Automate Podcast Summaries & Insights with n8n and OpenAI

1. Opening Problem Statement

Meet Alex, a devoted podcast producer who spends countless hours after each episode manually summarizing the transcript, extracting meaningful topics and questions, researching additional background info, and finally compiling all of it into a neat email digest for their audience. It’s a tedious, error-prone process that can easily take 2-3 hours per episode, delaying the delivery of engaging content and risking loss of audience interest.

Alex’s challenge is specific: how to efficiently convert dense audio transcripts from philosophical debates into insightful, well-structured summaries and discussion prompts without spending half the day in front of a screen?

Manual work leads to bottlenecks in content delivery, reduced productivity, and creative burnout. This exact problem is what the n8n workflow presented here solves.

2. What This Automation Does

Once triggered manually, this workflow transforms a raw podcast episode transcript into a polished digest email ready to send. Here’s what happens step-by-step:

• 1. A lengthy transcript is generated or loaded via a Code node.
• 2. The transcript is split into manageable chunks for processing.
• 3. Using OpenAI’s GPT-4 based summarization, the transcript is condensed into a focused summary.
• 4. The summary is analyzed to extract pertinent questions and discussion topics, each accompanied by explanatory context.
• 5. For each topic, the workflow calls Wikipedia to gather factual, external information enhancing the discussion depth.
• 6. Topics and questions are formatted into clean HTML sections.
• 7. Finally, a Gmail node sends a comprehensive email digest including summary, topics, and questions to a preset email address.

This detailed automation saves Alex at least 2 hours per episode, reduces human error, and consistently delivers quality content to subscribers faster.

3. Prerequisites ⚙️

• n8n account — to create and run the workflow.
• OpenAI account with API credentials — used by the Langchain OpenAI Chat Model nodes for summarization and information extraction.
• Gmail account configured with OAuth2 — to send the final digest email.
• Optional: Self-hosting n8n on a platform like Hostinger for better control ⏱️.

4. Step-by-Step Guide

Step 1: Trigger the workflow manually

Navigate to your n8n workflow editor.
Click on the Manual Trigger node named “When clicking “Execute Workflow””.
This node allows you to start the workflow manually in n8n, perfect for controlled testing.

Expected outcome: Workflow begins processing when you hit “Execute Workflow”.

Common mistake: Forgetting to click the manual trigger button after saving the workflow.

Step 2: Load the podcast transcript via Code node

Find the Code node named “Podcast Episode Transcript.”
This node contains JavaScript code returning the podcast transcript as a string. The code is pre-filled in the workflow and can be customized.

return { transcript: `Your long podcast transcript text here...` };

> Replace the internal text with your episode transcript.
You should see a JSON output with a single field named transcript.

Expected outcome: Transcript data is passed downstream for processing.

Common mistake: Not updating the transcript string; leaving placeholder text.

Step 3: Split transcript into chunks

Check the Recursive Character Text Splitter node.
It takes the long transcript and breaks it into smaller parts (6000 characters each with 1000 overlap) which is essential for processing large texts with AI limits.

Expected outcome: The output contains an array of manageable text chunks.

Common mistake: Setting chunk size too high causing API errors or timeouts.

Step 4: Load chunks as documents

The Default Data Loader node imports these chunks into the Langchain document format.
This prepares data correctly for the summarization chain.

Expected outcome: Text chunks are loaded as documents in the workflow.

Common mistake: Misconfiguring loader options which could break the chain.

Step 5: Summarize the transcript chunks

The Summarize Transcript node uses the GPT-4 model via the OpenAI Chat Model node.
Output is a concise, coherent summary of the entire episode.

Expected outcome: Summary appears in JSON under response.text.

Common mistake: Not having correct OpenAI credentials or API limits exceeded.

Step 6: Extract topics and questions

Use the Extract Topics & Questions node connected to the summary.
This prompts OpenAI to analyze the summary and produce JSON arrays of discussion topics and relevant questions with explanations as per a custom schema.

Expected outcome: JSON output containing well-crafted topics and thought-provoking questions.

Common mistake: Schema mismatch or incomplete prompt leading to poor extraction.

Step 7: Split questions for individual processing

The Topics node is a split node that isolates each question for separate processing in the AI Agent.

Expected outcome: Multiple outputs, one per question.

Common mistake: Using wrong field to split or misconnecting upstream node.

Step 8: Research topics using AI Agent and Wikipedia

The AI Agent node takes each question and calls Wikipedia tool via Langchain to fetch relevant background explanation.
This enriches the content beyond the transcript.

