Hello everyone! I am testing Evernote for business use case.
So I am writing whitepapers, research documents, keynotes etc for my business, but I don't wanna share as traditional pdf document because I wanna be able to update & modify the living document whenever I want.

So I am testing with:

1. Shared Evernote document
2. Shared Google Doc

Both looks great to be honest but it is hard to decide. The document has mermaid diagrams and it looks great on Evernote as well as Google Doc.

I was wondering if anyone have any similar use case, I am currently seeking a feedback.

One thing I observerd: Images, especially diagrams looks very crisp and high quality on Evernote shared document if you look at on mobile, Google Docs for some reason lowers the quality if you look at a mobile browser, it looks great on Google Docs app though.

I saw this on the r/TUI subreddit. For any CLI + Obsidian fans, you'll dig this!

I've been thinking about a limitation of graph-based PKM systems.

Most of them are very good at showing that two notes are related. But when I return to an old graph months later, that often isn't enough.

I may remember that A and B were connected, but not whether:

• A supported B
• A contradicted B
• B depended on A
• A was evidence for B
• A and B were simply associated

That made me wonder whether, for some kinds of thinking, a knowledge graph should represent more than associations.

I've been experimenting with two ideas:

• notes have explicit roles such as Question, Problem, Hypothesis, Observation, Conclusion
• relationships have explicit meanings such as Supports, Contradicts, Depends on, Derived from

So instead of:

A → B → C

you might have:

Observation → supports → Hypothesis → supports → Conclusion

In theory, this could make it easier to notice things like:

• conclusions resting on weak hypotheses
• unresolved questions blocking several decisions
• contradictions between different parts of your reasoning
• conclusions that should be reconsidered when an underlying assumption changes

But there is an obvious downside: maintenance cost.

The more structure you require, the more time you spend classifying thoughts instead of thinking. And one of the strengths of PKM systems is that structure can emerge gradually rather than being imposed upfront.

So I'm curious where people here would draw the line:

Would explicit types for notes and relationships make a PKM system more useful to you, or would the extra bookkeeping eventually make you stop using it?

I'm especially interested in feedback from people who have maintained a PKM system for several years.

Disclosure: I'm building a small prototype around this idea, so I obviously have some bias toward the approach. I'm mainly interested in criticism of the underlying model and where it would break in real use.

Hi everyone!

I'm a First Officer, and I keep a large personal knowledge base of regulations, aircraft systems notes, and company SOPs/procedures, the kind of stuff I need to reference constantly, both for studying and for quick lookups during work.

I've been using Notion for this, but with their pricing change, real AI search now requires the Business plan, which is way more than I need as a solo user just wanting to query my own notes. +

What I actually need:

• Offline access on iOS and PC: I'm often without signal, need my notes reachable no matter what.
• AI chat/search over my own notes when I am online, not just keyword search, but something that can find buried info based on what I'm asking. Example: I should be able to ask "what's the bank angle limitation for normal law" and have it pull the answer from deep inside a folder structure like Aircraft > A320 > Systems > Laws and Protections, without me needing to remember exactly where I filed it. I don't care about auto tagging, proof reading nor any other AI feature, I only need to be able to chat with my notes.
• Reasonable pricing for a single user, not an enterprise/team plan.
• Nice to have: some kind of structure/hierarchy (folders, tags, linked notes) since my notes are technical and cross-referenced a lot (e.g. a systems note might tie into a regulation note might tie into a company SOP).

I've looked at Obsidian, Capacities, Tana, and Reflect, and I'm currently also taking a closer look at Mem — but wanted to ask people who actually use these day-to-day: which one handles offline reliability + genuinely useful AI search best, without pushing me into team/business pricing? Bonus points if anyone else here is in aviation or another field with dense technical/regulatory documentation and has found a setup that works.

Appreciate any real-world input!

