- A
Receive network intent
This is the first step because the agentic AI system must first understand the high-level goal or policy from the user before any actions can be taken.
- B
Decompose intent into sub-tasks
Why wrong: This is incorrect because decomposition occurs after receiving the intent, not before. The system must first understand the intent before breaking it down.
- C
Call tools to execute sub-tasks
Why wrong: This is incorrect because tool invocation happens after decomposition, not before. The system must have sub-tasks defined before it can call tools to execute them.
- D
Validate output and apply closed-loop remediation
Why wrong: This is incorrect because validation and remediation are the final steps, occurring after tool execution. Placing them earlier would skip the execution phase.
Quick Answer
The correct order is: Receive network intent, decompose into sub-tasks, call tools, validate output, and apply closed-loop remediation. This sequence is essential because an agentic AI system workflow must first capture the high-level goal—such as a network intent to optimize a routing path—before it can logically break that goal into smaller, executable sub-tasks. Only after decomposition can the system invoke specific tools (e.g., APIs or CLI commands) to gather data or make changes, then validate the results against the original intent, and finally trigger automated remediation if the output deviates from expectations. On the CCNA 200-301 v2 exam, this drag-and-drop question tests your understanding of closed-loop automation principles, a key concept in network programmability and AI operations. A common trap is placing "validate output" before "call tools," but remember: you cannot check results until tools have been used. A helpful memory tip is the acronym R-D-C-V-R: Receive, Decompose, Call, Validate, Remediate—think of it as "Robots Don’t Care, Very Reliable."
CCNA AI and Network Operations Practice Question
This 200-301 practice question tests your understanding of ai and network operations. 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.
Drag and drop the following steps into the correct order for an agentic AI system that receives a network intent, decomposes it into sub-tasks, calls tools, validates output, and applies 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 network intent
The agentic AI system starts by understanding the intent, then splits it into manageable tasks, invokes tools, checks the outcome, and corrects any issues automatically.
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 network intent
Why this is correct
This is the first step because the agentic AI system must first understand the high-level goal or policy from the user before any actions can be taken.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decompose intent into sub-tasks
Why it's wrong here
This is incorrect because decomposition occurs after receiving the intent, not before. The system must first understand the intent before breaking it down.
- ✗
Call tools to execute sub-tasks
Why it's wrong here
This is incorrect because tool invocation happens after decomposition, not before. The system must have sub-tasks defined before it can call tools to execute them.
- ✗
Validate output and apply closed-loop remediation
Why it's wrong here
This is incorrect because validation and remediation are the final steps, occurring after tool execution. Placing them earlier would skip the execution phase.
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.
✓Receive network intentCorrect answer▾
Why this is correct
This is the first step because the agentic AI system must first understand the high-level goal or policy from the user before any actions can be taken.
✗Decompose intent into sub-tasksWrong answer — click to see why▾
Why this is wrong here
The specific factual error is that decomposition cannot happen without first having the intent; the order is reversed.
Why candidates choose this
Candidates might think that breaking down tasks is the first logical step, but they overlook the prerequisite of receiving the intent.
✗Call tools to execute sub-tasksWrong answer — click to see why▾
Why this is wrong here
The specific factual error is that tools are called only after the intent is decomposed into actionable sub-tasks.
Why candidates choose this
Candidates may confuse the order of execution, thinking that tools are called immediately after receiving intent, skipping the decomposition step.
✗Validate output and apply closed-loop remediationWrong answer — click to see why▾
Why this is wrong here
The specific factual error is that closed-loop remediation requires output from tool execution to validate and correct; it cannot occur before tools are called.
Why candidates choose this
Candidates might think that validation should happen early to catch errors, but in an agentic workflow, validation follows execution to ensure the changes were applied correctly.
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.
- →
AI and Network Operations — study guide chapter
Learn the concepts, then practise the questions
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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 network intent — The agentic AI system starts by understanding the intent, then splits it into manageable tasks, invokes tools, checks the outcome, and corrects any issues automatically.
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
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