hhhhansel

making things • connecting dots • @xAI

[brendan @bpjzy]

Queen St @superwhisper

[superwhisper @superwhisper]

Still typing?

[hhhhansel @hhhhansel]

@suekhim That is fire! Love that. Perfect thank you 🙏🏾

[hhhhansel @hhhhansel]

Elite

[Jason Zhao @byjasonz]

we just gave your computer infinite storage.

quickly find and edit terabytes of files, all while using zero disk space.

here’s a first look, updates shipping daily.

[hhhhansel @hhhhansel]

@thecosmos for the W

[hhhhansel @hhhhansel]

Why is Claude design not in the desktop app?

Someone please explain

@claudeai

[hhhhansel @hhhhansel]

Make em pay with tax + interest

Show them why you’re the asset they should have taking to time to invest in

[hhhhansel @hhhhansel]

When you tell someone your idea you’re actively executing on and they don’t get it… feels uncomfortable at first…

Then to realize that is the feeling you need vs them agreeing and saying it’s a great idea

[hhhhansel @hhhhansel]

It’s also absolutely hilarious to see someone rip your whole idea and try to flip it into something of their own after they tell you they don’t want to work on anything of that nature when you presented the opportunity countless times

[Issybeatz @Issybeatz_]

I’ve got a theory.

When people don’t create
music
art
ideas
anything…

they start creating problems instead.

Unused energy gets weird.

[kache @yacineMTB]

you can outsource your thinking
but you cannot outsource your understanding

[Dhruv @dhruvtwt_]

Why is no one talking about this?

@nvidia is offering around 80 AI models via hosted APIs absolutely for free.

You get access to MiniMax M2.7, GLM 5.1, Kimi 2.5, DeepSeek 3.2, GPT-OSS-120B, Sarvam-M etc.

This plugs straight into OpenClaude, OpenCode, Zed IDE, Hermes agent and even with Cursor IDE.

Setup:
– Grab API key: https://t.co/Wfdclm0hY2
– base_url = "https://t.co/VOGC10LmGP"
– api_key = "$NVIDIA_API_KEY"
– select model (e.g. minimaxai/minimax-m2.7)

If you’re building or experimenting, this is basically free inference.

Lock in and start building today anon.

Thank me later.

[hhhhansel @hhhhansel]

@XboxSupport Ayyyy just saying, we UP AGAIN @Xbox

Didn’t mind it being cooked cause I was 100x more focused and now I’m out here just coooking in Apex when I have the most work to do 🫠

[hhhhansel @hhhhansel]

I’ve had my @Xbox One for over 12 years

Never forgot when I bought it

Told my boss how I bought a new tv and Xbox as a gift to myself

Literally got let go 2 days later 😭

It brought me joy

Now, it just won’t update…

It’s now part of the archive

End of an era ✌🏾

[hhhhansel @hhhhansel]

@XboxSupport I know the squad has a spare Xbox to help ya boy out here

Or can at least help me troubleshoot this thing

[hhhhansel @hhhhansel]

@claudeai Fire! Now, how can we get to see our repo files directly within vs using traditional ide’s?

[hhhhansel @hhhhansel]

No suits in the boardrooms

Just a hoodie and some cargos

Fresh Nikes and a fitted

[Ethan:Print"Ethan";:GoTo Ethan @etok_me]

@hhhhansel @internetvin @karpathy MEGAMIND 🧠

[hhhhansel @hhhhansel]

And this
Combine the two and my goodness

[Andrej Karpathy @karpathy]

LLM Knowledge Bases

Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So:

Data ingest:
I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them.

IDE:
I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides).

Q&A:
Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale.

Output:
Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base.

Linting:
I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into.

Extra tools:
I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries.

Further explorations:
As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows.

TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

[hhhhansel @hhhhansel]

Combined @internetvin + @karpathy 2nd brain method together

[hhhhansel @hhhhansel]

This

[GREG ISENBERG @gregisenberg]

how to use obsidian + claude code to build a 24/7 personal operating system and build your startup:

1. write everything in markdown (daily notes, projects, beliefs, people, meetings)

2. link your notes together so they mirror how your brain actually thinks.

3. install obsidian cli so claude code can read your entire vault + the relationships.

4. stop reexplaining projects every session. use reference files instead.

5. build custom slash commands:

/context → load your full life + work state
/trace → see how an idea evolved over months
/connect → bridge two domains you’ve been circling
/ideas → generate startup ideas from your vault
/graduate → promote daily thoughts into real assets

6. keep a strict rule: human writes the vault. agents read it, suggest, execute.

7. let claude aka clode surface patterns you’ve been unconsciously circling for years.

8. delegate from inside your notes. one sentence in obsidian → agent handles the rest.

9. treat writing as leverage.the more you write, the more context your agents have.

10. understand this:markdown files are the oxygen of llms.

i really enjoyed seeing how to use obsidian thanks to @internetvin

vin uses ai like a thinking partner wired into his life’s work.

99.99% of people won’t do this because it requires reflection + setup.

but once the vault exists, the agent stops being generic.
it starts thinking in your voice.

episode is live on @startupideaspod (more there)

this one is different. send this tweet to a friend.

im still processing how game changer obsidian + claude code is, maybe you too

watch