惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
月光博客
月光博客
aimingoo的专栏
aimingoo的专栏
Google DeepMind News
Google DeepMind News
Recent Announcements
Recent Announcements
MyScale Blog
MyScale Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
S
SegmentFault 最新的问题
Hugging Face - Blog
Hugging Face - Blog
Martin Fowler
Martin Fowler
WordPress大学
WordPress大学
F
Fortinet All Blogs
小众软件
小众软件
D
Docker
U
Unit 42
博客园 - 聂微东
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
爱范儿
爱范儿
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
IT之家
IT之家
云风的 BLOG
云风的 BLOG
博客园 - 司徒正美
有赞技术团队
有赞技术团队
腾讯CDC

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
From ANSI to Ergo: Remapping the Transition
Leandro · 2026-06-27 · via DEV Community

Leandro

A common story in the mechanical keyboard community goes like this: someone starts suffering from repetitive strain injury (RSI) or general hand pain and decides to transition to an ergonomic keyboard. To make the transition easier, they look for a large layout with plenty of keys. However, once the keyboard arrives, they realize the learning curve is steep. Frustrated, they ask for help in forums, convince themselves they bought the wrong board, and buy another one. Those who don't quit often end up with an expensive collection of ornamental keyboards.

I wanted to avoid this trap. Instead of buying a series of physical keyboards until I found the one, I learned what features my ideal keyboard should have. I settled on the following: a 34-key, column-staggered, split ergonomic keyboard layout.

Next, I needed to find a way to reduce the number of keys I was using on my ANSI keyboard to 34 or less by:

  1. Identifying which keys were truly redundant or unnecessary.
  2. Efficiently mapping the remaining keys using a layered system.

But didn't I need a programmable keyboard for that?

Bridging the Gap in Software

That’s when I discovered KMonad: a powerful tool that allows you to reprogram any keyboard at the software/OS level. This enabled me to test and refine a 34-key layout directly on my standard ANSI keyboard before purchasing any ergonomic hardware.

Introducing Kenkyo (謙虚)

Through this software-first approach, I open-sourced my custom layout under the name Kenkyo (which means humility in Japanese). I chose this name as a contrast to the dominant Miryoku (allure in Japanese) layout.

While Miryoku is highly custom and fully featured, Kenkyo aims to be a simple, non-disruptive, software-driven bridge that allows standard ANSI keyboard users to gradually transition to a layered 34-key workflow.

Over time, I migrated my setup to more modern and lightweight alternatives:

  • keyd: A highly efficient keyboard remapping daemon for Linux.
  • Kanata: A cross-platform remapper focused on advanced features like tap-hold, home row mods, and custom combos.

By remapping the keyboard in software first, I was able to build muscle memory. By the time I received my first ergonomic keyboard I could be productive with it right away. To this day, I still use software for my layout, which allows me to switch between my ergo and laptop keyboards painlessly.