[HN Gopher] Your File System Is Already A Graph Database
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Your File System Is Already A Graph Database
Author : alxndr
Score : 155 points
Date : 2026-04-06 03:06 UTC (2 days ago)
(HTM) web link (rumproarious.com)
(TXT) w3m dump (rumproarious.com)
| alxndr wrote:
| > [...] the knowledge base isn't just for research. It's a
| context engineering system. You're building the exact input your
| LLM needs to do useful work. > [...] there's a real difference
| between prompting "help me write a design doc for a rate limiting
| service" and prompting an LLM that has access to your project
| folder with six months of meeting notes, three prior design docs,
| the Slack thread where the team debated the approach, and your
| notes on the existing architecture.
| WillAdams wrote:
| I've found a similar structure along with a naming convention
| useful at my day job --- the big thing is the names are such that
| when copied as a filepath, the filepath and extension deleted,
| and underscores replaced by tabs, the text may then be pasted
| into a spreadsheet and summed up or otherwise manipulated.
|
| In somewhat of an inversion, I've been getting the initial naming
| done by an LLM (well, I was, until CoPilot imposed file upload
| limits and the new VPN blocked access to it) --- for want of
| that, I just name each scan by Invoice ID, then use a .bat file
| made by concatenating columns in a spreadsheet to rename them to
| the initial state ready for entry.
| embedding-shape wrote:
| I've been playing around with the same, but trying to use local
| models as my Obsidian vault obviously contain a bunch of private
| things I'm not willing to share with for-profit companies, but I
| have yet to find any model that comes close to working out as
| well as just codex or cc with the small models, even with 96GB of
| VRAM to play around with.
|
| I've started to think about maybe a fine-tuned model is needed,
| specifically for "journal data retrieval" or something like that,
| is anyone aware of any existing models for things like this? I'd
| do it myself, but since I'm unwilling to send larger parts of my
| data to 3rd parties, I'm struggling collecting actual data I
| could use for fine-tuning myself, ending up in a bit of a catch
| 22.
|
| For some clients projects I've experimented with the same idea
| too, with less restrictions, and I guess one valuable experience
| is that letting LLMs write docs and add them to a "knowledge
| repository" tends to up with a mess, best success we've had is
| limiting the LLMs jobs to organizing and moving things around,
| but never actually add their own written text, seems to slowly
| degrade their quality as their context fills up with their own
| text, compared to when they only rely on human-written notes.
| weitendorf wrote:
| This is exactly what we're working on, is there any application
| in particular you're interested in the most?
|
| > I'm struggling collecting actual data I could use for fine-
| tuning myself,
|
| Journalling or otherwise writing is by far the best way to do
| this IMO but it doesn't take very much audio to accurately do a
| voice-clone. The hard thing about journalling is that it can
| actually be really biased away from the actual "distribution"
| of you, whether it's more aspirational or emotional or less
| rigorous/precise with language.
|
| What I'm starting to do is save as many of my prompts as
| possible, because I realized a lot of my professional writing
| was there and it was actually pretty valuable data (especially
| paired with outputs and knowledge of what went well and waht
| didn't) for finetuning on my own workloads. Secondly is
| assembling/curating a collection of tools and products that I
| can drop into each new context with LLMs and also use for
| finetuning them on my own needs. Unlike "knowledge
| repositories" these both accurately model my actual needs and
| work and don't require me to do really do anything unnatural.
|
| The other thing I'm about to start doing is "natural" in a
| certain sense but kinda weird, basically recording myself
| talking to my computer (verbalizing my thoughts more so it can
| be embedded alongside my actions, which may be much sparser
| from the computer's perspective) / screen recordings of my
| session as I work with it. This is something I've had to look
| into building more specialized tools for, because it creates
| too much data to save all of it. But basically there are small
| models, transcoding libraries, and pipelines you can use for
| audio/temporal/visual segmentation and transcription to
| compress the data back down into tokens and normal-sized
| images.
