7 Conclusion to Part II

In part II of this book, we’ve walked you through a range of tools and strategies designed to help you build an effective, AI-enhanced note-taking system, one inspired by Niklas Luhmann’s Slip-box method. At the heart of this system lies the principle of interlinking: creating webs of insight by connecting individual notes, ideas, and pieces of information to one another. The goal is to transform note-taking from a passive act of recording into an active process of thinking, learning, and knowledge building.

To help you construct this kind of system, we introduced several categories of AI-driven tools. We began with foundational platforms like Obsidian and Notion, both of which allow you to create, connect, and expand your ideas in a non-linear, networked environment, perfect for emulating the Slip-box structure. Next, we explored AI meeting assistants, which take the pressure off real-time documentation by capturing, transcribing, and summarizing live conversations, allowing you to focus on the discussion while still gathering valuable material. From there, we turned to mind mapping tools, which offer a visual, non-linear way to represent complex relationships and ideas. Finally, we wrapped up with reference management tools, essential for organizing your academic sources and building a long-term research library that supports your writing, collaboration, and scholarly development.

Now that you’ve laid the groundwork and built your personalized note-taking system, we’re ready to move on to the next major stage in the academic research process: searching for academic literature. Your note-taking system will accompany you throughout this journey and far beyond. That’s precisely why we began here, because having a thoughtful, connected, and efficient approach to capturing information is the foundation on which all the rest of your research will stand.