> ## Documentation Index
> Fetch the complete documentation index at: https://developers.autoplay.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Landbot tutorial

> Connect live user data from the Autoplay SDK straight into your Landbot agent for real-time context-aware conversations.

Learn how to connect live user data from the Autoplay SDK straight into your Landbot agent. This guide walks through wiring a lightweight backend route that pulls a user's live activity **on demand** from the Autoplay connector the moment Landbot needs context to answer — no background listener, no local event store to manage.

## ✨ Final result

<Frame>
  <img src="https://mintcdn.com/autoplayai/8xGzR9S6FQ4vpHLs/images/recipes/landbot/landbot_img_01_final_result.png?fit=max&auto=format&n=8xGzR9S6FQ4vpHLs&q=85&s=ace3a765917cab46ca3a15063aba4318" alt="Landbot support AI agent showing a context-aware response based on real-time user activity" width="1024" height="560" data-path="images/recipes/landbot/landbot_img_01_final_result.png" />
</Frame>

***

## 📋 Prerequisites

Complete the [Quickstart](/quickstart). You should have:

* **Your activity source set up** — PostHog (or Amplitude) in the browser, with `identify` (or `setUserId`) setting a stable `user_id` for each logged-in user
* **A registered product** — your `product_id`, `mcp_url`, and `mcp_key` printed by `onboard_product` in the Quickstart
* **A [Landbot](https://landbot.io) account**

***

## The building blocks

Follow the steps in order — each page stands alone so you can ship incrementally.

1. **[Connect real-time events](./step-1-connect-real-time-events)** — Set up the Landbot workflow, wire a lightweight backend server, and embed the support AI agent in your frontend app.
2. **[Define proactive triggers](./step-2-define-proactive-triggers)** — Proactively message users in Landbot based on what they're doing in your product. *(Coming soon)*