- A
receive intent, decompose into sub-tasks, call tools, validate output, apply closed-loop remediation
This is the correct order: the agentic AI system first receives the high-level intent, then decomposes it into sub-tasks, calls the necessary tools (e.g., APIs), validates the output, and finally applies closed-loop remediation if needed.
- B
call tools, receive intent, decompose into sub-tasks, validate output, apply closed-loop remediation
This is incorrect because the system must receive the intent before calling any tools; tools are called only after the intent is decomposed.
- C
receive intent, call tools, decompose into sub-tasks, validate output, apply closed-loop remediation
This is incorrect because decomposition must occur before tool calls; the system needs to break down the intent into specific tasks to know which tools to invoke.
- D
receive intent, decompose into sub-tasks, validate output, call tools, apply closed-loop remediation
This is incorrect because validation occurs after tool calls, not before; the output from tool calls must be validated to ensure correctness.
Quick Answer
The correct order is receive intent, call tools, decompose into sub-tasks, validate output, apply closed-loop remediation. This sequence is correct because the AI-assisted network automation workflow begins by capturing the high-level business or operational intent, then immediately invokes the necessary tools—such as APIs or scripts—to gather data or execute actions, after which the system decomposes the intent into specific sub-tasks based on the tool outputs, validates the resulting configuration against policies, and finally applies closed-loop remediation to automatically correct any deviations. On the CCNA 200-301 v2 exam, this drag-and-drop question tests your understanding of how AI/ML concepts integrate with network automation, and a common trap is placing “decompose into sub-tasks” before “call tools,” but remember that tools must be called first to provide the context needed for meaningful decomposition. A useful memory tip is to think of the acronym I-T-D-V-R: Intent, Tools, Decompose, Validate, Remediate—like a chef receiving a recipe (intent), grabbing utensils (tools), chopping ingredients (decompose), tasting (validate), and adjusting seasoning (remediate).
CCNA AI and Network Operations Practice Question
This 200-301 practice question tests your understanding of ai and network operations. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
Drag and drop the following steps into the correct order to describe the general workflow for AI-assisted network configuration automation: receive intent, decompose into sub-tasks, call tools, validate output, and apply closed-loop remediation.
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
receive intent, decompose into sub-tasks, call tools, validate output, apply closed-loop remediation
The general AI workflow in network automation begins with receiving the high-level intent, then breaking it down into executable sub-tasks, calling the appropriate tools (e.g., APIs or scripts), validating the output to ensure correctness, and finally applying closed-loop remediation to correct any deviations. This order reflects a logical progression from planning to action to verification and correction, which aligns with foundational AI/ML concepts covered in the CCNA.
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.
- ✓
receive intent, decompose into sub-tasks, call tools, validate output, apply closed-loop remediation
Why this is correct
This is the correct order: the agentic AI system first receives the high-level intent, then decomposes it into sub-tasks, calls the necessary tools (e.g., APIs), validates the output, and finally applies closed-loop remediation if needed.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
call tools, receive intent, decompose into sub-tasks, validate output, apply closed-loop remediation
Why this is correct
This is incorrect because the system must receive the intent before calling any tools; tools are called only after the intent is decomposed.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
receive intent, call tools, decompose into sub-tasks, validate output, apply closed-loop remediation
Why this is correct
This is incorrect because decomposition must occur before tool calls; the system needs to break down the intent into specific tasks to know which tools to invoke.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
receive intent, decompose into sub-tasks, validate output, call tools, apply closed-loop remediation
Why this is correct
This is incorrect because validation occurs after tool calls, not before; the output from tool calls must be validated to ensure correctness.
Related concept
Read the scenario before looking for a memorised answer.
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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AI and Network Operations — study guide chapter
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AI and Network Operations practice questions
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FAQ
Questions learners often ask
What does this 200-301 question test?
AI and Network Operations — This question tests AI and Network Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: receive intent, decompose into sub-tasks, call tools, validate output, apply closed-loop remediation — The general AI workflow in network automation begins with receiving the high-level intent, then breaking it down into executable sub-tasks, calling the appropriate tools (e.g., APIs or scripts), validating the output to ensure correctness, and finally applying closed-loop remediation to correct any deviations. This order reflects a logical progression from planning to action to verification and correction, which aligns with foundational AI/ML concepts covered in the CCNA.
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.
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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Last reviewed: Jun 6, 2026
This 200-301 practice question is part of Courseiva's free Cisco certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 200-301 exam.
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