AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are configuring an agent in Azure AI Foundry that needs to perform mathematical calculations accurately. Large language models often make arithmetic errors. How should you equip the agent to handle calculations reliably?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Provide a code interpreter tool so the model can write and execute Python code for calculations.
Giving the agent a code interpreter or calculator tool allows it to execute calculations deterministically rather than relying on internal probabilistic math.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Provide a code interpreter tool so the model can write and execute Python code for calculations.
Why this is correct
Executing Python code guarantees accurate mathematical computation.
- ✗
Set the model temperature to 0.0 and ask it to guess the result.
Why it's wrong here
Temperature 0 reduces randomness but does not fix the fundamental token-based math limitations of LLMs.
- ✗
Increase the presence penalty to force new tokens.
Why it's wrong here
Presence penalty does not improve arithmetic accuracy.
- ✗
Instruct the model in the system prompt to double-check its arithmetic mentally.
Why it's wrong here
Mental math by LLMs remains unreliable for complex calculations.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.