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AIF-C01 Practice Question: Building a content generation application using…
A company is building a content generation application using Amazon Bedrock. They need to ensure that the model does not generate offensive content and also avoids discussing certain prohibited topics. Which TWO Bedrock features should be combined to achieve this?
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
✓
Bedrock Guardrails topic denial
Bedrock Guardrails content filters (C) are the right choice for blocking offensive content because they let you configure thresholds across categories such as hate, violence, sexual, insults, and misconduct, filtering both prompts and model responses. Bedrock Guardrails topic denial (B) is also correct because it lets you define specific prohibited topics with natural-language descriptions and optional example phrases, so the model refuses to discuss them. Together, content filters handle offensiveness while topic denial handles restricted subject matter, which is exactly the two-part requirement. Bedrock Model Evaluation (A) only measures and compares model quality or metrics; it does not block content at runtime. Bedrock Knowledge Bases (D) is for retrieval-augmented generation over your own data, and Bedrock Agents (E) orchestrates multi-step tasks and API calls, neither of which enforces content or topic restrictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Bedrock Model Evaluation
Why it's wrong here
Model Evaluation scores and compares model outputs for quality, accuracy and responsibility metrics after the fact; it does not intercept or block live generations. Tempting when selecting a model, yet the scenario needs runtime filtering of offensive content and prohibited topics, which Guardrails and denied topics enforce.
- ✓
Bedrock Guardrails topic denial
Why this is correct
Topic denial defines prohibited subjects and blocks model responses that stray into them, enforcing the stem's requirement to avoid certain banned topics. It complements content filters, which handle offensiveness, giving the two-feature combination the scenario demands.
- ✓
Bedrock Guardrails content filters
Why this is correct
Bedrock Guardrails content filters evaluate both prompts and responses against configurable harmful-category thresholds, blocking offensive output such as hate, violence and sexual content. This directly satisfies the requirement to prevent offensive generation, though the separate prohibited-topics constraint needs Guardrails' denied-topics policy alongside it.
- ✗
Bedrock Knowledge Bases
Why it's wrong here
Knowledge Bases perform retrieval-augmented generation, grounding responses in your own documents; they apply no content filtering or topic denial. Tempting because they restrict what the model can draw on, but that constrains factual sourcing, not offensive output or prohibited subjects, which Guardrails and denied topics handle.
- ✗
Bedrock Agents
Why it's wrong here
Agents orchestrate API calls and multi-step tasks via action groups; they neither filter offensive output nor block prohibited topics. Tempting because they add control over model behaviour, but that control is task execution, not content moderation, which Guardrails with denied topics provides at inference time.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-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 AIF-C01 exam.