AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are building an advanced agentic RAG solution. When a user asks a complex question, the agent needs to generate multiple search queries, execute them in parallel against Azure AI Search, synthesize the findings, and then formulate a final answer. Which agent pattern are you implementing?
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
✓
Query decomposition and parallel retrieval
Query decomposition and parallel retrieval is an advanced RAG pattern where complex queries are broken into sub-queries and executed concurrently.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model fine-tuning
Why it's wrong here
Fine-tuning modifies model weights on a training dataset rather than orchestrating real-time search queries.
- ✗
Single-shot keyword extraction
Why it's wrong here
Single-shot keyword extraction uses a single prompt and basic search term extraction without multi-query synthesis.
- ✗
Static prompt templating
Why it's wrong here
Static templating injects variables into fixed prompt strings without multi-step agentic reasoning.
- ✓
Query decomposition and parallel retrieval
Why this is correct
Decomposition breaks complex prompts into targeted sub-queries, improving recall across diverse document sources.
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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
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