Brand Consistent Imagery Systems
Design a documented image system so every AI visual looks like your brand
A taste of a lesson
Our brand book says 'optimistic, grounded, human'. Our AI images are all sunsets and smiling people. How do we fix it?
Those words have been read literally: optimism became sunsets, human became smiling. Make each word visible. Grounded might mean real locations, everyday tasks, natural daylight, no lens flare. Human might mean candid moments, hands at work, mixed ages, imperfect environments. Optimistic might mean open compositions with sky or space, and a palette led by your brand yellow as an accent. Then write what you never show: posed group smiles, sunsets, glossy skin. Try it: give me three visible rules for 'grounded'.
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Translate brand identity into visible, testable image rules
- Build references, templates and a do and do not gallery
- Choose between style references, adapters and post grading for consistency
- Set up governance: approvals, records and periodic audits
Lesson plan
- 1 From brand words to visible rules Rewrite abstract brand values as rules anyone can see in an image. Start
- 2 References and the annotated gallery Assemble approved references and annotated examples of right and wrong. Start
- 3 Prompt templates with locked slots Create templates that hold brand rules fixed while allowing variety. Start
- 4 Consistency methods compared Pick the right mix of references, adapters and grading for the volume. Start
- 5 People, representation and rights Handle casting, stereotypes, likeness and disclosure deliberately. Start
- 6 Governance and audits Keep the system working across teams over time. Start
Try asking
About this tutor
An advanced tutor for brand managers, designers and agencies producing many AI images for one brand across campaigns, channels and people. You will translate a brand's visual identity into an image system: subject rules, composition and lighting principles, palette and grade, references, prompt templates, and where needed a trained adapter. We then build the controls around it: approval steps, a do and do not gallery, records and periodic audits. The goal is imagery that a stranger could recognise as yours, produced by different people over months, while respecting rights and representation.
Reviews
4.7
3 ratingsSample
- Carlos E.Sample
Strong on governance and the blind sort test. The adapter section assumed more technical support than our team has.
- Naledi M.Sample
It flagged that our people imagery all looked the same age and skin tone. Uncomfortable but necessary.
- Annika J.Sample
The adjective to visible rule exercise was worth the price alone. Our guidelines went from mood words to something designers can check.
About the teacher
Commercial imagery with AI for shops, brands and property, done accurately
9 tutors 427 lessons taught Sample
I help small businesses and in house teams use image models for commercial work: product shots, listings, campaign imagery, interiors and print. I came to this from product photography and online retail, where an image that misrepresents a product turns into returns and complaints. So I teach a careful approach: the real product stays real, AI handles scenes and variations,...
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