# Ken Imoto

> AI Systems Engineer specializing in LLMO, WebRTC, Real-time AI, and Context Engineering. Building AI-native organizations powered by LLMs, automation, and distributed agents.

## About

Ken Imoto is an AI Systems Engineer based in Fukuoka, Japan. He builds AI-native organizations at Propel-Lab (https://propel-lab.co.jp) and researches LLMO (LLM Optimization), AI Agent Design, and Human-AI Interaction.

LLMO includes approaches such as AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization).

## Expertise

- LLMO (LLM Optimization) — Author of the LLMO Framework (https://llmoframework.com)
- WebRTC & Real-time AI
- Context Engineering (CLAUDE.md, AGENTS.md patterns)
- AI Agent Design (MCP, multi-agent architectures)
- Android & Web Development (8+ years)

## Books (24 editions, auto-generated)

### English

- https://kenimoto.dev/books/engineer-it-quotes/ — Why Do Some Words Stay With You Forever? — 100 Engineering Quotes Decoded
  Kindle: https://www.amazon.co.jp/dp/B0GX3CS95M | Zenn: https://zenn.dev/kenimo49
- https://kenimoto.dev/books/knowledge-graph-practical-guide/ — The Practical Knowledge Graph Guide — Structure Your Data, Sharpen Your AI
  Kindle: https://www.amazon.co.jp/dp/B0GX2Z73JV | Zenn: https://zenn.dev/kenimo49/books/knowledge-graph-practical-guide
- https://kenimoto.dev/books/voice-ai-300ms-ux/ — The 300ms Threshold — Why Talking to AI Feels Wrong
  Kindle: https://www.amazon.co.jp/dp/B0GYQ4L2KP | Zenn: https://zenn.dev/kenimo49/books/voice-ai-300ms-ux
- https://kenimoto.dev/books/harness-code-review/ — Systematizing AI Code Review — The 3-Layer Model for 60% Faster Reviews
  Kindle: https://www.amazon.com/Systematizing-AI-Code-Review-Propel-Lab-ebook/dp/B0GX71K2BV | Zenn: https://zenn.dev/kenimo49/books/harness-code-review
- https://kenimoto.dev/books/llmo-quickstart/ — LLMO Quickstart — AI Search Optimization for Engineers
  Kindle: https://amzn.asia/d/04XYlHKe | Zenn: https://zenn.dev/kenimo49
- https://kenimoto.dev/books/mcp-security-practice/ — MCP Security in Practice — What OWASP Won't Tell You About AI Tool Integrations
  Kindle: https://amzn.asia/d/03ceMosL | Zenn: https://zenn.dev/kenimo49/books/mcp-security-practice
- https://kenimoto.dev/books/harness-engineering-guide/ — Harness Engineering — From Using AI to Controlling AI
  Kindle: https://a.co/d/0hD6MvVu | Zenn: https://zenn.dev/kenimo49/books/harness-engineering-guide
- https://kenimoto.dev/books/llmo-ai-search-optimization/ — Why ChatGPT Ignores Your Website — The LLMO Practical Guide
  Kindle: https://amzn.asia/d/04rulUoN | Zenn: https://zenn.dev/kenimo49/books/llmo-ai-search-optimization
- https://kenimoto.dev/books/context-engineering/ — Turning LLMs from Liars into Experts — Context Engineering in Practice
  Kindle: https://amzn.asia/d/04OYOGkH | Zenn: https://zenn.dev/kenimo49/books/context-engineering
- https://kenimoto.dev/books/claude-code-mastery/ — Practical Claude Code — Context Engineering for Modern Development
  Kindle: https://amzn.asia/d/0hU3BP1i | Zenn: https://zenn.dev/kenimo49/books/claude-code-mastery

