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Implement Generative AI And Agentic SolutionsmediumMultiple ChoiceObjective-mapped

AI-103 Implement Generative AI And Agentic Solutions Practice Question

You are implementing a RAG solution where documents contain complex hierarchical headings. To ensure search chunks retain sufficient context about which section they belong to, what chunking strategy should you adopt?

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

Hierarchical (parent-child) chunking retaining section headers

Hierarchical chunking or parent-child chunking retains parent section headings and metadata within smaller searchable child chunks, preserving document context.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Fixed-size character chunking with zero overlap

    Why it's wrong here

    Zero overlap fixed-size chunking frequently cuts sentences and headings in half, losing hierarchical context.

  • Random token sampling without structural awareness

    Why it's wrong here

    Random sampling destroys document flow and logical coherence.

  • Single-chunk whole document ingestion

    Why it's wrong here

    Ingesting entire documents as single chunks exceeds context limits and degrades retrieval precision.

  • Hierarchical (parent-child) chunking retaining section headers

    Why this is correct

    Parent-child chunking links small child chunks to larger parent chunks or headers, maintaining context during retrieval.

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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.