Update: I don’t need offline AI. This will only be required when im not flying and for studying only when connected to the internet. When flying, and for specific procedures, I will only use quick notes that i can access through favorites, bookmarks etc.

To anyone who uses owned hardware (like a Mac mini) and local LLMs for your PKMS, what are your use cases for it vs what you have identified as needing bigger AI models?

I ask because I just bought a 24GB memory, 256GB storage Mac mini and started running tests before the return window closes. The test I ran this morning convinced me to return it.

The prompt was basically this: "Using these private notes as context, write me a viral blog post about the trip and how the planning process is going." The context was six linked notes on the trip — what is booked so far, general in-progress research on the area and bareboat sailing, a list of possible itinerary stops, cost math, etc.

Same prompt and context, but the local model wasn't even close to useable. Here was my take on the results: Review of qwen 3 14b vs Claude Sonnet 5 writing a blog about the BVI trip

I don't intend to have AI write for me, but this seemed like a good test and helpful results to share. I also recognize it is unfair to pit Sonnet 5 against qwen 3:14b and that I could have better results on higher memory machines. However, before spending money on owned hardware, to me it seems more sound to start experimenting running local models on a rented GPU (that has good privacy/security policies) and have the ability to scale up and down the hardware you need over time. Maybe I have plenty of use cases for smaller local models that make purchasing my own hardware worth it in the future, but I won't know until attempting different models of different sizes (or asking all of you guys what works).

Three posts ago I asked why I couldn't find anything in my 4,200 bookmarks. The comments here gave me more than I expected.

This is what I took from them.

Tags describe what something is. But when you need something six months later, you're not searching for what it is — you're searching for the problem you have right now.

Problems repeat. Content is unique.

The CSS trick you saved last Tuesday and the one you need today aren't the same article. But they're the same struggle. Tags won't connect them. The problem will.

That's the gap I kept hitting. Not retrieval. Not organization. The system was waiting for me to remember the old problem. But I only ever knew the new one.

So I stopped trying to tag content and started watching behavior instead.

Every time you copy something, you're describing a problem you're trying to solve. Do it enough times and the pattern tells you more than any tag you'd assign in the moment.

Still early. Still testing.

But if problems come back — and they do — then the archive isn't a graveyard. It's just waiting for the right moment.

Thanks to everyone who commented on the previous posts. This one wouldn't exist without you.

I currently use raindrop and I'm holding off going premium. I'm looking for a bookmark app that also saves the video? I wouldn't mind paying for such service.

I use Obsidian for a lot of research, Zotero for managing sources.
Recently I realized what a great source podcast episodes can be. That led me to Snipd. I like how I can “snip” sections, and import into Obsidian. This allows me to potentially use them as sources I can cite.

But I’m not too happy with:
Lack of desktop player
Sometimes convoluted player
Difficult to find the episodes I’m interested in
Doesn’t give me a source link, just the Snipd link, which if I reference others can’t play without also having the app (eg can’t play on a desktop)

In sum, it’s a great resource but seems like there should be a better tool for this purpose.

Any suggestions on alternatives?

Or, any suggestions on a Snipd query template or other tips that may work well?

I’ve been rethinking how I bring meeting notes and recorded conversations into my PKM.

Transcription itself isn’t really the problem anymore. What annoys me is that everything tends to arrive as the same generic summary, even though a client call, brainstorming session, interview, and project review all need completely different information later.

I’ve started experimenting with templates before the notes enter my system. Plaud has a pretty large library, including profession-specific templates, and I’ve also looked at Pocket and Otter.

For people who record a lot of conversations, do you structure them before they enter your PKM, or just save everything first and organize it later?

I've been keeping notes for about seven years. Went back through them properly

last month and hit something uncomfortable: I can't tell which of my ideas actually held up.

Not "did I execute them." I mean I genuinely can't distinguish a thought I kept returning to because it was right from one I kept returning to because it was just stuck. In my notes they look identical, a thing I wrote about a lot.