|
| This is basically creating a semantic search engine of yourself
| as you work, kinda weird, but IMO it's just much weirder that
| your computer can actually talk back and learn about you now.
| With 96GB you can definitely do it BTW. I successfully
| finetuned an audio workload on gemma 4 2b yesterday on a 16GB
| mac mini. With 96GB you could do a lot.
|
| > letting LLMs write docs and add them to a "knowledge
| repository"
|
| I think what you actually want them to do is send them to go
| looking for stuff for you, or actively seeking out "learning"
| about something like that for their own role/purposes, so they
| can embed the useful information and better retrieve it when
| they need it, or produce traces grounded in positive signals
| (eg having access to this piece of information or tool, or
| applying this technique or pattern, measurably improves
| performance at something in-distribution to whatever you have
| them working on) they can use in fine-tuning themselves.
| embedding-shape wrote:
| I think maybe you're misunderstanding the issue here. I have
| loads of data, but I'm unwilling to send it to 3rd parties,
| so that leaves me with gathering/generating the training data
| locally, but none of the models are good/strong enough for
| that today.
|
| I'd love to "send them to go looking for stuff for you", but
| local models aren't great at this today, even with beefy
| hardware, and since that's about my only option, that leaves
| me unable to get sessions to use for the fine-tuning in the
| first place.
| weitendorf wrote:
| Right, that's exactly the situation I'm in too and "send
| them to go looking for stuff for you" without it going off
| the rails is the problem we've been working on.
|
| Basically you need a squad of specialized models to do this
| in a mostly-structured way that ends up looking kind of
| like a crawling or scraping/search operation. I can share a
| stack of about 5-6 that are working for us directly if you
| want, I want to keep the exact stack on the DL for now but
| you can check my company's recent github activity to get an
| idea of it. It's basically a "browser agent" where gemma or
| qwen guide the general navigation/summarization but mostly
| focus on information extraction and normalization.
|
| The other thing I've done, which obviously not everybody is
| going to want to do, is create emails and browser profiles
| for the browser agent (since they basically work when I'm
| not on the computer, but need identity to navigate the web)
| and run them on devices that don't have the keys to the
| kingdom. I also give them my phone number and their own
| (via an endpoint they can only call me from). That way if
| they run into something they have a way to escalate it, and
| I can do limited steering out of the loop. Obviously this
| is way more work than is reasonable for most people right
| now though so I'm hoping to show people a proper batteries-
| included setup for it soon.
|
| Edit: Based on your other comment, I think maybe what
| you're really looking for most are "personal traces". Right
| now that's something we're working on with
| https://github.com/accretional/chromerpc (which uses the
| lower level Chrome Devtools Protocol rather than Puppetteer
| to basically fully automate web navigation, either through
| an LLM or prescriptive workflows). It would be very simple
| to set up automation to take a screenshot and save it
| locally every Xm or in response to certain events and
| generate traces for yourself that way, if you want. That
| alone provides a pretty strong base for a personal dataset.
| embedding-shape wrote:
| > that ends up looking kind of like a crawling or
| scraping/search operation
|
| Sure, but what I'm talking about is that the current SOTA
| models are terrible even for specialized small use cases
| like what you describe, so you can't just throw a local
| modal on that task and get useful sessions out of them
| that you can use for fine-tuning. If you want distilled
| data or similar, you (obviously) need to use a better
| model, but currently there is none that provides the
| privacy-guarantees I need, as described earlier.
|
| All of those things come once you have something suitable
| for the individual pieces, but I'm trying to say that
| none of the current local models come close to solving
| the individual pieces, so all that other stuff is just
| distraction before you have that in place.