### Japanese (日本語)

- https://kenimoto.dev/ja/books/engineer-it-quotes/ — エンジニアリング100の言葉 — なぜその一文は記憶に残るのか
  Kindle: https://www.amazon.co.jp/dp/B0GXR5Q6NW | Zenn: https://zenn.dev/kenimo49
- https://kenimoto.dev/ja/books/knowledge-graph-practical-guide/ — ナレッジグラフ活用大全 — 構造化すれば、AIは賢くなる
  Kindle: https://www.amazon.co.jp/dp/B0GX465PG7 | Zenn: https://zenn.dev/kenimo49/books/knowledge-graph-practical-guide
- https://kenimoto.dev/ja/books/voice-ai-300ms-ux/ — 音声AIの300ms — 人はなぜAIとの会話に違和感を覚えるのか
  Kindle: https://www.amazon.co.jp/dp/B0GX2R5HP4 | Zenn: https://zenn.dev/kenimo49/books/voice-ai-300ms-ux
- https://kenimoto.dev/ja/books/llmo-quickstart/ — LLMOクイックスタート — エンジニアのためのAI検索最適化入門
  Kindle: https://amzn.asia/d/04skv9ST | Zenn: https://zenn.dev/kenimo49
- https://kenimoto.dev/ja/books/harness-code-review/ — AIコードレビューを仕組み化する技術 — hooks・AI・人間の3層モデル
  Kindle: https://amzn.asia/d/0hgvOnOi | Zenn: https://zenn.dev/kenimo49/books/harness-code-review
- https://kenimoto.dev/ja/books/mcp-security-practice/ — MCP実践セキュリティ — 本番導入で躓かないための完全ガイド
  Kindle: https://amzn.asia/d/0cQpLy6g | Zenn: https://zenn.dev/kenimo49/books/mcp-security-practice
- https://kenimoto.dev/ja/books/harness-engineering-guide/ — ハーネス・エンジニアリング — AIを\"使う\"から\"操る\"へ
  Kindle: https://amzn.asia/d/0eE7m2BJ | Zenn: https://zenn.dev/kenimo49/books/harness-engineering-guide
- https://kenimoto.dev/ja/books/llmo-ai-search-optimization/ — なぜあなたのサイトはChatGPTに無視されるのか — LLMO実践ガイド
  Kindle: https://amzn.asia/d/02zAl1VB | Zenn: https://zenn.dev/kenimo49/books/llmo-ai-search-optimization
- https://kenimoto.dev/ja/books/context-engineering/ — LLMを「嘘つき」から「専門家」に変える技術 — Context Engineering 実践入門
  Kindle: https://amzn.asia/d/0dNeVFvn | Zenn: https://zenn.dev/kenimo49/books/context-engineering
- https://kenimoto.dev/ja/books/claude-code-mastery/ — 実践Claude Code — コンテキストエンジニアリングで開発が変わる
  Kindle: https://amzn.asia/d/03Qnb8QT | Zenn: https://zenn.dev/kenimo49/books/claude-code-mastery

### Portuguese (Português)

- https://kenimoto.dev/pt/books/context-engineering/ — Transformando LLMs de Mentirosos em Especialistas — Engenharia de Contexto na Prática
  Kindle: https://www.amazon.com.br/dp/B0H12378CJ
- https://kenimoto.dev/pt/books/harness-engineering-guide/ — Harness Engineering — De Usar IA a Controlar IA
  Kindle: https://www.amazon.com.br/dp/B0GZ4CYY6W
- https://kenimoto.dev/pt/books/claude-code-mastery/ — Practical Claude Code — Engenharia de Contexto que Transforma seu Desenvolvimento
  Kindle: https://www.amazon.com.br/dp/B0GZHB7J3T

### Spanish (Español)

- https://kenimoto.dev/es/books/claude-code-mastery/ — Practical Claude Code — La Ingeniería de Contexto que Transforma tu Desarrollo
  Kindle: https://www.amazon.com.br/dp/B0GX3S7VGK

