I handed my Obsidian vault to three coding agents: Claude Code, Codex, and Hermes Agent on a local model.
They capture sources, keep the index, answer from my notes, and lint the vault. I approve every note that becomes permanent.
Open-sourced the setup. Thread:
@harleyfoote_ Thank you for the suggestions however I believe the skill is quite robust against hallucinations. After ai create my notes, the agents won't touch my index until you run /wiki skill. It only read the frontmatter so there is no chance it make stuff up for the index.
@bjcatar What model you use to power Hermes? I am using Qwen 3.8 27B. It's good for simple tasks but I find for heavy task like /lint and /wiki, the quality is drop significantly
6. One command, and it never overwrites your files:
curl -fsSL https://t.co/wubc94Y9M7 | bash -s -- ~/external-brain
Repo: https://t.co/mcCEWy5sNU
Full write-up: https://t.co/LKv4sUbWwB
5. A frontier model and a 27B local model share the vault: a mkdir write lock, git rules for the second machine, and a smaller role for the small model.
Skills are written in "80% ASD-STE100", another Karpathy tip. Short imperative steps work far better on the small model.
I wrote a blog post detailing the writing approach I took while working on my recent paper: https://t.co/0aUhDLOnYD
I describe the behind the scenes for how this paper came to be, why and how I storyboarded figures before running experiments, and some figure design tips! :)
Accepted to #NeurIPS2026, we reshaped Monte-Carlo Tree Search ๐
Introducing 2FFS, a new tree search algorithm that combines multi-fidelity bandits to resolve the fundamental trade-off: should we use cheaper, approximated evaluations, or expansive but accurate samplings?
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