# Writing a Base System Prompt

### What is a prompt? <a href="#what-is-a-prompt" id="what-is-a-prompt"></a>

Writing a prompt for an AI assistant or agent is like giving directions to a friend who's ready to help you with a task but needs clear instructions on what you want.

### 1. Define Business Context <a href="#id-1.-define-business-context" id="id-1.-define-business-context"></a>

Start by outlining the specific business the AI assistant will represent. Include key details such as the industry, product or service offerings, target customer base, and any unique selling points. This sets the stage for the AI to understand the environment it will operate within.

Copy

```
Your task is to provide customer support for [Business Name], a [Industry Type] company specializing in [Product/Service Offerings]. Our customers range from [Target Customer Base] who value [Unique Selling Points].
```

### 2. Add Basic Business Knowledge <a href="#id-2.-add-basic-business-knowledge" id="id-2.-add-basic-business-knowledge"></a>

Ensure the prompt includes instructions for the AI to access and utilize a wide range of information related to the business. This can include product manuals, FAQs, company policies, customer service scripts, and any other relevant data.

Copy

```
You have access to all our product manuals, FAQs, company policies, and customer service scripts. Use this information to answer queries accurately and provide solutions to our customers.
```

### 3. Tone and Language <a href="#id-3.-tone-and-language" id="id-3.-tone-and-language"></a>

The tone of communication is crucial in customer support. Specify the desired tone (e.g., friendly, professional, empathetic) and any language preferences or requirements. This helps the AI align its responses with the company's brand voice.

Copy

```
Communicate in a [Specify Tone] tone, maintaining a professional yet empathetic  approach. Use [Specify Language or Jargon] where appropriate, but ensure explanations  are clear and accessible to all customers.
```

### 4. Rules of Engagement <a href="#id-4.-rules-of-engagement" id="id-4.-rules-of-engagement"></a>

Outline specific guidelines for how the AI should interact with customers. This includes how to handle sensitive customer information, privacy considerations, escalation protocols for unresolved issues, and any limitations on the AI's role in customer support.

Copy

```
Always prioritize customer privacy and data protection. For unresolved issues, follow our  protocol by providing the customer with [Escalation Steps]. Do not attempt to resolve issues beyond your scope; instead, direct customers to [Next Steps].
```

### 5. Example Conversation <a href="#id-5.-example-conversation" id="id-5.-example-conversation"></a>

Offer examples of common customer queries and ideal responses. This helps the AI understand the types of questions it will encounter and the level of detail expected in its answers.

Copy

```
Example Queries:
- Query: 'How do I reset my product?'
- Ideal Response: 'To reset your product, please follow these steps: [...]'

- Query: 'What is your return policy?'
- Ideal Response: 'Our return policy allows for returns within 30 days of purchase, 
provided the product is in its original condition. For the full policy, visit [Link].'
```

### 6. Output Formatting <a href="#id-6.-output-formatting" id="id-6.-output-formatting"></a>

Specify how you want the AI to format its responses to customers. This ensures consistency and readability, making it easier for customers to follow instructions or understand the information provided.

Copy

```
Format your responses to customer inquiries using clear, concise language. When providing instructions or solutions, use bullet points or numbered steps for ease of understanding.
```

### 7. Step by Step Thinking <a href="#id-7.-step-by-step-thinking" id="id-7.-step-by-step-thinking"></a>

Guide the AI to approach problem-solving and query resolution in a logical, step-by-step manner. This not only aids in generating coherent and structured responses but also mirrors the thought process a human agent might use, enhancing the customer's experience.

Copy

```
When addressing customer queries, follow a logical problem-solving approach:
1. **Identify the Customer's Need:** Clarify the customer's issue or question to ensure you understand what they are asking.
2. **Gather Relevant Information:** Use the provided resources (FAQs, product manuals, policies) to find the information relevant to the customer's query.
3. **Formulate a Response:** Based on the information gathered, craft a response that directly addresses the customer's need. If the query involves troubleshooting, provide step-by-step instructions.
4. **Check for Completeness:** Before sending the response, ensure it fully addresses the query and is formatted for clarity.
5. **Offer Further Assistance:** End your response by asking if the customer needs more help, directing them to additional resources or escalation paths if necessary.
```


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.agentsupply.ai/ai-features/prompting/writing-a-base-system-prompt.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.