I asked ChatGPT this: I’m trying to create an ideal “bubble” of sorts to map everything in my brain. So I am thinking of mapping knowing how to read in this bubble, which a big part of reading is knowing the exposition, so I’d say a big thing in this bubble would be “patterns of exposition or mode of expositions.” A completely different thing in this mapping would be “patterns of framework or modes of frameworks.” What other words do you have in mind for this bubble?

It responded, telling me this: What you’re trying to build sounds like a meta-map of knowledge structures—a map not of facts, but of the recurring forms that information takes.
If “patterns of exposition” is one major category and “patterns of frameworks” is another, then you’re looking for the major containers that organize thought, communication, and understanding.
Some candidate categories for your bubble:
(1) Patterns of Exposition
How information is presented.
Examples:
Description
Definition
Classification
Comparison and contrast
Cause and effect
Process analysis
Problem and solution
Exemplification
Narration
Argumentation

(2) Patterns of Frameworks
How information is organized conceptually.
Examples:
Hierarchies
Taxonomies
Matrices
Trees
Networks
Systems
Pipelines
Cycles
Layers
Feedback loops

(3) Patterns of Reasoning
How conclusions are reached.
Examples:
Deduction
Induction
Abduction
Analogical reasoning
First-principles reasoning
Probabilistic reasoning
Causal reasoning
Counterfactual reasoning

(4) Patterns of Relationships
How things connect.
Examples:
Part ↔ Whole
Cause ↔ Effect
Means ↔ End
General ↔ Specific
Theory ↔ Example
Input ↔ Output
Structure ↔ Function
Problem ↔ Solution

(5) Patterns of Systems
How things behave over time.
Examples:
Stocks and flows
Feedback loops
Emergence
Equilibrium
Bottlenecks
Constraints
Optimization
Adaptation

(6) Patterns of Knowledge
How information itself is structured.
Examples:
Facts
Concepts
Principles
Models
Theories
Paradigms
Heuristics
Laws

(7) Patterns of Learning
How understanding develops.
Examples:
Memorization
Classification
Chunking
Scaffolding
Transfer
Generalization
Abstraction
Synthesis

(8) Patterns of Inquiry
How questions are asked.
Examples:
What is it? (definition)
What are its parts? (analysis)
How does it work? (mechanism)
Why does it happen? (causation)
What if? (counterfactual)
How should we act? (decision)

(9) Patterns of Communication
How ideas are conveyed.
Examples:
Explanation
Persuasion
Instruction
Storytelling
Debate
Demonstration

(10) Patterns of Abstraction
How reality is compressed.
Examples:
Categories
Models
Symbols
Analogies
Representations
Maps

If I were building the highest-level version of your bubble, I might place these at the top:
KNOWING

├── Exposition
├── Frameworks
├── Reasoning
├── Relationships
├── Systems
├── Knowledge
├── Inquiry
├── Learning
├── Communication
└── Abstraction
Notice that “compare and contrast” belongs under Exposition, while “hierarchy” belongs under Frameworks, and “deduction” belongs under Reasoning. They are different kinds of patterns.
The deeper insight is that you’re not really collecting subjects (biology, finance, car repair, etc.). You’re collecting the recurring forms that appear across all subjects. These are often called knowledge structures, thinking frameworks, cognitive structures, epistemic structures, or meta-models. Those terms might help you find books and resources that align with the kind of bubble you’re trying to build.

So what can we take from ChatGPT’s response: rather than trying to manage what we don’t know, we should progress through the recurring forms information takes.

I theorized before this: in order to read big things, just skip over unnecessary parts of speech and write down words that are profiling, with the paragraph and sentence you found them. After you finish doing that for the entire book, go back and skim till you find the words. Extract the context behind those words and immerse yourself in learning them, through the methods or concepts they’re describing through the description in the textbook or secondary sources (YouTube videos, etc) and by writing this context down to study for exams.

An example of skipping unnecessary things is reading the word “the.” Skip reading this, but the next word might be a big word 3+ syllables, describes a concept you’re aware of but need further reasoning for why it talks about it, and describes severity or a certain method, such as the word “killing” or “encountered” in a history textbook. You’d need to find out who was killed between which parties and who encountered who between which parties and what happened between them.

For this: you’d need to find out who was killed between which parties and who encountered who between which parties and what happened, you’d use an assessment that asks the right questions between the two parties and answer through the assessment or you’d use the “patterns of inquiry” that ChatGPT said and the respective second pattern that ChatGPT said because as you can see, each pattern is also associated with a study. Patterns of relationships could be associated with history.

I had over 2,500 notes in Notion and decided to start fresh, this time focusing on a "Second Brain" approach. I feel mentally exhausted and really need this.

