An insurance provider creates an AI escalation assistant powered by Claude. The assistant can:
* ret

Q: What is the correct answer for Claude CCA-F Claude CCA-F?

The correct answer is B. Option B is the BEST architectural improvement for this scenario. The problem described—Claude repeatedly making the same tool request without new information—is a common issue in agentic systems without proper orchestration. Implementing loop state tracking and stopping conditions, such as detecting redundant tool requests or unchanged outputs, is crucial for preventing infinite loops, ensuring e

Q: An insurance provider creates an AI escalation assistant powered by Claude. The assistant can: * retrieve policy details, * search prior claims, * check fraud indicators, * and generate escalation…

The correct answer is B. Option B is the BEST architectural improvement for this scenario. The problem described—Claude repeatedly making the same tool request without new information—is a common issue in agentic systems without proper orchestration. Implementing loop state tracking and stopping conditions, such as detecting redundant tool requests or unchanged outputs, is crucial for preventing infinite loops, ensuring e

Q: What are the options for this Claude CCA-F Claude CCA-F question?

A. Remove all retry behavior from the workflow to prevent repeated actions. · B. Implement loop state tracking and stopping conditions that detect redundant tool requests or unchanged outputs. · C. Increase token limits so Claude can remember earlier reasoning steps more effectively. · D. Require human approval after every tool invocation.

Question

An insurance provider creates an AI escalation assistant powered by Claude. The assistant can:
* retrieve policy details,
* search prior claims,
* check fraud indicators,
* and generate escalation summaries.

Developers notice the assistant occasionally repeats the same fraud-check tool request multiple times even when no new information is returned.

What is the BEST architectural improvement?

FirstInTest · Accepted Answer

Option B is the BEST architectural improvement for this scenario. The problem described—Claude repeatedly making the same tool request without new information—is a common issue in agentic systems without proper orchestration. Implementing loop state tracking and stopping conditions, such as detecting redundant tool requests or unchanged outputs, is crucial for preventing infinite loops, ensuring efficiency, and maintaining control in an enterprise context. This directly relates to the CCA-F principle of robust agent orchestration and safeguards. Option A (removing all retry behavior) is too drastic; some retries might be necessary for transient errors. Option C (increasing token limits) addresses context length but doesn't directly solve the issue of repetitive, unproductive actions; the model might still re-request the same tool even with a longer context. Option D (requiring human approval after every tool invocation) would severely limit autonomy and introduce significant latency, negating the benefits of an AI assistant for automation.

Answer

Remove all retry behavior from the workflow to prevent repeated actions.

Answer

Implement loop state tracking and stopping conditions that detect redundant tool requests or unchanged outputs.

Answer

Increase token limits so Claude can remember earlier reasoning steps more effectively.

Answer

Require human approval after every tool invocation.

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