To create a consistent set of AI-generated brand images, define the visual rules first, reuse a small set of approved references and a stable prompt structure, then review every result against the same checklist. A reference can guide an image’s style, but it does not guarantee that a product, character, logo, or layout will be reproduced exactly. For recurring subjects or team-wide reuse, a custom model or shared settings kit may help if your platform and plan support it.
Define what “on brand” looks like
Turn your existing brand guide into concrete visual instructions before generating a batch. Describe features a reviewer can actually see, rather than relying only on subjective terms such as “premium,” “friendly,” or “modern.” For example, specify a warm cream background and soft side lighting alongside the tone you want.
- Palette: name the dominant colors, supporting colors, and desired contrast.
- Lighting: specify direction, softness, brightness, and whether shadows should be prominent.
- Texture or medium: describe whether the image should feel photographic, illustrated, grainy, smooth, or otherwise treated.
- Composition: state preferred framing, subject placement, negative space, and background treatment.
- Recurring details: list product features, character traits, or other elements that should remain recognizable.
- Exclusions: call out unwanted colors, props, visual effects, or other elements that would make an image feel off-brand.
This brief is a practical working system, not a guarantee of exact results. It gives the team a shared standard for selecting references, writing prompts, and judging outputs.
Choose references that represent the intended look
Select a small set of approved images that clearly demonstrate the visual direction. Use source images that your organization owns or has permission to use. Avoid combining examples with incompatible art directions: a reference set that pulls in opposite directions makes it harder to judge whether a result fits the brand.
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Keep style guidance separate from subject preservation. Midjourney says its Style Reference guides colors, medium, textures, or lighting and “doesn’t copy objects or people”; Adobe describes its style-reference feature as guiding the look and feel of image variations. A style reference alone should therefore not be treated as a dependable way to retain a particular product, person, character, or layout. See Midjourney’s Style Reference documentation and Adobe’s Firefly style-reference guidance.
Build a reusable prompt and reference workflow
Keep the approved reference images, prompt scaffold, model and version, generation settings, and approval status together in a team-accessible source of truth. Reuse the same visual inputs across a batch; change scene-specific content without casually rewriting the brand rules each time.
A useful prompt structure is:
Subject + action or context + composition or framing + lighting + required brand details + exclusions
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For example, a team might keep its palette, lighting, and texture requirements constant while changing the subject and setting for each asset. Keep the scene description clear and avoid stacking on style language that conflicts with the reference. Midjourney recommends simple prompts, selectively using style words that match the reference, and describing the desired content rather than instructing the model to modify the reference.
Midjourney
Midjourney’s documentation says Style References are compatible with versions 6 and later. On the website, upload or select an image and assign it as a Style Reference; the documentation also describes pinning references for reuse. In Discord, attach the reference with --sref followed by a valid image URL. Multiple references can be supplied. The --sw parameter controls how strongly the reference influences the result; Midjourney documents a range of 0 to 1000 and a default of 100. These details reflect the documentation available in 2026, and platform controls can change. See Midjourney’s current Style Reference documentation.
Adobe Firefly
The Firefly web experience supports uploaded or curated style-reference images. Adobe’s API documentation gives reference strength a range of 1 to 100 and a default of 50 when omitted. That is a separate platform control and scale from Midjourney’s --sw; the values should not be compared as if they meant the same thing. See Adobe’s style-reference guidance and Adobe’s Style Image Reference API documentation.
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Text that must appear inside an image
When a graphic needs a label or headline, give the text, type style, size, color, and placement explicitly, and keep the copy short. OpenAI Academy suggests putting requested text in quotes or capitals and spelling uncommon brand words letter by letter. For dense layouts or text that must be exact, finish the typography in a design tool rather than relying on generated lettering alone. See OpenAI Academy’s image-generation guidance.
Generate batches and tune one variable at a time
Generate several candidates using the same references and core prompt, then compare them using the same review checklist. If the set drifts from the desired look, adjust the reference influence or simplify language that conflicts with the reference before changing unrelated parameters. This is a practical iteration approach, not a documented setting that guarantees consistency.
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Review each image before it goes into production
Apply the same checks to every candidate, whether it will be used in an ad, a product page, or a social post:
- Do the colors, contrast, lighting, texture, and composition match the visual brief?
- Are recurring product or character details present and accurate?
- Is the crop suitable for the intended channel and layout?
- Is any text spelled correctly and placed as intended?
- Are the source references, likenesses, logos, and other assets cleared for the intended use?
- Does the image meet the channel’s production requirements?
Where precise logo placement or typography matters, add those elements in an appropriate design workflow instead of treating a generated result as final artwork. Record the prompt, reference, settings, model/version, and approval status with the selected asset so the team can reproduce its process and identify which version was approved.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose the right workflow for the scale of the work
A reusable reference and prompt are a sensible starting point. The options below solve different problems; feature availability and access terms can change.
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| Workflow | Setup | Best-documented use | Access and main caution |
|---|---|---|---|
| Reusable reference and prompt | Low: select a reference and establish a prompt | Influencing the style of image variations | Depends on platform support. A style reference does not necessarily preserve objects or people. |
| Custom model | Higher: curate and train on representative images | Recurring style or subject across generated assets | Adobe reported Custom Models as beta in its overview updated September 21, 2026; supported plans and use cases vary. Training assets need quality, consistency, and usage rights. |
| Shared kit or template | Low to moderate: save settings and arrange access | Reusing approved generation settings among collaborators | Adobe limits Style Kit creation and saving to select enterprise plans. Team permissions and plan entitlement can constrain adoption. |
When to consider an Adobe Custom Model
Adobe describes Custom Models as a way to train on your own images to reflect a style or subject and use the model for variations. Its overview, updated September 21, 2026, lists the feature as beta and notes plan and use-case limits; check the current plan information in your account before relying on access. Adobe’s training guide, updated September 24, 2026, recommends 10–30 representative JPG or PNG images, consistent high-quality examples, and reviewed captions and tags. It estimates training may take 30 minutes to several hours depending on dataset complexity. Those are Adobe’s training guidelines and estimates, not general benchmarks for other image generators. The guide also asks users to confirm they have rights to images submitted for training. See Adobe’s Custom Models overview and Adobe’s training guidance.
When to use a shared Style Kit
Adobe Style Kits can package and share generation settings, including prompt, content, structure, and style, for reuse. Creation and saving are limited to select enterprise plans, although access to a shared kit may be available through invitation links. Verify access in the relevant account before designing a team workflow around the feature. See Adobe’s Style Kits guidance.
Check usage rights and brand rules
Use reference images, product photos, characters, logos, and likenesses only when you have permission for the intended generation and training use. Adobe’s Custom Model training flow asks users to confirm they have the necessary rights to submitted images. OpenAI Academy advises obtaining permission for references depicting real people and suggests requesting generic or ownable designs rather than imitating a particular brand, product, or artwork. These are workflow checks, not a complete legal determination for every jurisdiction.
If an image uses another organization’s logo or marks, consult that organization’s current brand rules. For example, OpenAI’s own brand guidelines say its marks must not be more prominent than the user’s marks and describe permission as non-exclusive and non-transferable; those terms apply to OpenAI’s marks, not to other companies’ brands. See OpenAI’s brand guidelines.
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