| weitendorf wrote:
| Understood. I guess I'm saying "soon" but definitely
| agreed its not "now" yet. I will say though, with 96GB,
| in a couple months you're going to be able to hold tons
| of Gemma 4 LoRa "specialists" in-memory at the same time
| and I really think it will feel like a whole new world
| once these are all getting trained and shared and adapted
| en-masse. And also, you _could_ set up personal traces
| now if you want. Nobody can make you, but in its laziest
| form it can be literally just taking screenshots of your
| screen periodically as you work, and that 'll have
| applications soon
| embedding-shape wrote:
| > And also, you could set up personal traces now if you
| want. Nobody can make you, but in its laziest form it can
| be literally just
|
| But again, you're missing my point :) I cannot, since the
| models I could generate useful traces from are run by
| platforms I'm not willing to hand over very private data
| to, and local models that I could use I cannot get useful
| traces from.
|
| And I'm not holding out hope for agent orchestration,
| people haven't even figured out how to reliably get high
| quality results from agent yet, even less so with a fleet
| of them. Better to realistically tamper your expectations
| a bit :)
| SeanLang wrote:
| Couldn't you create synthetic data based on your entries using
| local models? Or would that defeat the purpose of fine tuning
| it?
| embedding-shape wrote:
| Yeah, I suppose, but how do I get sufficiently high quality
| synthetic data without sending the original data to
| OpenAI/Anthropic, or by using local models when none of them
| seem strong enough to be able to generate that "sufficiently
| high quality synthetic data" in the first place?
| mswphd wrote:
| you _could_ do something like rent GPU time yourself, and
| use it to run a higher-quality local model (e.g. one of the
| Chinese "close to frontier" ones). Not guaranteed to
| preserve privacy of course, but it at least avoids directly
| sending the data to OpenAI/Anthropic.
| terminalkeys wrote:
| You can fine-tune local models using your own data. Unsloth has
| a guide at https://unsloth.ai/docs/get-started/fine-tuning-
| llms-guide.
|
| I'm currently experimenting with Tobi's QMD
| (https://github.com/tobi/qmd) to see how it performances with
| local models only on my Obsidian Vault.
| embedding-shape wrote:
| Right, the technical know-how about fine-tuning isn't the
| problem here, getting sufficiently high quality session logs
| without basically giving away my private data for free is the
| issue.
|
| Today, I can use even the small models of OpenAI and
| Anthropic to get valuable sessions, but if I wanted to
| actually use those for fine-tuning a local model, I'd need to
| actually start sending the data I want to use for fine-tuning
| to OpenAI and Anthropic, and considering it's private data
| I'm not willing to share, that's a hard-no.
|
| So then my options are basically using stronger local models
| so I get valuable sessions I can use for fine-tuning a
| smaller model. But if those "stronger local models" actually
| worked in practice to give me those good sessions, then I'd
| just use those, but I'm unable to get anything good enough to
| serve as a basis for fine-tuning even from the biggest ones I
| can run.
| gchamonlive wrote:
| Models are lossy, so fine-tune can only take you so far with
| small models. What we need is reasonably capable local models
| with a huge context window and a method to make efficient use
| of token and cram as much info as possible in the context
| before degrading the output quality.
| exossho wrote:
| I can't remember how many file structures I've already tried...
| LLMs seem to be a great help here. Also used CC to organize my
| messy harddrive.
|
| Now just need to find a good way to maintain the order...
| freedomben wrote:
| > _Also used CC to organize my messy harddrive._
|
| Do you still have your prompt by chance, and willing to share
| it? I took a stab at this and it didn't want to make much
| change. I think I need to be more specific but am not sure how
| to do that in a general way
| exossho wrote:
| I don't have the exact prompt anymore, but it was very lean.
| I first asked to do an assessment: "Review the content of the
| whole folder structure. I want you to assess it, and suggest
| a better setup and structure based on its content. Don't
| change anything yet, just assess"
|
| and then worked from there, giving feedback on the proposed
| folder structure, until I was happy
| itake wrote:
| I'm wonder though:
|
| 1. Why does AI need that folder structure? Why not a flat list of
| files and let the AI agent explore with BM25 / grep, etc.
