After the latest NotebookLM update, I’m rethinking how much I trust AI

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Every AI chatbot greets you with some variation of the same warning: “AI can make mistakes.” And if you’ve spent enough time using these tools, you’ve probably seen exactly why that disclaimer is there. Obviously, I’ve seen enough AI hallucinations over the years to become increasingly skeptical of taking anything an AI says at face value.

That’s why NotebookLM’s latest update has caught my attention. Even when I feed it nothing more than rough ideas, it manages to pull together surprisingly structured research. But that’s only a part of what’s new. The more I explored, the more I realized Google has turned NotebookLM into something much more adept than I expected.

Having used NotebookLM for everything from college projects to work-related research, I’ve seen firsthand how much effort it took to get useful results. Before this update, I had to do most of the tedious work myself — gather sources, provide context, explain exactly what I was trying to understand, and carefully steer the conversation toward something useful.

Now, the process feels very different. Instead of spending time hunting for articles, videos, and references before I even begin, I can start with a rough idea and simply talk it through. As the conversation unfolds, Gemini pulls in relevant sources that I can import directly into my notebook, review at my own pace, and use to shape the direction of my research.

What impressed me even more was how well it handled large documents. I uploaded my psychology thesis and started asking questions about specific concepts, arguments, and findings. Usually, that kind of task sends me down a rabbit hole of scrolling through pages, opening different sections, and trying to remember where I mentioned something in the first place. This time, NotebookLM did most of the navigation for me.

For instance, if I wanted to revisit a particular theory or check how I had interpreted a finding, I didn’t have to hunt through dozens of pages. I could simply ask a question, and NotebookLM would surface the relevant information and synthesize it into a clear, concise answer. The whole experience felt remarkably natural — almost like discussing the document with someone who had just finished reading it cover to cover. Needless to say, the first few times I used it, I went through everything with a fine-tooth comb, checking paragraph after paragraph to make sure it wasn’t making things up. To my surprise, it was consistently on the right track.

I keep wanting to say it does this really well. In fact, I’ve probably already thought the word really about five times while writing this paragraph. But that’s because it really does. If you’ve ever tried to find a specific insight buried in a massive PDF, you’ll understand why I’m so enthusiastic. NotebookLM doesn’t do my reading for me, but it definitely makes finding the information I need feel suspiciously easy.