AI-103 Implement Generative AI And Agentic Solutions Practice Question
An agent is performing poorly on multi-hop reasoning tasks. What architectural pattern should you implement to improve performance?
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
✓
Use a Chain-of-Thought prompting strategy in the agent's system prompt.
Chain-of-thought prompting forces the model to break down complex queries into intermediate logical steps.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the temperature to 1.0.
Why it's wrong here
High temperature increases randomness, which hurts logical reasoning.
- ✗
Switch to a smaller model to increase speed.
Why it's wrong here
Smaller models have less reasoning capability.
- ✗
Decrease the max_tokens parameter.
Why it's wrong here
This will truncate responses.
- ✓
Use a Chain-of-Thought prompting strategy in the agent's system prompt.
Why this is correct
CoT is specifically designed to improve multi-hop reasoning.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
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.