Behind the product: NotebookLM | Raiza Martin (Senior Product Manager, AI @ Google Labs)
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What is NotebookLM and how does its Audio Overview feature work?
Hey everyone, we're here on Lenny's podcast.
It's uh great to be here. I'm a longtime listener.
So awesome. Really is. We're the hosts of a different show of Deep Dive.
And we just we just wanted to say thanks. A huge, huge thank you to everyone, everyone who's been listening.
Yeah, seriously. It's been incredible. Just incredible. And thank you to Lenny for having us.
Blown away, really, by the response and all the shows you've all had us make on Notebook LM, even that poop fart one, remember that?
Oh yeah, that was something. Learned a lot on that one.
Definitely a learning experience for everyone, I think.
But we're learning right alongside you.
Exactly. Learning and growing.
And we're glad you're along for the ride.
So yeah, keep listening.
Keep listening and stay curious. We promise to keep diving deep. And uh Bringing you even more in the future.
Stay curious.
If you are confused about what you just heard, don't worry, it'll all make sense very soon. Today my guest is Riza Martin. Riza is product lead for a product called Notebook LM, one of the most delightful and inspiring new AI products out there, incubated within Google Labs. And this product is where the intro you just heard came from. In our conversation, Riza shares how Notebook LM came to be, how it got so good, the technology that was necessary. To make it possible, how the team works internally, how it's incubated specifically within Google Labs and out of the team's 20% time, plus a bunch of really fun and crazy use cases that she's seen and a glimpse into where the product is going long term.
This was such a fun and timely conversation, and I'm excited to spread the love for Notebook LM. If you enjoyed this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to to avoid missing future episodes and it helps the podcast tremendously. With that, I bring you Ryza Martin. Riza, welcome to the podcast.
Hi, Lenny. Thanks for having me.
What the heck did we just listen to? What was that?
So that was an audio overview from Notebook LM, where you upload a source, any source, and it will generate uh an AI generated audio for you.
Okay. So for folks that don't know anything about No Book LM, it's basically been blowing up on Twitter, on LinkedIn. I think it's blowing a lot of people's minds. It's sparking a lot of imagination of what could happen in AI and what what potential we have with the stuff that's happening. And uh I wanted to bring you on to talk about the history of this product, where it's going, how it became so great and all these things. And so thanks for doing this. I know this kind of came on short notes. Yes.
Yeah, I mean I was I was excited to do it in particular because, you know, I'm I'm a big fan, big listener of Lenny's. Read the newsletter, I love it. Uh so really happy to be here.
Awesome. Uh clearly these hosts are too, which I love.
Yeah.
By the way, I love uh the slight awkwardness at the end of their conversation. If folks are whine they could hear it again, because it's very relatable. Uh I sometimes have trouble ending a podcast conversation and they're like, okay, let's say a couple more things and then okay, we're done.
It's funny because um I've listened to so many of these and they do have catchphrases they stay at the e they say at the end. And uh stay curious is one of my favorite ones.
Uh well let me just ask, is that something you all uh told them to do or is that like an emergent property?
So in this case, this is based on what they think is the most appropriate thing to say at the end.
Okay. Interesting. Okay. This episode is brought to you by Expllo, a game changer for customer-facing analytics and data reporting. Are your users craving more dashboards, reports, and analytics within your product? Are you tired of trying to build it yourself? As a product leader, you probably have these requests on your roadmap, but the struggle to prioritize them is real. Building analytics from scratch can be time-consuming, expensive, and a really challenging process.
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Chapters
8 chapters
1
What is NotebookLM and how does its Audio Overview feature work?
0:03–6:02
2
How did NotebookLM originate as a 20 % project at Google Labs?
6:02–12:42
3
What role did Steven Johnson play in shaping NotebookLM?
12:42–18:36
4
How does the team operate with a startup mindset inside Google?
18:36–24:29
5
What are the key user demographics and growth metrics for NotebookLM?
24:29–30:30
6
What is the product roadmap and future vision for NotebookLM?
30:30–36:44
7
How does NotebookLM address ethical concerns and red‑team testing?
36:44–43:29
8
How can listeners provide feedback and help improve NotebookLM?
43:29–48:56
Speakers
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