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Question # 1
You have a customer support agent that uses the Microsoft Foundry Agent Service.
Sometimes, customers return to a session days later to continue the same support case,
and the agent must resume with the full historical context. The agent must provide the
following:
• Multi-turn continuity within the session
• Cross-session continuity for the same case
• Access to the full interaction history, including user messages, agent messages, tool
calls, and tool outputs
You need to ensure that the agent automatically reloads the complete history on each new
turn.
What should you do?
A. Persist only the final model response stored in the client application and prepend the response to future prompts.
B. Enable memory summarization on the agent definition to persist the context automatically.
C. Create and reuse a conversation by storing the conversation’s ID and supplying the ID on subsequent requests.
Question # 2
You have a Microsoft Foundry project.
You plan to build a customer support solution that contains an agent. The solution must
meet the following requirements:
• Provide accurate, context-aware responses grounded in internal product documentation
stored in Azure AI Search.
• Require deep, multi-step reasoning across long contexts.
• Generate detailed natural language responses.
Which type of model should you use to power the agent?
A. a multimodal model
B. a key phrase extraction model
C. a small language model (SLM)
D. a large language model (LLM)
Question # 3
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 Microsoft Foundry project that contains an agent. The agent generates
summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses
are present in the retrieved content.
You need to improve response completeness.
Solution: You increase the value of the temperature parameter.
Does this meet the goal?
A. Yes
B. No
Question # 4
You have an app named App1 that uses a Microsoft Foundry multimodal model
deployment.
App1 runs optical character recognition (OCR) on uploaded images and appends the OCR
output to the prompt as additional
context.
Some uploaded images contain embedded text.
You need to prevent potentially malicious instructions from being processed by the model.
What should you use?
A. protected material text
B. prompt shields for user prompts
C. image moderation
D. prompt shields for documents
Question # 5
You have an Azure Speech in Foundry Tools resource that hosts a custom speech to text
model deployed to a custom endpoint. An
agent uses the endpoint to perform real-time speech recognition.
You are approaching the expiration date of the custom speech to text model.
What is the expected behavior when the model expires?
A. Speech recognition requests will fall back to the most recent base model for the same locale.
B. Speech recognition requests will continue to use the expired custom model until the model is removed manually.
C. Speech recognition requests will return a 4xx error until a new custom model is deployed.
D. The custom model will be deleted automatically when the model expires.
Be part of the discussion — drop your comment, reply to others, and share your experience.
When I first started preparing for AI-103, I felt overwhelmed by the number of Azure AI services covered in the exam. I created a study plan, focused on one topic at a time, and practiced regularly. Over time, my confidence grew, and I felt much more comfortable with the exam objectives. I Passed today with AllExamTopics.com
I'm planning to take AI-103 in the next few months. I have experience with machine learning concepts but very limited exposure to Azure services. For those who have already studied for the exam, how difficult is the Azure-specific content? Which areas should I focus on first?
I recently prepared for AI-103, and if you already have a machine learning background, you're off to a good start. The Azure-specific content isn't overly difficult, but you'll need to understand which Azure AI service fits a particular business scenario and how to implement it.
My preparation focused on understanding Azure AI services, machine learning concepts, and real-world implementation scenarios. Regular practice testing helped me identify weak areas and improve my time management. I was pleased with my overall exam experience and would recommend a structured study plan to future candidates.
The AI-103 certification covers a wide range of Azure AI concepts. During my preparation, I used multiple study resources, including practice exams, documentation, and labs. The practice questions were useful for checking my readiness and improving my confidence before exam day.
I recently passed the AI-103 exam after several weeks of preparation. The practice questions helped me become familiar with the exam structure and identify topics that required additional study. I recommend combining practice tests with official Microsoft learning resources and hands-on experience for the best results.
Paulo Carvalho
My AI-103 journey started with Microsoft Learn modules and hands-on labs. Initially, I struggled with understanding which Azure AI service to use in different scenarios. Consistent practice and reviewing explanations helped me strengthen my weak areas and improve my understanding.