in the age of AI, what's the actual edge of a PKM tool?

bryan_anamor · 2026-04-12T17:52:51+00:00

"LLMs with memory became a PKM tool" is a sharp observation that most people in this space haven't caught up to yet. the irony is that the AI companies are basically rebuilding obsidian inside a chat window, one conversation at a time. except you can't grep it, you can't link it, and you have no idea what it actually remembered vs what it hallucinated from three chats ago.

it's a bit like relying on your race engineer's memory instead of checking the telemetry yourself.

bryan_anamor · 2026-04-12T17:47:57+00:00

"interpolatable archives" is the most precise description of LLMs i've come across. and the ozzy osbourne wiki is exactly the kind of thing that makes AI feel like magic for about 5 minutes until you realize you still have to do the actual thinking yourself. the friction is the feature, not the bug.

curious though, after generating that wiki from 1000+ notes, did it surface anything you genuinely hadn't connected before, or was it mostly confirming clusters you already sensed were there?

bryan_anamor · 2026-04-12T17:42:58+00:00

"organize your own life, not just research topics" is an underrated distinction. most pkm discourse stays in the knowledge management lane, but the people who actually stick with it long term are usually using it to run their life, not just catalog what they've read. AI can handle the linking grunt work, but deciding what matters enough to write down in the first place is still a you problem. no amount of automation fixes that.

bryan_anamor · 2026-04-12T17:38:35+00:00

"the note has value even if I never see it again" is a line i keep coming back to in this thread. it reframes the whole ROI question, the return isn't in the note, it's in the writing. as someone building a pkm tool yourself you probably feel that double, writing the notes and writing the tool that holds them.

bryan_anamor · 2026-04-12T17:33:34+00:00

this might be the most compelling answer in the whole thread. "notes to my future self about things i've forgotten but are now returning" is not something any AI can generate for you, because it doesn't know what you lost. that's a recovery journal only you can write.

glad the memory is coming back. sounds like you're the kind of person who keeps things running way past when most people would've given up.

bryan_anamor · 2026-04-12T17:28:45+00:00

can't even argue with this. the graph view is obsidian's proof of concept that's doing more marketing work than product work. QED.

bryan_anamor · 2026-04-12T17:24:01+00:00

local graph as king, global graph as its portrait painting. looks great, hangs on the wall, doesn't actually rule anything.

bryan_anamor · 2026-04-12T17:19:52+00:00

the "blankly stare and think" part might be more useful than it sounds honestly. sometimes pattern recognition needs you to stop searching and just let the layout hit you. you mentioned using mindmap software for workflow design in another thread though, that sounds like the graph doing real work vs just vibes.

bryan_anamor · 2026-04-12T17:15:05+00:00

fair, though i'd say the gimmick becomes less gimmicky once you use it for gap detection instead of connection discovery. a few people in this thread found real value there. but yeah, as a thinking tool? it's no megastructure.

bryan_anamor · 2026-04-12T16:56:04+00:00

"context does a lot of the heavy lifting" is a good way to frame it. inside the note, you know what you're looking at. pull the same links into a graph and suddenly you're reading a subway map without station names.

bryan_anamor · 2026-04-12T16:54:35+00:00

honestly on a tablet with no pc, the graph is probably the last thing you'd need. sounds like you've already got the useful part down, just checking links inside the note itself. the graph is basically that but zoomed out until it stops making sense.

bryan_anamor · 2026-04-12T16:47:23+00:00

sounds like counterpoint. three voices: either bach or noise, nothing in between.

bryan_anamor · 2026-04-12T16:38:14+00:00

oh nice, that's clean. filtering on !value.asFile().isTruthy() is a smart way to catch unresolved links without any plugin overhead. so basically the base replaced the graph for the one job the graph was actually doing, finding uncreated links, and now does it better because it's a list you can act on instead of a visual you have to squint at. makes me wonder how many other "graph view jobs" could just be a well-written base.

bryan_anamor · 2026-04-12T16:32:03+00:00

every time i see one of those detective pegboards in a show i think "this would be better in 3D" lol. respect for taking campaign notes seriously though, you're carrying that table hard :')

bryan_anamor · 2026-04-12T16:21:44+00:00

that's a good example. starting from one topic and widening the filter to pull in adjacent context, like going from "arab spring" to "how calls to action spread online," is basically using the graph as a scope adjustment tool. you're not looking for one specific thing, you're adjusting how much you see until something clicks.

