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Question 81

Which capability allows an AI agent to work with information from multiple sources?

1. Screen sharing
2. Knowledge grounding
3. File renaming
4. Printer management

Correct Answer: 2

Explanation

Knowledge grounding allows an AI agent to use information from relevant sources when generating responses. These sources can include business documents, databases, applications, or other approved repositories. Grounding is useful when the agent needs organization-specific or frequently changing information. The architect should evaluate source quality, relevance, freshness, permissions, and retrieval methods. Proper access controls are essential so that grounding does not expose information to unauthorized users. Grounding should also be tested to determine whether the agent retrieves the right information for different business scenarios.

Question 82

What is the purpose of an AI agent evaluation dataset?

1. To store passwords
2. To replace business applications
3. To test agent performance against defined scenarios
4. To manage network devices

Correct Answer: 3

Explanation

An evaluation dataset contains representative scenarios, inputs, expected outcomes, or other criteria used to assess an AI agent. It helps architects and developers measure whether the agent performs according to business requirements. Evaluation datasets can be used to test accuracy, relevance, groundedness, safety, and task completion. They should represent realistic user requests and include important edge cases. Maintaining evaluation datasets also allows teams to compare results after changing models, prompts, knowledge sources, or workflows.

Question 83

Which factor should influence model selection?

1. Business requirements
2. Office furniture
3. Keyboard color
4. Screen size

Correct Answer: 1

Explanation

Model selection should be based on the requirements of the business scenario. Architects should consider capabilities, accuracy, latency, cost, context requirements, safety, availability, and integration needs. A more powerful model is not automatically the correct choice if a simpler model can satisfy the requirements. Testing representative workloads provides evidence about model performance. The architect should also consider operational requirements such as scalability and monitoring. Selecting a model based on measurable requirements helps balance quality, performance, and cost.

Question 84

A company wants an AI agent to complete several steps without asking the user after every step. What capability is relevant?

1. Manual processing
2. Autonomous agent behavior
3. Static reporting
4. File compression

Correct Answer: 2

Explanation

Autonomous agent behavior allows an agent to plan or execute multiple steps toward a defined objective with less continuous user intervention. This can be useful for complex workflows where the agent needs to determine intermediate actions. However, autonomy should be introduced carefully because additional independence can increase operational and security risks. Architects should define permissions, action boundaries, approval requirements, monitoring, and escalation paths. The level of autonomy should match the business need rather than being maximized by default.

Question 85

What does an AI agent need before it can safely update a business record?

1. Appropriate authorization
2. A larger monitor
3. More storage space
4. A different keyboard

Correct Answer: 1

Explanation

An AI agent should have appropriate authorization before updating a business record. The architect must determine whether the agent is allowed to perform the operation and whether the requesting user has the necessary rights. Least privilege should be applied so the agent can modify only the required records or fields. Sensitive operations may also require human approval, validation, or additional controls. Auditing should capture important actions so that changes can be investigated when necessary. Authorization should never be assumed simply because an agent can technically access an application.

Question 86

Which approach can improve the consistency of AI responses?

1. Removing instructions
2. Using clear prompts and defined output requirements
3. Allowing random responses
4. Disabling evaluation

Correct Answer: 2

Explanation

Clear prompts and defined output requirements can improve the consistency of AI responses. Instructions can specify the agent’s role, task, context, constraints, and expected response format. Consistency can be further improved through reusable prompt patterns, evaluation datasets, and testing. Architects should remember that prompts alone do not guarantee deterministic behavior, particularly for generative models. Applications should validate important outputs when they are used in automated processes. Continuous evaluation can identify prompt changes that improve or reduce response quality.

Question 87

What is a major benefit of using a multi-agent design?

1. It removes all security requirements
2. It eliminates testing
3. It allows specialized agents to handle different responsibilities
4. It guarantees perfect responses

Correct Answer: 3

Explanation

A multi-agent design allows different agents to specialize in particular responsibilities. For example, one agent can handle information retrieval while another performs analysis or completes a business action. Specialization can make complex workflows easier to organize and maintain. An orchestration mechanism can coordinate communication and determine which agent should handle each task. However, multi-agent architectures also introduce additional complexity. Architects must address identity, permissions, communication, monitoring, failure handling, and governance across all participating agents.

