Debugging With AI: Stack Trace In, Hypothesis Out

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ai-coding-debug-loop-r12a1-creators

1. What is the core idea behind "Debugging With AI: Stack Trace In, Hypothesis Out"?

   1. Turn AI into a structured hypothesis generator for bugs.
   2. Proprietary competitor code — your agent's training data or logs may leak
   3. Know which options your team actually relies on.
   4. Netlify: similar, free tier is generous.

2. Which term best describes a foundational idea in "Debugging With AI: Stack Trace In, Hypothesis Out"?

   1. hypothesis
   2. stack-trace
   3. reproduction
   4. Proprietary competitor code — your agent's training data or logs may leak

3. A learner studying Debugging With AI: Stack Trace In, Hypothesis Out would need to understand which concept?

   1. stack-trace
   2. reproduction
   3. hypothesis
   4. Proprietary competitor code — your agent's training data or logs may leak

4. Which of these is directly relevant to Debugging With AI: Stack Trace In, Hypothesis Out?

   1. stack-trace
   2. hypothesis
   3. Proprietary competitor code — your agent's training data or logs may leak
   4. reproduction

5. Which of the following is a key point about Debugging With AI: Stack Trace In, Hypothesis Out?

   1. Rank likely causes of an error from a stack trace and code.
   2. Suggest the smallest reproduction script for a reported bug.
   3. Proprietary competitor code — your agent's training data or logs may leak
   4. Know which options your team actually relies on.

6. What is one important takeaway from studying Debugging With AI: Stack Trace In, Hypothesis Out?

   1. Know about state in your database, queues, or environment.
   2. Reproduce a bug it cannot run.
   3. Proprietary competitor code — your agent's training data or logs may leak
   4. Know which options your team actually relies on.

7. What is the key insight about "Ranked-causes prompt" in the context of Debugging With AI: Stack Trace In, Hypothesis Out?

   1. Proprietary competitor code — your agent's training data or logs may leak
   2. Know which options your team actually relies on.
   3. Send: trace + the function + 'List the top 5 likely causes ranked by probability.
   4. Netlify: similar, free tier is generous.

8. What is the key insight about "Do not apply fix #1 blindly" in the context of Debugging With AI: Stack Trace In, Hypothesis Out?

   1. Proprietary competitor code — your agent's training data or logs may leak
   2. Know which options your team actually relies on.
   3. Netlify: similar, free tier is generous.
   4. The first hypothesis is rarely correct. Run the diagnostic steps to confirm before patching.

9. Which statement accurately describes an aspect of Debugging With AI: Stack Trace In, Hypothesis Out?

   1. AI is strongest as a hypothesis machine: feed it the trace plus relevant code and ask for ranked causes, not a single fix.
   2. Proprietary competitor code — your agent's training data or logs may leak
   3. Know which options your team actually relies on.
   4. Netlify: similar, free tier is generous.

10. Which best describes the scope of "Debugging With AI: Stack Trace In, Hypothesis Out"?

    1. It is unrelated to ai-coding workflows
    2. It focuses on Turn AI into a structured hypothesis generator for bugs.
    3. It applies only to the opposite beginner tier
    4. It was deprecated in 2024 and no longer relevant

11. Which section heading best belongs in a lesson about Debugging With AI: Stack Trace In, Hypothesis Out?

    1. Proprietary competitor code — your agent's training data or logs may leak
    2. Know which options your team actually relies on.
    3. What AI does well here
    4. Netlify: similar, free tier is generous.

12. Which section heading best belongs in a lesson about Debugging With AI: Stack Trace In, Hypothesis Out?

    1. Proprietary competitor code — your agent's training data or logs may leak
    2. Know which options your team actually relies on.
    3. Netlify: similar, free tier is generous.
    4. What AI cannot do

13. Which of the following is a concept covered in Debugging With AI: Stack Trace In, Hypothesis Out?

    1. stack-trace
    2. hypothesis
    3. reproduction
    4. Proprietary competitor code — your agent's training data or logs may leak

14. Which of the following is a concept covered in Debugging With AI: Stack Trace In, Hypothesis Out?

    1. stack-trace
    2. hypothesis
    3. reproduction
    4. Proprietary competitor code — your agent's training data or logs may leak

15. Which of the following is a concept covered in Debugging With AI: Stack Trace In, Hypothesis Out?

    1. stack-trace
    2. hypothesis
    3. reproduction
    4. Proprietary competitor code — your agent's training data or logs may leak