[rokbenko]

Thanks for the feedback!

Let's say you recently became interested in X. You don't know much about it. You hear that John Doe is an expert in X.

> You don't care about your guest at all, so why would we want to listen to you talk to them?

It's not that you don't care about your guest. It's that you simply don't know much about X and John Doe.

Is this a reason not to make a podcast at all? I don't think so. Why? Because many listeners might be in your shoes (i.e., not knowing about X and John Doe). In other words... Do you only listen to podcasts when you know everything about the topic and the guest?

> As the guest, why bother responding to questions made like this?

I don't see podcasts as a ring where two egos fight. I wouldn't care about the podcast host's knowledge about my area of expertise at all, as long as they're genuinely interested in it. Isn't this exactly the reason why they invited me? To learn more about it and share it with the world?

I don't think podcast hosts and guests need to be completely "on the same level". PodcastPrepper is able to process dozens of sources from the web in parallel and create a report on the guest in about 3 minutes. If you have 0 prior knowledge about X and John Doe, with PodcastPrepper's report you quickly gain 10x more knowledge about X and John Doe. Enough to be able to make an episode.

[satvikpendem]

Why would you...make a podcast given you know nothing about that person? Or rather, the podcast created by your product is not necessarily "yours." Your product should more accurately be called a somewhat of a NotebookLM by Google, synthesizing data and in the future perhaps creating a podcast from different sources for personal use, not for being production grade enough to publish for others to listen to, as one would expect from a traditional podcast about hosts and guests, like Tim Ferriss, Joe Rogan, etc. Your product is essentially LLM deep research, with text to speech in the future perhaps. This distinction is where most commenters are getting tripped up.

[tdeck]

I could easily imagine a scenario where you do know something about a guest - enough to see that they are a compelling speaker, or have an interesting area of expertise that an audience would appreciate - without being fully "read in" on that person.

It's like when you go to a lecture hosted by an institution and they give a little intro about the lecturer beforehand. Most likely some of those little facts about the person's biography weren't known to the institution when they invited the person - they did a little extra research later to prepare the intro. They may not have known what state the person grew up in or where they did their undergrad but they looked it up in case it helps someone make a connection.

[satvikpendem]

So it's just LLM deep research as I mentioned, something that's a feature that many LLMs have these days.

[BrenBarn]

> Let's say you recently became interested in X. You don't know much about it. You hear that John Doe is an expert in X.

Then you can learn about them. That is better than asking an AI to generate questions for you without you actually learning about them.