Question 88

A business wants to use its own documents as context for an AI response. Which technique is appropriate?

1. RAG
2. DNS
3. DHCP
4. NAT

Correct Answer: 1

Explanation

Retrieval-augmented generation, or RAG, can provide an AI model with relevant information retrieved from business documents or other knowledge sources. The retrieved content becomes context for generating a response. This approach is useful when the organization needs responses based on information that may not be part of the model’s general knowledge. Architects should consider document quality, indexing, retrieval accuracy, access permissions, freshness, and security. RAG should also be evaluated using realistic questions to determine whether the correct information is retrieved consistently.

Question 89

Which activity should be performed after deploying an AI agent?

1. Stop all testing
2. Disable telemetry
3. Monitor performance and behavior
4. Remove access controls

Correct Answer: 3

Explanation

Monitoring after deployment helps determine whether an AI agent continues to meet performance, reliability, security, and business requirements. Architects should monitor relevant indicators such as latency, failures, usage, tool calls, response quality, and resource consumption. Monitoring can also reveal unexpected behavior that was not identified during testing. The organization should define procedures for investigating incidents and improving the solution. Production monitoring should respect privacy and security requirements while providing enough information to maintain the AI solution effectively.

Question 90

What is a key purpose of a system prompt?

1. Define instructions for the model or agent
2. Configure network switches
3. Manage user hardware
4. Store application backups

Correct Answer: 1

Explanation

A system prompt provides instructions that establish how an AI model or agent should behave. It can define the role, objectives, constraints, response style, and rules relevant to the scenario. System instructions should be carefully designed and tested because they can influence how the agent handles user requests. They should be combined with appropriate authorization and technical controls rather than being relied upon as a security boundary. Architects should also consider how user input and retrieved content could attempt to conflict with the intended instructions.

Question 91

Which factor is important when estimating AI operating costs?

1. Token consumption
2. Monitor size
3. Number of keyboards
4. Office lighting

Correct Answer: 1

Explanation

Token consumption can affect the operating cost of generative AI workloads. Input tokens may include prompts and retrieved context, while output tokens are generated by the model. Large prompts, extensive retrieved content, and unnecessarily long responses can increase consumption. Architects should consider model pricing, expected request volume, context size, and response length when estimating costs. Monitoring actual usage after deployment can reveal differences between estimates and real consumption. Cost optimization should not reduce response quality below the level required by the business scenario.

Question 92

Which approach helps an agent handle requests outside its supported scope?

1. Fallback or escalation
2. Unlimited execution
3. Anonymous access
4. Automatic administrator privileges

Correct Answer: 1

Explanation

Fallback or escalation provides a controlled response when an agent receives a request outside its supported capabilities. The agent may ask for clarification, provide supported alternatives, redirect the user, or transfer the issue to a human or another process. Architects should define these behaviors during solution design and test them with unsupported and ambiguous requests. Clear fallback handling helps prevent the agent from inventing unsupported answers or attempting unauthorized actions. It also makes the solution’s capabilities and limitations clearer to users.

Question 93

A company wants to compare the cost and quality of two AI models. What should it use?

1. Model evaluation
2. User interface themes
3. Printer diagnostics
4. Network cables

Correct Answer: 1

Explanation

Model evaluation can compare different models using the same representative workloads and defined criteria. The organization may measure response quality, accuracy, latency, safety, task completion, and cost. The architect should identify which metrics matter for the business scenario and use consistent test cases where possible. A model that performs well technically may still be unsuitable if its cost or latency exceeds requirements. Evaluation provides evidence for model selection and can be repeated when models, prompts, or workloads change.

Question 94

What can help an AI agent access structured business data?

