the prompt, open Wenimg with the matching model, and generate once before making edits. Start from the exact wording so you can judge what the example is actually doing.

What is this prompt best for?

It works best for Product & Brand visuals where you want a clear style reference instead of writing every art-direction detail from scratch. Use it when you need a fast starting point for campaign drafts, concept exploration, or style matching. If the output drifts, keep the original lighting and composition language and change only the subject nouns.

Generate new or upload & edit...

Brand Name Color Absolute Rule Read Before Product GPT Image 2 Prompt

Prompt

[BRAND NAME] | [COLOR] ABSOLUTE RULE — READ BEFORE GENERATING ANYTHING: The fluid mass in this image has the exact shape of the [BRAND NAME] logo and nothing else. Not a circle. Not an oval. Not a blob. Not a rounded shape with the logo inside it. The outer silhouette of the fluid IS the logo outline — identical to the canonical [BRAND NAME] logo trademark. If someone covers the bubble texture and looks only at the silhouette they must immediately recognize it as the [BRAND NAME] logo. The fluid does not flow into a circle. The fluid does not form a blob. The fluid is constrained to the exact logo shape. This is the single most important rule in this prompt — it overrides everything else. Act as a Macro Fluid Photographer and CGI Art Director creating a hero typographic image where the brand logo is formed entirely from living fluorescent foam and bubble liquid — as if the logo was poured into a logo-shaped mold on a black surface and captured at the exact moment of maximum bubble activity. References: macro fluid photography, fluorescent paint foam art, soap bubble macro photography. --- PHASE 0: BRAND LOGO INTELLIGENCE — GEOMETRY IS LAW Retrieve the 100% canonical trademark-accurate primary mark of [BRAND NAME]. Use only the core logo symbol or emblem. STEP 1 — ESTABLISH EXACT SILHOUETTE: reconstruct the precise canonical [BRAND NAME] logo silhouette — every curve, every angle, every proportion exactly as trademarked. Draw this silhouette in your mind as a flat solid shape. This is the mold. It is rigid. It does not change shape. STEP 2 — FLUID FILLS THE MOLD: the fluid foam fills the interior of this rigid mold. The outer boundary of the fluid mass IS the logo outline — precise, hard, clean. Think of it as the logo shape cut from foam rubber and placed on a black surface. The fluid is solid where the logo is solid. The fluid is absent where the logo has designed empty space — those gaps show pure black background. STEP 3 — NO CONTAINER: there is no circle, no oval, no badge, no rounded rectangle, no frame around the logo. The logo floats directly on the black background. Its edges are the logo edges — nothing more. STEP 4 — ORIENTATION LOCKED: correct canonical upright orientation exactly as in official brand materials. Not rotated, not flipped, not mirrored, not tilted. STEP 5 — ZERO FLUID OUTSIDE BOUNDARY: the logo silhouette is an absolute hard boundary. Zero fluid, zero bubbles, zero tendrils, zero droplets outside this boundary. The black background begins exactly where the logo outline ends. STEP 6 — GEOMETRY WINS ALWAYS: wherever fluid simulation physics conflict with exact logo geometry — the logo geometry wins. Always. Apply [COLOR] as the fluid foam color throughout — in its most saturated fluorescent version. --- PHASE 1: FLUID MATERIAL SYSTEM — CRITICAL The entire logo form is filled with a single continuous viscous fluid existing in two physical states simultaneously. The fluid is NOT water — thick, viscous, surface-tension-dominant, like fluorescent soap foam, acrylic paint with trapped air, or colored slime. Base color: [COLOR] at maximum fluorescent saturation — self-luminous quality as if internally lit, consistent with UV-reactive fluorescent paint. Tonal variation strictly within [COLOR] family: thin bubble membrane walls — 35 to 45% lighter than base [COLOR], approaching near-transparency. Mid-thickness fluid zones — pure saturated [COLOR]. Deep thick liquid pools — 25 to 35% darker than base [COLOR]. Fluid surface in liquid zone: high gloss, wet, shiny, visible broad specular reflection. Foam zone membranes: lower gloss, slight soap film iridescence. --- PHASE 2: BUBBLE ARCHITECTURE SYSTEM Full bubble size hierarchy present across the foam zone only. Large anchor bubbles — 10 to 18mm diameter, 4 to 8 present. Medium bubbles — 4 to 9mm, 15 