Debug With Error Receipts

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-vibecoder-debug-with-error-receipts

1. What is the main idea of "Debug With Error Receipts"?

   1. Do not tell the AI 'it broke.' Bring receipts: URL, action, expected result, actual result, console error, network.
   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 "Debug With Error Receipts"?

   1. console
   2. debugging
   3. network tab
   4. reproduction

3. Which use of AI fits this topic best?

   1. Let the AI decide what matters without your review
   2. Use the answer before checking whether it fits the situation
   3. Name the job before naming the tool.
   4. Treat the AI output as automatically correct

4. What should a careful learner remember about "Community signal"?

   1. Use "Community signal" as a reminder to verify the AI output before anyone relies on it.
   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

5. 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

6. 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

7. Name one way to verify an AI answer about debugging.

8. Which action would help you apply "Debug With Error Receipts" responsibly?

   1. Use the tool to avoid thinking through the tradeoff
   2. Keep going even if the output conflicts with a trusted source
   3. Treat the AI output as automatically correct
   4. Write the smallest useful scope the agent can finish.