|
| 2. pre-compute compression vs compute at query time.
|
| Kaparthy (and you) are recommending pre-compressing and sorting
| based on hard coded human abstraction opinions that may match how
| the data might be queried into human-friendly buckets and
| language.
|
| Why not just let the AI calculate this at run time? Many of these
| use cases have very few files and for a low traffic knowledge
| store, it probably costs less tokens if you only tokenize the
| files you need.
| laurowyn wrote:
| > Why does AI need that folder structure? Why not a flat list
| of files and let the AI agent explore with BM25 / grep, etc.
|
| It doesn't. The human creating the files needs it, to make it
| easier to traverse in future as the file count grows. At 52k
| files, that's a horrendous list to scroll through to find the
| thing you're looking for. Meanwhile, an AI can just `find .
| -type f -exec whatever {} \;` and be able to process it however
| it needs. Human doesn't need to change the way they work to
| appease the magic rock in the box under the desk.
| itake wrote:
| > The human creating the files needs it
|
| why? The human would just talk to the AI agent. Why would
| they need to scroll through that many files?
|
| I made a similar system with 232k files (1 file might be a
| slack message, gitlab comment, etc). it does a decent job at
| answering questions with only keyword search, but I think i
| can have better results with RAG+BM25.
| laurowyn wrote:
| And when the system fails for whatever reason?
|
| Just because AI exists doesn't mean we can neglect basic
| design principles.
|
| If we throw everything out the window, why don't we just
| name every file as a hash of its content? Why bother with
| ASCII names at all?
|
| Fundamentally, it's the human that needs to maintain the
| system and fix it when it breaks, and that becomes
| significantly easier if it's designed in a way a human
| would interact with it. Take the AI away, and you still
| have a perfectly reasonable data store that a human can
| continue using.
| dgb23 wrote:
| > 1. Why does AI need that folder structure? Why not a flat
| list of files and let the AI agent explore with BM25 / grep,
| etc.
|
| Two reasons I think:
|
| Coding agents simulate similar things to what they have been
| trained on. Familiarity matters.
|
| And they tend to do much better the more obvious and clear a
| task is. The more they have to use tools or "thinking", the
| less reliable they get.
| weitendorf wrote:
| > Why does AI need that folder structure? Why not a flat list
| of files and let the AI agent explore with BM25 / grep, etc.
|
| Progressive disclosure, same reason you don't get assaulted
| with all the information a website has to offer at once, or
| given a sql console and told to figure it out, and instead see
| a portion of the information in a way that is supposed to
| naturally lead you to finding the next and next bits of
| information you're looking for.
|
| > use cases
|
| This is essentially just where you're moving the
| hierarchy/compression, but at least for me these are not very
| disjoint and separable. I think what I actually want are
| adaptable LoRa that loosely correspond to these use cases but
| where a dense discriminator or other system is able to adapt
| and stay in sync with these too. Also, tool-calling +
| sql/vector embeddings so that you can actually get good
| filesystem search without it feeling like work, and let the
| model filter out the junk.
|
| > let the AI calculate this at run time?
|
| You still do want to let it do agentic RAG but I think more
| tools are better. We're using sqlite-vec, generating multimodal
| and single-mode embeddings, and trying to make everything typed
| into a walkable graph of entity types, because that makes it
| much easier to efficiently walk/retrieve the "semantic space"
| in a way that generalizes. A small local model needs at least
| enough structure to know these are the X ways available to look
| for something and they are organized in Y ways, oriented
| towards Z and A things.
|
| Especially on-device, telling them to "just figure it out" is
| like dropping a toddler or autonomous vehicle into a dark room
| and telling them to build you a search engine lol. They need
| some help and also quite literally to be taught what a search
| engine means for these purposes. Also, if you just let them
| explore or write things without any kind of grounding in what
| you need/any kind of positive signals, they're just going to be
| making a mess on your computer.
