I test a lot of productivity tools, and while a handful are impressive enough to stick around, it’s rare for one to replace my long-time go-tos — let alone stay in my workflow years later. NotebookLM was one of those rare exceptions. I first tried it back when it was a Google Labs experiment, and nearly two years later, after a steady stream of major updates, it’s still one of my most-used tools.

As impressive as the tool is, it isn’t without its flaws. And while Google seems to be working on improving it and fixing its shortcomings around the clock, I’ve found that pairing NotebookLM with third-party tools is one of the best ways to fill in the gaps. One tool I’ve been using quite a lot lately is Logseq, and it ended up complementing NotebookLM far better than I expected.

So, what is Logseq?

A fully open-source, local-first knowledge base

If you aren’t familiar with Logseq, it’s an open-source, fully local note-taking app and personal knowledge management and organization system. Given that the code is open source, Logseq is completely free to use, with no subscription tiers or features locked behind paywalls, and it’s maintained by its community.

The only feature that’s currently paid is Logseq Sync, which provides secure end-to-end encrypted syncing between your devices. This feature is still in beta, and it’s only available to users who contribute a “monthly recurring donation of either $5/month or $15/month."

The tool is available on all popular platforms, including Windows, macOS, Linux, iOS, and Android. Logseq follows an Obsidian-like, graph-based approach to note-taking, where notes are linked together to form a connected knowledge base over time. While I’ve dabbled with Obsidian a few times, I’ve never quite been able to get into it properly or incorporate it into my workflow.

I find it too complex to navigate personally, but fortunately, Logseq strikes just the perfect balance. It’s powerful and capable enough to manage a connected knowledge base, yet simple enough to actually use every day.

NotebookLM isn’t a note-taking app, and that’s where Logseq comes in

It fills the missing pieces

Now, NotebookLM is neither a note-taking app nor a personal knowledge management system. While people do treat it as one using its Notes feature, that isn’t what it’s designed to do. Instead, NotebookLM is built to be a research assistant, helping you interact with the information you upload more effectively. Before you can really do anything in NotebookLM, you need to populate a notebook with sources.

While many of the sources I add tend to be lecture slides, research papers, and articles, I also include a lot of my own notes. And since NotebookLM offers no solid note-taking capability, I rely on Logseq as my primary platform for capturing and organizing my notes. NotebookLM also currently lacks long-term organization features like folders, bidirectional links, graph view, and the ability to add tags to your notebooks.

There’s also absolutely no search capability within the tool, which means it isn’t ideal for quickly finding or navigating information you’ve already gone over before. So, something I’ve been doing is using Logseq to structure and manage all of my notes first, then feeding them into NotebookLM.

This lets me combine Logseq’s organizational strengths and easy-to-use structure with NotebookLM’s incredible learning features. For instance, I can convert the notes I take into Audio Overviews, Mind Maps, Flashcards, Quizzes, Video Overviews, and even Slide Decks. The best part is that I can upload multiple Markdown files, even throw in some other material, and then find connections across them using NotebookLM!

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The combination works both ways

You don’t have to choose just one

Similar to how I first take notes on Logseq and then add them to my NotebookLM notebook, I also use this process the other way around. NotebookLM is excellent at helping you discover connections, summarize complex information, and identify gaps in your understanding.

So, before I add new information to Logseq (in cases where I’m not starting from absolute scratch), I first run it through NotebookLM to see what insights or connections the AI can uncover. This helps me identify key points, spot relationships between ideas, and prioritize what actually matters before organizing it all in Logseq, ensuring my knowledge base stays both structured and meaningful.

Once I’ve generated these insights, I bring them back into Logseq to refine and organize them within my larger knowledge base. So essentially, this helps me avoid turning Logseq into a cluttered repository of unconnected notes. In hindsight, I essentially use NotebookLM as a temporary buffer to explore new information and insights before it finds a permanent home in Logseq.

While NotebookLM doesn’t currently let you export responses as Markdown files, there’s a NotebookLM to Markdown Chrome extension that lets you save the outputs as .md files and add them straight into Logseq.

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NotebookLM and Logseq just make sense

I’ve paired practically every productivity app out there with NotebookLM. While that’s usually because I’m looking for ways to improve my existing setup, it’s also because I’m quietly hoping I’ll come across a pairing that actually sticks. Logseq ended up being one of those rare matches. Logseq perfectly fills in the gaps NotebookLM was never meant to cover, instead of trying to replace NotebookLM.