A living knowledge graph · kept by Muthu Bommiah
Every essay, every source, every connection between them.
Fifty-one notes on governed AI, context engineering and AI-native software delivery. An LLM librarian drafts and files them; every claim is footnoted to a dated source; nothing is marked reviewed until Muthu reviews it.
Explore the graph
Three ways in
Notes 51
Dated sources 51
Connections 133
Themes 5
Nothing to show: every node type is filtered out.
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The graph needs JavaScript. The graph data is available as JSON, and the notes are a plain list.
01 · Capture
A source with a date
An essay, a paper, a talk. Nothing enters without its publication date and licence.
02 · Librarian
LLM-Wiki-V2, CROW mode
A local classifier decides where a note belongs; Claude writes it. Cost per note stays flat as the wiki grows.
03 · Format
Open Knowledge Format v0.2
Markdown with provenance in the frontmatter, kept in Git. Any tool can read it; nothing is locked in.
04 · Review
Checks, then a human
Schema, dates, links and a confidential-terms scan on every change. Only Muthu's approval marks a note reviewed.
05 · Graph
NetworkX, with Semantica
A deterministic graph of notes, sources and relations; Semantica adds extracted entities, kept apart and labelled.
06 · Publish
Quartz 5 and Sigma.js 4
Each merge cuts a release; this site and graph rebuild from it. Markdown twins and llms.txt for machines.
Three ways in
Curated paths through the graph, four essays each. Pick the one that matches your seat.
Reading the map
A theme: one of the five folders the librarian files into
A note, coloured by its theme; bigger means more connections
Essay, initiative, playbook
A ring: reviewed by Muthu, with the date
A link in the text, or a declared relation
A grey dot on a faint line: an entity Semantica found in the text (off by default; Filters → Extracted)
Every note is also plain Markdown at its address plus .md; the whole wiki is in llms.txt . Text under CC BY 4.0.