AIToday
Zenn AI/MLPublished: Oct 13, 2026, 10:00 JST

カンパニーブレイン converges on Markdown bodies with YAML labels

カンパニーブレイン converges on Markdown bodies with YAML labels

3 Key Points

  1. What happened

    The author argues company knowledge for AI agents is settling on Markdown bodies with YAML labels, noting Anthropic's SKILL.md pairs YAML frontmatter with a Markdown body so agents grasp each skill in 約100トークン.

  2. Why it matters

    Under that split, the agent reads only the label first and loads the full body later, so only the layer of knowledge that people organize and write by hand converges on the format, the author argues.

Not sure about something? Ask the AI

Questions and answers are published on this page.

Summaries like this, in your inbox every morning.

Context & Analysis

The author's argument builds on earlier work of their own: an instruction to write procedures into SKILL.md, and mdschema, a tool that validates Markdown structure against a YAML schema. Both, the author notes, favored Markdown with YAML added alongside — the pattern this essay now spells out.

The concept has precedent. The author says the term company brain began appearing in English-speaking circles around 2026, and cites Andrej Karpathy's LLM Wiki and Garry Tan's GBrain, both of which use a Markdown repository as the knowledge store. Anthropic and OpenAI formats already lean this way: CLAUDE.md is a Markdown instruction file Claude Code reads per project, AGENTS.md is OpenAI's Markdown-style agent description placed next to a README, donated to the Linux Foundation's Agentic AI Foundation in December 2025, and SKILL.md was published as an open standard in December 2025.

Databases still have their place for large records, frequent updates, simultaneous writes and strict filtering, and vector databases are useful as an index built from Markdown rather than as the source of truth. The author's own caveats are practical: YAML lets anyone write anything, so a typo like cf0 for cfo goes unnoticed, cross-cutting queries such as listing every document past its review date need a script, and branching in Git for review remains unfamiliar to non-engineers.

FAQ
What separates the Markdown part from the YAML part?
Markdown holds the body text, while YAML holds the labels and the skeleton of the organization, such as an approval route or glossary. SKILL.md requires YAML frontmatter at the top and a Markdown body beneath it.
Why not keep this knowledge in a database instead?
The author argues a database limits who can write, forces the shape to be fixed before entry, needs a conversion layer to hand text to AI, and lacks built-in history and review. It suits large records, frequent updates and strict filtering.
Does all company knowledge fit this format?
No. The author lists four areas that stay outside it: constantly changing data, fine-grained permissions, simultaneous editing, and scale and relationships. Pushing those into files too would leave an outdated pile, the author says.

AI news that matters for your work, delivered every morning.

Pick your industry and the AI tools you use, and get news related to your work every day.

Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →

Ask AI

Ask AI anything about this article. The AI reads this article, earlier AIToday articles, and Wikipedia, and cites its sources. Q&As are published on this page for other readers too.

Questions and answers are published on this page.

Next articleHarvey to enter Japan in early 2027, CEO says