AI-300 Generative AI Optimization Practice Question
Which TWO methods are best for debugging an LLM pipeline that fails on complex queries?
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
✓
Inspecting raw input and output tokens via logs.
Prompt logging and trace inspection are the best ways to understand why a model fails on specific inputs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Inspecting raw input and output tokens via logs.
Why this is correct
Allows developers to see exactly what the model saw.
- ✓
Tracing the request flow through the RAG pipeline.
Why this is correct
Helps identify if retrieval or generation is the failure point.
- ✗
Increasing the number of API users.
Why it's wrong here
Irrelevant to debugging.
- ✗
Disabling all security controls.
Why it's wrong here
Unsafe and does not fix pipeline logic.
- ✗
Deleting the deployment and rebuilding it.
Why it's wrong here
Unnecessary and doesn't provide debugging information.
About these practice questions
This AI-300 question is part of Courseiva's 204-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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-300 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-300 exam.