Question 1

Why would you choose the Argument input method for an activity field?

Options :

A : Applies one constant value you enter during design every time the agent executes the activity.

B : Receives a runtime value from an agent input argument defined earlier in the workflow.

C : Lets the agent infer the field value at runtime using the Description and its reasoning.

D : Prompts a person to supply the value each time the field is evaluated at runtime.

Answer: B

Question 2

Which of the following best describes how agents handle dynamic environments?

Options :

A : Agents fail to execute tasks when information or processes change.

B : Agents adapt to changing conditions by learning.

C : Agents rely solely on static rules without contextual learning.

D : Agents require complete human assistance whenever processes change.

Answer: B

Question 3

Which of the following is an essential aspect of crafting a comprehensive agent story during the validation stage?

Options :

A : Brainstorming automation use cases without validating personas or critically evaluating existing processes, focusing purely on agent capabilities.

B : Understanding the daily pain points and inefficiencies of the selected role to identify tasks that consume unnecessary time and potential gains from agent intervention.

C : Starting immediately with agent behavior prototyping using tools like the Agents designer canvas in Studio Web without assessing mapped automations or impacted systems.

D : Generalizing automation opportunities across all processes and roles without tailoring solutions based on specific personas or organizational contexts.

Answer: B

Question 4

Which configuration area defines what the agent should do after a human resolves the escalation?

Options :

A : Assignment recipient list

B : Agent Memory toggle

C : Inputs description fields

D : Outcome behavior section

Answer: D

Question 5

An agent is being designed to generate step-by-step troubleshooting guides for software issues. Testing shows that the guides lack clarity and include redundant steps, confusing users. What is the best refinement for the prompt?

Options :

A : Add generic examples to allow the agent to experiment with the step format.

B : Enable the agent to generate longer troubleshooting guides for completeness.

C : Provide clear instructions to make steps actionable, concise, and free of redundancies.

D : Avoid explaining each step in detail to simplify the prompt.

Answer: C

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