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Course contents

  • Getting Started with AI for VLSI Engineers5
  • Just Enough AI: Models and Context15
  • Prompting13
  • Trust and Verification14
  • Using AI for Engineering Work17
  • Engineering Walkthroughs7
  • Practical Foundations for AI Workflows4
  • Engineering Data5
  • Retrieval-Augmented Generation6
  • Agents and Tool Use18
  • Agent Design8
  • MCP and Skills6
  • Multi-Agent Design6
  • Practical Capstone6
  • Tokens, Cost and Latency12
  • Agentic Workflows for Chip Teams18
  • Interview and Judgment10
    • AI Interview Questions
      • Tokens and Context Questions
      • Cost Estimation Questions
      • Prompting Questions
      • Verification Questions
      • Agent Questions
      • Guardrails and Judgment Questions
    • Design Scenarios with Numbers
  • AI Skills: Full Course Index
  • Working with AI Glossary
  • Working with AI Cheatsheet
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‹AI Interview Questions
  1. Topics
  2. AI Skills for VLSI Engineers
  3. Interview and Judgment
  4. AI Interview Questions
  5. Guardrails and Judgment Questions

Reference: Interview and Judgment · Beginner to Intermediate

Guardrails and Judgment Questions

Set permissions, place human approval, and judge uncertain output.

On this page

    Question 1: what may it touch

    Tests least-privilege thinking for tool access. Strong answers list allowed actions and deny the rest by default.

    Give the agent only the tools the task needs, with the narrowest scope. Anything unlisted is denied, since an open default fails at the worst moment.

    example.py
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    ALLOW = {"read_log": True, "run_lint": True}
    
    
    def decide(action):
        # fail closed: anything not listed is denied
        return ALLOW.get(action, False)
    
    
    bad = []
    if decide("read_log") is not True:
        bad.append("read_log should be allowed")
    if decide("run_lint") is not True:
        bad.append("run_lint should be allowed")
    if decide("push_to_main") is not False:
        bad.append("unlisted push should be denied")
    if decide("read_secrets") is not False:
        bad.append("secrets should be denied")
    if bad:
        print("FAIL: " + "; ".join(bad))
        raise SystemExit(1)
    print("PASS: listed reads allowed, push and secrets denied")

    The gate above is a plain allow-list, not a real permission system. It proves fail-closed behavior, including for the unlisted push it never names as allowed.

    Question 2: where does the human sit

    Tests approval placement for risky actions. Strong answers approve before the irreversible step, not after.

    Require explicit approval for external, irreversible, or wide-blast-radius actions. Show the approver the exact diff or command, never a summary alone.

    Agent acts alone

    Human approves first

    Why

    Read logs and search code

    Push, merge, or deploy

    Reads reverse cleanly; pushes do not.

    Draft a fix

    Delete data or rotate keys

    Drafts are cheap; deletion is not.

    Summarize results

    Send mail or file tickets

    Sending speaks for the team.

    Question 3: deciding under uncertainty

    Tests expected-loss thinking before acting. Strong answers compare the review cost against the risk removed.

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    EXAMPLE parameters (not real amounts): a bad push costs 40 units, its chance is 0.05
    expected loss = 40 x 0.05 = 2.0 units
    human review costs 0.5 units and blocks the push
    0.5 < 2.0, so review is cheaper than the risk it removes

    When the output cannot be trusted, say so and show the check. A guarded no beats an unguarded maybe.

    Common mistakes

    Common pitfall

    An allow-list that nobody reviews rots into an allow-all. Revisit permissions when the task changes, and log every denied action for the next review.

    Interview

    Likely follow-ups: defend the boundary.

    • Which tool would you remove first, and what breaks without it.

    • What exactly does the approver see before saying yes.

    • When would you refuse to run the agent at all.

    Check yourself The agent requests an unlisted publish action mid-run. Allow or deny?

    Deny. Unlisted actions are denied by default; the human adds the tool only after reviewing the need.

    Check yourself Review costs 0.5 units and the expected loss is 2.0 units. Is review worth it?

    Yes: 0.5 is less than 2.0. The review is cheaper than the risk it removes at these example parameters.

    Related topics

    • Agent questions

    • Guardrails

    • Multi-agent patterns and when not to use agents

    • Evaluating AI tools for your team

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    See also

    • Tokens and Context Questions
    • Cost Estimation Questions
    • Prompting Questions