, and a few thousand words of other compiled research. As I imported each source, NotebookLM generated what it calls a “Source Guide,” with a paragraph summarizing the doc and then a list of key topics and suggested questions to ask. In general, the guides were very good: for that Levy story, it surfaced “Electronic spreadsheet,” “VisiCalc,” “Lotus 1-2-3,” “Spreadsheet modeling,” and “Spreadsheets and decision-making.
Along with every answer, NotebookLM provides citations. They’re not sources, exactly, since the underlying model isn’t just searching for and returning text; they’re more like points on a map, the 10 bits of text that NotebookLM deemed most relevant to the question and then synthesized and used in order to provide an answer.
Raiza Martin, the product manager in charge of NotebookLM, says my experience seems to match other NotebookLM users. “The source guide and citations are the two top features that get called out the most,” she says. “We’re also seeing behavior change, where more and more people are like, ‘Oh, I have to read something, so I put it into Notebook so I can generate the source guide.”
Speaking of the internet: one odd quirk about NotebookLM is that it actually does know things that aren’t in your documents. At one point, I asked for information about an old Excel competitor that was referenced in one document I’d uploaded, but only by name and with no other information, and NotebookLM spat back some basic information about when it was founded and what it did.