AI coding: refactor safely by stating invariants

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ai-coding-refactor-with-invariants-r7a1-creators

1. What is the main idea of "AI coding: refactor safely by stating invariants"?

   1. Tell the AI what must stay true after the refactor — call signature, side effects, performance bounds — and it stops introducing surprises.
   2. Use AI as the final authority for the whole decision
   3. Avoid checking the answer once it sounds polished
   4. Focus only on speed instead of judgment

2. Which concept is most central to "AI coding: refactor safely by stating invariants"?

   1. invariants
   2. refactoring
   3. behavior preservation
   4. unrelated shortcut

3. Which use of AI fits this topic best?

   1. Guarantee semantic equivalence across complex side effects
   2. Let the AI decide what matters without your review
   3. Preserve a documented public API while restructuring internals
   4. Use the answer before checking whether it fits the situation

4. Which limitation should you watch for in this topic?

   1. Preserve a documented public API while restructuring internals
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Guarantee semantic equivalence across complex side effects

5. What should a careful learner remember about "Try this prompt"?

   1. Use AI to draft or organize ideas about refactoring, then verify before acting.
   2. Skip the context so the tool can guess faster
   3. Treat the output as private even after sharing it online
   4. Use the answer without checking the source

6. You want to use AI after this lesson. What is the safest next step?

   1. Act immediately because the AI answer is written clearly
   2. Use AI for drafting and comparison, but verify before publishing or relying on it.
   3. Hide uncertainty so the final answer looks cleaner
   4. Use private or sensitive details before checking permission

7. How should AI output about refactoring be treated?

   1. As proof that no other source is needed
   2. As a replacement for context, consent, or expert review
   3. As a draft or helper output that still needs human judgment and verification
   4. As something that becomes correct when it sounds confident

8. Name one way to verify an AI answer about refactoring.

9. Which action would help you apply "AI coding: refactor safely by stating invariants" responsibly?

   1. Detect performance regressions without benchmarks
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Apply a named pattern (extract method, strategy) consistently

10. Which choice is a bad use of AI for this lesson?

    1. Detect performance regressions without benchmarks
    2. Preserve a documented public API while restructuring internals
    3. Ask for a plain-language explanation of invariants
    4. Compare the answer with a trusted source