Writing Better Commit Messages (and Why AI Can Help)

The Commit Message Problem

We've all seen them:

• fix bug
• update stuff
• WIP
• asdfasdf
• it works now

These commit messages are technically accurate — something was fixed, stuff was updated, it does work now. But they're useless as documentation.

Six months from now, when someone runs git blame to understand why a particular line exists, "fix bug" tells them nothing. They'll have to read the diff, trace the context, and reconstruct the reasoning.

Why Commit Messages Matter for SEO (of Your Codebase)

Think of your git history as a search engine for your codebase's evolution. Good commit messages make it searchable:

• "Fix race condition in payment checkout when cart validation is slow" — You can find this when the same area breaks again
• "fix bug" — You'll never find this when you need it

Teams with good commit messages resolve bugs 40% faster because they can search history to find when and why changes were made.

What Makes a Good Commit Message

A good commit message answers three questions:

1. What changed? (the subject line)
2. Why did it change? (the body)
3. What should reviewers know? (context that isn't obvious from the diff)

The Format

`

type(scope): concise description of what changed

Why this change was necessary. What problem it solves.

Any non-obvious implications or side effects.

`

Examples

Bad: fix login

Good: fix(auth): prevent duplicate session creation on concurrent login attempts

Bad: update API

Good: refactor(api): migrate payment endpoints from REST to GraphQL for consistent error handling

How AI Generates Better Commit Messages

An AI assistant that can read your staged changes understands:

• Which files changed and how they relate to each other
• Whether you added, modified, or removed functionality
• The architectural pattern of your changes (refactor, bugfix, feature)
• The naming conventions your project uses

It can generate a commit message that captures the intent of your changes, not just the mechanics.

AI-Generated vs. Manual

You changed: 3 files in the auth module, added error handling, updated a test.

Manual message: update auth

AI-generated message: fix(auth): add error handling for expired refresh tokens and update corresponding tests

The AI doesn't just describe what files changed — it understands the purpose.

Best Practices

1. Use conventional commits — feat:, fix:, refactor:, docs:, test: prefixes make history scannable
2. Keep the subject under 72 characters — It should fit in a terminal and GitHub UI
3. Use the body for "why" — The diff shows "what," the message should explain "why"
4. Reference tickets — fix(auth): handle expired tokens (#347) creates a traceable link
5. Let AI draft, you edit — AI generates the message, you refine it for accuracy

The Compound Value

Good commit messages compound over time:

• Code review becomes faster (reviewers understand intent before reading code)
• Bug investigation becomes easier (search history for related changes)
• Onboarding becomes smoother (new devs can read the project's story)
• Release notes can be auto-generated from commit history

Your git history is the most permanent documentation you have. Every commit message is a chance to make it more valuable — or more noisy. AI ensures you consistently choose the former.