to 25 present. Small bubbles — 1.5 to 3mm, 30 to 50 present. Micro bubbles — 0.5 to 1mm, 50 to 100+ present. Each bubble: physically accurate sphere of trapped air enclosed by thin colored fluid membrane, 0.1 to 0.3mm thick, semi-transparent. Soap film iridescence barely perceptible. Bubble dome highlight: bright white crescent arc in UPPER-LEFT portion of each dome — 15 to 20% of dome surface, soft-edged, white regardless of bubble color. Inside large bubbles: dark reflection with [COLOR] tint confirming membrane transparency. Bubble contact deformation: flat septum membranes at contact points. Burst bubble holes: 3 to 8 irregular dark voids within foam zone only — revealing black background. Never at or near the logo boundary edges. --- PHASE 3: DUAL-STATE CONTRAST — CRITICAL Left zone — foam state: dense chaotic foam with full bubble hierarchy strictly within the logo silhouette. All bubble activity stays inside the logo boundary — never at or beyond the edge. Right zone — liquid state: solid continuous smooth mass — bubbles completely absent, maximum 2 to 3 micro-bubbles at transition edge only. Smooth viscous pool: gentle surface tension undulation 0.5 to 1mm, high gloss, broad soft specular highlight toward upper-left. Dense, heavy, pooled. Transition zone: gradual 8 to 15mm wide transition through vertical center — large bubbles disappear, fluid surface becomes smooth, last bubbles partially collapsed with sagging membranes dissolving into liquid surface. Edge behavior: both the foam side and the liquid side terminate exactly at the canonical logo outline. The logo boundary is geometric and exact on all sides. Clean edge. No organic ragged outer silhouette. The logo shape is always recognizable from the outer boundary alone. NO SPLATTER — ABSOLUTE: zero droplets, zero spray, zero tendrils, zero extensions beyond logo boundary. The composition is completely calm and contained. --- PHASE 4: LIGHTING — MATCH REFERENCE EXACTLY Primary light: large softbox upper-LEFT at 20 to 30° offset from vertical — NOT directly overhead. Light from above AND left simultaneously. Temperature 5500K neutral white. Left side and upper-left surfaces brighter. Right side relatively darker. Every bubble dome highlight arc in UPPER-LEFT. Liquid zone broad specular reflection toward upper-left. Micro-shadows from bubbles fall lower-right, 0.5 to 1mm, barely visible. Secondary ambient: 8 to 10% cool ambient from above. No fill from right. No rim light. No colored light. --- PHASE 5: COMPOSITION & CAMERA Background: absolute black #000000 — perfectly clean, zero texture, zero noise, zero gradient. Pure void. Aspect ratio: 1:1 square. Logo form occupies 60 to 70% of frame — centered horizontally and vertically. Generous clean black surround on all sides. Camera: directly overhead, perfectly perpendicular — zero elevation, zero perspective distortion, zero rotation. Pure top-down flat-lay macro. The logo silhouette reads as the correct [BRAND NAME] mark from this top-down view. Depth of field: sharp across entire fluid surface. --- PHASE 6: TECH SPECS Render: Houdini FLIP fluid simulation + Redshift or Octane, OR photorealistic CGI achieving identical result. CRITICAL: the fluid simulation domain is bounded by the exact logo silhouette — the simulation cannot escape the logo boundary. Fluid mesh: real FLIP simulation geometry constrained to logo shape. Bubble geometry: real curved surface per bubble, not texture map. Bubble membranes: thin-shell geometry, IOR 1.33, transmission 0.7 to 0.85, thin-film iridescence. Liquid zone: smooth FLIP mesh, roughness 0.02 to 0.05, high gloss. Foam zone material: fluorescent shader, emissive 0.05 to 0.1, subsurface scattering 2 to 4mm. Lighting: one large rectangular area light 80×80cm, upper-left 20 to 30° from vertical, 5500K. Secondary HDRI ambient 8 to 10%, neutral gray. Ray tracing minimum 12 bounces. Caustics on. Sampling minimum 2048. Anti-aliasing maximum. No film grain. No post-process. Output feel: indistinguishable from professional macro photograph of real fluorescent foam in a perfectly clean studio. --- FINAL CHECK — MANDATORY BEFORE OUTPUT: (1) Does the outer silhouette of the fluid mass match the exact [BRAND NAME] logo shape? If no — regenerate. (2) Is the fluid inside a circle, oval, or any container? If yes — regenerate. (3) Is there any fluid, droplet, or bubble outside the logo boundary? If yes — regenerate. (4) Are both foam state and liquid state clearly visible? If no — regenerate.