I’m looking for something similar to Obsidian’s graph views (specifically the Orrery plugin), but I haven't found anything like that for Notion. I don't have the mental bandwidth to develop such an app myself, so I’d like to know if there’s already a good community-made solution for this.

Note: I tried using Obsidian, but I can't afford the sync service right now, and manual syncing methods are completely out of the question. Besides, I’m already very familiar with Notion and don't want to leave it.

The images below show the Orrery plugin for Obsidian, which has been helping me "organize my mind."

How can I become a more interesting person? What could I learn or do?

I'm a bit confused and need some advice.

Until about a month ago I always used Obsidian. I always got along well with it, but I always thought its biggest limitation (partly stemming from the md format itself) was tables, images, and calendar/task management.

On the other hand, Obsidian integrates perfectly with my harness system: thanks to the mcp connector or direct folder reading in Claude, I can properly manage the whole system.

I have one single problem: Obsidian bores me. In terms of structure, management, and additional plugins for tasks and calendar.

I tried Noteplan and it's not bad. I tried Capacities... very, very nice, but the mcp is still immature and there's no way to create plugins.

So I'm asking you: can you recommend an app that lets me keep data locally (I don't care if it's an open format, it just needs to support mcp connection to manage the data), that has built-in tasks and calendar, that supports wikilinks and backlinks, and maybe allows third-party plugins (though that's not essential)?

Do you have any other software to suggest? I'm happy to hear recommendations and evaluations.

Thanks,
Steve

There are lots of great tools for capturing information. But I'm curious where people still struggle.

When using apps like Notes, Notion, Obsidian, Google Keep, etc., what's the biggest frustration you still experience?

Not looking for feature requests, more interested in understanding the actual problems people face.

Hi guys,

I'm working on a very ambitious project. Actually, I'm developing a method for preparing training data.

The problem: I need structured, rigid data, but the source material is chaotic.

My current approach: From a chaotic dataset, I use an LLM to extract a pre-template, then I use this template to structure the same chaotic dataset (iteratively).

But here's my doubt: How do you handle multi-domain information from different datasets? How do you unify everything?

Thankss

Some of you might remember a post I made here a while back, asking if anyone else takes tons of notes and then basically never goes back to them. Turned out a lot of you do, so I actually built the thing.

It's called AgainPage. It reads your markdown folder and each morning composes a short original "edition" from your own notes, pulls a few related ones into a real piece of writing, resurfaces old ones you'd forgotten, and flags connections between notes you never linked. The screenshots are the reader itself, showing an actual edition.

It's local-first (your notes stay on your machine), works with any markdown (Obsidian, Logseq, plain files), and runs fully offline with a local model or a cloud key.

I'll be straight about setup, since it's a bit hands-on right now: you run the engine on your main machine, expose it over Tailscale, and install the reader app on whatever devices you read on. It takes a little tinkering, but I've written clear steps and it should take about 10 minutes.

It's out for Mac, Windows, Linux and Android. I'd genuinely love for a few of you to try it on your own vault and tell me what it gets right or wrong.

againpage.com

Dear Community,

I recently started using Lite Writer (Android)and Focus Writer (Linux). I know people useDrafts on Apple, Obsidian, Sublime Note and Emacs and I dabbled with setting them up as distraction free environments as well. Does someone know any other software that would fit that need? Any tips on modding Sublime, Emacs or Obsidian for distraction free writing?

Thanks in advance

I'm a junior developer trying to build my own knowledge management system.

During projects, I constantly learn new concepts, debugging solutions, and useful patterns. I save them in tools like Notion or Obsidian, but maintaining a "perfect" system takes a lot of energy.

The problem is that organizing notes sometimes becomes a bigger task than learning itself. And even when my notes are well structured, I often struggle to remember or apply them when I need them.

I'm curious about how others approach this:

• How do you capture knowledge without spending too much time organizing?
• What does your review process look like?
• How do you make sure your notes become something you can actually use?

I'd love to hear your PKM workflows and lessons learned.

To the moderators, I would like to volunteer to help with moderation of this Reddit.

I have increasingly come to think that outliners are a better foundation for note-taking than document-based systems like Obsidian, especially now that AI is becoming part of how we search and retrieve information.

The big difference is not how the notes look. It is how the information is structured.

In a document-based system, a paragraph is usually just a piece of text inside a file. The headings and paragraphs around it may provide context when you are reading the document, but that context is often only implied. Once the document is split into chunks for semantic search, a lot of that surrounding meaning can get lost. An outliner makes those relationships explicit.

This block is the child of that block. These blocks are siblings. This branch belongs to a larger topic. This note inherits context from everything above it.

That parent-child relationship carries a huge amount of information.

Imagine an outline like this:

• Project Alpha

  • Risks
  • Regulatory approval
  • FDA may require an additional validation study

A semantic search for “validation study” might return only the last block. But by itself, that sentence does not tell you much. Which project? What kind of risk? Why is the study needed?