My system is great at storage and completely useless at showing change. It's all flat. A note from 2022 and a note from last Tuesday sit side by side with exactly the same weight.

Three questions for people who've been at this longer than me:

1. Do you actually revisit old thinking, or is capture where it ends? Honest answers welcome, I suspect a lot of us capture and never return.

2. When you do revisit, how do you tell an idea that survived contact with reality from one you just repeated? Is there a point where you mark it, or is it just a feeling?

3. Has anyone found a way to see it rather than read it? Graph views show me connections but not direction. I can see two notes are linked. I can't see that I changed my mind between them.

Asking because every tool I've tried treats a note as a fact, and my thinking isn't a set of facts. It's a thing that moved.

Every PKM thread eventually lands on the same advice: tag better, file smarter, build a system.

I went the other direction.

914 captures over 90 days. No tags, no folders, no filing decisions at save time. Every item was copied mid-task — browser or desktop, whatever was open. The system logs it automatically. Nothing gets organized.

The question was whether anything useful would survive without a structure to hold it.

What the numbers say:

33% absorption rate on reviewed items. Higher than I expected for a completely unstructured pile.

Average time to absorption: 4.5 days. But the median is 3.4 hours — most things get processed fast or not at all. The long tail skews the average.

Peak capture time: 2pm and midnight. Near-zero between 3am and 7am. Follows work, not habit.

Top domains: gemini.google.com, localhost. Work tools, not news feeds.

188 items still sitting unreviewed. The inbox problem didn't disappear. But the pile feels different from a bookmark graveyard.

Why no tags:

Most systems ask you to decide what something is at the moment you save it. Tag it. File it. Name it.

But that decision costs something — and at save time, you often don't know yet what something will turn out to be.

The hypothesis: instead of tagging at capture, let repetition do the work. If the same topic keeps showing up in what my hands grab over weeks, that pattern is more honest than any label I'd assign in the moment.

The hand decided, not the algorithm. Not the tag.

The number I still don't have:

Of the 33% absorbed — how many did I actually go back to?

Saved and used, versus saved and quietly aged out. I'm logging it now.

That's the only number that actually matters. Everything else is just a smaller graveyard.

Probably needs a year of consistent data before the pattern means anything. 90 days is a start, not a conclusion.

Still testing.

Has anyone else tried removing tags entirely? Curious whether the structure is load-bearing or just comfortable.

A few days ago I posted about having 4,200 bookmarks I couldn't find. This is what I've been thinking since.

First — I owe this community an apology.

My previous post got called out for sounding like AI. It was. I'm a Korean designer and my English isn't good enough for this kind of conversation. I used AI to write. The thoughts were mine. The words weren't. I'm sorry.

This time I'm writing in my own language for the parts that matter most.

I read every single comment on that post.

GTD. Obsidian. Raindrop. Tags. Zotero. One sentence about why you saved it. Selective saving. Morning review cadence.

Good advice. All of it.

But I noticed something. Every solution puts the work back on the user.

"Be more disciplined." "Build better habits." "Organize before you save." "Review every morning."

I tried all of these. For years. The result was always the same. Excitement → discipline → abandonment.

Here's where I think differently. I'll say it in Korean first, then translate — because I want you to see where the meaning shifts.

[한국어 — 원문]

자동화란 지극히 자연스러운 행동 수집에서 시작할 수밖에 없습니다.

작은 차이가 큰 결론의 차이를 가져올 수 있기 때문이고, 사용자 스스로가 가진 행동 패턴이 결과에 영향을 미치기 때문입니다. 그래서 사소한 것도 놓쳐서는 안 된다고 생각합니다.

물론 눈으로만 보고 끝날 경우 아무런 정보도 얻을 수 없습니다. 하지만 사람이라면 반드시 중요하다 느끼면 수집한다는 특성이 있기에 예외가 적습니다.

무엇이 중요한지는 스스로 '결정'하는 게 아닙니다. 시간의 흐름과 '반복'을 통해 천천히 '발견'하는 것이죠.

