> For the complete documentation index, see [llms.txt](https://docs.qolaba.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.qolaba.ai/chatbot/prompt-and-controls/writing-your-prompt.md).

# Writing your Prompt

#### Prompt Structure

A well-structured prompt typically includes four elements:

| Element           | What It Means                         |
| ----------------- | ------------------------------------- |
| **Objective**     | What you want the AI to do            |
| **Context**       | Background, audience, or purpose      |
| **Constraints**   | Tone, length, format, or limitations  |
| **Output format** | How the response should be structured |

**Example:**

Instead of:

```
Write a blog post.
```

Use:

```
Write a 600-word blog post about AI in retail.
Target audience: startup founders.
Tone: professional but conversational.
Include 3 subheadings and a short conclusion.
```

The second prompt gives the model everything it needs to produce a usable first draft — reducing back-and-forth and credit usage.

***

#### Best Practices

1. **Be specific** — Vague instructions produce vague outputs. Define exactly what you need.
2. **Provide context** — Mention the audience, purpose, background, or constraints relevant to the task.
3. **Define the output format** — Tell the model how to structure the response: bullet points, table, JSON, numbered list, paragraph, etc.
4. **Iterate rather than overload** — Start with a focused prompt and refine with follow-ups. Trying to cover everything in one prompt often produces unfocused responses.
5. **One objective per chat** — Start a new chat when switching to a completely different task. Mixing objectives in one thread affects context quality and output consistency.

***

#### Voice Input — Mic Icon

For quick or natural language input, use the **Mic icon** in the prompt input area. Click it and speak your prompt directly — Qolaba transcribes your speech into text, which you can review and edit before sending.

This is useful when:

* You want to describe a task naturally without typing out a structured prompt
* You are working quickly and want to capture an idea before refining it
* Typing a long, detailed prompt feels slower than speaking it