AIP-C01 Implementation And Integration Practice Question
Which THREE techniques are commonly used to mitigate hallucinations in RAG applications?
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
✓
Adding 'I don't know' as a fallback response
System prompts, retrieval-augmented generation (RAG) itself, and strict source citation reduce hallucinations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Adding 'I don't know' as a fallback response
Why this is correct
Prevents guessing.
- ✗
Using the longest possible output token limit
Why it's wrong here
Longer output increases hallucination risk.
- ✓
Requiring the model to provide citations
Why this is correct
Increases transparency and accuracy.
- ✓
Instructing the model to only answer based on provided context
Why this is correct
Limits the model's knowledge scope.
- ✗
Increasing the inference temperature
Why it's wrong here
High temperature increases hallucinations.
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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 Amazon Web Services exam blueprint
This AIP-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIP-C01 exam.