Leonard Egwuekwe
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Using AI in UX
Read time: 5 minutes
Project date: 2025 - 2026
Using AI to think better, not just work faster
Explored how AI can support research synthesis, content clarity, ideation, and portfolio design while maintaining UX judgment, consistency, and human-centred decision-making.
Workflows
AI
Strategy
TL;DR...a quick snapshot of the project!
Project
Exploring interaction patterns to make hero content optional while retaining value for new or less tech-confident users.
Goal
Improve speed, clarity, and decision-making without losing UX judgment
My Role
UX Designer experimenting with AI-assisted research, content, and ideation
Challenges
- Maintaining consistency
- Avoiding over-automation
- Prompt discipline
Outcomes
- Faster synthesis
- Clearer content
- Improved portfolio and workflow efficiency
Impact
More strategic use of AI as a design partner, not a replacement
Context
Before Figma’s 2025 suite (Make, Buzz, Sites, etc.), I built case studies in Figma as static slide-deck style designs. These were interactive via custom components like up/down arrows, but ultimately exported as large PDFs.
As I sought to stand out in future applications, I wanted a dynamic web-first portfolio, reflecting both my design work and my evolving workflow. This project became a testbed for AI integration in UX design, exploring how emerging tools could accelerate ideation, content creation, and visualisation.
Problem
Traditional portfolio methods (PDFs, slide decks) were:
- Hard to update and scale
- Non-interactive for users
- Limited in reflecting iterative design thinking
At the same time, early AI tools introduced opportunities to:
- Draft structured, professional content quickly
- Generate visual inspiration for layouts and components
- Summarise and translate complex project details for varied audiences
The question was
How can I used AI to enhance UX design decisions, and not replace them?
My Role
As a personal project, I wore different hats:
- UX/UI Design veteran: Designing portfolio layout, interaction and visual hierarchy
- AI Workflow Strategist: Integrating AI tools like ChatGPT, Figma Make, and Lovable into research, content creation, and visual ideation
- Prompt Engineer: Crafting precise instructions to ensure consistent, usable outputs across multiple tools
Process
Content Strategy with AI
- Identified audience needs: some viewers want deep dives, others need a quick overview
- Used ChatGPT to summarise case studies into TL;DR snapshots at the top of each page
- AI helped flesh out personas, archetypes, competitor analyses, and content drafts for case studies
Visual Ideation and Design Assistance
- Explored Figma Make and Lovable for generating component variations and layout options
- Treated AI-generated visuals as inspiration, iterating manually for cohesion and accessibility
- Learned to refine prompts for consistency in typography, spacing, and interactive elements
Technical Workflow Optimization
- Used Figma Sites for the portfolio build, leveraging universal breakpoint adjustments
- Integrated AI content and design outputs while maintaining control over navigation, hierarchy, and interactivity
- Overcame “one-prompt-away” volatility by iteratively testing AI outputs and documenting best practices
Progressive Disclosure
- Implemented multi-level content presentation: detailed case studies for in-depth readers and concise TL;DR snapshots for quick scannability
- Ensured the UX of the portfolio itself reflected user-centered principles, optimizing readability and flow
Impact in Action
Case study content was dense and full of technical jargon. AI suggested clear, structured summaries that highlighted key project outcomes without losing nuance.
- Problem: recruiters or hiring managers might skip long and dense content
- Solution: TL;DR snapshots for each case study, generated with AI and refined manually
- Impact: Portfolio became both comprehensive and scannable, improving the user experience for all types of visitors
Outcomes
- Delivered a fully functional, interactive portfolio on Figma
- Developed a repeatable AI-assisted workflow for ideation, content refinement, and visual inspiration
- Incorporated TL;DR summaries for better information architecture and user experience
- Strengthened prompt engineering and AI curation skills, now part of a modern UX toolkit
Reflections
This project highlighted the importance of flexible, inclusive design, especially when your user base ranges from digital newcomers to confident returners. Providing guidance shouldn’t come at the cost of speed or autonomy. Giving users control over the interface allowed us to preserve accessibility for those who need it while streamlining the experience for others.
It also reinforced the value of testing even small interface elements. What seemed like a simple block of text was a point of tension for users. Prototyping and testing helped us see that micro-interactions can significantly affect comfort, clarity and trust.
