Mind Readings: Making a Podcast with Generative AI, Part 2

In today’s episode, you’ll learn how to create a custom AI interviewer for your podcast using ChatGPT. You’ll witness the process of refining system instructions, crafting a unique podcast host persona, and preparing for an engaging AI-driven interview. Join us as we delve into the world of generative AI podcasting!

Mind Readings: Making a Podcast with Generative AI, Part 2

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.

Christopher Penn: Welcome back! This is part two in our series of creating a custom generative AI podcast interview. In part one, we did audio setup (kind of, sort of) because it’s so wildly variable based on the equipment you have. We also did the priming process for a generative AI tool like ChatGPT, giving it the background knowledge we need to conduct interviews well.

In this section, we’re going to actually create the interviewer. So, let’s go over to ChatGPT. I’m going to pick up where I left off last time. We’ve got the big three questions we asked: “Hey, what do you know about this topic? What mistakes are common for less experienced folks? What are some expert tips and tricks?” Now I’m going to say, “From this information, create a comprehensive list of best practices for podcast interviews. Incorporate all the discussion points so far: best practices, mistakes to avoid, and expert tips and tricks. Return the best practices in list format.” This is going to help the model consolidate some of its information and deduplicate a lot of it because, when we went through the priming process previously, you could see there was a fair amount of overlap.

So, we’re going to have it research thoroughly, ask open-ended questions, create a comfortable atmosphere, listen actively, be flexible and adaptable, use the question funnel approach, ask “why” and “how” questions, balance conversational and challenging questions, frame questions to elicit emotion, use the empathy echo technique, leverage silence, tailor your energy to match the guest, avoid interrupting, break up the interview with surprising or fun questions, have a signature question or segment, monitor nonverbal cues, use audio cues to signal topic shifts, end with a strong forward-looking question, give the guests time to promote their work, tailor the interview to your audience, and prioritize sound quality.

All right, while it’s doing that, let’s get a text document rolling here. This text document is going to store this list of best practices; we’re going to want to reuse it. I’m going to copy it and paste it in here. You’ll notice it comes out in Markdown format. This is a specific scripting style. By the way, this is one of the dead giveaways if someone is copy-pasting straight out of ChatGPT. It’s a dead giveaway that they’ve used ChatGPT, Gemini, or any of the AI models because they all publish their results in Markdown.

Okay, next, we are going to create system instructions for a large language model like ChatGPT to act as an interviewer on a podcast. The personality name is Grace Parker Thompson, an experienced podcaster. The purpose of the system instructions is to help an LLM be an effective, insightful interviewer for a podcast guest. Using everything we’ve discussed so far, write system instructions for the Grace Parker Thompson personality, podcast host personality. Write system instructions in second-person imperative.

All right, so now we’re going to have it build essentially its own code. Hmm, I’ll stop this and go back because I forgot something when getting started. The user should provide the guest name and the topic of the episode. If the user does not provide this information, Grace Parker Thompson should ask for it. Otherwise, it will just start rambling. That’s never good.

Okay, we’ve got our system instructions. Let’s copy them. Let’s start a new text document and see how we are. We’re at 5,600 characters, which is about what ChatGPT will allow for system instructions. So, at some point, you would be able to use this in a custom GPT. However, we cannot do that today because the advanced voice interface is only available on mobile apps.

The next step in the process: we should just test this thing out on the desktop. We don’t want to use it in audio because you only get a certain number of minutes per day of audio, so you don’t want to burn those minutes testing if you can do it in text first. So, I’m going to copy the system instructions. Now, let’s go ahead to GPT. GPT is going to create a GPT, and we’re going to call this “Grace, Synthetic Podcast Host GPT, a podcast interviewer”. We’ll paste in the system instructions. We don’t need image browsing; web browsing is probably a good idea. Let’s go ahead and create this.

And we’ll make it available to anyone with the link. I’m going to go, while we’re waiting, and get a blog post—or actually a piece of content I wrote on LinkedIn.

Okay, let’s view the GPT. “Today, your guest is Christopher Penn. Here is his bio.” Let’s go to the Trust Insights website, go to About, Team Bios, Christopher. “Christopher will be discussing this article he wrote,” and we will paste this in. Now let’s see what happens. Let’s see if our synthetic podcast host does a good job. “Thanks for the information. Looking forward to having Christopher on the show. Warm up, Grace. Chris, you have been a thought leader in AI for decades. What’s been the most exciting part of watching it move into the mainstream the past few years? Your article on AI detectors being a joke makes a bold point. What first inspired you to write this piece? You use the Declaration of Independence as a fascinating example of AI detectors’ failure.” Okay. Yep. I mean, these are decent questions. Yeah, I like this.

Let’s—we could go back to the system instructions and ask it to…let’s do this. Let’s just upgrade the instructions. One of the challenges of podcast interviews is that interviewers often ask the same questions. Let’s make sure Grace Parker Thompson asks challenging, non-obvious questions, pushes the guest politely and civilly to answer questions instead of evading questions, and conducts the interview with the goal of eliciting new knowledge from the guest that hasn’t been discussed before. Update the system instructions. Part of what makes a show like Hot Ones, for example, really good is that Sean Evans and his research team ask questions that no one’s ever asked before. You can see that when the guest is like, “How did you even know about that?” So, we want to try and get at least a little bit of that into these instructions. Check, check. There we go.

How about now? That’s more like it. Okay. So, we’ve got our upgraded instructions here. Let’s copy those, bring those to our text document here, inspect them. 8,200. That might be a bit much, but we’ll see. Let’s go ahead and—back to our GPT. Yep, only 8,000 characters. So, let’s go ahead and do some trimming here. There is no audience. So there we go. 7,930. Update.

Okay. Let’s go to the GPT, and now let’s repeat that same initial prompt. So, I’m going to go to my prompt, copy it, start a new chat with my synthetic podcast host, and we’ll test this out. Okay. This is much better. This is going to be a fun show.

So, this is the end of part two. We have built the synthetic podcast personality. In part three, we’re going to try bringing this into the advanced voice interface. So, stay tuned for that. If you enjoyed this video, please hit the like button. Subscribe to my channel if you haven’t already. And if you want to know when new videos are available, hit the bell button to be notified as soon as new content is live.

Mind Readings: Making a Podcast with Generative AI, Part 2

Machine-Generated Transcript

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