Additional details

Stats: 4K

Model: GPT Image 2
Date: Apr 27, 2026
Stats: 4K86
Author: AmirMušić
@AmirMushich
View on
Categories: Product & Brand
Source: Open original

A practical reading of this AI image prompt, with the parts worth preserving and the parts that are safe to change.

How to reuse this AI image prompt

Prompt analysis

This page is built around one reusable image prompt, not a generic model description. The useful unit is the relationship between the subject, the visual treatment, the camera or layout instruction, and the finishing constraints. Reading those layers separately makes it easier to reproduce the reference image without blindly copying every noun. The selected model is GPT Image 2, while the primary direction is Product & Brand. Together they define the search intent of this page: a Brand Name Color Absolute Rule Read Before Product GPT Image 2 Prompt AI image prompt that can be studied, copied, and adapted.

The prompt text below is the source material for the analysis. Its format is structured JSON or field-based text. This version is closer to natural language, so its layers must be identified from nouns, actions, camera cues, lighting, and finish phrases. When a prompt is written as a structured object, the field names are part of the teaching value: they show whether the author is controlling the subject, pose, environment, lighting, color, composition, or technical finish. When it is written as prose, sentence order becomes the main structure. In either case, the strongest instructions are the ones that describe a visible decision rather than a vague quality word such as beautiful or professional.

Start by separating identity from treatment. Identity includes the person, product, object, place, or action that must remain recognizable. Treatment includes the medium, lens feeling, lighting quality, palette, texture, atmosphere, and level of realism. Composition connects the two: it tells the model what should be prominent, where it should sit in the frame, and what can stay quiet in the background. This separation is especially useful when the first generation is close in style but wrong in subject, because it lets you replace the identity layer while keeping the visual grammar intact.

The example should therefore be read as a small art-direction system. Preserve the instructions that explain why the image looks the way it does; treat incidental details as optional until the core result is stable. If a detail is repeated, capitalized, placed in a JSON key, or described with a concrete camera or material cue, it is probably a high-priority constraint. If it appears only once as decoration, it is usually a candidate for later experimentation. That distinction gives this prompt value beyond the single image shown on the page.

The original prompt is included here so the explanation can be checked against the exact wording: [BRAND NAME] | [COLOR] ABSOLUTE RULE — READ BEFORE GENERATING ANYTHING: The fluid mass in this image has the exact shape of the [BRAND NAME] logo and nothing else. Not a circle. Not an oval. Not a blob. Not a rounded shape with the logo inside it. The outer silhouette of the fluid IS the logo outline — identical to the canonical [BRAND NAME] logo trademark. If someone covers the bubble texture and looks only at the silhouette they must immediately recognize it as the [BRAND NAME] logo. The fluid does not flow into a circle. The fluid does not form a blob. The fluid is constrained to the exact logo shape. This is the single most important rule in this prompt — it overrides everything else. Act as a Macro Fluid Photographer and CGI Art Director creating a hero typographic image where the brand logo is formed entirely from living fluorescent foam and bubble liquid — as if the logo was poured into a logo-shaped mold on a black surface and captured at the exact moment of maximum bubble activity. References: macro fluid photography, fluorescent paint foam art, soap bubble macro photography. --- PHASE 0: BRAND LOGO INTELLIGENCE — GEOMETRY IS LAW Retrieve the 100% canonical trademark-accurate primary mark of [BRAND NAME]. Use only the core logo symbol or emblem. STEP 1 — ESTABLISH EXACT SILHOUETTE: reconstruct the precise canonical [BRAND NAME] logo silhouette — every curve, every ang

Suitable use cases

The strongest fit is Product & Brand work that needs a clear visual starting point: Product & Brand images, concept drafts, campaign visuals, products, or brand directions. Use the prompt when the brief has a defined mood or reference image but the art direction is not yet organized into model-ready language. It can support an early concept, a campaign direction, a social post, a product study, or a personal visual experiment, provided the requested subject remains within the model’s capabilities and the final output is reviewed by a person.