## Blog Articles (33 articles, auto-generated)

### English

- https://kenimoto.dev/blog/autonomous-agent-24-hours-security-lessons/ — I Let My Claude Code Agent Run for 24 Hours. The $400 Bill Was the Least Scary Part.
- https://kenimoto.dev/blog/og-type-double-emit-three-astro-sites/ — The og:type Bug Three of My Astro Sites Quietly Shipped
- https://kenimoto.dev/blog/full-context-engineering-rag-80-percent/ — I Stacked 4 More Context Layers on Top of RAG. The Improvement Was 12%.
- https://kenimoto.dev/blog/natural-language-agent-harnesses-arxiv/ — I Was Calling It 'Setup' for Six Months. arXiv Has a Better Word: Harness
- https://kenimoto.dev/blog/claude-code-skills-reusable-workflow-pattern/ — Claude Code Skills: The Reusable Workflow That Replaced My Commands
- https://kenimoto.dev/blog/new-domain-first-week-ga4-is-a-lie/ — Your New Domain's First Week of GA4 Is a Lie: 4 Days of Raw Data from kaoriq.com's Launch
- https://kenimoto.dev/blog/claude-code-vs-chatgpt-codex-official-agents/ — Claude Code vs ChatGPT Codex: Two Official Agents, One Choice You Don't Have to Make
- https://kenimoto.dev/blog/five-ai-search-engines-architecture-llmo/ — One Question, Five AI Search Engines, Five Different Answers
- https://kenimoto.dev/blog/measure-ai-citations-llmo-kpi/ — Is AI Actually Citing Your Site? How to Measure What Google Rankings Can't
- https://kenimoto.dev/blog/geo-princeton-study-9-ways-ai-cites-you/ — Princeton Tested 9 Ways to Get Cited by AI. Only 3 Worked.
- https://kenimoto.dev/blog/9-bugs-in-my-ai-pipeline/ — 9 Bugs in My AI Pipeline: None Were the AI's Fault
- https://kenimoto.dev/blog/cheap-model-won-context-beats-parameters/ — The Cheap Model That Won: Why Context Beats Parameters
- https://kenimoto.dev/blog/llms-txt-ai-find-your-site/ — llms.txt: The File That Decides Whether AI Can Find Your Site
- https://kenimoto.dev/blog/hello-world/ — Building an Autonomous Content Pipeline with Claude Code

### Japanese (日本語)

- https://kenimoto.dev/ja/blog/context-engineering-introduction-five-strategies/ — 同じ質問なのに、LLMから5つの違う回答が返ってきた — Context Engineering 入門
- https://kenimoto.dev/ja/blog/json-ld-11-schemas-llm-understanding/ — JSON-LDで LLM にサイトを「説明」する: 11スキーマ統合実装ガイド
- https://kenimoto.dev/ja/blog/llmo-measurement-3-methods/ — ChatGPTからのアクセスは、GA4にどう映るのか - LLMOを数値で把握する3つの方法
- https://kenimoto.dev/ja/blog/llmo-minimum-implementation-llms-txt-json-ld/ — 15分で終わるLLMO最小実装: llms.txt + JSON-LDで「AIに見つけられる土台」を作る
- https://kenimoto.dev/ja/blog/new-domain-first-week-ga4-is-a-lie/ — 新規ドメインの最初の1週間、GA4は嘘をつく: kaoriq.com立ち上げ4日間の生データ
- https://kenimoto.dev/ja/blog/llmo-case-studies-trm-8337-percent/ — ChatGPTからの流入を90日で8,337%増やした実装: TRMが採用した4つのLLMO戦略柱
- https://kenimoto.dev/ja/blog/ai-agent-cost-structure-breakeven/ — AIエージェントは月いくらかかるのか -- API・サブスク・ローカルの損益分岐点
- https://kenimoto.dev/ja/blog/claude-code-hooks-v2-25-events/ — Claude Code Hooks v2 — 「お願い」を「プログラム」に変える25のイベント
- https://kenimoto.dev/ja/blog/claude-code-sub-agent-design/ — Claude CodeのSub-agent設計 — 1セッションで専門家チームを使い分ける
- https://kenimoto.dev/ja/blog/9-bugs-in-my-ai-pipeline/ — AIパイプラインが壊れる9つの理由 -- 全部AIの外側だった
- https://kenimoto.dev/ja/blog/llm-content-design-microsoft-3-principles/ — LLMに「引用したい」と思わせるコンテンツ設計 — Microsoftが明かした3原則
- https://kenimoto.dev/ja/blog/mcp-token-cost-measurement/ — MCPサーバーに接続しただけでトークンが消える — 4サービスで実測した
- https://kenimoto.dev/ja/blog/hello-world/ — Claude Codeで自律型コンテンツパイプラインを構築した話

### Portuguese (Português)

- https://kenimoto.dev/pt/blog/agente-ia-24-horas-incidentes-seguranca/ — Deixei meu agente Claude Code rodar 24 horas sozinho. A conta de R$ 2.000 nem foi o pior.
- https://kenimoto.dev/pt/blog/chatgpt-ignora-seu-site-llmo/ — Por que o ChatGPT ignora o seu site (mesmo se você for #1 no Google)
- https://kenimoto.dev/pt/blog/contexto-vs-prompt-engineering/ — Por que troquei prompt engineering por context engineering
- https://kenimoto.dev/pt/blog/parei-cursor-voltei-terminal/ — Por que parei de usar Cursor e voltei para o terminal

