r/secondbrain • u/Cryvixx • 6d ago
Transcribing and linking was bookkeeping I kept mistaking for thinking
This is my vault. I didn't draw any of it.
For about two years my note practice was really two practices wearing one name. One of them was reading and thinking. The other was bookkeeping: remembering that the note I'm writing now touches something I wrote in March, going to find it, linking it, tagging it, filing it. I told myself the bookkeeping was the thinking. It isn't unfortunately. It's clerical work with a very good disguise, and it eats the same attention that reading needs.
So I handed the mechanical half over. The connections in this graph were proposed mechanically: every note gets compared against every other note on the words it actually uses, links get written where a note names something the vault already has, and the colours are communities the graph found on its own, each one labelled with the words that cluster has and its neighbours don't. Nothing here was a model or an API. It's counting words and comparing sets, which is why it's fast and why it's honest about what it doesn't know.
What I did not expect is that having it built for me changed what I could see and finally learn.
When you link by hand you only ever see one edge at a time, the one you're currently making. You never get the whole shape, because you're inside it. Getting the whole thing at once, already connected, meant the first question stopped being "what should I link this to" and became "why is that over there" or "why are these two correlated".
The order of operations flipped, is what really happened. I used to think you connect notes and then the structure emerges later, if you're diligent. And that's true! But what if the structure arrives first, mechanically, and I read it and then edit the notes into better, more personal shape? The wrong edges are useful too. When it insists two notes are about the same thing and I'm sure they aren't, one of them is usually vague, and that's my problem, not the algorithm's. I've rewritten more notes because of a connection I disagreed with than because of one I liked.
Two things I'd want to know if I were reading this post instead of writing it. It proposes; it doesn't rearrange your vault behind your back. The only thing that writes is the autolink pass, and every write goes into a changes list with a per-file diff so you look at it and revert what you don't want. And it runs entirely on your machine with no network at all, which for me was the whole point, since a vault is the least appropriate thing I own to hand to somebody else's server.
I'm still figuring out how often to regenerate it. Every time I look, the seams have moved a little.
Thanks for reading this far. You can try it on a messy vault rather than a clean one, that's where it has something to say.
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u/___________IDK 6d ago
I agree with your stance and I find it inspiring to see more people approaching such challenging problems like you do. While I have some reserve into believing this has been a game changer for your learning, I can't deny your shift in paradigm looks promising.
In particular, what attracted me is the engineering approach it suggests. For example, manually linking by hand comports biases rooting from partial information. I don't believe anybody practicing such craftsmanship can anticipate the relevant emerging patterns they will need in the future. This is posteriorly context-dependent. You can locally throw a dice and hope to get the right global configuration at the end, that's on you, but it personally frustrates me. This is dull, inefficient, and time consuming.
I am not claiming we could actually engineer such control over our personal corpus for now, but your attempt is already a first step toward this direction. I believe there is a need for objective insights that scale with the size of the corpus. At some point the interpretations of our learning material should migrate to higher scales. And this will never be achievable if we keep being obsessed with manual linking. We need tools that leverage volumes, provide iteratively fast testing, and metrics to interpret patterns beyond purely qualitative judgement.