AI in visual creation: from your first model to a custom visualisation pipeline
For graphic designers, product designers and art directors in furniture and bathroom showrooms and design studios. Nine modules take participants from how generative models work through Figma Weavy, prompt engineering and product visual consistency to a ready workflow with an AI assistant aligned to the team's brand guidelines.
Designers handle product variants without a photographer or renderer
Participants leave with a workflow they can use from the next day. Changing upholstery, glaze or background does not require a new external brief—variants are generated from one reference photo, cutting asset prep from days to hours.
Clients see several variants in the meeting, not a week later
An architect or showroom advisor shows the product in a specific project context live. The conversation shifts from "I'll send visuals on Thursday" to "let's look now", shortening decisions and reducing revisions after product choice.
The whole creative team shares one AI assistant
The assistant built during training knows brand guidelines, style guide and product parameters. Every designer starts from the same baseline, not an empty prompt, which reduces drift between projects.
What you get
How generative models work and why a designer who understands them gets better results than one who only clicks
Working in Figma Weavy: prompts, parameters, scalable composition and iterative product visual refinement
Product consistency across generations: keeping furniture, fittings or interior schemes visually aligned on every asset and context change
A custom AI assistant for the creative team with brand guidelines, style guide and a ready workflow
Live training in groups of up to 15. Session recordings available for 90 days after completion.
Schedule
Times are indicative. Day 2 ends around 18:00 at a standard group pace.
Day 1 · Foundations and first visualisations
9:00–17:00
9:00–11:002hlecture + demo
Panorama of AI in visual creation
How the designer's and creator's role is changing. Is style non-replicable? Local and cloud tools. Text-to-image and text-to-video models. Local vs cloud models. First model run.
11:15–12:451.5hlecture
Foundations of generative AI technology
How generative models work: text to image. Transformers and diffusion models. Context-window limits for multimedia creation. Visual hallucinations and artefacts: causes and how to reduce them.
13:30–16:002.5hlecture + workshop
Introduction to Figma Weavy
Weavy interface. Human vs LLM image description. Mood and style. Technical image parameters. Anatomy of an effective visual prompt. Common prompt mistakes. Parameters and modifiers: aspect ratio, quality, style, seeds. Negative prompts. Composer option and scalable graphics.
16:00–17:001hworkshop
First workshop: consistent graphics for client visualisations
Generating basic visual compositions. Working across styles: photorealism, illustration, abstract, vintage. Visual consistency across generations. Basic inpainting. Social media assets. Delivering a simple creative brief.
Day 2 · Advanced techniques and your own pipeline
9:00–18:00
9:00–12:303.5hworkshop
Working with visual tools
Reference images and style transfer. Building consistent character and visual narrative. Keeping style and scene across generations. Advanced composition: framing, perspective, depth of field. Video from concept to animation: Runway, Veo 3, Pika.
13:15–15:152hlecture + workshop
Advanced prompts and visual storytelling
System prompts and persona for creative tasks. Chain-of-Thought for complex visual projects. Metaprompts for complex visual prompts. Visual storytelling through image sequences. AI moodboards and style guides. Designing advanced visual campaigns.
15:15–16:451.5hworkshop
AI assistants for creative teams
Building an AI assistant for creative projects. Assistants for campaigns and concept art. Assistants for moodboards and mockups. Knowledge base: brand guidelines, style guides, best practices. Integrating the assistant into creative workflow.
16:45–17:451hlecture
Safety, copyright and ethics
Copyright in the AI era: who owns generated content. Training data and style mimicry: ethical issues. Watermarking and identifying AI-generated content. Responsible use of AI in creation.
17:45–18:000.5hdiscussion + Q&A
Development strategy and wrap-up
Identifying creative processes to augment with AI. Building AI-first workflow in the creative team. Competency roadmap. Q&A and summary.
Tailor the programme to your team
Select participant profile and modules to go deeper on—we will align emphasis and examples to your context.
Participant profile
Modules to go deeper on (select several)
Your choices are attached when you send the enquiry.
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