The Short Version: Is PodScribe AI Worth It?
Short version: PodScribe AI is the fastest tool I’ve found for generating decent podcast show notes, but you will absolutely need to do a 10-minute manual cleanup on every single episode. It’s worth the price if you publish weekly, but a total waste of money if you need perfect speaker labels for interviews.
I paid for three months of the Creator plan to test it on my own podcast. It’s good, not great, and this automated podcast show notes tutorial will show you how to get the most out of it without pulling your hair out.
Full disclosure: some links below are affiliate links. I only recommend tools I’ve paid for and actually use.
What PodScribe AI Gets Right (The 90% Solution)
Let’s start with the good stuff. The core promise is simple: upload an audio file, and get back a full transcript, a summary, chapter markers, and ideas for social media posts. For the most part, it delivers on this. The transcription accuracy is on par with other AI services like Descript or Otter.ai.ai — about 95-98% correct, depending on your audio quality and accents. It handles technical jargon surprisingly well.
But the one feature I genuinely love, and the reason I keep my subscription active, is the ‘Key Takeaways’ generator. This isn’t just a generic summary. It pulls out 5-7 distinct, actionable bullet points from the conversation. They are consistently insightful and well-phrased. I literally copy and paste these directly into my weekly email a newsletter platform like Beehiiv to promote the new episode. It saves me 20 minutes of re-listening and trying to find the most salient points myself. That alone is a huge win.
The chapter generation is also solid. It correctly identifies topic shifts in a 45-minute episode about 80% of the time. You might have to merge two chapters or slightly rename one, but it provides a fantastic starting point for YouTube timestamps or podcast player chapters. It’s much faster than scrubbing through the audio manually.
My Exact Automated Podcast Show Notes Tutorial Workflow
If you just hit ‘generate’ and copy the output, your show notes will be mediocre. Here’s the workflow I developed over a dozen episodes to get a result I’m happy to publish.
Step 1: Upload and Wait.
I upload my final MP3 file. For a 45-minute episode (around 65MB), PodScribe AI takes about 8-10 minutes to process everything. Go make a coffee. When you come back, you’ll have a dashboard with the transcript, summary, and other generated assets.
Step 2: Ignore the Default Summary.
The main ‘Episode Summary’ it generates is almost always bland and generic. It reads like a book report. I skip it entirely. The gold is in the other sections.
Step 3: Fix the Transcript First.
This is critical. Before you use any other feature, go to the transcript editor. Read through it and fix any glaring errors in terminology or names. But most importantly, you have to fix the speaker labels. This is my biggest gripe with the tool, which I’ll detail below. If you don’t fix the speakers here, all the downstream features that quote people will be wrong.
Step 4: Generate and Refine Chapters.
Once the transcript is clean, I go to the ‘Chapters’ tab. The suggestions are usually good. I’ll read through the titles it created, maybe tweak the wording to be more compelling, and check the timestamps. This takes maybe two minutes.
Step 5: Copy the ‘Key Takeaways’ and ‘Quotes’.
This is the payoff. I open the ‘Key Takeaways’ section and copy the bullet points into my show notes document. Then I’ll check the ‘Pull Quotes’ section. It finds a few powerful sentences that are great for social media graphics or blockquotes in the blog post version of the episode. I grab two or three of the best ones.
Step 6: Export and Assemble.
I export the final transcript as Markdown. Then I assemble my final show notes in my CMS. I use the Key Takeaways as the summary, add the chapters with their timestamps, and drop in a few of the pull quotes. The whole process, including the manual fixes, takes about 15 minutes, down from the 45-60 minutes it used to take me.
What Sucks: The Speaker Detection is a Mess
Here’s my concrete gripe. The speaker diarization (the process of identifying who is speaking when) is just plain bad. I host a show with one co-host. Our voices are distinct. Yet PodScribe AI routinely assigns my lines to him and his lines to me. It’s not just a few mistakes; sometimes entire paragraphs are misattributed.
It gets exponentially worse if you have a guest. With three speakers, the transcript becomes a chaotic mess of ‘Speaker 1’, ‘Speaker 2’, and ‘Speaker 3’ labels that seem to be assigned almost randomly. Fixing this is a tedious process of listening and manually re-assigning dozens of blocks of text. It completely undermines the ‘automation’ promise. If your podcast is primarily interviews with multiple guests, do not buy this tool. You will spend more time fixing the transcript than you would have spent doing it manually from the start.