Automatically Deliver NotebookLM Outputs Into Telegram
Overview
This guide shows you how to automatically share NotebookLM outputs—summaries, insights, analyses—into a Telegram chat or channel. Whenever you add new content to a designated Google Doc or Drive folder, your Telegram bot posts it.
What You Will Build
A workflow where:
NotebookLM produces a summary.
You paste or export it into a Google Doc or a Drive folder.
An automation tool detects the new content.
Your Telegram bot posts it into a Telegram group/channel.
This avoids manual copy–paste steps and keeps your team informed.
Prerequisites
Telegram bot token (via @BotFather)
Google Drive + Google Docs
NotebookLM
Make or Zapier (example uses Make)
Step-by-Step Instructions
Step 1 — Create your “summary output” location
You have two options:
Option A — One Google Doc
Create a doc named:
NotebookLM → Telegram Summaries
Option B — A Google Drive folder
Create a folder named:
NLM Summaries Folder
Each summary you paste or export into this folder triggers the workflow.
Step 2 — Tell NotebookLM where to output results
NotebookLM currently doesn’t auto-export, so you’ll copy/paste:
After generating a summary or answer
Paste it into the Doc or create a new Doc inside your “NLM Summaries” folder
This becomes your automation trigger.
Step 3 — Set up Make to detect new summaries
3.1 Start a scenario
Open Make.com → Create Scenario.
3.2 Add a Google Drive module
Choose:
Watch Files in a Folder (for folder-based)
ORWatch Document Changes (for single Doc)
3.3 Add your Telegram Bot Posting module
Add Telegram Bot → Send a Text Message or Reply.
Connect your bot token.
Choose:
A group
A channel
Or a personal chat
3.4 Format the outgoing message
Example:
📘 New NotebookLM Summary
Title: {{file_name}}
Preview:
{{snippet_of_doc_text}}
Full doc: {{doc_url}}
Step 4 — Turn on the scenario and test it
Generate a summary in NotebookLM.
Paste it into the doc or folder.
The bot should immediately post the summary in Telegram.
Done!
Your Telegram community now receives NotebookLM summaries automatically—making NotebookLM a team-wide knowledge engine.