Let’s connect and work together!
Back to Portfolio
Using AI in UX
Read time: 5 minutes
Project date: 2025 - 2026
Using AI to think better, not just work faster
Explored how AI can support research synthesis, content clarity, ideation, and portfolio design while maintaining UX judgment, consistency, and human-centred decision-making.
Workflows
AI
Strategy
TL;DR...a quick snapshot of the project!
Project
Exploring interaction patterns to make hero content optional while retaining value for new or less tech-confident users.
Goal
Improve speed, clarity, and decision-making without losing UX judgment
My Role
UX Designer experimenting with AI-assisted research, content, and ideation
Challenges
- Maintaining consistency
- Avoiding over-automation
- Prompt discipline
Outcomes
- Faster synthesis
- Clearer content
- Improved portfolio and workflow efficiency
Impact
More strategic use of AI as a design partner, not a replacement
Context
Before Figma’s 2025 suite (Make, Buzz, Sites, etc.), I built case studies in Figma as static slide-deck style designs. These were interactive via custom components like up/down arrows, but ultimately exported as large PDFs.
As I sought to stand out in future applications, I wanted a dynamic web-first portfolio, reflecting both my design work and my evolving workflow. This project became a testbed for AI integration in UX design, exploring how emerging tools could accelerate ideation, content creation, and visualisation.
Problem
Traditional portfolio methods (PDFs, slide decks) were:
- Hard to update and scale
- Non-interactive for users
- Limited in reflecting iterative design thinking
At the same time, early AI tools introduced opportunities to:
- Draft structured, professional content quickly
- Generate visual inspiration for layouts and components
- Summarise and translate complex project details for varied audiences
The question was
How can I used AI to enhance UX design decisions, and not replace them?
My Role
As a personal project, I wore different hats:
- UX/UI Design veteran: Designing portfolio layout, interaction and visual hierarchy
- AI Workflow Strategist: Integrating AI tools like ChatGPT, Figma Make, and Lovable into research, content creation, and visual ideation
- Prompt Engineer: Crafting precise instructions to ensure consistent, usable outputs across multiple tools
Process
Content Strategy with AI
- Identified audience needs: some viewers want deep dives, others need a quick overview
- Used ChatGPT to summarise case studies into TL;DR snapshots at the top of each page
- AI helped flesh out personas, archetypes, competitor analyses, and content drafts for case studies
Visual Ideation and Design Assistance
- Explored Figma Make and Lovable for generating component variations and layout options
- Treated AI-generated visuals as inspiration, iterating manually for cohesion and accessibility
- Learned to refine prompts for consistency in typography, spacing, and interactive elements
Technical Workflow Optimization
- Used Figma Sites for the portfolio build, leveraging universal breakpoint adjustments
- Integrated AI content and design outputs while maintaining control over navigation, hierarchy, and interactivity
- Overcame “one-prompt-away” volatility by iteratively testing AI outputs and documenting best practices
Progressive Disclosure
- Implemented multi-level content presentation: detailed case studies for in-depth readers and concise TL;DR snapshots for quick scannability
- Ensured the UX of the portfolio itself reflected user-centered principles, optimizing readability and flow
Impact in Action
Case study content was dense and full of technical jargon. AI suggested clear, structured summaries that highlighted key project outcomes without losing nuance.
- Problem: recruiters or hiring managers might skip long and dense content
- Solution: TL;DR snapshots for each case study, generated with AI and refined manually
- Impact: Portfolio became both comprehensive and scannable, improving the user experience for all types of visitors
Outcomes
- Delivered a fully functional, interactive portfolio on Figma
- Developed a repeatable AI-assisted workflow for ideation, content refinement, and visual inspiration
- Incorporated TL;DR summaries for better information architecture and user experience
- Strengthened prompt engineering and AI curation skills, now part of a modern UX toolkit
Reflections
This project highlighted the importance of flexible, inclusive design, especially when your user base ranges from digital newcomers to confident returners. Providing guidance shouldn’t come at the cost of speed or autonomy. Giving users control over the interface allowed us to preserve accessibility for those who need it while streamlining the experience for others.
It also reinforced the value of testing even small interface elements. What seemed like a simple block of text was a point of tension for users. Prototyping and testing helped us see that micro-interactions can significantly affect comfort, clarity and trust.
