Automated Podcast Production Workflow

Introduction

Podcast production involves dozens of repetitive tasks: uploading audio to hosting platforms, generating transcripts, creating social media clips, distributing show notes, and notifying subscribers. Most creators handle these manually, spending hours each week on work that adds no creative value. A single 60-minute episode can easily consume 4-6 hours of post-production labour once you factor in editing, uploading, and distribution.

The good news is that modern AI tools, combined with proper orchestration, can automate nearly all of this. You record and edit your episode once. The workflow handles the rest: it transcribes audio, extracts key moments for clips, generates social media captions, writes show notes, publishes to multiple platforms, and notifies your audience. No manual handoff. No switching between tabs. No copy-pasting.

This post walks through a production-ready automated podcast workflow using real API endpoints and configuration examples. We'll use Claude for intelligent content generation, Whisper for transcription, and a no-code orchestration platform to tie it all together.

The Automated Workflow

Architecture Overview

The workflow follows this sequence:

1. You upload a finished MP3 file to a cloud storage folder (Google Drive or Dropbox).
2. The orchestration tool detects the new file and downloads it.
3. Whisper transcribes the audio to text.
4. Claude analyses the transcript and generates: a show summary, three social media posts, and formatted show notes.
5. The platform publishes show notes to a static site or CMS, uploads clips to YouTube, and sends emails to subscribers.
6. A notification confirms completion with links to all published content.

Choosing Your Orchestration Tool

For this workflow, I recommend n8n or Make. Both support native integrations with OpenAI (Whisper and Claude), webhook triggers, and conditional logic. Zapier works but limits API calls; n8n is self-hosted so you control costs at scale. Make offers a middle ground with reasonable pricing and a visual builder.

This example uses n8n, but the logic translates directly to Make or Zapier.

Step 1: Trigger on New File Upload

First, set up a Google Drive trigger that monitors a specific folder for new MP3 files.

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Trigger: Google Drive - New File in Folder
Folder ID: 1a2b3c4d5e6f7g8h9i0j (your podcast folder)
File Types: audio/mpeg
Poll Interval: Every 5 minutes

When a file appears, the workflow captures the file ID, name, and a download link.

Step 2: Download and Transcribe with Whisper

Next, use OpenAI's Whisper API to transcribe the audio. You'll need an OpenAI API key.

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POST /v1/audio/transcriptions
Host: api.openai.com
Authorization: Bearer sk-YOUR_API_KEY
Content-Type: multipart/form-data

--boundary
Content-Disposition: form-data; name="file"; filename="episode-42.mp3"
Content-Type: audio/mpeg

[binary audio data]
--boundary
Content-Disposition: form-data; name="model"

whisper-1
--boundary
Content-Disposition: form-data; name="language"

en
--boundary--

In n8n, configure this as an HTTP Request node with the file data from the Google Drive trigger. Whisper returns:

Copy{
  "text": "Welcome to the podcast. Today we discuss...",
  "language": "en",
  "duration": 3842
}

Step 3: Analyse Transcript and Generate Content with Claude

Now send the transcript to Claude for analysis. You'll use the Messages API with specific prompts for each output type. This example generates a show summary and social media posts.

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POST /v1/messages
Host: api.anthropic.com
Authorization: Bearer sk-ant-YOUR_API_KEY
Content-Type: application/json

{
  "model": "claude-3-5-sonnet-20241022",
  "max_tokens": 2000,
  "messages": [
    {
      "role": "user",
      "content": "You are a podcast producer. Analyse this transcript and provide: 1) A 100-word episode summary, 2) Three Twitter posts (under 280 characters each), 3) A LinkedIn post (under 500 characters). Format the output as JSON with keys: summary, twitter_posts, linkedin_post. Transcript: [FULL TRANSCRIPT HERE]"
    }
  ]
}

Store the Claude API response in workflow variables. The response will look like:

Copy{
  "content": [
    {
      "type": "text",
      "text": "{\"summary\": \"...\", \"twitter_posts\": [...], \"linkedin_post\": \"...\"}"
    }
  ]
}

Parse this JSON to extract individual fields for use in later steps.

Step 4: Format and Store Show Notes

Create a structured show notes document. This step combines the original file metadata, transcript, summary, and timestamps.

