mrq vs Git for AI Coding: When to Use Each
Git and mrq serve different purposes for AI-assisted development. Here's when to use each and how they work together.
When developers first hear about mrq, the immediate question is: “How is this different from git?”
It’s a fair question. Both are version control tools. Both let you go back to previous states. But they solve different problems, and understanding when to use each makes both more valuable.
The Short Answer
Git is for intentional history and collaboration. You commit when you reach meaningful milestones, and those commits become the story of your project.
mrq is for continuous protection during iteration. It captures every change automatically, so you can recover from any point, not just where you committed.
They work well together rather than competing with each other.
What Git Does Well
Git is exceptional at:
Collaboration: Sharing code with teammates, pull requests, code review. The entire professional development workflow is built around git.
Intentional history: Clean commits that document why changes were made. “Added user authentication” tells a story that “snapshot-7ah36” doesn’t.
Deployment: CI/CD pipelines, production releases, rollbacks. Your infrastructure expects git.
Branching: Experimenting with features, managing releases, isolating work.
For these purposes, git is irreplaceable. Nothing about mrq changes that.
Where Git Falls Short for AI Coding
Git was designed for deliberate, discrete changes. You decide when to commit and what message to write.
AI coding breaks this model:
- Changes happen in rapid bursts
- You try multiple approaches quickly
- The AI modifies files you didn’t ask about
- You’re focused on reviewing AI output, not on committing
In practice, developers end up with long gaps between commits. And those gaps are exactly when AI breaks things.
Git protects what you commit. It can’t protect what you don’t.
Git works fine. AI coding just creates a workflow git wasn’t designed for.
What mrq Does Differently
mrq takes a fundamentally different approach:
mrq watch
From this point, every file change is captured automatically. No commits, no messages, no decisions.
When AI breaks something:
mrq history # See all recent states
mrq restore abc123 # Go back to any point
You’re back to exactly where you were, even if you never committed.
mrq protects what you didn’t commit. That’s the gap it fills.
Direct Comparison
| Aspect | Git | mrq |
|---|---|---|
| Trigger | Manual commit | Automatic |
| Granularity | Per-commit | Every file change |
| History type | Intentional, meaningful | Continuous, complete |
| Effort required | Staging, messages | None after setup |
| Best for | Collaboration, deployment | Protection during iteration |
| Recoverable states | What you committed | Everything |
When to Use Git
Use git when you want to:
- Share code with teammates
- Create a meaningful project history
- Deploy to production
- Do code review via pull requests
- Mark intentional milestones
Git commits should be meaningful. “User authentication complete” or “Fix checkout race condition” instead of “checkpoint before AI” or “WIP.”
When to Use mrq
Use mrq when you want to:
- Protect yourself during rapid AI iteration
- Recover from any state, not just commits
- Not think about version control while coding
- Experiment freely without fear
mrq runs silently in the background. You don’t think about it until you need it.
How They Work Together
The best workflow uses both:
# Start your session
mrq watch # Continuous protection starts
# Work with AI
# Iterate freely, try things, experiment
# Everything captured automatically by mrq
# Hit a meaningful milestone
git add -A
git commit -m "Search feature complete"
# Push for collaboration
git push origin feature-branch
# Something broke during iteration?
mrq restore abc123 # Recover any state
Git gives you: Clean history, collaboration, deployment.
mrq gives you: Continuous protection, no gaps, instant recovery.
Together, you get the best of both:
- Meaningful git history that tells a story
- Complete protection during the messy iteration phase
- Freedom to iterate as fast as AI allows
Common Questions
“Doesn’t git stash solve this?”
Git stash helps for single experiments, but it’s manual (requires discipline), limited to one stash at a time, and doesn’t capture intermediate states. When you’re doing 15 micro-experiments in an hour with AI, stash becomes impractical.
“What about committing more often?”
You can try, but discipline breaks down when you’re in flow. The times you forget to commit are usually the times AI breaks something. mrq removes the need for discipline.
“Won’t my git history get cluttered?”
mrq doesn’t touch git. Your git history stays exactly as clean as you want it. mrq keeps its own history of every change, separate from git.
“Do I really need both?”
For light AI usage (occasional suggestions), git alone is probably fine. For heavy AI coding (Cursor Composer, Claude Code, agent mode), the gaps between commits become dangerous. That’s when mrq matters.
Summary
Git and mrq aren’t competing. They solve different problems:
| Problem | Solution |
|---|---|
| Collaboration and deployment | Git |
| Meaningful project history | Git |
| Protection during AI iteration | mrq |
| Recovery from any state | mrq |
Use git for what git is good at: intentional history and collaboration.
Use mrq for what’s missing: continuous protection during the fast, unpredictable AI coding workflow.
Together, you get clean history AND complete protection.
Related Reading
- Git for AI Coding: What’s Missing - The gap explained
- Why Git Commits Don’t Work for AI Iteration - The friction problem
- Git Alternatives for AI Coding - Full comparison of options
- Cursor Checkpoints vs Git vs mrq - Three-way comparison
mrq adds continuous protection to your git workflow. Every change captured automatically, instant recovery when AI breaks things.
Written by mrq team
