---
title: First Conversation
description: This tutorial walks you through your first complete agent conversation in DeerFlow — from launching the app to getting meaningful work done with the agent.
---

import { Callout, Steps } from "nextra/components";

# First Conversation

This tutorial walks you through your first complete agent conversation in DeerFlow — from launching the app to getting meaningful work done with the agent.

## Prerequisites

- DeerFlow app is running (see [Quick Start](/docs/application/quick-start))
- At least one model is configured in `config.yaml`

## Steps

<Steps>

### Open the workspace

Open [http://localhost:2026](http://localhost:2026) in your browser. You will see the conversation workspace.

### Send your first message

Type a question in the input box, for example:

```
Research the top 3 most popular open-source LLM frameworks in 2024 and compare their strengths and weaknesses.
```

Press Enter to send.

### Watch the agent work

You will see the agent start working:
- Expand the **thinking steps** to see which tools it is calling
- Watch search results stream in
- Wait for the final report to be generated

### Interact with the result

Once the report is generated, you can:
- Ask for more detail on a specific section
- Ask to export the report as a file (the agent will use the `present_files` tool)
- Ask to create a chart based on the research findings

</Steps>

## What just happened

The agent used the DeerFlow Harness to:
1. Receive your message and add it to the thread state
2. Run the middleware chain (memory injection, title generation)
3. Call the LLM, which decided to search the web
4. Execute web search tool calls
5. Synthesize results into a structured response
6. Update the thread state with any artifacts produced

## Next steps

- [Use Tools and Skills](/docs/tutorials/use-tools-and-skills)
- [Workspace Usage](/docs/application/workspace-usage)
