Agentic AI: Build Evals That Catch Loop and Tool-Misuse Failures

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-agentic-evals-for-agent-loops-r8a1-creators

1. What is the main idea of "Agentic AI: Build Evals That Catch Loop and Tool-Misuse Failures"?

   1. Standard answer-quality evals miss agent-specific bugs; design evals that score loops, wasted tools, and abandoned subgoals.
   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 "Agentic AI: Build Evals That Catch Loop and Tool-Misuse Failures"?

   1. tool efficiency
   2. trajectory eval
   3. subgoal completion
   4. LLM-as-judge

3. Which use of AI fits this topic best?

   1. Replace user-perceived quality measurement
   2. Let the AI decide what matters without your review
   3. Score tool-call efficiency and redundancy
   4. Use the answer before checking whether it fits the situation

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

   1. Score tool-call efficiency and redundancy
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Replace user-perceived quality measurement

5. What should a careful learner remember about "Prompt: design trajectory eval"?

   1. Use AI to draft or organize ideas about trajectory eval, 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 trajectory eval 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 trajectory eval.

9. Which action would help you apply "Agentic AI: Build Evals That Catch Loop and Tool-Misuse Failures" responsibly?

   1. Detect issues your rubric does not name
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Detect loops and dead-end retries

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

    1. Detect issues your rubric does not name
    2. Score tool-call efficiency and redundancy
    3. Ask for a plain-language explanation of tool efficiency
    4. Compare the answer with a trusted source