Answer: Context enrichment

## Explanation The correct answer is **B) Context enrichment**. **Context enrichment** refers to the practice of providing additional relevant information or context to an AI model's prompts to improve the quality and accuracy of its responses. In this scenario: - The AI-powered FAQ bot was producing **inconsistent answers** to policy-related questions - The developer **added excerpts from the company's policy document** to the prompts - This provides the AI model with **specific, relevant context** about the company's actual policies - With this enriched context, the AI can generate more **accurate and consistent** responses that align with the company's official policies **Why the other options are incorrect:** - **A) Zero-shot prompting**: This refers to asking a model to perform a task without providing any examples, which is not what's happening here since the developer is adding policy excerpts. - **C) Negative prompting**: This involves telling the model what NOT to do, rather than providing positive context. - **D) Temperature adjustment**: This refers to adjusting the randomness/creativity of AI responses, not adding contextual information. Context enrichment is a common best practice in AI prompt engineering to ensure models have the necessary background information to generate appropriate responses.

Author: Ritesh Yadav