Explanation

Correct Answer: A

Why Option A is correct:

1. Increase grounding within Amazon Bedrock Guardrails: This addresses the core issue of the model recommending products not in the company's catalog. Grounding in Amazon Bedrock allows you to connect the foundation model to your company's data sources (like the product catalog) to provide relevant, accurate, and up-to-date information. This ensures the model only recommends products that actually exist in the catalog.

2. Enable Automated Reasoning checks: This helps ensure the model's responses are logical and relevant to the customer's query, addressing the issue of irrelevant recommendations.

3. Set up provisioned throughput: This addresses the latency issue by guaranteeing dedicated model capacity, which reduces inference time and improves response speed for customers.

Why Option B is incorrect:

1. Prompt engineering alone is insufficient: While prompt engineering can help guide the model, it cannot guarantee that the model will only recommend products from the catalog. Foundation models can still hallucinate or generate information not in the prompt context.

2. Streaming reduces perceived latency but doesn't solve the core issues: Streaming techniques like InvokeModelWithResponseStream can make responses feel faster by delivering tokens as they're generated, but they don't address:

   • The fundamental problem of recommending non-existent products
   • The actual inference latency (just the perception of it)
   • The need for accurate, grounded responses

Key AWS Concepts:

• Grounding in Amazon Bedrock: Connects foundation models to your enterprise data sources
• Provisioned Throughput: Guarantees dedicated model capacity for consistent performance
• Automated Reasoning: Helps validate model outputs for logical consistency

This solution comprehensively addresses both the accuracy issues (grounding + automated reasoning) and the performance issues (provisioned throughput).