---
type: source
title: "Build a Chatbot for Your Website in 4 Minutes (No Code)"
description: "Building a custom RAG-powered website chatbot trained on your own data is a use case worth handling with a no-code product like Folder rather than coding it yourself."
youtube_id: ceQcKm061aU
url: https://www.youtube.com/watch?v=ceQcKm061aU
slug: build-a-chatbot-for-your-website-in-4-minutes-no-code
published: 2024-08-14
duration: "0:03:59"
recency_rank: 174
raw: "../raw/build-a-chatbot-for-your-website-in-4-minutes-no-code.md"
tags: [no-code-agents, rag, chat-interfaces, knowledge-bases, website-chatbot]
created: 2026-07-21
updated: 2026-07-21
---

Cole usually teaches coding AI agents from scratch, but some use cases are better served by an off-the-shelf product, and a custom RAG website chatbot is one of them. Nearly every business with a website needs a chatbot that can answer questions about its products and services from its own data, and doing this with no code in under five minutes beats building it by hand.

He demonstrates Folder end-to-end: create an account, make an "assistant" (choosing an AI model like Claude, GPT, or Llama, writing a base prompt/system message, and picking a personality), then upload documents (PDFs, text, Google Drive, YouTube, a JSON API) to train it for RAG. Training the assistant on five documents takes about 20 seconds, after which it correctly answers a question that could only be answered from the uploaded meeting notes. He then wires the assistant into a website chatbot, customizes branding, lead capture, and popup placement, and grabs an embed snippet to paste into any site.

Finally he shows Folder's workflow builder, where an assistant can be chained into automations, for example pulling action items from a meeting and texting them via SMS. He notes the differentiator versus n8n, Zapier, and Make is that the automations can leverage the assistants built inside the same platform, with integrations for SMS, Google Drive, and Slack.

## Concepts covered

- [Retrieval-Augmented Generation (RAG)](../concepts/rag.md)
- [Knowledge Bases](../concepts/knowledge-bases.md)
- [No-Code AI Agents](../concepts/no-code-agents.md)
- [Chat Interfaces](../concepts/chat-interfaces.md)
- [Agentic Workflow Engineering](../concepts/agentic-workflow-engineering.md)

## Entities

- [Cole Medin](../entities/people/cole-medin.md)
- [n8n](../entities/tools/n8n.md)
- [Zapier](../entities/tools/zapier.md)

## Key moments

- **[0:00:00]** Custom RAG website chatbots framed as one of the most common AI agent use cases
- **[0:00:32]** Argues some things are worth using a product for instead of coding yourself
- **[0:01:10]** Creating an assistant: name, AI model, base prompt (system message), personality
- **[0:01:38]** Uploading PDF/text files (plus Drive/YouTube/JSON API) to train RAG
- **[0:02:05]** Training finishes in ~20 seconds; answers a doc-only question correctly
- **[0:02:34]** Wiring the assistant into a website chatbot with branding, lead capture, embed code
- **[0:03:01]** Workflow view: assistant chained into an SMS automation for meeting action items

## Transcript

[Raw transcript](../raw/build-a-chatbot-for-your-website-in-4-minutes-no-code.md)
