AI coding: debugging from a stack trace without guessing

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ai-coding-debug-from-stack-trace-r7a1-creators

1. What is the main idea of "AI coding: debugging from a stack trace without guessing"?

   1. Paste the trace, the failing input, and the relevant function. Ask for a hypothesis tree — not a fix — until one branch is confirmed.
   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: debugging from a stack trace without guessing"?

   1. hypothesis-driven
   2. debugging
   3. stack traces
   4. unrelated shortcut

3. Which use of AI fits this topic best?

   1. Know your runtime state without you describing it
   2. Let the AI decide what matters without your review
   3. Map a stack trace to suspect lines and call paths
   4. Use the answer before checking whether it fits the situation

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

   1. Map a stack trace to suspect lines and call paths
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Know your runtime state without you describing it

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

   1. Use AI to draft or organize ideas about debugging, 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 debugging 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 debugging.

9. Which action would help you apply "AI coding: debugging from a stack trace without guessing" responsibly?

   1. Distinguish a symptom from a root cause without verification
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Generate ranked hypotheses with reasoning

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

    1. Distinguish a symptom from a root cause without verification
    2. Map a stack trace to suspect lines and call paths
    3. Ask for a plain-language explanation of hypothesis-driven
    4. Compare the answer with a trusted source