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

罗磊的独立博客
Y
Y Combinator Blog
Recent Announcements
Recent Announcements
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
Visual Studio Blog
MyScale Blog
MyScale Blog
M
MIT News - Artificial intelligence
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
T
The Blog of Author Tim Ferriss
Martin Fowler
Martin Fowler
博客园 - 【当耐特】
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
宝玉的分享
宝玉的分享
Engineering at Meta
Engineering at Meta
WordPress大学
WordPress大学
Google DeepMind News
Google DeepMind News
C
Check Point Blog
Last Week in AI
Last Week in AI
F
Fortinet All Blogs
博客园 - 聂微东
Blog — PlanetScale
Blog — PlanetScale
H
Help Net Security
GbyAI
GbyAI
云风的 BLOG
云风的 BLOG

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
How to Write Better Git Commit Messages with AI
The AI Leverage Weekly · 2026-06-15 · via DEV Community

The AI Leverage Weekly

Bad commit messages are a tax you pay forever. You hit git log six months later and find a wall of "fix stuff", "WIP", "asdf", and "final final v2" — and now you're archaeologist instead of engineer. The good news: AI can eliminate this problem almost entirely, and in this walkthrough I'll show you exactly how to wire it into your workflow with copy-paste prompts you can use today.

Why Commit Messages Fail (And Why AI Actually Helps Here)

The root cause isn't laziness — it's timing. You write the commit message right after a long coding session, when your brain is fried and you just want to push. Context is all in your head, not on the screen.

AI flips this. You feed it the diff and your rough notes; it drafts a structured message. You edit for accuracy. Total time: 30 seconds. The output is consistently better than what most engineers write under pressure.

Step 1: Stage Your Changes and Generate a Diff

Before prompting, get a clean diff of what you're about to commit:

git diff --staged

Copy the output. If the diff is large (500+ lines), narrow it to the most meaningful files:

git diff --staged -- path/to/relevant/file.ts

You don't need to paste every line into the prompt — a representative slice plus a plain-English summary of your intent is enough.

Step 2: Use This Base Prompt

Paste this into your AI assistant of choice (ChatGPT, Claude, Copilot Chat, etc.):

You are a senior engineer helping me write a Git commit message.

Here is the staged diff:
<paste diff here>

My intent: <one sentence about what this change accomplishes and why>

Write a commit message using the Conventional Commits format:
- First line: type(scope): short imperative summary (max 72 chars)
- Blank line
- Body: 2–4 bullet points explaining WHAT changed and WHY, not HOW
- If there's a breaking change, add a BREAKING CHANGE footer

Output only the commit message, no commentary.

A real example output for a token-refresh bug fix might look like this:

fix(auth): prevent silent token refresh on expired session

- Remove automatic refresh call when session TTL has already elapsed
- Add explicit expiry check before calling refreshToken()
- Prevents a race condition that caused duplicate refresh requests
  under slow network conditions

That's immediately useful to the next engineer reading git log.

Step 3: Refine With a One-Line Follow-Up

If the first draft is close but not quite right, don't re-explain from scratch. Just correct the specific problem:

The scope should be "session" not "auth", and the first line
is too long — tighten it to under 60 characters.

AI handles surgical edits like this well. You're the reviewer; it's the first-draft writer.

Step 4: Build a Shell Alias for Speed

The friction of copy-pasting manually will kill this habit. Automate it. Add this to your .zshrc or .bashrc:

alias gcm='git diff --staged | pbcopy && echo "Diff copied. Paste into your AI prompt."'

On Linux, swap pbcopy for xclip -selection clipboard. Now your staged diff is on your clipboard in one command, ready to paste into any AI chat.

For teams using the GitHub CLI, you can go further and pipe directly into a script that calls an API — but the manual copy-paste habit alone will get you 80% of the value.

Step 5: Add a Linter to Enforce the Format

Writing good messages is only half the battle — the other half is making sure they don't regress. Add commitlint to your repo:

npm install --save-dev @commitlint/cli @commitlint/config-conventional
echo "module.exports = { extends: ['@commitlint/config-conventional'] };" > commitlint.config.js
npx husky add .husky/commit-msg 'npx --no -- commitlint --edit "$1"'

Now any commit that doesn't follow Conventional Commits format gets rejected before it ever touches your branch. Pair this with the AI prompt above and the format issues go away almost entirely.


This prompt pattern is one of the ones I've packaged into The AI Leverage Playbook: 50 Prompts & Workflows for Engineers — but the version above is enough to get real value on its own.


What Good Looks Like at Scale

Once this habit is set, your git log becomes actual documentation. You can:

  • Run git log --oneline to get a readable changelog for a release
  • Use git log --grep="fix(auth)" to find every auth-related fix without grepping source
  • Onboard new engineers by pointing them at commit history, not Confluence

The commit message becomes a first-class artifact, not an afterthought.

Quick Reference: The Prompt, One More Time

You are a senior engineer helping me write a Git commit message.

Diff:
<paste>

Intent: <one sentence>

Format: Conventional Commits. First line ≤72 chars, imperative mood.
Body: 2–4 bullets on what changed and why. BREAKING CHANGE footer if needed.
Output the commit message only.

Save that. Reach for it every time you're about to type "fix stuff."


I break down one workflow like this every week in The AI Leverage Weekly — practical, no fluff, free. Subscribe: https://theaileverageweekly.beehiiv.com/subscribe?utm_source=devto&utm_medium=article&utm_campaign=long_w6