Let’s connect and work together!
Back to Portfolio
Using AI in UX
Read time: 5 minutes
Project date: 2025 - 2026
Using AI to think better, not just work faster
Explored how AI can support research synthesis, content clarity, ideation, and portfolio design while maintaining UX judgment, consistency, and human-centred decision-making.
Workflows
AI
Strategy
TL;DR...a quick snapshot of the project!
Project
Integrating AI into day-to-day UX practice
Goal
Improve speed, clarity, and decision-making without losing UX judgment
My Role
UX Designer experimenting with AI-assisted research, content, and ideation
Challenges
- Maintaining consistency
- Avoiding over-automation
- Prompt discipline
Outcomes
- Faster synthesis
- Clearer content
- Improved portfolio and workflow efficiency
Impact
More strategic use of AI as a design partner, not a replacement
Context
Before Figma’s 2025 suite (Make, Buzz, Sites, etc.), I built case studies in Figma as static slide-deck style designs. These were interactive via custom components like up/down arrows, but ultimately exported as large PDFs.
As I sought to stand out in future applications, I wanted a dynamic web-first portfolio, reflecting both my design work and my evolving workflow. This project became a testbed for AI integration in UX design, exploring how emerging tools could accelerate ideation, content creation, and visualisation.
Problem
Traditional portfolio methods (PDFs, slide decks) were:
- Hard to update and scale
- Non-interactive for users
- Limited in reflecting iterative design thinking
At the same time, early AI tools introduced opportunities to:
- Draft structured, professional content quickly
- Generate visual inspiration for layouts and components
- Summarise and translate complex project details for varied audiences
The question was
How can I used AI to enhance UX design decisions, and not replace them?
My Role
As a personal project, I wore different hats:
- UX/UI Design veteran: Designing portfolio layout, interaction and visual hierarchy
- AI Workflow Strategist: Integrating AI tools like ChatGPT, Figma Make, and Lovable into research, content creation, and visual ideation
- Prompt Engineer: Crafting precise instructions to ensure consistent, usable outputs across multiple tools
Process
Content Strategy with AI
- Identified audience needs: some viewers want deep dives, others need a quick overview
- Used ChatGPT to summarise case studies into TL;DR snapshots at the top of each page
- AI helped flesh out personas, archetypes, competitor analyses, and content drafts for case studies
Visual Ideation and Design Assistance
- Explored Figma Make and Lovable for generating component variations and layout options
- Treated AI-generated visuals as inspiration, iterating manually for cohesion and accessibility
- Learned to refine prompts for consistency in typography, spacing, and interactive elements
Technical Workflow Optimization
- Used Figma Sites for the portfolio build, leveraging universal breakpoint adjustments
- Integrated AI content and design outputs while maintaining control over navigation, hierarchy, and interactivity
- Overcame “one-prompt-away” volatility by iteratively testing AI outputs and documenting best practices
Progressive Disclosure
- Implemented multi-level content presentation: detailed case studies for in-depth readers and concise TL;DR snapshots for quick scannability
- Ensured the UX of the portfolio itself reflected user-centered principles, optimizing readability and flow
Impact in Action
Case study content was dense and full of technical jargon. AI suggested clear, structured summaries that highlighted key project outcomes without losing nuance.
- Problem: recruiters or hiring managers might skip long and dense content
- Solution: TL;DR snapshots for each case study, generated with AI and refined manually
- Impact: Portfolio became both comprehensive and scannable, improving the user experience for all types of visitors
Outcomes
- Delivered a fully functional, interactive portfolio on Figma
- Developed a repeatable AI-assisted workflow for ideation, content refinement, and visual inspiration
- Incorporated TL;DR summaries for better information architecture and user experience
- Strengthened prompt engineering and AI curation skills, now part of a modern UX toolkit
Reflections
This project highlighted the importance of flexible, inclusive design, especially when your user base ranges from digital newcomers to confident returners. Providing guidance shouldn’t come at the cost of speed or autonomy. Giving users control over the interface allowed us to preserve accessibility for those who need it while streamlining the experience for others.
It also reinforced the value of testing even small interface elements. What seemed like a simple block of text was a point of tension for users. Prototyping and testing helped us see that micro-interactions can significantly affect comfort, clarity and trust.
Let’s connect and work together!