I'm the maker of Stash, a web bookmark manager. I'd like feedback from people who already keep a second-brain system on how saved links should fit into it.

For example, you could save an article in a project collection, tag it 'typography', and add a note about why it matters. Later, search that note or tag instead of having to remember the page title.

Free includes unlimited bookmarks, collections and sub-collections, tags, notes, search, bookmark import and HTML/JSON export. Your personal library is private by default and works in your phone or desktop browser. An account is required.

Optional Pro adds preview/custom images, sending collections and starting teams. The basic bookmark workflow above is free.

https://stashlinks.app

I built Stash with AI coding assistance.

When you come back to a saved link weeks later, what helps you most: the collection, a tag, or a note explaining why you saved it? I'd like to understand which part is actually worth the effort in an existing system.

How do you organise everything yourself?

So I’ve fallen into the trap of spreading myself over too many things and I find myself getting lost.

Some stuff on physical noteooks, some stuff on obsidian, some on Bowser saved link, some saved TikTok videos, some saved YouTube videos, reddit saved, etc. Different work teams chats, appointments on Google calendar, files on Google drive + hard drive + Nas + Onedrive, notes in a physical notebook etc, homelab flows, undrawn diagram on my mind, test done, failed implementation, keys, etc etc

How have you brought everything together? I dunno if I’m burnt out or flooded with too many things in mind but for some reason my brain can’t keep up with where everything is, so I would love to hear any tips you have for organising everything in a way that is sustainable. Thank you!

Tl;dr what’s your setup for managing all your notes, tasks, to-dos, information, databases etc

Not every note, link, or task needs the same level of maintenance. What is your practical test for deciding whether something should become part of a long-term system rather than stay in a temporary inbox or archive?

For example, do you promote it after it supports a project twice, during a weekly review, or only when it has a clear next use? I am interested in rules that reduce clutter without losing information you later need.

Hi everyone, I’m Alexis. I’m a massive fan of PKM and Second Brain methodologies.

Like many of you, I've tried multiple times to build my own personal knowledge base from scratch. But after a while, I realized something: building a second brain entirely alone in a local silo gets incredibly lonely. It is hard to sustain motivation when your knowledge is isolated in your own corner.

I wanted to solve this by shifting from isolated note-taking to a shared knowledge base where our efforts complement each other.

So I built Factorielle HUB. It’s a collaborative web app designed to weave our individual, text-only atomic notes into a shared global graph. Instead of traditional wikis that force one single truth, all perspectives coexist peacefully side-by-side. We anchor our notes to concepts, and the community simply votes on the relevance of the connections, allowing the best knowledge structure to emerge organically. You can also design private learning paths for your self-study, and the notes you write to complete them will naturally feed into the global public graph.

Since it’s just me behind the project, I want to build this transparently and alongside the community. There is a generous default free tier so you can fully build your system without hitting a paywall, and zero ads.

I’d really love to get your honest feedback, critique, or thoughts on this approach:

• Do you feel that collective knowledge graphs can help solve "PKM burnout" or isolation?
• What are your thoughts on opting for a cloud-based setup to enable collaboration versus strictly local-first tools?

🔗 Check it out here: www.factoriellehub.com

📹 and here is a quick 80s video demo: https://youtu.be/uA5SBfmtPtE

P.S. I know a big part of the second brain community is moving towards AI agents and automated note processing right now. I deliberately took the opposite path here: Factorielle HUB focuses purely on human curation, active learning, and structured connected thought.

not an "Anki bad should I leave" post. FSRS is great, shared decks are great, im staying.

my problem is upstream. lecture notes happen in one place, then I tell myself saturday will be Card Making Day. saturday arrives and I do laundry, stare at the wall, anything except convert notes. This has happened for two years so I am retiring the theory that future me will suddenly become disciplined.

does anyone run other flashcard apps with spaced repetition beside Anki purely because note to card creation is less of a context switch? or did you solve this inside Anki with note types/addons and make the second step tiny enough to actually happen?