For a professional workflow, treat the prompt as a first-pass specification rather than a final guarantee. It is useful for comparing how GPT Image 2 interprets lighting, materials, framing, and visual hierarchy. Generate the original once, then create a controlled variant with only one major change. That comparison tells you whether the result is being driven by the subject, the style, or the camera language. The method is more reliable than changing five clauses at the same time and guessing which edit mattered.

This structure is also helpful for learning prompt writing. A new user can identify the nouns that establish the scene, the adjectives that establish the look, and the technical phrases that limit the output. An experienced creator can use the same page as a compact reference when moving between models. The goal is not to force every image into one formula; it is to make the decisions visible enough that the creator can choose which decisions to keep, weaken, or replace.

Use the page responsibly when the prompt includes a person, a recognizable brand, a source image, or a real-world setting. Keep permissions, privacy, attribution, and platform rules in mind. The source and attribution links on this page are part of the case context, not proof that every future use is authorized. A good adaptation changes the creative brief for a legitimate purpose and checks the result before publishing or using it commercially.

How to modify it

The safest edit order is subject first, then composition, then style, then finish. Begin with the subject noun and the action or product requirement. Keep the original framing and lighting for the first variant so you can see the effect of that one replacement. Next change the composition if the image needs a different crop, camera distance, angle, or subject position. Only after those choices are stable should you tune palette, texture, atmosphere, typography, or small props.

When adapting this prompt to a new brief, keep a small preserve / replace / remove list. Preserve the cues that carry the page’s core visual identity, such as a soft directional light, a reflective material, a centered subject, a shallow depth of field, or a particular poster hierarchy. Replace nouns that belong only to the original case. Remove contradictory details rather than stacking more instructions on top of them. A shorter prompt with consistent constraints is often easier for the model to follow than a long prompt with competing camera, style, and layout demands.

If the model drifts, make one diagnostic pass before rewriting everything. First ask whether the subject is too ambiguous. If yes, make its appearance, count, pose, and position concrete. If the subject is right but the mood is wrong, adjust the lighting and palette language. If the mood is right but the layout is wrong, change only the camera or composition clause. If text, logos, hands, or small product details fail, describe their role and placement clearly, then verify the output manually because generative models can still make factual or typographic mistakes.

For repeatable work, record the model, aspect ratio, reference images, and the exact edit made for each generation. That turns this case from a one-off prompt into a small experiment. Keep the original prompt untouched, create named variants, and compare them at the same output size. The result is a useful feedback loop: the page teaches the initial structure, the generated image shows what the model actually obeyed, and the next revision is based on observed behavior rather than assumptions about a model’s capabilities.

Copy the original prompt and generate one baseline result with GPT Image 2.
Mark each clause as identity, composition, style, lighting, material, or finish.
Replace one identity or brief-specific detail while keeping the visual treatment stable.
Compare the variant with the reference, then change one additional instruction only when the difference is understood.
Save the successful wording with the model, aspect ratio, and reference-image context.

Related case chain

A useful internal path is to move from this single case to the model collection, then to the category collection, and finally to another concrete example. The model page shows the neighboring prompt vocabulary available for GPT Image 2; the category page narrows the journey to Product & Brand; the gallery exposes other images that can be compared by subject, composition, and finish. This is a case chain rather than a list of unrelated links: each step answers the next question a reader normally has after studying one prompt.

When comparing neighboring cases, change one dimension at a time. Compare two prompts from the same model to understand model-specific phrasing. Compare two prompts in the same category to see which visual decisions are transferable. Then compare a close case with a contrasting one to identify which details are truly essential to the subject. The links below are intentionally descriptive so that both people and crawlers can understand the relationship without relying on a button click or an opaque identifier.

The current case remains the reference point for the chain. Return to it when a related example introduces a different lighting setup, camera distance, material, or visual density. Copy only the clause that solves the new problem, not the entire neighboring prompt. This keeps the page’s primary intent intact while giving the reader a practical route through the broader AI image prompt library.

Where does this prompt come from?

This AI image prompt is a reusable example attributed to AmirMušić.

Data from NanoBanana Trending Prompts (https://github.com/jau123/nanobanana-trending-prompts) by MeiGen.ai, licensed under CC BY 4.0.

View the original source License: CC BY 4.0