Overview
The Project
The advent of generative AI has opened new frontiers in product design. As an intern for Greg Aper, hired by Netflix to demonstrate this transformative potential, my role was to explore and test generative AI tools to create final design assets.
How might generative AI be used to improve the design process?
The Challenge
The main challenge was effectively integrating generative AI tools into the design workflow, understanding their strengths and weaknesses, and mastering prompting for each model.
The Solution
The result was an AI super framework composed of prompts that enhanced agility in the design process, enabling rapid exploration of diverse design directions.
AI Super Framework
Note: This case study highlights my specific contributions to the design phase, with certain details omitted to respect the work and confidentiality of others involved. For more details, feel free to get in touch with me directly.
Research
AI Tools Tested
Design
AI Visual Design Concepts
AI Wireframes Concepts
Curating Elements
Final Concept for Search Page
Impact
How Gen AI Changes the Design Process
Accelerated Adaptation: Generative AI enhances agility, enabling instant shifts in creative direction to respond to market changes.
Predictive Conceptualization: Using qualitative research, AI generates design concepts for future markets, akin to predictive modelling.
Ideation Cross-Pollination: Modular AI output allows blending UX research data for diverse ideation.
Rapid Regeneration: AI can "re-roll" design variants or entire phases, facilitating quick iterations.
Resource Reutilization: AI's modularity ensures efficient reuse of content, saving time and resources.
Modular Methodologies: AI supports both sequential and non-linear processes, offering versatile content toolkits.
Imagination Amplification: AI amplifies creativity, limited only by the user's imagination.
Holistic Insight: AI-organized content provides holistic project overviews.