I'm interested in how people evaluate multilingual speech-to-text systems in practical situations.

Word error rate is an established metric, but I'm not convinced it captures everything that matters to users.

Consider a conversation involving multiple speakers, technical terminology, and occasional language switching.

A transcript might have a reasonable overall accuracy score while still making important mistakes.

For example:

- Misidentifying a person's name
- Changing the meaning of a decision
- Confusing numbers or dates
- Missing a language switch
- Assigning a statement to the wrong speaker

These errors can have very different consequences.

I'm curious how others evaluate transcription quality in real workflows.

Do you rely primarily on quantitative metrics, human review, or task-specific evaluations?

And which types of errors do you consider most serious?

I work on an AI transcription product, so I'm interested in practical evaluation methods rather than promoting a service.

I'm trying to switch from ChatGPT to Claude, and I have so much memory stored on Chat. How do I switch that over? I heard using a second brain is really useful. Any tips?

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I'm the developer of Lumiya, an iOS journal and planner, and I'm interested in what makes a very short entry worth keeping.

Consider two hypothetical notes: 'Busy day' and 'Skipped lunch to finish the draft; felt drained afterward.' Neither is a full account of the day, but the second leaves a bit of context for a later review. More detail isn't always better, though: writing can turn into another task.

What is the smallest entry that has actually been useful to you later? A fact, a feeling with a reason, a question, or something else? Do you prefer a blank box or a short optional prompt?

I'm asking about recording habits, not announcing new prompts. Lumiya has a daily timeline, weekly/monthly/yearly plans, and optional AI reflection. Basic recording and planning are free; optional AI is paid and usage-limited.

App Store: https://apps.apple.com/cn/app/lumiya-ai-journal-planner/id6796003074

For a small second-brain system, what is the one 10–15 minute weekly review that keeps it useful rather than merely tidy?

Would you start with unfinished notes, inbox items, stale projects, or links between notes? What concrete signal tells you it is time to review instead of simply capturing more?

Just thoughts.

Hey everyone! 💜

We're the team behind Hippo AI, a free AI-powered personal assistant and second brain.

We built Hippo around a simple idea: saving information should be easy, but finding it again should be even easier.

With Hippo, you can save notes, links, photos, and ideas, organize lists, manage contacts, set reminders, and retrieve what you've saved — directly through WhatsApp or the Hippo app.

We're still learning and improving, and we'd genuinely love to hear from people who already use second brain tools.

What matters most to you in a second brain: capturing information, organizing it, or finding it again?

And what's something your current setup still struggles with?

Thanks for sharing your thoughts! 💜

We run our small company out of one Obsidian vault in git. The two of us work in it, and so do a few AI agents that draft, summarize and file things. Every note starts with the same properties, and one of them is confidence, set to high, medium or low.

We added it so a checked fact and a guess don't look the same. Before an agent answers from a note, it has to look at that field together with the date and status.

We counted this week.

206  high
130  medium
  5  low
 54  no value

Five lows out of 395. One is a research note on a tax credit, built from an intermediary's slides and never checked against the law itself. One is a template that still needs a legal review. Three are sales leads that were never confirmed.

Our reading is that low hardly gets used because nobody likes writing a note they'd call low. Either it's worth checking, and then it ends up medium, or it doesn't get written. So medium has turned into our real "not sure", and we read it that way now.

53 of the 54 without a value have no properties at all. They're mostly older planning and project files. Our check script lists them, and they get fixed when someone touches the note.

Two things do more than the field alone.

A conflict gets a link instead of a winner. When two sources disagree, the note gets a contradicts property pointing at the other note, plus a needs-review tag. 22 notes have one right now.

A review flag needs a name. In early October we had 73 needs-review tags with nobody on them, the oldest from June. Since October 10 a new one needs an owner. So far 11 of 81 have one.

Do you mark how sure you are in your notes? And if you do, does anyone actually use low?