AI-103 Safe Question Preview

Question 1. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem. After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen. You have a multimodal Al generative model that accepts image uploads and uses extracted image text to generate responses. You discover that users can upload unsafe images and embed hidden instructions into images to manipulate the model. You need to implement controls to mitigate the risk. Solution: You configure a prompt shield for user prompts. Does this meet the goal?

Question 2. You have a Microsoft Foundry project that contains an agent. You need to enable long-term memory to ensure that the agent can recall user preferences across separate conversations. Stored memories must be isolated per authenticated user without the client application manually generating user IDs. How should you complete the Python code? To answer, drag

Question 3. Your organization is optimizing an existing generative AI application in Azure AI Foundry where users report that responses sometimes contain hallucinations and lack sufficient reasoning depth. You need to improve response quality through model tuning and evaluation strategies. Which combination of techniques should you implement? (Select two.)

Question 4. You have a Microsoft Foundry project that uses Azure AI Search to ground an agent in internal documentation. After a content update, users report that the agent's answers have become less accurate. You need to determine whether the generated responses remain supported by the retrieved documentation. Which observability signal should you use?

Question 5. You have a generative AI application deployed in Microsoft Foundry. You need to track safety-related metrics and application behavior continuously in production. Which observability capability should you use?