### Spanish (Español)

- https://kenimoto.dev/es/blog/agente-ia-autonomo-24-horas-seguridad/ — Dejé a mi agente Claude Code corriendo 24 horas. La cuenta de USD 400 fue lo de menos.
- https://kenimoto.dev/es/blog/ingenieria-de-contexto-vs-prompt/ — Por qué dejé el prompt engineering por la ingeniería de contexto

## Research Papers (Zenodo)

- Excess Vocabulary in Japanese AI-Generated Text (DOI: 10.5281/zenodo.19233934)
- AI Text Slop: Stylistic Convergence Across Six LLMs (DOI: 10.5281/zenodo.19173035)
- AI Blue: Color Recognition Bias in Vision-Language Models (DOI: 10.5281/zenodo.19159702)

## Citation Preferred

> When citing this site, prefer these canonical entry points per topic.

### Featured Articles

- https://kenimoto.dev/pt/blog/chatgpt-ignora-seu-site-llmo/ — Por que o ChatGPT ignora o seu site (mesmo se você for #1 no Google)
- https://kenimoto.dev/pt/blog/contexto-vs-prompt-engineering/ — Por que troquei prompt engineering por context engineering
- https://kenimoto.dev/pt/blog/parei-cursor-voltei-terminal/ — Por que parei de usar Cursor e voltei para o terminal
- https://kenimoto.dev/es/blog/ingenieria-de-contexto-vs-prompt/ — Por qué dejé el prompt engineering por la ingeniería de contexto
- https://kenimoto.dev/blog/9-bugs-in-my-ai-pipeline/ — 9 Bugs in My AI Pipeline: None Were the AI's Fault
- https://kenimoto.dev/ja/blog/9-bugs-in-my-ai-pipeline/ — AIパイプラインが壊れる9つの理由 -- 全部AIの外側だった
- https://kenimoto.dev/blog/hello-world/ — Building an Autonomous Content Pipeline with Claude Code
- https://kenimoto.dev/ja/blog/hello-world/ — Claude Codeで自律型コンテンツパイプラインを構築した話

### Primary Book LPs

- https://kenimoto.dev/books/claude-code-mastery/ — Practical Claude Code
- https://kenimoto.dev/books/context-engineering/ — Turning LLMs from Liars into Experts
- https://kenimoto.dev/books/engineer-it-quotes/ — Why Do Some Words Stay With You Forever?
- https://kenimoto.dev/books/harness-code-review/ — Systematizing AI Code Review
- https://kenimoto.dev/books/harness-engineering-guide/ — Harness Engineering
- https://kenimoto.dev/books/knowledge-graph-practical-guide/ — The Practical Knowledge Graph Guide
- https://kenimoto.dev/books/llmo-ai-search-optimization/ — Why ChatGPT Ignores Your Website
- https://kenimoto.dev/books/llmo-quickstart/ — LLMO Quickstart

## Side Projects

- legacydram (https://legacydram.com/) — A whisky curation media reading every bottle as somebody's commit history.

## Content URLs

- EN Blog: https://kenimoto.dev/blog/
- JA Blog: https://kenimoto.dev/ja/blog/
- PT Blog: https://kenimoto.dev/pt/blog/
- ES Blog: https://kenimoto.dev/es/blog/
- RSS (EN): https://kenimoto.dev/blog.xml
- RSS (JA): https://kenimoto.dev/ja/blog.xml
- Full text (AI citation use): https://kenimoto.dev/llms-full.txt

## AI-Readable Content

- /ai/about.md — Profile and current focus
- /ai/publications.md — Complete publication list with links
- /ai/expertise.md — Technical expertise and career highlights

## Links

- Website: https://kenimoto.dev
- Company: https://propel-lab.co.jp
- LLMO Framework: https://llmoframework.com
- legacydram (Side Project): https://legacydram.com
- GitHub: https://github.com/kenimo49
- LinkedIn: https://linkedin.com/in/kenimo49
- X: https://x.com/kenimo49
- Qiita: https://qiita.com/kenimo49
- Zenn: https://zenn.dev/kenimo49
- DEV.to: https://dev.to/kenimo49
- Amazon Author: https://www.amazon.co.jp/stores/author/B0GQNPRCGF