Design Better Podcast: Elizabeth Lin – Rethinking Design Education in the Age of AI

Date: August 26, 2025
Host(s): Eli Woolery, Aaron Walter (The Curiosity Department)
Guest: Elizabeth Lin, Founder of Design as a Party

Episode Overview

In this episode of Design Better, Eli Woolery and Aaron Walter sit down with Elizabeth Lin, a design educator with a computer science background, to discuss the evolving intersection of design education and AI. Elizabeth, founder of the innovative school “Design as a Party,” shares her experiences with AI-powered prototyping tools like Cursor and reflects on the future of design education, debugging as a critical skill, and how learning can be transformed into an engaging, joyful process.

Key Discussion Points & Insights

1. Elizabeth’s Path: From Product Designer to Design Educator

• Background:

  • Elizabeth left her full-time product design role to follow her passion for education, founding Design as a Party (04:13).
  • She leverages her computer science background to help designers bridge the coding gap, especially with new AI tools.

• Teaching with AI:

  • Developed the course “Prototyping with Cursor” after realizing how AI tools could enhance creativity and make technical prototyping accessible.

2. Prototyping with Cursor and AI Tools

• Discovery and Impact:

  • First used Cursor on a whim for side projects—was able to realize creative UI ideas without advanced math or development skills (05:14).
  • “Being able to accomplish something I normally wouldn’t be able to…made me feel like I was building websites in Neopets as a kid.”
    — Elizabeth Lin (05:41)

• Why Cursor?:

  • Preferred Cursor for its familiar editor environment and transparency (“less stuff was hidden behind a black box”) (06:24).
  • High flexibility for creative prompts—AI implemented playful features like animated button hover states, going beyond standard design systems.

3. Lowering Barriers: AI-Driven App Creation

• For Non-Coders:

  • Recommends zero-to-one tools like Claude, v0, and Lovable for generating initial project structure, which can then be further developed in Cursor (07:43).
  • Emphasizes that choice of tool can depend on personal working style.

• Image-to-Code Possibilities:

  • Uploading screenshots to Cursor for UI implementation works well for standard layouts but can be overwhelmed by excess complexity.
  • New developments like MCP (Model Context Protocol) servers now allow Cursor to interpret Figma files more directly, increasing fidelity and context (09:34).

• Explaining MCP:

  • “MCP servers allow these tools to communicate with each other…Figma’s MCP server will allow Cursor to get the code, the Figma file…variables in the frame…a screenshot...”
    — Elizabeth Lin (09:39)

4. AI’s Impact on Design and Development Practice

• Evolving Prototyping:

  • Designers are beginning to build “interactive clickthroughs” directly in AI-augmented environments, making static mockups less relevant (10:46).
  • Teams are establishing “playground” code environments to encourage hands-on prototyping without risk to production codebases.

• Looking Ahead:

  • Projects and feedback cycles will become much faster; iteration will dramatically accelerate, driving a “learn faster” mentality on teams (12:37).

  • Quote:
    “I hope that people build things faster and try new ideas faster…With AI tools, teams can iterate faster, get feedback faster…cycles will all be faster.”
    — Elizabeth Lin (12:37)

5. Learning Challenges for New Designers

• Where Students Get Stuck:

  • Debugging is the single biggest hurdle—not just technical, but grappling with ambiguity and frustration (13:14).

  • Elizabeth now emphasizes resilience and strategic problem-solving in her teaching methods.

  • Quote:
    “Not understanding what’s happening is really frustrating…A lot of what I’ve been trying to help students understand is how to get out of that mindset and keep pushing forward...”
    — Elizabeth Lin (13:44)

6. Prompting, Debugging, and Model Limitations

• Context Management:

  • Discusses the importance of controlling the amount of context you provide to AI agents. Too much can overwhelm and confuse (“like working with a junior engineer”) (14:47).
  • Recommends starting fresh with a new chat when the AI stops making progress.

• Best Prompting Practices:

  • Break complex problems into simple, step-by-step prompts to improve results (15:14–15:39).
  • Be aware of and tolerant to AI “regression” (slipping into previous faulty answers).

• Model Switching & Hallucinations:

  • Advices trying different AI models for wrong or nonsensical results; creativity and analytical strength can vary (16:48).

  • Quote:
    “It’s hard to know when the agent is wrong versus when you’re wrong. And trying to figure that out is definitely something to learn.”
    — Elizabeth Lin (17:20)

7. Creating a Joyful Learning Experience

• Design as a Party:
  • Elizabeth’s business is built on the idea that “learning should feel more like a party than work” (summary from intro, 00:57).
  • Encourages experimentation, creativity, and resilience in both students and professionals.

Notable Quotes & Moments

• On the magic of AI in design:
  “It kind of had that same feeling to me [as] building websites in Neopets as a kid. And so that was really my aha moment.”
  — Elizabeth Lin (05:41)

• On collaboration and new tools:
  “Designers are going to be able to create more interactive prototypes more quickly and maybe their designs won’t always live in static mockups anymore...”
  — Elizabeth Lin (11:17)

• Advice for new learners:
  “Here are some ways you can try to figure out what the actual problem is and then maybe talk to the agent to figure out how to solve the problem. And I think getting in that mindset is really hard...”
  — Elizabeth Lin (13:44)

• The importance of debugging:
  “I think as someone who studied computer science, I didn’t realize how useful that skill is: just getting unstuck in general.”
  — Elizabeth Lin (13:20)

• On model selection and AI limitations:
  “Switching the model is a great strategy...It’s hard to know when the agent is wrong versus when you’re wrong.”
  — Elizabeth Lin (16:52; 17:20)

Timestamps for Important Segments

• Elizabeth’s background and origin story – 04:13
• First experiences with Cursor and AI creativity – 05:14–06:24
• Approaching code as a designer, tool recommendations – 07:43
• The role of MCP servers and Figma integration – 09:34
• How AI is changing prototyping and design workflows – 10:46–12:37
• Biggest student challenge: debugging & ambiguity – 13:14–14:15
• Best practices for prompting and overcoming AI limitations – 14:47–17:20

Tone and Style

The conversation is open, enthusiastic, and accessible, blending technical depth with encouragement, practical tips, and a love of experimentation. Elizabeth’s approach is all about reducing frustration and making learning collaborative and fun—a “party” where anyone can build creative things with AI.

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