| stared wrote:
| Filesystem is a tree - a particular, constrained graph. Advanced
| topics usually require a lot of interconnections.
|
| Maybe it is why mind maps never spoke to me. I felt that a tree
| structure (or even - planar graphs) were not enough to cover any
| sufficiently complex topic.
| nutjob2 wrote:
| If it has hard or soft links, its a proper graph.
| calgoo wrote:
| That what i was thinking! Instead of Wiki links, use Symlinks
| (i guess windows would not like it?)
| zahlman wrote:
| On Linux at least, hard links can't be made to directories,
| except for the magic . and .. links. So this only allows for
| a DAG.
|
| Symbolic links can form a graph, and you can process them as
| needed using readlink etc. to traverse the graph, but they'll
| still be considered broken if they form a cycle.
| Retr0id wrote:
| Considered broken by what?
| rleigh wrote:
| Historically, it made deletion rather difficult with some
| problematic edge-cases. You could unlink a directory and
| create an orphan cycle that would never be deleted.
| Combine that with race conditions on a multi-user
| systems, plus the indeterminate cost of cycle-detection,
| and it turns out to be a rather complex problem to solve
| properly, and banning hard-links is a very simple way to
| keep the problem tractable, and result in fast, robust
| and reliable filesystem operations.
| Retr0id wrote:
| GP was talking about symlink cycles though, which can't
| produce orphans during deletion.
| rleigh wrote:
| True, I missed that. I suppose with symlinks you have the
| reverse problem: you can point to deleted filenames and
| then have broken links. The cycle detection is still an
| issue though--it has indeterminate complexity and the
| graph can be modified as you are traversing it!
| Retr0id wrote:
| This is true, but just about everyone has a symlink cycle
| on their system at `/proc/self/root`, and for the most
| part nobody notices. Having a max recursion depth is
| usually more useful than actively trying to detect
| cycles.
| PunchyHamster wrote:
| I guess technically you could do bind mounts but that's
| messy
| vinaigrette wrote:
| Isn't text a basic linear structure that can cover sufficiently
| complex topics ?
| stared wrote:
| Yes. And precisely for this reason reading a dictionary is
| not a way of learning a language.
| bullen wrote:
| Yep, my distributed JSON over HTTP database uses the ext4 binary
| tree for indexing: http://root.rupy.se
|
| It can only handle 3 way multiple cross references by using 2
| folders and a file now (meta) and it's very verbose on the disk
| (needs type=small otherwise inodes run out before disk space)...
| but it's incredibly fast and practially unstoppable in read
| uptime!
|
| Also the simplicity in using text and the file system sort of
| guarantees longevity and stability even if most people like the
| monolithic garbled mess that is relational databases binary table
| formats...
| appsoftware wrote:
| I created AS Notes (https://www.asnotes.io) (an extension for VS
| Code, Antigravity etc) partly because of this use case. It works
| like Obsidian, being markdown based, with wikilinks, mermaid
| rendering and task management. In VS Code, we have access to
| really good Agent harnesses and can navigate our notes and
| documents in a file system like manner. Further, using AGENTS.md,
| idea files etc we can instruct the agent how to interact, add to
| our notes etc. I've found working with my notes like this really
| useful, and provided I trim anything generated by an AI that's
| not going to be useful, provides an investment in the information
| I've gathered as the information is retained in markdown rather
| than getting lost in multiple chatbot UI s.
| itmitica wrote:
| I can see over engineering when I look at one. And premature
| optimization.
|
| Anyway, why care how the data is stored? You need a catalog. You
| need an index. You need automation. Helps keeping order and helps
| with inevitable changes and flips and pivots and whims and trends
| and moods and backups and restoration and snapshots and history
| and versioning and moon travels and collaboration and
| compatibility and long summer evening walks and portability.
