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Question 612 of 1,052
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CCNA Practice Question: Which THREE of the following best describe how…
This 200-301 practice question tests your understanding of 200-301 exam topics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE of the following best describe how agentic AI is used in network automation, specifically regarding AI agents, tool-calling, and closed-loop remediation workflows?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.
Agentic AI in network automation involves autonomous AI agents that can call external tools (like APIs or CLI commands) to perform tasks and use closed-loop remediation to continuously monitor, detect, and fix network issues without human intervention. The correct answers highlight these core aspects: AI agents making decisions and taking actions, tool-calling for executing network commands, and closed-loop workflows that automatically remediate based on feedback. The distractors are incorrect because they either misrepresent the role of AI agents (e.g., only monitoring without action) or describe non-automated processes (e.g., manual approval or static rule-based actions).
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.
Why this is correct
This is a key feature of agentic AI: agents use reasoning to select and call tools (e.g., show commands, configuration APIs) to gather data or make changes.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AI agents only monitor network traffic and alert humans for any remediation actions.
Why it's wrong here
This describes traditional monitoring, not agentic AI. Agentic AI agents take action themselves, not just alert.
- ✓
Tool-calling in agentic AI allows the agent to execute network commands or scripts to collect data and implement changes.
Why this is correct
Tool-calling is a core mechanism where the AI agent invokes external functions (e.g., netmiko, RESTCONF) to perform network operations.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
A closed-loop remediation workflow continuously monitors network state, detects anomalies, triggers an AI agent to diagnose, and applies corrective actions automatically.
Why this is correct
This defines the closed-loop process: monitor, detect, diagnose, act, and verify, all automated without human in the loop.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Closed-loop remediation always requires a human to approve each corrective action before it is executed.
Why it's wrong here
Closed-loop implies automation without manual approval; human approval would break the loop.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The 200-301 exam frequently reuses these exact scenarios with slightly different constraints.
✓AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.Correct answer▾
Why this is correct
This is a key feature of agentic AI: agents use reasoning to select and call tools (e.g., show commands, configuration APIs) to gather data or make changes.
✗AI agents only monitor network traffic and alert humans for any remediation actions.Wrong answer — click to see why▾
Why this is wrong here
Agentic AI is proactive and autonomous; it does not rely solely on human intervention for remediation.
✗Closed-loop remediation always requires a human to approve each corrective action before it is executed.Wrong answer — click to see why▾
Why this is wrong here
Agentic AI closed-loop workflows are designed to be autonomous; human approval is optional and not required for the loop to function.
Analysis generated from the official 200-301blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 200-301 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which 200-301 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this 200-301 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs. — Agentic AI in network automation involves autonomous AI agents that can call external tools (like APIs or CLI commands) to perform tasks and use closed-loop remediation to continuously monitor, detect, and fix network issues without human intervention. The correct answers highlight these core aspects: AI agents making decisions and taking actions, tool-calling for executing network commands, and closed-loop workflows that automatically remediate based on feedback. The distractors are incorrect because they either misrepresent the role of AI agents (e.g., only monitoring without action) or describe non-automated processes (e.g., manual approval or static rule-based actions).
What should I do if I get this 200-301 question wrong?
Identify which 200-301 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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