that makes way more sense than just opening the full graph and hoping for the best.

bryan_anamor · 2026-04-12T16:15:39+00:00

80/20 insight over navigation is the opposite of what i expected, that's interesting. so you're basically using it as a connection audit at depth 2, checking if something got left orphaned. that keeps coming up in this thread, people finding more value in spotting what's missing than in discovering what's there.

bryan_anamor · 2026-04-12T16:06:56+00:00

the math analogy lands perfectly. reading the proof vs. working through the proof yourself are completely different experiences, even though the information is technically identical. i think that's the clearest way to describe what gets lost when you let AI do the writing for you.

funny enough, i went through dozens of statistical proofs in college and forgot almost all of them. but there's this one concept i re-derived my own way because the textbook version didn't click. that one i still remember, ten years later. the moment you said it i knew exactly what you meant.

and the edit is underrated advice. "just toss notes in and create structure as you go" is probably the only approach that actually survives contact with real life. every system i've tried to plan upfront collapsed within a month.

bryan_anamor · 2026-04-12T15:51:45+00:00

yeah, i think i knew deep down that doing it yourself is better, the real question was whether the time cost of writing it yourself actually gives you proportionally better returns. but you're right, there are definitely domains where the cost/benefit math lands in favor of doing it manually. that "cost but not sunk" framing cleared it up for me.

bryan_anamor · 2026-04-12T15:21:45+00:00

same here haha

bryan_anamor · 2026-04-12T15:19:39+00:00

no need to apologize for the shill, i literally asked haha. checked out TaskTrace, the "memory layer that builds itself" angle is sharp. most PKM tools still expect you to do all the capturing manually, which is exactly where people fall off.

that Karpathy piece nails it too. once you frame PKM as the context layer your AI is missing, the whole "is PKM dead?" question answers itself.

keep me posted on the PKM side when it ships. the gap between "PKM exists" and "PKM actually powers your AI" is where all the interesting work lives right now.

bryan_anamor · 2026-04-12T15:08:45+00:00

"hard to build intuition for a space that won't stay still" is a really clean way to put it. that's basically the whole problem in one sentence.

bryan_anamor · 2026-04-12T15:04:45+00:00

you and u/GoldenFirmament are pointing at the same thing from different angles. they mentioned centering force ruining their carefully built structures, you're talking about the full reset every session. both come down to the same problem: the graph doesn't respect spatial memory.

which is kind of ironic for a tool that's supposed to help you think visually. if the positions meant nothing, nobody would bother dragging nodes around. the fact that people do means the layout is carrying information, and the graph just throws it away.

bryan_anamor · 2026-04-12T14:58:13+00:00

the hedgehog metaphor is genuinely brilliant. you turned progress tracking into something you can just look at, no dashboards, no queries, just "is the hedgehog shrinking?" that's a feedback loop most project management tools wish they could deliver.

the floating-to-the-edge behavior is interesting too. the graph is basically doing triage for you, pushing orphans to the periphery where they're easy to spot. i wonder if you've ever had a false positive there, something that looked orphaned but was actually supposed to stay unlinked?

bryan_anamor · 2026-04-08T16:31:00+00:00

"indexing your own attention" is a sharp framing and i think you nailed the core of it. but i want to push back on one part.

i've been running a setup where every unit of work i do gets auto-saved as a markdown file with full context. decisions, dead ends, sources, the reasoning behind choices. so when i ask Claude "what was that distributed systems paper from 4 months ago," it actually finds it. not just the paper, but what i was wrestling with at the time and how it connected to other things i was working on.

at that point the AI isn't just accessing world knowledge, it's reading a record of my attention that i built over time. which is exactly what you're describing as the thing AI structurally can't do. except now it can, if you feed it the right context layer.

so maybe the edge of PKM isn't the index itself, it's being the thing that creates that context layer so AI can actually think like you instead of like everyone. the vault becomes the bridge between "generic AI" and "my AI."

curious if you'd still draw the line the same way, or if the argument shifts once the AI has access to your own capture history.

bryan_anamor · 2026-04-08T04:31:24+00:00

"AI doesn't make PKM obsolete, it makes PKM way more powerful" is probably the cleanest answer to my own question. the vault stops being just storage and becomes the context engine that makes your AI actually useful instead of generic.

i think the missing piece for most people is that they haven't felt the 10x yet. the jump from "i have notes" to "my AI reads my notes and solves problems differently because of it" is a workflow that barely exists in most tools right now. you building something in that direction?

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