| stingraycharles wrote:
| Using the same logic, a key/value database is also a graph
| database?
|
| Isn't the biggest benefit of graph databases the indexing and
| additional query constructs they support, like shortest path
| finding and whatnot?
| sorokod wrote:
| Yes, the author is likely unaware of this. They see markdown
| files with links, so a graph and the set of those files, so a
| "database".
|
| https://neo4j.com/docs/graph-data-science/current/algorithms...
| esafak wrote:
| His argument is that the LLM is the query engine. By that
| logic you can approximate anything since LLMs can.
| sorokod wrote:
| Indeed, what is the point of links/edges when the llm can
| figure out the relations by itself?
| coldtea wrote:
| > _what is the point of links /edges when the llm can
| figure out the relations by itself_
|
| Making it work less, faster, and saving tokens. Duh!
| lamasery wrote:
| Neo4j _looooooves_ the "if you think about it, everything is
| graphs!" marketing maneuver. They (their marketing
| department) were the very first thing I thought of when I
| read this headline.
| zadikian wrote:
| "Everything is graphs, so let's use a graph DBMS for
| anything" is a classic blunder
| lamasery wrote:
| I've seen it work to sell their product to managers who
| definitely should have gone with something else, so I get
| why they do it. It works.
| volemo wrote:
| I think the confusion stems from the fact that we call a
| database what is really a database management system.
| altmanaltman wrote:
| You confuse the raw fist with the master who calculates the
| shortest path to your destruction.
| rzzzt wrote:
| I'd just like to interject for a moment. What you're refering
| to as a database, is in fact a database management system, or
| as I've recently taken to calling it, database plus
| management system.
| mzelling wrote:
| If I understand this right, the difference between the author's
| suggested approach and simply chatting with an AI agent over your
| files is hyperlinks: if your files contain links to other
| relevant files, the agent has an easier time identifying relevant
| material.
| kenforthewin wrote:
| I keep harping on this, but the question is not "can you use your
| filesystem as a graph database" - of course you can - but whether
| this performs better or worse than a vector database approach,
| especially at scale.
|
| The premise of Atomic, the knowledge base project I'm currently
| working on, is that there is still significant value in vectors,
| even in an agentic context.
| https://github.com/kenforthewin/atomic
| iwontberude wrote:
| Oh neat! Whenever I was working on RAG proof of concepts vector
| databases seemed to generate noisiest outputs that happened to
| include my information from my chunks but it was unable to draw
| reasonable contextual associations. I swap RAG out with a web
| search tool, all of a sudden the quality goes way up. Is RAG
| ever going to be easier to hold or should lay people like me
| just stay moving on?
| kenforthewin wrote:
| I think agentic RAG still has its place. a hybrid
| semantic/keyword search tool in addition to other research
| tools outperforms the baseline in my experience.
| pyinstallwoes wrote:
| Cool project.
| kenforthewin wrote:
| thanks for checking it out!
| zadikian wrote:
| On the other hand, I get why cloud drive users completely
| disregard file structure and search everything. Two files usually
| don't have the same name unless you're laying it out
| programmatically like this. I use dir trees for code ofc, but
| everything else is flat in my ~/Documents.
|
| Deep inside a project dir, feels like some the ease of LLMs is
| just not having to cd into the correct directory, but you
| shouldn't need an LLM to do that. I'm gonna try setting up some
| aliases like "auto cd to wherever foo/main.py is" and see how
| that goes.
| embedding-shape wrote:
| > I use dir trees for code ofc, but everything else is flat in
| my ~/Documents.
|
| Which is great, but on all major OSes you'd eventually hit
| performance issues with flat directories like this. Might not
| be an issue in month one, or even year one, but after 10 years
| of note taking/journaling that approach will show the issue
| with large flat directories.