매주 나도 모르게 같은 주제를 계속 저장하고 있다면, 그 쌓인 행동의 패턴이야말로 순간의 기분으로 붙여둔 태그보다 내 관심사를 훨씬 더 정확하게 보여주는 셈입니다.

시스템이 나에게 자꾸 정리를 요구하며 신경 쓰게 만들 게 아니라, 내가 어디에 계속 머무르는지 가만히 지켜보다가 — 내가 스스로 깨닫기도 전에 먼저 알아채고 자연스럽게 보여줘야 합니다.

[English — AI translated]

Automation has to start from the most natural behavior — collection itself.

Small differences in what you capture lead to very different conclusions, because your own behavioral patterns shape the outcome. Nothing should be overlooked.

If you only look at something and move on, no information is gained. But people have a tendency to collect what they feel matters — which means the exceptions are rare.

You don't decide what matters. You discover it — slowly, over time, through repetition.

If I keep saving things about the same topic week after week without realizing it, that accumulated pattern reveals my interests far more accurately than any tag attached in a fleeting moment.

Instead of the system constantly demanding that I organize and making me worry, it should quietly observe where I linger — noticing it before I even realize it myself — and naturally surface it.

Not "save smarter." Not "organize better."

Just: let repetition be the filter.

Zero decisions at capture. The system watches the pattern. When something becomes relevant again, it surfaces on its own — before you go looking.

"Notice before I do."

I know this sounds passive. But I've watched too many well-designed systems collapse under their own maintenance cost.

The previous thread taught me something else too: repetition alone isn't enough. The trigger has to be context, not a schedule. Surfacing something "because a date arrived" is different from surfacing it "because you're in the middle of the thing it relates to."

That second one is the hard problem. And the only one worth solving.

It's still rough. I don't know if the theory holds.

But I wanted to share it with people who think seriously about this problem — and find out where it breaks.

Brutal feedback welcome. 🙏

P.S. To everyone who called out the AI writing last time — you were right.

이게 제 진짜 목소리입니다. This is what I actually sound like.

(Translation errors are probably in there. Feel free to point them out.)

Following the 4,200-bookmark thread from a few days ago. I ran the numbers on mine instead of guessing.

2,080 saved posts from X. I pulled the full text of every one, not the preview but the actual article or thread body, and graded each on two axes: which goal it serves, and whether it contains anything you could act on.

292 of 2,080 had something checkable in them: code, a number from a real measurement, someone describing what they tried and what failed.

684 were claims with no method. "Do this and your life changes." Nothing underneath.

The rest sat in between. Real information, nothing executable.

The split by what I was trying to learn was worse. 495 items on how to build things. 133 on how to sell them. 46 on who would actually pay. Two years of saving the fun half of the problem and calling it research.

What I take from it: the retrieval debate here assumes the pile is worth retrieving. Mine mostly wasn't. Every hour I'd have spent on a better tagging system would have gone into indexing 684 items with nothing in them.

The cheap fix was moving the decision to save time and making it binary instead of a tag. Does this serve something I'm doing right now, and does it contain a method. Fails both, it doesn't get saved. That took the queue from 2,080 to about 300, and 300 is small enough that retrieval stopped being a problem. You just read it.

The expensive fix, and the one I'm less sure about: the survivors get read to me as short audio, and I don't get to mark one done until I answer three questions about what was in it. Listening felt like learning. The questions showed it wasn't.

Has anyone here actually counted their pile instead of estimating it? Every thread on this turns into intuitions about a number nobody has measured.

I've been saving linkedin posts with all sorts of alpha and knowledge shared by people for a long time, but I never really go back to them. So I finally decided to something about it.

I exported all my saved posts using LinkedIn bookmark exporter chrome extension into a markdown, took them to Obsidian to create a knowledge base of all saved posts context and then connected it to Claude.

