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Google Notebook LM: Exploring with WebExpo content integrations

Behind the scenes at WebExpo HQ, we try to experiment with the tools and techniques talked (or to be talked) about on the WebExpo stage. And this new Google tool has been getting a bit of buzz; Notebook LM.

We’re still getting acquainted with Notebook LM, but it has already proven to be an enjoyable tool to experiment with. Are you familiar with it? Here’s how Google describes it:

“The ultimate tool for understanding the information that matters most to you, built with Gemini 2.0. Your Personalized AI Research Assistant”.

But what does that mean? Like many of these tools, it’s really about jumping in and start using it.

For us, this is a common scenario. Someone sends us a DM with something like this:

  • “I’m a React developer, just wondering what’s on the line-up?”
  • “What design focused talks are good for UXers?”.

How does Notebook LM manage this? First up, we need to get WebExpo data in, and this is where I feel it’s a little simpler than OpenAI’s approach with custom GPTs. We’ve got a little URL flag to add to sessions (?feature=markdown if you’re curious) on our website where content is served as MD format, so this streamlines copy for LLM integrations. Once we have that, we collate the pages to a source file for Notebook LM. Once it’s in, we can chat away.

Prompt 1: I’m a React developer, just wondering what’s on the line-up?

There are several sessions at WebExpo 2025 that may be of interest to you as a React developer.

Here’s a breakdown of relevant talks and workshops:

Prompt 2: What design focused talks are good for UXers?

Screenshot from Notebook LM with WebExpo talks focused on design

So the chat is pretty neat, but that’s not all. Notebook LLM has got a few tricks up its sleeve, including the ability to have a ‘podcast style chat’, where the source material is discussed in a lot of detail. Unsure if this is too cringy and in the uncanny valley, but the audio discussion is certainly a talking point. Here’s a little demo… And yes, it’s a bit long!

While it might be a bit off the mark at some points, it’s certainly an unusual way to ‘absorb’ content or ideas, which are based around my own source inputs. That in itself is food for thought.

Other than that, it’s a really fun way to engage with content by listening or chatting and it’s worth a bit of a play.

If you want to play for yourself, you’ll need some data. Feel free to play with the markdown data we’ve used here – it’s up on Github.

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