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What is the best way to organize files? | Build Your Second Brain Series (6/10) thumbnail

What is the best way to organize files? | Build Your Second Brain Series (6/10)

Shuvangkar Das, PhD·
5 min read

Based on Shuvangkar Das, PhD's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.

TL;DR

Divide everything into exactly 10 main areas, then break each area into numbered subcategories to create unique folder addresses.

Briefing

A simple “Johnny Decimal” (JD) system—organizing files into 10 numbered areas and then numbering subcategories—aims to make digital documents instantly findable and keep teams aligned. Instead of relying on memory or random folder naming, the method uses sequential numbering so the most frequently used categories naturally appear first, reducing the time spent hunting for the right place to store or retrieve a file.

The JD system starts by dividing everything into 10 main areas. In a company setting, those areas might be finance, marketing, sales, or administration; for an individual, the areas can be personal, academic, tools, and so on. Each main area is then broken into multiple categories, with a sequential number assigned to each category. The result is a unique numeric “address” for every folder. That structure brings three practical benefits: categories sort automatically, folder locations become easier to remember through “hand memory,” and file queries speed up because users can jump directly to a folder by typing its number. The system also emphasizes a key operational rule: nothing should be more than two clicks away.

Crucially, the method isn’t limited to one storage location. The same folder logic should be replicated across every part of a “second brain” workflow—explicitly including Google Drive, Zotero, and Obsidian. When the numbering scheme stays consistent across applications, adding a file to the correct place becomes less of a decision and more of a routine. That consistency also helps teams: a shared structure reduces the need to repeatedly explain where information lives.

The transcript then illustrates the approach with a Google Drive layout tailored to a PhD student. The drive is divided into 10 main areas, with smaller numbers reserved for the areas the user works on most. A “readme” file is placed in the top-level structure to clarify what each area contains—especially useful when collaborating. The example categories include “Home” for personal material (with a practical note about what could be donated if needed), “Academic” for coursework and related subjects, and “Tools” for microcontroller work, programming, simulation software, and daily research tools.

Other areas include “General,” which holds everything outside academic studies such as books (non-fiction and fiction), personal knowledge management, finance, investment, and productivity. The most important area, “Content,” is reserved for internet-facing outputs: YouTube videos, blog content, books in progress, future publishing plans, courses, and social media posts. The takeaway is straightforward: there isn’t a universal “best” organization method—what matters is adopting a structure like JD that fits how the user (or team) actually works, and then applying it consistently.

Cornell Notes

The JD (“Johnny Decimal”) file organization system divides all information into 10 main areas, then numbers subcategories so every folder has a unique numeric address. Smaller numbers go to the most frequently used categories, which makes sorting automatic and keeps the most important items near the top. Numbered folders also build “hand memory,” letting users find items quickly by typing a number and keeping retrieval to about two clicks. The method works best when the same structure is repeated across tools like Google Drive, Zotero, and Obsidian, so file placement and retrieval become routine. A practical example for a PhD student shows areas like Home, Academic, Tools, General, and Content, with a readme file to help teams understand the system.

How does the JD system make folders easier to find without relying on long search sessions?

JD assigns numeric addresses to folders by dividing everything into 10 main areas and then numbering subcategories within each area. Because the numbers determine order, frequently used categories can be given smaller numbers so they appear first. Users also build “hand memory” for where folders live, and retrieval can be faster because someone can type a number (e.g., “11”) to jump to a specific folder such as “tax return.” The workflow aims to keep any item within about two clicks.

Why does JD recommend using the same structure across multiple applications like Google Drive, Zotero, and Obsidian?

Consistency reduces decision fatigue. If the same numeric scheme and folder logic appear in Google Drive, Zotero, and Obsidian, users don’t have to mentally translate where something belongs each time they switch tools. That means placing new files becomes more automatic, and team members can follow the same map of categories across systems.

What is the role of the “readme” file in the example Google Drive structure?

A readme file sits alongside the top-level areas to explain what each area contains. In a team environment, that documentation helps people understand the structure without needing repeated explanations. It also clarifies the intent behind categories, which makes the system easier to adopt and maintain.

How should the numbering scheme be chosen for main areas and categories?

The transcript emphasizes assigning smaller numbers to the most important categories that get used most often. That way, sorting happens automatically and the most relevant folders appear at the beginning. Subcategories also receive sequential numbers so each has a unique identifier, enabling quick navigation by numeric queries.

What does the PhD-focused Google Drive example include, and how does it map to the JD principle?

The example divides the drive into 10 main areas, with the most frequently used areas assigned smaller numbers. It includes Home (personal items), Academic (coursework and related subjects), Tools (microcontroller work, programming, simulation software, and daily research tools), General (books, personal knowledge management, finance/investment, productivity), and Content (YouTube videos, blog content, books in progress, courses, and social media posts). The structure demonstrates how JD can be tailored to a specific life and research workflow.

Review Questions

  1. What are the two levels of organization in the JD system, and how do numbers function at each level?
  2. How does assigning smaller numbers to frequently used categories change day-to-day navigation?
  3. Why does repeating the same structure across Google Drive, Zotero, and Obsidian reduce friction when storing and retrieving files?

Key Points

  1. 1

    Divide everything into exactly 10 main areas, then break each area into numbered subcategories to create unique folder addresses.

  2. 2

    Assign smaller numbers to the most frequently used categories so sorting automatically surfaces what matters most.

  3. 3

    Use the numeric structure to build “hand memory,” enabling faster retrieval by typing folder numbers.

  4. 4

    Design the system so any file should be reachable in about two clicks, reducing the need for searching.

  5. 5

    Replicate the same JD structure across all tools in the workflow (e.g., Google Drive, Zotero, Obsidian) to make file placement routine.

  6. 6

    Add a readme file to document what each top-level area contains, especially for team environments.

  7. 7

    Adopt JD because it fits how you work; there’s no single universally “best” organization method.

Highlights

JD turns folder navigation into numeric addressing: unique numbers for categories make retrieval faster and more predictable.
Smaller numbers for frequently used categories create automatic sorting that keeps key folders near the top.
The system works best when the same numbering scheme is repeated across Google Drive, Zotero, and Obsidian.
A well-documented top-level structure (including a readme) helps teams adopt the system without constant explanations.

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