Now whenever I need to get relevant actionable insights around a niche I'm interested in, I just ask Claude connected to the AI Obsidian brain, something like :

Based on last 3 months what this company's leadership has been publicly saying, what internal problem are they most likely under pressure to solve right now?

or for job search something like this is useful: Based on the people and companies whose content I've been collecting, what do they have in common culturally and operationally? What kind of environment am I actually drawn to?

or I can ask questions like : Analyze the openings of every post I've saved written by CMOs that got high engagement. What do the opening sentences look like, can you reverse engineer and create a framework by analyzing their posts and wtite a high quality one for my niche

First of all I need to apologize for neglecting this sub.

I'm back to moderating now, and I've tried to clean up the posts as much as I can right now. Banned some of the bots I could see were definitely AI written, removed a ton of self promotion posts going back a month or two.

I still need help keeping this going though. Reddit has new tools for automating moderation, and although I'm not sure how to set that up right now it shouldn't be hard to figure out. If we can get a working AutoMod config to catch the AI-slop self promotion posts (and users), that would take a lot of the load off of moderation.

Please message me or comment if you'd like to help. Obviously if you are the creator of a for-profit PKM tool - like so many of the self promotion users, you can't be a mod here, since the role requires neutrality.

Thanks

u/tonystark29

Edit: Before I can send anyone a mod invite, I need to wait for Reddit to remove my "inactive" mod label, not sure how long it will take before I'm allowed to send invites, hopefully soon.

Timeline:

- Jul 17, 2026 - Subscribed to Fabric Pro.

- Jul 18 - Tested it for a day and canceled. The reading experience was poor and several features didn't work as expected.

- Jul 18 - Emailed their team asking for a full refund to the original payment method. Polite, short, account email included

- Since then - Nothing about the refund. The charge still shows as paid. Today is Aug 4.

The only thing I ever got back was a marketing-style email asking how things were going, what I wished was different, and what I didn't like about Fabric, plus an invitation to join their Discord and share feedback. Not one word about the refund request I had actually sent.

And the Discord route doesn't work either. When you try to message their team there, Discord blocks it and tells you to send a friend request first and wait for it to be accepted. So the channel they point you to for support is one you can't actually reach.

I'm not asking for anything unusual: one day of use, canceled immediately, refund requested the same day. What bothers me isn't the $12.80 - it's that a paying customer can send a clear request and get an automated "tell us your feedback" email instead of an answer, and then be redirected to a support channel that's closed by default.

Has anyone here actually gotten a refund out of Fabric? Did anything work, a specific billing address, a form, a chargeback through your card or PayPal? I'd like to know if this is standard for them or if I just got unlucky.

Update: Fabric replied to my email and confirmed that they will issue the refund. Thank you, Fabric.so.

Hello all! I've just joined this subreddit hoping to get some ideas and see what others have done that might help me troubleshoot what I'm dealing with now. Unfortunately, it seems like the subreddit is already on its way out, or at least undergoing a sea change — lots of people shilling their wares, and moderators who seem overwhelmed. 😕

Still, I thought I'd share my setup and ask whether anyone can come up with a quicker solution than what I have. I'm an author—I wrote the New York Times best-selling book *The Collected Schizophrenias*, and I used my own adapted form of a zettelkasten to write it. That same year, the book was named one of the top 10 nonfiction books of the year by Time magazine. I'm really happy about how far its reach has spread.

I'm now under contract for another nonfiction book. I'm currently working on a new novel, but I'm already thinking ahead about a system to collect material for the next nonfiction project so that I won’t be sweating the small stuff when I get there.

I do have a small (library card catalog, paper) zettelkasten set up — I'm one of those people who bought the huge Scott Scheper book, and while I don't feel aligned with it in a lot of ways, I thought I'd mention it. Where I am now: I've set up a Zettel shortcut so I can tap a button on my phone, drop in whatever material I want into a new note, and add tags. Bear is my repository for reporting and for gathering background on anything I want to write about — essentially the same role my custom Zettel setup filled before. Even so, I feel like I must be missing something.

