Extract Design Tokens Before Screens Multiply

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-claude-design-tokens-creators

1. What is the primary purpose of extracting design tokens before generating multiple screens with AI?

   1. To make the AI run faster on older computers
   2. To give the AI a reason to be creative and experiment
   3. To reduce the amount of code the AI needs to write
   4. To ensure all screens maintain consistent visual language

2. Which of the following is NOT typically classified as a design token?

   1. Color palette codes
   2. Border radius values
   3. Component library documentation
   4. Font size scale

3. A developer tells an AI agent to 'build an e-commerce app' without breaking the work into smaller pieces. What problem does this create?

   1. The AI will automatically add payment processing
   2. The project will be completed in a single file
   3. The AI may produce inconsistent UI because it has no incremental checkpoints
   4. The AI will refuse to work on such a large project

4. What does it mean to 'run the result as a user, not as a fan of the tool'?

   1. Only share results that make the tool look impressive
   2. Test the output by actually using it as an end user would, not admiring the technology
   3. Avoid using the tool in front of other people
   4. Use the tool as much as possible to show loyalty

5. Before sharing AI-generated code with a team, what three things should you inspect?

   1. The AI's confidence level, token count, and API calls
   2. The color scheme, font choice, and file size
   3. The team members' preferences, company mission, and budget
   4. The diff, data access patterns, and failure path

6. Why do Claude Code users commonly share DESIGN.md files with their teams?

   1. To show off their writing skills
   2. To meet legal requirements for open source projects
   3. To reduce the amount of storage their projects use
   4. To establish durable visual rules that keep work consistent across sessions

7. When developing AI-assisted applications, which question helps identify security concerns?

   1. Which team member likes the design the most?
   2. How much did the AI tool cost to use?
   3. What data should the app or agent never expose?
   4. What is the most popular color scheme in 2024?

8. What is a rollback path and why is it important for AI-generated outputs?

   1. A script that automatically fixes all bugs in AI code
   2. A way to delete the AI tool from your computer if it misbehaves
   3. A predefined way to revert changes if the AI output causes problems
   4. A mechanism to undo any user action in the final app

9. What does it mean for an AI output to be 'observable'?

   1. The output can be watched like a movie
   2. The system provides clear feedback about what it's doing and what state it's in
   3. The code is written in a language with observation capabilities
   4. The AI can see more colors than humans can

10. What makes AI-generated demos different from production-ready outputs?

    1. Production outputs must be observable, reversible, and safe enough for others to use
    2. There is no difference — AI generates production code directly
    3. Demos use more advanced AI models
    4. Demos are always free to use

11. If an AI generates five different products from the same requirements, what is most likely the cause?

    1. No design tokens were established to enforce consistency
    2. The AI was running on slow hardware
    3. The user provided too much detail
    4. The AI was using five different models

12. What question should you ask to verify that AI-generated changes actually work?

    1. Which celebrity would like this design?
    2. What test proves the change works?
    3. How much does the AI love making UI?
    4. Does the code look pretty?

13. What does 'failure path' refer to in AI-assisted development?

    1. What happens and what resources are affected when something goes wrong
    2. The route the AI takes when it fails to generate any code
    3. A type of error message the AI produces
    4. The file path where failed AI attempts are saved

14. Why is it important to review the diff before sharing AI-generated code?

    1. To count how many lines the AI wrote
    2. To see exactly what changed and verify it matches your intentions
    3. To make the code longer before sharing
    4. To check if the AI used your favorite programming language

15. What does 'write the smallest useful scope' help prevent?

    1. The code from becoming too fast
    2. The AI from using too much memory
    3. Inconsistent results from overly broad requests
    4. The developer from working too hard