D-AAI-FN-A-00 Sample Questions & Answers
Defining agentic AI and comparing agent architectures dominates the weighting, followed by how agents perceive and interpret their surroundings, how feedback loops drive learning, and the ethics, safety, and compliance side of running agents.
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- Question 1Intermediate
Concepts of Agentic AI and Agent Architectures · State the different forms of Agentic AI
When classifying autonomous agents based on operational behavior and internal decision logic, how does a reactive agent differ from a goal-driven (plan-driven) agent?
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Correct answer: B
A reactive agent operates primarily on immediate stimulus-response or trigger-action mechanisms, acting solely on current perception. In contrast, a goal-driven (or plan-driven) agent maintains a representation of desired future states, formulates multi-step plans, anticipates downstream tool requirements, and actively monitors progress toward reaching defined targets.
- Question 2IntermediateSelect 3
Concepts of Agentic AI and Agent Architectures · State the different forms of Agentic AI
Enterprises implement varying degrees of autonomy when integrating autonomous agents into production business processes. Which THREE interaction models define the standard operational spectrum of human supervision over AI agents? (Select THREE)
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Correct answers: A, C, D
'Human in the loop' requires explicit human validation and authorization before an agent can execute an action or finalize an output. 'Human on the loop' provides continuous supervisory oversight via operational dashboards, allowing humans to intervene or abort actions in real time. 'Human near the loop' allows agents to operate with high autonomy, triggering automated alerts or escalations only when confidence drops below thresholds or unexpected exceptions arise.
- Question 3Intermediate
Concepts of Agentic AI and Agent Architectures · Show the primary components of an agent and how they interact to create a system
A systems engineer is reviewing the core architectural building blocks of an autonomous AI agent. Which component is specifically responsible for breaking high-level user directives into actionable subtasks and sequencing them before calling tools?
flowchart TD Input([User Goal / Directive]) --> Planning[Component X: Subtask Decomposition] Planning --> Model[Foundation Model Reasoning] Model --> Tools[Tool Calling / APIs] Tools --> Env[(External Environment)] Env --> Memory[Memory: Context Retention] Memory --> ModelShow answer & explanation
Correct answer: C
The Planning component in an agent architecture decomposes high-level goals into tactical subtasks, determines execution sequence, and reflects on intermediate steps prior to invoking external tools. The Model provides reasoning capabilities, Memory stores short- and long-term context, and Tools execute specific interactions with external environments.
- Question 4Advanced
Concepts of Agentic AI and Agent Architectures · Show the primary components of an agent and how they interact to create a system
A global financial institution is deploying an IT Operations autonomous agent to diagnose and remediate production infrastructure incidents across private cloud clusters.
During a database failover incident, the agent performs the following steps:
- Ingests high-priority alerts emitted by monitoring sensors and retrieves historical cluster runbooks.
- Stores intermediate diagnostic findings in a dedicated state buffer to track root-cause hypotheses.
- Formulates a structured JSON command payload and triggers an administrative REST endpoint to restart a degraded replica node.
- Pauses before running a storage rebalance command to request explicit cryptographic authorization from the on-call Site Reliability Engineer (SRE).
Which component of the agent architecture is directly responsible for coordinating the execution policies, managing state transitions between steps, and routing the storage rebalance request to the SRE for sign-off?
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Correct answer: A
The Orchestration layer is responsible for running and managing the lifecycle of the agentic workflow. It coordinates the interactions among the reasoning model, memory buffers, external tools, security policies, and human-in-the-loop approval gates. In this scenario, it handles the state transitions and halts execution to route the high-risk storage rebalance action to the on-call SRE.
- Question 5Beginner
Concepts of Agentic AI and Agent Architectures · Show the primary components of an agent and how they interact to create a system
What is the primary function of the 'tool calling' (or tool invocation) capability within an autonomous agent architecture?
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Correct answer: D
Tool calling allows an agent to bridge the gap between abstract reasoning and external action. By generating structured parameters to invoke external APIs, web services, database queries, and enterprise applications, the agent interacts with its surrounding operational environment to retrieve real-time state and perform tasks.
- Question 6Intermediate
Concepts of Agentic AI and Agent Architectures · Recognize frameworks available for different Agentic scenarios
Dell Technologies champions open enterprise AI ecosystems and collaborative standards. Which open-source framework, hosted under the Linux Foundation, is designed to enable the creation, discovery, and secure management of interoperable multi-agent systems across diverse organizational environments?
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Correct answer: D
AGNTCY is an open-source framework established under the Linux Foundation, co-founded with industry leaders including Dell Technologies, to provide standard protocols and infrastructure for developing, managing, and federating interoperable multi-agent AI systems across enterprise boundaries.
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