# What to do BEFORE You Build an AI Agent

**Identify your use case and value hypothesis**. Where do you believe an AI agent may be useful? To which customers or people? 

**How will you measure the agent's value?** Usually, that is: 

1. \# of messages sent
2. D1, D3, D7, D30 Retention of users
3. Positive vs negative feedback from users
4. % of questions asked by the user that were answered by the agent

**Curate the knowledge base dataset** e.g. documents, videos, PDFs, websites, and soon real-time data sources. 

**Create "Golden" Questions and Answers**

Let’s assume a human expert understood all of the documents in the above knowledge base dataset and then one of your users asked the human expert a question; what ideal answer would you expect the human expert to provide? This is the *Golden Answer.*

1. Collect 10 questions and the ideal **Golden Answer** for each
2. The question should be captured in whatever form we believe the user is likely to ask it - e.g. in Bhojpuri as a WhatsApp audio note, mixed-Hinglish text, English text, and/or Tamil text.
3. If non-English, provide the English text translation of the question
4. The ideal “golden” answer in English text
5. Collect the above as rows in the Excel or Google sheet.


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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.gooey.ai/ai-agent/copilot/what-to-do-before-you-build-a-bot.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.