You are developing an agent that needs to perform a complex set of tasks repeatedly.
Why is periodic fine-tuning an important aspect of long-term knowledge retention for this type of agent?

• A. It prevents the agent from becoming overly specialized to a single task.
• B. It prevents the agent from forgetting past successes and failures.
• C. It guarantees the agent will produce the same output for the same input.
• D. It eliminates the need for external storage like RAG.

Which two orchestration methods are MOST suitable for implementing complex agentic workflows that require both external data access and specialized task delegation? (Choose two.)

• A. Static rule-based routing with predefined pathways
• B. Manual workflow coordination without automation
• C. Retrieval-based orchestration for external data
• D. Prompt chaining to accomplish state management
• E. Agentic orchestration with specialized expert system delegation

Implement Memory Systems for Contextual Awareness
An enterprise AI system needs to maintain contextual information over multiple interactions with users.
Which memory implementation approach would be MOST effective for managing both immediate context and long-term historical interactions within an agentic workflow?

• A. Implement a hybrid memory system with short-term memory for immediate context and a vector database for long-term memory with semantic retrieval capabilities.
• B. Rely predominantly on the context window of the base LLM model to store all historical interactions with minimal external memory supplementation.
• C. Store all user interactions in a simple key-value database which will by default provide organization and retrieval strategy for historical context management.
• D. Use a static prompt template with fixed context for all interactions, thereby providing memory information in that form across conversation sessions.

An AI Engineer is analyzing a production agentic AI system's compliance with responsible AI standards.
Which evaluation approaches effectively identify potential safety vulnerabilities and ethical risks in multi- agent workflows? (Choose two.)

• A. Emphasize latency metrics and throughput performance as key evaluation factors for safety vulnerabilities, providing a baseline for operational measures and resource allocation.
• B. Implement comprehensive audit trails using NVIDIA NeMo Guardrails with semantic similarity checks, tracking agent decisions across conversation flows and evaluating policy violations through automated compliance scoring.
• C. Use user feedback as a primary signal for risk identification, emphasizing post-deployment observations and qualitative experience reports alongside operational monitoring.
• D. Deploy multi-layered evaluation combining bias detection metrics (demographic parity, equalized odds) with adversarial testing to probe agent responses for harmful outputs across diverse user populations