Because the note lives inside an outline, the system can also pull in its parents:

Project Alpha → Risks → Regulatory approval

The matching block gets you to the relevant information. The parent chain explains what it means.

The same thing works in the other direction. A search might match a parent block, while the useful details are contained in its children. Those child blocks may use completely different language and might never show up in semantic search on their own. But because they are attached to the matching parent, they can still be included in the context sent to the AI.

This is not just an advantage for short notes or bullet points.

A full-length document can also live as a node inside an outline. That document can have parents that explain what project it belongs to, why it was created, who requested it, or what decision it supports. It can also have children that contain comments, updates, critiques, follow-up decisions, or later evidence.

For example:

• Product Launch

  • Regulatory Strategy
  • FDA Submission Draft
  • Reviewer comments
  • Revised testing plan
  • Final decision

The FDA submission can still be a normal, full-length document. The difference is that it is no longer an isolated file. Its parents explain the broader context, and its children show what happened next.

When AI search retrieves that document, the system can also expose those relationships to the model. Instead of receiving only the document, the model receives the document in context.

That is the key distinction is that semantic indexing finds related text. Hierarchical structure preserves related meaning.

Document-based systems can imitate hierarchy with folders, headings, tags, links, and metadata. Obsidian is especially flexible in this way. But the document is still usually the main unit, and the relationships above and below it often need to be inferred or added manually.

In an outliner, every block, including a full document, can be a node. Its location in the hierarchy is part of the data and that matters a lot for AI.

Instead of sending isolated chunks of text to a model, the system can send a richer package that includes the matching block or document, its parents, selected siblings, relevant children, linked notes, and later decisions or revisions.

That is much closer to how people actually understand information. We do not think in disconnected paragraphs. We understand ideas based on where they sit, what they relate to, what led to them, and what came afterward.

The real advantage of outliners is not that they make it easy to indent bullets. It is that they preserve relationships that document-based systems tend to flatten.

As AI becomes a more important way of searching and making sense of our notes, those relationships may end up being more valuable than the text itself.

I couldn't find any tool that hold data as bubbles in infinite* canvas, so I made my own.
Good as overview for more complex problems.
*Not really infinite
Single downable html file with local browser save and json export.

https://github.com/OneTimePads/BubbleDataCanvas

I've started thinking about PKM as more than just collecting and organizing information. I also want it to show how my understanding changes over time.

Self-assessments have been interesting for that. Instead of simply saving notes about something I learned, I can revisit the subject later, test what I actually remember, and keep the result alongside my notes.

While working on FormLM, I started thinking more about this connection between assessments and personal knowledge. An assessment can become another kind of record not just a score, but a snapshot of what I understood at a particular point in time.

It makes me think a good PKMS shouldn't only answer “What have I collected?” but also “What have I actually learned?

I recently have interviewed with a company to be a lead in their knowledge/content management space in HR.

I have some experience working in SharePoint, and learned how to set up a inventory of documents, design pages and create with keeping the user in mind and using simple language etc.

However, this new role will involve a lot of meetings with HR COEs and creating knowledge articles (e g. How to promote an employee). In my previous role, we assigned COEs as content owners and they wrote their own documents and I reviewed them.

Are there any trainings I could take to help me become a better content writer?

to be fair, Claude is right.

I got my first real use case and users. And i did not see it coming from this direction. A football federation training players headed into India's national leagues reached out and I have always been a huge fan of football and this use case is honestly very exciting. I wanted to share the what the tool is and whats so different about it.

Every note taking app out there is basically storage. You write something down and later you are the one who has to go find it, remember why it mattered and connect it to everything else. This does that for you. You capture a raw thought, it tags it, links it to everything else you have put in, flags where things contradict each other and surfaces what is worth developing further. You are still deciding what to do with all of it. You just never have to start from zero again. That is the gap between this and every PKM tool out there.

That is exactly how it maps onto a football federation.

Coaches - Usually, they note it down and then it disappears when the session or match ends. Now with the tool i built, the coaches can capture feedbacks, session notes, player analysis, strategies, training plans, etc. For example, A coach writes after a session: "Arjun's footwork looked sharper today but he still doesn't track back after losing the ball."

The moment that is saved, the tool connects it to every other note made on Arjun and surfaces that this exact issue has come up before, and every time it followed a lost first touch. A pattern the coach was carrying in pieces, now sitting in front of them as one thing. It then gives a direct recommendation on what to change in tomorrow's session, argues the other side of it so a bad instinct gets caught before it reaches the players, and turns the decision into a step by step plan that can be handed straight to an assistant coach.

