AI-AIDED GRAPHIC DESIGN

Meet Tom and the course team, set up your final project deck, and see how each weekly assignment builds toward your finished, AI-directed brand system by the end of the course.

• Instructor and course team introductions
• Course structure and expectations
• Final project overview
• Setting up your Google Slides project deck
• Tool access and approved equivalents

Learn to define a focused graphic design brief with a clear audience, communication goal, and creative north star before generating a single image, with AI working as your creative team.

• Interpreting the brief
• Finding your creative north star
• AI as your creative team
• Fixed brand requirements and constraints
• Demo: Tracing a finished design back to its original problem and idea

Discover how to turn your brief into specific direction AI can act on, combining written instructions, visual references, and brand constraints while you stay in control of the outcome.

• Breaking briefs into creative tasks
• Briefing AI like a creative team
• Directing toward a creative outcome
• Vague vs. directed instructions
• Workshop: Brief + Destination Lab, refining AI direction based on early results

Assignment #1: Bring Me an Idea
Start your final project deck by defining your audience, creative north star, and the first placement you want to create.

Explore how to use AI to investigate your audience, category, and competitors, then challenge your assumptions and verify claims to find insights that sharpen your visual direction.

• Audience and competitor research
• Challenging assumptions with AI
• Verifying important claims
• Filtering out generic suggestions
• Guided research exercise: Turning findings into design implications

Master the difference between subject matter and visual treatment as you develop three possible visual territories, then select and justify one through a focused, annotated mood board.

• Subject matter vs. visual treatment
• Developing three visual territories
• Annotating references
• Selecting a territory to develop
• Workshop: Reference + Mood Board Lab with peer feedback

Assignment #2: Build the World Around the Idea
Add key research findings, three possible visual territories, and an annotated mood board for your selected direction to your project deck.

Generate and curate AI image explorations that express your selected territory, learning when to generate, edit, extend, or refine, and how to recognize AI defaults and useful failures.

• Choosing the right image technique
• Directing imagery with references
• Recognizing AI defaults
• Spotting useful failures
• Demo: Testing a territory and curating 3–5 explorations

Build an editable design asset that combines AI imagery with purposeful typography, layout, and branding, treating each generated image as raw material for a specific placement.

• Selecting imagery for a placement
• Adding editable headlines and CTAs
• Resolving hierarchy and legibility
• Layout dimensions
• Workshop: References → Image → Design Asset, building a rough asset from a starter file

Compare a directed AI revision with local editing, compositing, or a second model to fix a specific design flaw, then choose the workflow that gives you the most control.

• Diagnosing the problem
• Protecting approved details
• AI revision vs. local editing
• Recording settings and versions
• Workshop: Controlled Repair of a shared flawed asset

Assignment #3: Test the Team
Compare two approaches to one design correction, document your process, and show a before-and-after repair with a reasoned choice of workflow.

Develop a short motion test from an existing visual asset, directing movement through frames, transitions, and rhythm while keeping the original design intent consistent from start to finish.

• Defining a focused motion task
• Directing movement through frames
• Rhythm and transitions
• Knowing when to switch to manual motion craft
• Demo: Testing a static-to-motion workflow

Apply the Keep / Fix / Kill framework to judge AI-assisted work against the brief, separating visually impressive outputs from design solutions that genuinely communicate with their audience.

• Keep / Fix / Kill framework
• Assessing brand fit and originality
• Accessibility and craft checks
• AI as a critique partner
• Breakout room: Keep / Fix / Kill peer critique of selected explorations

Implement a substantive revision that turns peer feedback into a specific correction, prioritizing problems in the idea before visual polish and choosing the main execution to develop.

• Translating feedback into corrections
• Prioritizing communication problems
• Before-and-after comparisons
• Selecting your main execution
• Revision clinic: Applying feedback and documenting the improvement

Assignment #4: Make the Cut
Label 6–10 existing explorations Keep / Fix / Kill, complete one substantive revision, and define the master execution for your three-asset system.

Define repeatable rules for imagery, typography, color, and spacing that let one design direction work across three applications, each with its own distinct communication purpose.

• Visual system rules
• Fixed elements vs. variables
• Choosing three applications
• Adapting your main execution to a second format

Put your visual system to work by translating it into AI direction and applying it across different design applications, reviewing each asset alone and together for consistency.

• Adapting copy and imagery per application
• Spotting inconsistencies across assets
• Cohesive identities across applications
• Demo: Developing three core executions with peer review

Assignment #5: Build the System
Define your system rules, complete three core executions, and record what AI produced versus what you designed or edited by hand.

Refine AI-assisted assets with retouching, compositing, and quality checks, fixing artifacts and weak details until your work holds up as polished design at its intended output size.

• Spotting artifacts and weak details
• Retouching and compositing
• Upscaling evaluation
• Final image quality checks
• Workshop: Final Craft + Polish on a raw AI-assisted asset

Prepare editable working files and final exports in Figma and Illustrator, checking dimensions, resolution, and formats so another designer could pick up and follow your process.

• Integrating AI imagery into Figma
• Editable typography in Illustrator
• Raster vs. vector artwork
• Asset organization and documentation
• Guided handoff exercise: Preparing a working file and final export

Shape your AI-assisted project into a portfolio case study that shows employers and clients exactly where your design judgment and problem-solving drove the final work.

• Selecting portfolio evidence
• Structuring your project story
• Explaining AI's role in interviews and pitches
• Project clinic: Rehearsing your presentation and refining the narrative

Present your AI-Directed Brand World, critique classmates' projects, and explain how AI workflows and your own design judgment shaped the finished work in a live showcase.

• Breakout room: Peer presentations and critique
• Live showcase of selected projects
• Reflection and feedback from Tom