|
| So eventually you'd need to shard it somehow, so might as well
| start categorizing/sorting things from the get go, at least in
| some broad major categories at least, because doing so once you
| already have 10K entries in a directory, it sucks big time to
| do it.
| zadikian wrote:
| If it's just performance, cd ~/Documents && mkdir old && mv
| ./* old/ (or today's date instead of old). I actually have
| that layout on one PC.
|
| If real organization is needed, seems like that'd be easier
| in hindsight than having foresight
| embedding-shape wrote:
| So then you have one intentionally slow directory ("old/"
| in this case) and one fast directory?
|
| Personally I'd categorize stuff, but you do you, there
| really isn't any wrong way to do it, if it works it works
| :)
| zadikian wrote:
| I meant you mv into old before it gets too big. I've
| never actually seen a dir get slow like this. Only seen
| that with programmatic things like making 1M json files.
| bhewes wrote:
| Wow just strings in files. Are you jumping node to node via
| pointers index free?
| game_the0ry wrote:
| There for sure a "second brain" product hiding in plain site for
| one of the frontier AI companies. Google/Gemini should be all
| over this _right now_.
| aleksiy123 wrote:
| I've been thinking about this in a couple of contexts and pretty
| much how I've come to think about it.
|
| Folders give you hierarchical categories.
|
| You still want tags for horizontal grouping. And links and
| references for precise edges.
|
| But that gives you a really nice foundation that should get you
| pretty damn far.
|
| I also now am telling the llm to add a summary as the first
| section of the file is longer.
| estetlinus wrote:
| I am more curious on the note taking. How do you ingest data
| here? Export from slack via LLM:s? Store it in GitHub?
|
| My "knowledge" is spread out on various SaaS (Google, slack,
| linear, notion, etc). I don't see how I can centralize my
| "knowledge" without a lot of manual labour.
| LocalPCGuy wrote:
| Unless you're forced into using certain tool (work, etc), start
| by standardizing on a single tool. That's one reason a lot of
| people like Obsidian, but there are plenty of similar tools, or
| you can just write markdown in your editor of choice. Then set
| of some sort of sync so you have it everywhere you are (mobile
| can be a bit tricky for some set-ups) and commit to using that
| method as much as possible for your notes.
|
| You may want to do as described and link to Slack messages
| (etc), but just remember any external link should be treated as
| ephemeral. You may not have access to the Slack anymore, for
| example. That may mean you don't need that note either, or it
| may mean you lost access to a node on your knowledge graph, you
| have to determine whether that matters.
|
| By starting now, at least everything going forward is captured
| in a way you can both own and utilize it. Then it may be a bit
| of a pain and some manual work to get existing notes into your
| tool of choice, but you can determine what needs to be in there
| from other tools as you go forward.
| kesor wrote:
| So you have some folders with markdown files ... which are
| insanely hard to query without a tool ... impossible to traverse
| via their relationships ... and you call that a graph database?
| WHAT?!
|
| Clicked the link expecting to see some tool or method that
| actually allows graph-like queries and traversals on files in a
| file system, all I found was some rant about someone on the
| internet being wrong.
|
| Waste of time.
| Jayakumark wrote:
| Interesting approach but how do you download Google Docs, XLS and
| Slack threads etc.. and how is it saved in obsidian, are they all
| converted to markdown before saving or summarized to extract key
| topics and saved. What about images ?
| themafia wrote:
| Sure. It just fails to be atomic. Which is a property I really
| like.
| SoftTalker wrote:
| I will always be in awe of people who can remain diligent doing
| this level of journaling/personal information management.
|
| I've got scraps of paper and legal pads and post-it notes and
| just throw them away after they've been sitting around for a
| while and I forget what they are about.
| evanjrowley wrote:
| I thought he was gonna talk about inodes:
| https://en.wikipedia.org/wiki/Inode
|
| Maybe someday someone will expose these in the form of a graph
| database API (just for fun).
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