Progressive Trust Models for Newly Deployed Agents

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-agentic-agent-progressive-trust-model-creators

1. What is the main idea of "Progressive Trust Models for Newly Deployed Agents"?

   1. Grant agents broader permissions only as they earn trust through measured outcomes.
   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 "Progressive Trust Models for Newly Deployed Agents"?

   1. permission expansion
   2. progressive trust
   3. outcome metrics
   4. graduated rollout

3. Which use of AI fits this topic best?

   1. Skip trust tiers because the agent 'feels' competent.
   2. Let the AI decide what matters without your review
   3. Define trust tiers with explicit permissions per tier.
   4. Use the answer before checking whether it fits the situation

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

   1. Define trust tiers with explicit permissions per tier.
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Skip trust tiers because the agent 'feels' competent.

5. What should a careful learner remember about "Trust tier definition"?

   1. Define 4 trust tiers for agent <A>: tier name, permissions, promotion criteria, demotion triggers, review cadence.
   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 progressive trust 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 progressive trust.

9. Which action would help you apply "Progressive Trust Models for Newly Deployed Agents" responsibly?

   1. Measure trust without honest outcome labeling.
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Promote based on measured success rate and human-override rate.

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

    1. Measure trust without honest outcome labeling.
    2. Define trust tiers with explicit permissions per tier.
    3. Ask for a plain-language explanation of permission expansion
    4. Compare the answer with a trusted source