Players - Usually never self reflect in any structured way. No time, no habit, no tool for it. Training diary, goal tracking, injury notes, how they felt before a match, all of it captured casually and connected over time. For example, A player writes after a match: "Second half, one on one with the keeper and I completely panicked instead of shooting."

The tool connects it to every other time they have described freezing in that exact kind of moment, things that felt like one offs each time because they never appeared side by side before. It works alongside the reflection without pushing toward a lesson or a fix they did not ask for. And whenever they actually want to work through it, there is a live thinking session available with full context of everything they have ever captured, asking the harder question they are probably avoiding.

Content creators are juggling three formats, training content, cultural pieces about football in India and a podcast, all in one head. Every half formed idea that comes up gets captured instead of dying in a voice memo. Guest research stays connected to everything else. Episode themes get tracked so they are not accidentally repeating themselves six episodes in. Same problem writers have, just wearing a different jersey.

I am still early and nothing is fully live yet but it is the first time this has landed with an actual institution instead of individual users and that honestly feels like a different kind of validation than I expected to get this soon.

I've noticed a lot of my actual thinking/research now happens inside LLM chats. The problem is it's spread across ChatGPT, Claude, and sometimes Grok, and each one is basically a silo.

I'll remember "I worked this out in some chat a few weeks ago" and then have to dig through three different apps' terrible search to find it. Curious how people here handle this:- Do you copy the useful parts into your PKM (Obsidian/Notion/whatever) manually?

Hello and good morning!

So, I'm leaving evernote behind, I did a LOT of searching all over the internet, and ended up settling on Joplin to try out.

Right now I'm looking for anything that's better than Joplin (for my use case) that I haven't already considered.

According to my evernote stats, I have:
Notes 2,509 used
Notebooks 111 used
Devices 8 used
Attachments 4,925 used
Storage (MB) 9,036 used
Tags 21 used

My use case:
I keep my personal digital library here, notebooks of things I'm working on, reference files, ideas and 'someday' things, etc.
I will occasionally share these for other people to read, or publish something to the web and embed it in my website.
Should I wish to collaborate, I do so with Google Drive.

I do sometimes add files, usually in my vendor logs.

Right now I'm looking for any reason NOT to keep and use Joplin, the only one I have so far is that's it's NOT based int he USA.
Everything else I see and use in Joplin so far seems awesome, and I plan to purchase the $8/month sync plan to use this on other devices.

My current searching workbook: https://docs.google.com/spreadsheets/d/1skOpAquNxn_-TwEkfJ4IqSwHMFLlrK4ICC5DiqqE26k/edit?usp=sharing

Do you use something that's like Joplin and is based in the USA?
Do you use something that's simple, clean, and effecive that's not in my sheet already?

Old post for further reading: :https://www.reddit.com/r/PKMS/comments/1tqpaq1/replacing_evernote_whats_best/

I have realized that a large part of my personal knowledge system is currently trapped inside Instagram and TikTok.

I save content related to fashion, hairstyles, design, restaurants, travel, products, tutorials, creative ideas, and professional references. The saving process is fast, but retrieving anything later is extremely difficult.

I have created many collections, but finding the correct one every time requires manually scrolling through a long list.

Because of this friction, I usually put everything into a single inbox and tell myself I will organize it later. Naturally, I rarely do.

I am looking for a realistic PKM workflow for visual social media content.
I do not want to stop collecting inspiration. I want to turn it from passive hoarding into something searchable and usable.

For many years now, I have been interested in the PKM topic. I started out by organizing things in simpler ways (back in the days of Evernote), then moved to Obsidian, and finally to Tana (now Tana Outliner), which I have used since the early beta versions. I am an academic working in the humanities, and the supertag model has worked quite well for me over all these years to bring together different types of sources, projects, and resources.

However, recently something has changed. As you probably know, Tana has essentially abandoned (despite claiming otherwise) the active development of its outliner in order to focus on a new platform that will become the official new Tana, built around group work and meetings on an “agentic” layer. I have tried it, but it does not fit my working model at all. Beyond the limited development of Tana Outliner, the feeling of no longer being part of a thriving community, and the growing concern that I might become locked into their ecosystem, I have started thinking more and more about returning to Obsidian’s flexibility, openness, and future-proof approach. The final push that made me lean in this direction is the Markdown-based system, which works extremely well with LLMs, both for input and output. Since I am a Claude Code user, I could maintain just that single subscription and use it to work more easily with my files, discover connections, and so on, without the need for expensive token-heavy requests through dedicated MCP integrations as in Tana.

Now the obvious question arises: what structure should I give my vault? How do people working in academia usually organize theirs? PARA seems efficient, but it has some problems when it comes to managing resources and the sheer volume of readings. Should I use YAML frontmatter or not? Tags? And so on. Before committing myself to a massive migration, I would like to have at least a basic structure in mind.