1. A tool or connector
2. Screen brightness
3. Printer ink
4. Desktop wallpaper

Correct Answer: 1

Explanation

Tools and connectors can provide agents with access to structured business information or application capabilities. For example, a connector may allow an agent to retrieve information from an approved business system. The architect should evaluate authentication, authorization, data mapping, API limits, error handling, and security before enabling the connection. Only the necessary operations should be exposed to the agent. Testing should verify that the connector returns accurate information and that the agent cannot access records beyond the permissions defined for the solution.

Question 95

Which security principle should be applied to AI tools?

1. Maximum privilege
2. Least privilege
3. Anonymous access
4. Shared credentials

Correct Answer: 2

Explanation

Least privilege means providing an AI tool or agent with only the permissions necessary for its intended function. This limits the potential impact of errors, compromised identities, prompt injection, or unintended actions. Architects should identify the exact operations required and avoid granting broad permissions simply for convenience. Tool access should also be monitored and reviewed periodically. When sensitive operations are involved, additional controls such as approval, validation, and auditing may be appropriate. Least privilege is a fundamental part of securing agentic business solutions.

Question 96

A customer-service agent must retrieve current order status from a business system. What is required?

1. A suitable data connection
2. A larger display
3. More keyboard shortcuts
4. A new office layout

Correct Answer: 1

Explanation

A suitable data connection allows the customer-service agent to retrieve current order information from the relevant business system. The architect should identify the appropriate API, connector, or tool and define how authentication and authorization will work. The solution should retrieve only the information necessary for the user’s request. Error handling is also important if the business system is unavailable or returns incomplete data. The retrieved information should be validated where appropriate before being presented to the customer or used for another automated action.

Question 97

Why should AI solutions be tested with unexpected inputs?

1. To identify failure and safety issues
2. To increase screen size
3. To reduce storage
4. To change application colors

Correct Answer: 1

Explanation

Unexpected and adversarial inputs can reveal weaknesses that normal testing may not identify. An agent may encounter ambiguous questions, unsupported requests, malformed information, malicious prompts, or attempts to bypass its instructions. Testing these cases helps determine whether the solution fails safely and follows its defined boundaries. Architects should include representative edge cases in evaluation datasets and validate both responses and actions. Findings from testing can lead to changes in prompts, permissions, tools, grounding, orchestration, or other architectural components.

Question 98

Which factor is important when designing a production AI architecture?

1. Reliability
2. Logo color
3. Keyboard model
4. Office furniture

Correct Answer: 1

Explanation

Reliability is important because business users need an AI solution to operate consistently and recover appropriately from failures. Architects should consider service availability, dependency failures, timeouts, retries, fallback paths, monitoring, and recovery procedures. Agentic solutions may depend on several models, tools, APIs, and knowledge sources, so a failure in one component can affect the overall workflow. The architecture should identify critical dependencies and define appropriate handling for failures. Reliability requirements should be tested before production deployment and monitored afterward.

Question 99

An agent needs to use different tools depending on the user’s request. What should control this behavior?

1. Orchestration and tool selection logic
2. Screen settings
3. File compression
4. Printer configuration

Correct Answer: 1

Explanation

Orchestration and tool selection logic can determine which capabilities an agent should use for a particular request. The design may evaluate the user’s intent, available tools, required data, and business rules before selecting an action. Architects should ensure that tool selection respects permissions and does not expose unnecessary capabilities. Tool calls should also have suitable error handling and monitoring. In complex solutions, clear orchestration helps coordinate multiple steps while maintaining predictable behavior and keeping the agent aligned with its intended business objective.

Question 100

What is an important goal of AI governance?

1. Ensuring AI solutions are used responsibly and consistently
2. Removing all security controls
3. Allowing unrestricted data access
4. Eliminating human oversight

Correct Answer: 1

Explanation

AI governance establishes policies, responsibilities, controls, and processes for developing and operating AI solutions. It can address areas such as responsible use, data protection, security, access, evaluation, monitoring, accountability, and change management. Governance helps ensure that AI systems remain aligned with organizational requirements throughout their lifecycle. Architects should define ownership and approval processes and determine how risks are identified and managed. Effective governance supports innovation while providing appropriate controls for the business, users, data, models, agents, and connected systems.