Every few months a new wave of personal knowledge management tools sweeps through my timeline. Obsidian vaults with thousands of backlinks. Logseq graphs that look like neural tissue under a microscope. Zettelkasten disciples explaining how their “second brain” has finally freed them from forgetting. I find it all fascinating, and I am quietly convinced most people do not actually need any of it.
The pitch is seductive: capture everything, link everything, and your mind will become a searchable, navigable web. The trouble is that the human brain does not store memory the way a graph database does. A knowledge graph is a clean structure of nodes and edges, each one precise and typed. Memory is messier, warmer, and far more personal. It is shaped by who you are, what you felt, and what you happened to be looking at when the thought arrived.
Memory is not one thing. Some people think in propositions and crisp definitions. Some remember through sound and rhythm. Some rehearse by talking out loud. I am a scene‑based rememberer. What sticks for me is a picture—where I was sitting, what the light looked like, the texture of a particular afternoon. When I try to recall a concept, I do not search an index; I replay an episode. A conversation at a café, a paragraph on a specific page, the smell of rain during a lecture. The idea arrives wrapped in context, and the context is half the meaning.
Forcing that kind of memory into a tidy graph feels like pinning butterflies. You get a specimen, but the flight is gone. The graph can show me that Concept A links to Concept B, but it cannot reproduce the reason the link mattered to me in the first place—the small, private jolt of recognition that made me care. Strip away the scene and I am left with trivia I no longer have a reason to remember.
This is why I never got along with Obsidian. I tried, more than once. It is a beautiful piece of software and clearly a labor of love. But every time I sat down to “maintain” my vault, I felt like I was doing the paperwork of thinking instead of the thinking itself. Tagging, linking, renaming, reorganizing—the overhead kept eating the thing it was supposed to support. For a while I mistook the busyness for progress. Eventually I noticed that my best ideas were still coming from long walks, half‑finished drafts, and conversations I had not indexed anywhere.
There is also a quieter argument against the tools, and I think it is the more important one. The act of organizing by hand—slowly, with a pen or in a plain text file—is not a bottleneck to get rid of. It is the work. When I sit down and try to write out what I learned this week, I am forced to decide what actually matters. I drop the parts I cannot justify. I notice which ideas keep showing up next to each other. I simplify, rephrase, and sometimes discover that two things I thought were separate are really the same thing in different clothes. The friction is where the understanding happens. Automate it away and you get a larger archive and a smaller mind.
This is the part of the conversation where I have to talk about Karpathy, because a few days ago he posted about his “LLM Wiki” setup and the whole timeline tilted in response. The idea is elegant in the way his ideas usually are: you keep a folder of raw sources the model is never allowed to edit, you let an LLM agent maintain a second folder of markdown articles on top of those sources, and you give it a schema file—a CLAUDE.md or the equivalent—that tells it how to ingest new material, cross-link entities, and periodically lint the whole thing for contradictions and orphan pages. He mentioned that one of his research wikis has grown to around a hundred articles and four hundred thousand words, and that he rarely edits it by hand anymore. The day after, he dropped a gist meant to be copy-pasted into your own agent as a starting point. Within hours people were forking it, wiring it into Obsidian vaults, writing Medium posts with titles like “Karpathy just 10x’d everyone’s Claude setup,” and shipping GitHub repos called things like second-brain and llm-wiki. It has become a small genre.
I want to be honest about what is interesting here, because I do not think Karpathy is wrong in the way the loudest Obsidian evangelists are wrong. His framing actually concedes my main point: the tedious part of knowledge management is not reading, it is bookkeeping, and bookkeeping grows faster than the value it produces. That is exactly why I gave up on Obsidian. Where we part ways is on what to do about it. His answer is to hand the bookkeeping to a machine that does not get bored. Mine is to notice that the bookkeeping was mostly make-work in the first place, and to stop doing it. If the cross-references only existed because a human could not hold the material in their head, automating them does not make the material more yours—it just makes the scaffolding cheaper to maintain. You end up with a four-hundred-thousand-word wiki that an agent wrote on your behalf, and a vague feeling that you have read it, when in fact the model has.
There is a specific failure mode I want to name. When the wiki is maintained by an LLM, the canonical version of what you “know” lives outside your head, in prose you did not write. Querying it feels like remembering, but it is not—it is retrieval from a system whose compression choices you never made. For a scene-based rememberer this is especially bad, because the scenes never get encoded at all. There was no afternoon at the café. There was a diff in a markdown file. And the next time you want to recall the idea, there is nothing to replay, only something to look up. The copy-pasted gist is a beautiful piece of engineering and I understand why it went viral, but I think a lot of people are going to build one, feel productive for a month, and then quietly notice that their sense of having learned anything has gotten thinner, not thicker.
The thing worth stealing from Karpathy’s pattern, I think, is much smaller than the pattern itself. The useful primitive is the raw-sources folder: a flat pile of things you actually read, kept immutable, and occasionally grepped. That part costs nothing and preserves the context you might someday want to replay. Everything on top of it—the generated articles, the backlinks, the lint passes, the schema document—is optional, and for most people optional means “not worth it.” You can get eighty percent of the benefit by keeping the sources and writing the occasional essay in your own words when something refuses to settle.
Herbert Simon once said that a wealth of information creates a poverty of attention. Knowledge graphs, for all their elegance, tend to push in exactly the wrong direction. They make capture cheap and retrieval plausible, which encourages you to save more and decide less. But the scarce resource in adult life is not storage. It is the willingness to sit with a handful of ideas long enough to know what you think about them.
None of this is an argument against tools. If you are a researcher stitching together citations across a decade, a graph is probably indispensable. If your work genuinely has the shape of a network—legal precedents, drug interactions, an investigation with hundreds of named entities—then by all means, build the thing. What I am skeptical of is the default assumption that every knowledge worker needs a personal ontology, and that forgetting is a bug to be engineered out.
Forgetting is not a bug. It is a feature of a mind that has decided what matters. The things you cannot let go of are, almost by definition, the things worth keeping. A plain notebook, a few running documents, and the stubborn practice of writing in full sentences will take most people further than any graph ever will. Your brain already knows how it wants to remember. The job is to listen to it, not to overwrite it with somebody else’s schema.
So I will keep my notes simple. A handful of markdown files. A few drafts that grow in public. Long walks when something refuses to come clear. If that counts as a knowledge system, it is one with exactly one user, and the maintenance cost is the thinking itself—which, it turns out, is the only part I wanted in the first place.