Agentic AI (NCP-AAI) Free Practice Test

Question 1

You are tasked with comparing two agentic AI systems - System A and System B - both designed to generate marketing copy.
You've run identical prompts and have recorded the generated outputs.
To objectively assess which system is performing better, what is the most appropriate approach?

A. Measure the click-through rate for each system's marketing copy as the primary indicator of performance.

B. Gather ratings from a panel of users, with each rating marketing copy on a 1 to 5 scale for overall impression of relevance, creativity, and grammatical correctness.

C. Implement a human-in-the-loop to subjectively rate each output on a scale of 1 to 5 based on the user's personal preference.

D. Implement a benchmark pipeline that automatically compares the generated outputs using metrics like relevance, creativity, and grammatical correctness.

Correct Answer: D

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Question 2

What NVIDIA framework can be used to train a better agent?

A. NeMo-RL

B. NeMo Guardrails

C. TensorRT-LLM

Correct Answer: A

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Question 3

You're working with an LLM to automatically summarize research papers. The summaries often omit critical findings.
What's the best way to ensure that the summaries accurately reflect the core insights of the research papers?

A. Having the LLM generate the summaries and then manually review every output.

B. Asking the LLM to "understand" the paper to generate a summary.

C. Asking the LLM to "extract the key findings."

D. Asking the LLM to "summarize the paper."

Correct Answer: C

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Question 4

A financial services company is deploying a multi-agent customer service system consisting of three specialized agents: a reasoning LLM for complex queries, an embedding agent for document retrieval, and a re-ranking agent for result optimization. The system experiences significant traffic variations, with peak loads during business hours (10x normal traffic) and minimal usage overnight. The company needs a deployment solution that can handle these fluctuations cost-effectively while maintaining sub-second response times during peak periods.
Which NVIDIA infrastructure approach would provide the MOST cost-effective and scalable deployment solution for this variable-load multi-agent system?

A. Deploy agents directly on individual NVIDIA RTX workstations without containerization or orchestration, relying on load balancers with round-robin for traffic distribution.

B. Deploy all agents on a single large GPU instance without containerization, scaling compute by upgrading to larger GPU instances when needed.

C. Deploy NVIDIA NIM microservices on Kubernetes with auto-scaling capabilities, utilizing NVIDIA NIM Operator for lifecycle management and horizontal pod autoscaling based on custom metrics.

D. Deploy each agent on dedicated NVIDIA DGX systems with manual scaling based on previous days traffic predictions and static resource allocation for peak loads.

Correct Answer: C

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Question 5

An AI agent must interact with multiple external services, handle variable user requests, and maintain reliable operation in production.
Which design principle is most critical for ensuring stable and resilient integration with external systems?

A. Implementing timeouts and circuit breakers for external service calls

B. Storing all external credentials directly in the agent's source code

C. Using hardcoded endpoints without configuration management

D. Bypassing error handling to reduce latency during API calls

Correct Answer: A

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Question 6

When analyzing an agent's failure to complete multi-step financial analysis tasks, which evaluation approach best identifies prompt engineering improvements needed for reliable task decomposition and execution?

A. Rely on generic prompt templates which are by default already optimized for general use, instead of tailoring them to financial terminology, calculation needs, or specialized multi-step analysis patterns.

B. Implement systematic prompt testing with chain-of-thought reasoning templates, step-by-step decomposition analysis, and success rate tracking across tasks of varying complexity.

C. Focus primarily on response speed optimization as a primary focus over reasoning quality, step completion accuracy, and prompt clarity for complex analytical requirements.

D. Test only final output accuracy as this will automatically include intermediate reasoning steps, decomposition quality, and prompt structure effectiveness for complex workflows.

Correct Answer: B

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Question 7

When evaluating a multi-agent customer service system experiencing unpredictable scaling costs and performance bottlenecks during peak hours, which analysis approaches effectively identify optimization opportunities for both infrastructure efficiency and service reliability? (Choose two.)

A. Deploy agents with configurable scaling workflows, allowing analysis of resource adjustment strategies and their effects on service stability during variable demand periods.

B. Deploy distributed tracing with cost attribution per agent type, correlating resource consumption with business value metrics to identify optimization opportunities in agent deployment strategies.

C. Scale agent infrastructure based on aggregate performance trends, using system-wide monitoring tools to identify broader optimization patterns across resources.

D. Implement comprehensive workload profiling using NVIDIA Nsight to analyze GPU utilization patterns, identify underutilized resources, and optimize batch sizing for dynamic scaling with Kubernetes HPA.

E. Maintain consistent resource allocation across all service hours, for a more precise view of baseline traffic impact on long-term infrastructure efficiency.

Correct Answer: B,D

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Question 8

A development team is building an AI agent capable of autonomously planning and executing multi-step tasks while retaining context and learning from past interactions.
Which practice is most important to enable the agent to effectively manage long-term memory and complex tasks?

A. Implement memory mechanisms for context retention and apply chain-of-thought prompts to enhance reasoning.

B. Use basic rule-based decision methods that emphasize fast responses over adaptive planning.

C. Apply short-term memory approaches that handle each interaction independently of previous ones.

D. Reduce planning features and memory management to keep the system streamlined.

Correct Answer: A

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Question 9

An AI agent is being built to execute database queries, generate reports, and interact with cloud services.
Which design choice best improves long-term scalability and maintainability when adding new tools?

A. Hardcoding each new tool directly into the agent's core logic

B. Using a plugin-based system with uniform tool registration and invocation

C. Implementing all tools inside a single large function with many if-else branches

D. Storing tool parameters as unstructured text parsed at runtime

Correct Answer: B

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NVIDIA Agentic AI (NCP-AAI) Free Practice Test