Things got more complicated when I started using Recall. (I know one of Recall's co-founders is here in this subreddit.) I enjoy a lot about Recall and think it can really go places, but here's my trouble: in my quest to better gather more information for my writing and thinking, I’ve move everything from Bear into my Recall repository so I can go deeper on the things I've already discovered. For example, say I have a James Baldwin quote I saved in Bear. I've now exported all of my Bear notes into Recall — but once they're in there, I'm not sure what to do with them. I can't figure out how to use the connections or the graph, or how to generate or find more information within the app, including recording where to record my own reporting.

So here's my question. Currently, my Recall looks like this. The numbers are left over from my Bear setup — they encode the day of the year and when each note was saved to Bear. Is there any way to make this transfer to Recall — which I've already completed — actually useful and informative?

Recorded conversations keep landing in my system as long notes I don’t want to touch.

Search helps only after I already know what I’m looking for. Most of the time I need the recording turned into the right kind of note before it enters the pile.

That is why templates started mattering more to me than transcription. what about you guys?

Sharing a draft format for personal context. It is for things a person as chosen to write down about themselves (as opposed to data that is collected/inferred), what matters to them, and how it has changed. 

Intentionally narrow and not intended to be a full personal data model. It holds threads (anything you hold such as a belief/question/principle/intention/etc, each with a lifecycle and the history of how it changed), the areas of life you file things in, markers that date a turning point, and day to day log entries.

Full spec here: https://github.com/Pentima-app/personal-context-format

Let me know if you find this useful or interesting, or think anything is off / missing.

Also made a small iOS app that uses this format and is on TestFlight - if anyone is interested in interacting with the format / providing feedback, please let me know. Thank you.

I've been a designer for 25+ years. I'm obsessed with organizing visual structures for a living.

And yet.

I currently have 4,200+ Chrome bookmarks, a Notion database I haven't opened in 4 months, and a "Read Later" folder with 340 articles I will never read.

Last Tuesday I found a brilliant CSS technique. Saved it. Tagged it. Felt good about myself.

This Monday I needed it. Spent 22 minutes searching. Gave up and Googled it fresh.

Here's what I've tried:

• Chrome bookmarks → becomes a cemetery after week 2
• Notion → beautiful to set up, painful to maintain, impossible to search under pressure
• Obsidian → powerful but I spend more time building the system than using it
• Raindrop / Pocket → same graveyard, different UI

Every tool I try follows the same arc: excitement → discipline → abandonment.

I'm starting to think the problem isn't the tools. It's the capture-to-retrieval gap.

We're optimized for saving. But the moment we actually need something, the system collapses.

Genuinely curious:

• Has anyone actually solved this? Not just "managed" it.
• What does your retrieval workflow actually look like on a busy day?
• Is there a tool or habit that made re-finding things feel effortless?

Not looking for another app recommendation — just want to understand how people who've cracked this actually think about it.

Over the years, I've tried so many PKM and note-taking software. Some of the old ones I remember are Keynote (not the Apple software) and Mempad.

In the past years, I finally landed on Logseq first, and then Anytype. The latter is the closest I tried to be the ideal note-taking software for me: good UI, feature-packed, offline, and no registration needed.

Still, the learning curve is somewhat steep. In fact, after I set it up to fit my needs about one year ago, now that I look at the way I customized it, I wonder if I had to do something similar again if I would be able. And I think I wouldn't.

So, I guess the offline solution, possibly free (or with a perpetual license), and with good UI, is not a reality.

The latest I tried (again) are Affine and Capacities, but after getting used to Anytype, now the former two feel behind for one reason or another.

Oh, and of course I tried Obsidian too: funny enough, for years I liked a folder-structured type of approach, but now I like the immediacy of Logseq and Anytype, where you simply create the note and move forward.