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Episode Title: {{ trigger.filename }}
Published: {{ now.toISOString() }}

Summary
{{ claude_response.summary }}

Transcript
{{ whisper_response.text }}

Key Topics
- Topic 1
- Topic 2
- Topic 3

Many creators store show notes as Markdown in a GitHub repository or as a Google Doc. For this workflow, we'll write to a simple Markdown file in Google Drive.

Step 5: Publish to Multiple Platforms

This is where the workflow branches. You might publish to:

1. Your website or CMS via REST API
2. YouTube (automated using your existing podcast channel)
3. Email subscribers via a mailing list service

For a WordPress site hosting your show notes:

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POST /wp-json/wp/v2/posts
Host: yoursite.com
Authorization: Bearer YOUR_WORDPRESS_TOKEN
Content-Type: application/json

{
  "title": "Episode 42: {{ trigger.filename }}",
  "content": "{{ show_notes_content }}",
  "status": "publish",
  "categories": [5],
  "featured_media": 0
}

For email notifications via SendGrid:

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POST /v3/mail/send
Host: api.sendgrid.com
Authorization: Bearer SG.YOUR_API_KEY
Content-Type: application/json

{
  "personalizations": [
    {
      "to": [{"email": "subscriber@example.com"}],
      "dynamic_template_data": {
        "episode_title": "{{ trigger.filename }}",
        "summary": "{{ claude_response.summary }}",
        "listen_link": "{{ spotify_url }}"
      }
    }
  ],
  "from": {"email": "podcast@yoursite.com"},
  "template_id": "d-YOUR_TEMPLATE_ID"
}

Step 6: Error Handling and Notifications

Wrap each major step in error handlers. For instance, if Whisper fails (perhaps due to audio quality), send yourself a Slack notification instead of crashing silently.

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ON ERROR:
  POST to Slack webhook
  {
    "text": "Podcast workflow failed for {{ trigger.filename }}: {{ error.message }}"
  }

n8n calls this an "Error Workflow". You set it once and it triggers automatically when any node fails.

Complete Workflow Diagram

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Google Drive (new file) 
  ↓
Download MP3 from Drive
  ↓
Whisper API (transcribe)
  ↓
Claude API (analyse & generate)
  ↓
Split into three parallel branches:
  ├→ Write show notes to WordPress
  ├→ Send email to subscribers
  └→ Post to Twitter/LinkedIn
  ↓
Slack notification (complete)

The Manual Alternative

If you want more control over generated content, keep manual steps in the workflow. For example:

1. Run the transcription and Claude analysis as before.
2. Pause the workflow and send you an email with the generated content.
3. You review, edit, and click "Approve" via a workflow button.
4. The workflow resumes and publishes the approved content.

n8n supports this via the "Wait" node and manual approval triggers. It adds maybe 10 minutes to your process but lets you quality-check Claude's output before it reaches your audience. This is worth doing, especially early on, until you trust the prompts.

Pro Tips

1. Rate Limiting and Cost Control

Whisper charges per minute of audio processed. A 60-minute episode costs around $1.20. Claude's Messages API costs based on input and output tokens. A typical podcast analysis uses 2,000-3,000 output tokens, roughly $0.03 per episode. Set up monthly budget alerts in your OpenAI dashboard to avoid surprises. Also, add delays between API calls using n8n's "Pause" node to avoid rate-limiting errors from downstream services like WordPress or SendGrid.

2. Transcript Caching

If you ever re-publish or re-analyse an episode, you'll pay Whisper again. Store transcripts in a simple database (even a Google Sheet works) keyed by file hash, so you only transcribe once per unique audio file.

3. Parallelisation for Speed

The workflow above publishes to email and social media in series. Run these in parallel instead using n8n's "Merge" node. This cuts your total execution time from 60 seconds to 30 seconds.

4. Environment Variables for API Keys

Never hardcode API keys in your workflow. Use n8n's Credentials feature to store them securely and reference them by name in your nodes. If you use Make, store keys in environment variables.

5. Dry Run Before Going Live

Test the entire workflow with a single test MP3 file before letting it run automatically. Check that WordPress posts are formatted correctly, emails contain the right links, and Slack notifications reach the right channel. One typo in a live workflow can spam your entire subscriber list.

Cost Breakdown

The cost scales almost entirely with episode volume. A creator publishing one episode per week sits at the lower end. Daily podcasters or networks running multiple shows move toward the higher end.

In summary: a one-person podcast operation publishing weekly costs roughly £20-40 monthly in actual API usage, plus whatever you pay for hosting and email. The orchestration tool itself (n8n self-hosted) is free.