Expected outcome: Detailed researched information for each topic appended to the workflow data.

Common mistake: Wikipedia tool timeout or invalid question format.

Step 9: Format topics and questions as HTML

The Format topic text & title Code node composes the collected data into formatted HTML sections with headings and paragraphs.
Paste this JavaScript code below to transform and combine the inputs:

const inputItems = $input.all();
const topics = [];
const questions = [];
const summary = $('Summarize Transcript').first().json.response.text;
// Format Topics
for (const [index, topic] of inputItems.entries()) {
  const title = $('Topics').all()[index].json.question

  topics.push(`
    
${title}
    
${topic.json.output}
`.trim()
  )
}

// Format Questions
for (const question of $('Extract Topics & Questions').first().json.output.questions) {
  questions.push(`
    
${question.question}
    
${question.why}
`.trim()
  )
}

return { topics, summary, questions };

Expected outcome: JSON with HTML-formatted properties for email content.

Common mistake: Mismatched index access causing undefined errors.

Step 10: Send the digest email with Gmail

The Send Digest node is a configured Gmail node that emails the formatted digest.
Fill in the sendTo parameter with your recipient’s email and personalize the message using HTML placeholders:
=Greetings 👋,
Hope you're doing well! Here's your digest for this week's episode of Philoshopy This!

🎙 Episode Summary

{{ $json.summary }}

💡 Topics Discussed

{{ $json.topics.join('n') }}

❓ Questions to Ponder

{{ $json.questions.join('n') }}

Expected outcome: Digest email arrives in inbox with neatly structured podcast insights.

Common mistake: Misconfigured Gmail OAuth2 credentials or blocked access due to Gmail security settings.

5. Customizations ✏️

• Change email recipient: In the Send Digest Gmail node, update the sendTo parameter to your desired email address.
  This sends the digest wherever you want.
• Adjust chunk size: Modify the Recursive Character Text Splitter node’s chunkSize and chunkOverlap parameters to optimize for transcript length and API usage.
• Add more AI tools: Integrate additional Langchain tools in the AI Agent node to expand research abilities beyond Wikipedia, like Wolfram Alpha or custom APIs.
• Customize email layout: Edit the HTML structure in the Format topic text & title Code node to match your branding and style.
• Automate trigger: Replace the manual trigger node with a webhook or schedule trigger to automatically process new episodes as they are published.

6. Troubleshooting 🔧

• Problem: “OpenAI API quota exceeded”
  Cause: Your account has reached the monthly usage limit.
  Solution: Check OpenAI usage dashboard, apply for higher quota or optimize prompts to reduce tokens.
• Problem: “Gmail OAuth2 authentication failed”
  Cause: Incorrect or expired OAuth token.
  Solution: Reauthenticate Gmail account in n8n credentials manager.
• Problem: “Index out of range” in Format topic text & title node.
  Cause: Mismatch in the number of topic responses and extracted questions.
  Solution: Ensure consistent splitting and correct indexing in code logic.

7. Pre-Production Checklist ✅

• Verify OpenAI API keys and Gmail OAuth credentials are correctly configured.
• Test the workflow end-to-end with a sample transcript to confirm expected outputs.
• Confirm email arrives without formatting errors and content matches the transcript.
• Backup original transcripts and workflow configurations before deployment.

8. Deployment Guide

Activate the workflow by enabling it in n8n.
For manual testing, use the manual trigger node.
Monitor executions via n8n’s execution logs to catch errors or bottlenecks early.
Optionally, automate the workflow with webhook or cron nodes when ready for production.

9. FAQs

• Can I use other email providers instead of Gmail?
  Absolutely, replace the Gmail node with other supported SMTP or email nodes configured with your credentials.
• Does this workflow consume a lot of OpenAI credits?
  Depending on transcript length and chunk count, yes, summarization and extraction calls can add up; consider API plan accordingly.
• Is my podcast data secure?
  n8n runs workflows locally or hosted securely; ensure sensitive transcripts are handled per privacy policies.
• Can this handle large podcast episodes?
  Yes, the Recursive Character Text Splitter and chunk processing is designed to handle long transcripts efficiently.

10. Conclusion

By following this guide, you’ve automated the laborious task of transforming dense podcast transcripts into insightful, research-backed email digests using n8n, Langchain AI tools, and Gmail. Alex now saves hours of manual work and delivers higher-value content promptly.

Next up, you might explore automating episode audio editing, integrating social media posting for episodes, or generating video highlights using similar AI-augmented n8n workflows.

Keep experimenting — automation unlocks creative freedom!