Nathaniel Whittemore

Users can also build out custom instruction sets for Gemini within their notebooks, allowing them to modify the model for each different project they have.

Still, Josh Woodward from Google argues that this goes beyond the normal project settings.

He writes, Most AI chatbots give you basic projects.

Gemini just built you a second brain.

He goes on to call notebooks some of the magic of Notebook LM directly integrated into Gemini app.

Basically, you can take the resource management that you're doing in Notebook LM and put it directly in the Gemini app.

Writes Google, Think of notebooks as personal knowledge bases shared across Google products starting in Gemini.

Now, one of the common critiques you will hear when it comes to Google is that even if people like their models, the product suite is so spread out across all the different surface areas that people interact with Google through that it can be confusing and even overwhelming.

It makes sense then, based on that, to see them start to consolidate, if not the surface area of the products, the transportability of the features across those different surface areas so that effectively any door you walk in gets you to the same room.

This may not be a full model, but I think when it comes to many Gemini users' day-to-day experience, this will be an even bigger improvement than if they had released Gemini 3.3.

Now, for those of you who are interested in going a little bit deeper in anthropic managed agents, I think I'm going to do a main episode about harness engineering soon, where we'll dig deeper into that.

For now, however, that's going to do it for today's AI Daily Brief.

Appreciate you listening or watching, as always, and until next time, peace.

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