What file formats does the guide recommend for text and diagrams?

It suggests writing the body in Markdown and preparing diagrams in SVG, with Mermaid as an option for relationship and flow diagrams. If the publishing destination does not support SVG, convert to PNG while keeping the editable SVG source.

Why does the guide suggest 3 to 5 elements per diagram group?

It cites research on subitizing, which puts quick counting of small sets at roughly 4 items, and studies suggesting a working-memory capacity of about 4 chunks under limited conditions. The guide treats 3〜5要素 as a practical guideline to adjust by complexity and reader knowledge.

How does the guide say corrections should be carried over between rounds?

It recommends recording the target expression, the correction policy and the situation where it applies in a correction table, then passing that table to the AI at each review. New findings are added to the table so they carry into the next round.

Zenn AI/ML2h agoNov 12, 2026, 04:00 JST

Diagram-first guide: keep AI documents to 3–5 elements

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3 Key Points

What happened
The Zenn guide lays out a four-part method — organizing text, organizing diagrams, expressing diagrams, and managing and revising materials — with diagrams kept to roughly 3〜5要素 per group.
Why it matters
AI can generate large volumes of text quickly, but people cannot realistically read all of it, so turning the structure into diagrams is presented as a way to make review and correction exchanges with AI more efficient.

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Context & Analysis

The guide is built around a practical constraint it states up front: AI can produce large amounts of text in a short time, but reading all of it is not realistic, so the material has to be reorganized into a form a person can grasp. Diagrams are offered as one way to do that, because showing the overall picture and the relationships between elements makes it easier to ask whether a relationship is correct or which part needs fixing.

The document then moves from text to diagrams to housekeeping. On text, it pushes a claim-then-reason structure in each paragraph and suggests splitting paragraphs that carry several claims. On diagrams, it proposes grouping related elements and layering overview and detail, with names and colors kept consistent between the two so a reader can tell which part of the whole is being explained. It also sets a practical guideline of 3〜5要素 per group, backed by research on subitizing and on working memory capacity.

A large share of the guide is devoted to keeping revisions stable over repeated passes. A glossary pins down terms such as グループ, レイヤー, 全体図 and 詳細図, while a correction table records phrasing to avoid and how to rephrase it. The reasoning given is that AI-generated text can drift in wording and meaning with each revision, so both documents are fed back to the AI at review time, with a person validating the proposed fixes.

FAQ

What file formats does the guide recommend for text and diagrams?: It suggests writing the body in Markdown and preparing diagrams in SVG, with Mermaid as an option for relationship and flow diagrams. If the publishing destination does not support SVG, convert to PNG while keeping the editable SVG source.
Why does the guide suggest 3 to 5 elements per diagram group?: It cites research on subitizing, which puts quick counting of small sets at roughly 4 items, and studies suggesting a working-memory capacity of about 4 chunks under limited conditions. The guide treats 3〜5要素 as a practical guideline to adjust by complexity and reader knowledge.
How does the guide say corrections should be carried over between rounds?: It recommends recording the target expression, the correction policy and the situation where it applies in a correction table, then passing that table to the AI at each review. New findings are added to the table so they carry into the next round.

Zenn AI/MLRead Original Article

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