Why don't git commits work for AI coding?

Git commits require you to stop, stage files, and write a message. During rapid AI iteration, this friction causes developers to skip commits, leaving them unprotected when AI breaks things.

How often should I commit when using AI?

For meaningful history, commit at milestones. For protection during iteration, use automatic snapshots (mrq) instead of constant commits. This gives you clean history plus continuous safety.

What's wrong with checkpoint commits?

Checkpoint commits ('before AI', 'WIP', 'trying something') clutter your history and require discipline that breaks down when you're in flow. Automatic snapshots provide the same protection without the noise.

Is there a better alternative to git commits for AI coding?

Use git commits for intentional milestones and automatic snapshots (like mrq) for continuous protection. They complement each other: git for history, snapshots for safety.

Why Git Commits Don't Work for AI Iteration

The standard advice for AI coding is simple: commit before every AI operation. That way, if something breaks, you can revert.

In theory, this works. In practice, it doesn’t.

The Theory

The disciplined workflow looks like this:

git commit -am "checkpoint before AI refactor"
# Ask AI to do something
# Review the changes
git commit -am "AI: refactored auth module"

Safe. Clean. Recoverable.

The Reality

Here’s what actually happens when you’re coding with Cursor or Claude:

You ask the AI to make a change
It works, you keep going
You ask for another change
That works too
You’re in flow now, iterating quickly
The AI makes another change
Something breaks
You realize you haven’t committed in 20 minutes

You didn’t forget because you’re careless. Committing interrupts flow, and your brain optimizes to avoid interruptions.

When you’re iterating rapidly, trying different approaches and accepting suggestions, stopping to write commit messages feels like friction. So you skip it “just this once.” Then again. Then AI deletes half your files.

Why Discipline Fails

Git commits require three things:

Decision: You have to decide it’s time to commit
Action: You have to stage files and write a message
Context switch: You have to think about what to say

During rapid AI iteration, all three create friction.

You don’t want to stop and think about commit messages when you’re testing whether an approach works. You want to keep moving. The AI is fast, and you want to keep up.

Interrupting flow has a real cost, and your brain naturally optimizes to avoid it.

The Checkpoint Commit Problem

Some developers try to solve this with low-effort checkpoint commits:

git commit -am "before AI"
git commit -am "WIP"
git commit -am "trying something"
git commit -am "another attempt"

This technically works for recovery. But it creates problems:

Cluttered history: Your git log becomes noise
Still requires discipline: You still have to remember to do it
Breaks collaboration: These commits aren’t meaningful for teammates

And even with checkpoint commits, you still have gaps. The moment between one checkpoint and the next is unprotected.

A Different Approach

What if you didn’t have to decide when to save?

mrq takes a different approach. Instead of requiring commits, it captures every file change automatically:

mrq watch

Now every change is recorded. No decisions, no messages, no friction.

When AI breaks something:

mrq restore abc123

Back to any point, not just commits. Including the state from 30 seconds ago that you definitely wouldn’t have committed.

Git for History, Snapshots for Safety

You don’t need to abandon git. Git serves a different purpose than continuous protection.

Purpose	Tool	When
Meaningful history	Git commits	When features are complete, before deployment
Continuous safety	Automatic snapshots	Always, during all iteration

The workflow:

# Start session
mrq watch                    # Protection starts

# Iterate with AI
# No commits needed, everything captured

# Hit a real milestone
git commit -m "User auth complete"   # Clean, meaningful

# Something broke earlier?
mrq restore abc123           # Recover any state

Your git history stays clean. Your intermediate states are all recoverable. You iterate as fast as AI allows.

The Key Insight

Git commits require discipline. Discipline breaks down during rapid iteration.

Automatic snapshots require no discipline. They just run.

The developers who work confidently with AI aren’t more disciplined about committing. They’ve set up protection that doesn’t require discipline.

Summary

Git commits don’t work for AI iteration because:

They require decisions that interrupt flow
Discipline fails when you’re iterating quickly
Checkpoint commits clutter history without solving the problem

Automatic protection that runs without thinking solves this:

mrq for continuous snapshots (every state recoverable)
Git for intentional milestones (clean history)

Stop trying to be more disciplined. Set up protection that doesn’t require it.

Git for AI Coding: What’s Missing - The gap in detail
Git Alternatives for AI Coding - What else exists
Backup Your Code Before Using AI - Complete protection guide
How to Safely Use AI Coding Assistants - Full workflow

mrq captures every change automatically. No commits, no discipline, no gaps. Instant recovery when AI breaks things.