How to Recover AI Coding Mistakes

If you've spent any significant time coding with AI assistants, you've probably had that moment where something goes wrong. Maybe the AI overwrote a file you needed, or confidently refactored something in a way that broke half your tests, or went down a rabbit hole that left your codebase in a confusing state.

AI tools are genuinely useful for accelerating development. Their capability to make sweeping changes quickly can occasionally work against you though. Here's how we think about preventing and recovering from these situations.

The Recovery Problem

AI coding assistants can modify code in ways that are hard to track manually. A single prompt might touch a dozen files. The AI doesn't hesitate or ask for confirmation the way a human collaborator might. Changes happen fast, sometimes faster than you can review them.

AI assistants are actually quite capable and reliable for most tasks. The challenge is that their speed and confidence can outpace human review capacity, especially during longer sessions. You need a way to capture state continuously so you can always get back to where you were.

How mrq Handles This

We built mrq specifically for this workflow. It runs in the background while you work with AI assistants and automatically captures snapshots when meaningful changes happen. You don't need to think about version control during your session, just focus on the work.

Getting started is simple:

npm install -g mrq-cli@latest
mrq login
mrq watch --daemon

Once the daemon is running, every significant change to your codebase is captured automatically. You can see your snapshot history anytime:

$ mrq history

Recent Snapshots
────────────────────────────────────────────────────
  10:47:23  abc123  Added OAuth provider config and login route
                    +142 lines, -3 lines across 4 files

  10:43:51  def456  Refactored auth middleware to support JWT
                    +87 lines, -45 lines across 2 files

  10:41:02  ghi789  Fixed token validation edge case
                    +12 lines, -8 lines across 1 file

  10:38:15  jkl012  Initial auth module setup
                    +234 lines across 6 files
────────────────────────────────────────────────────

Each snapshot includes an AI-generated summary describing what changed, so you can quickly scan and find the point you want to return to.

Instant Recovery

When something goes wrong, recovery is a single command:

mrq restore def456

Your current state is automatically backed up before the restore, so if you change your mind, you can get back to where you were. There's no hunting through history or trying to remember when things last worked. You just pick a snapshot and restore.

The dashboard at dashboard.getmrq.com gives you a visual interface for browsing snapshots, comparing changes between any two points, and viewing the actual diffs. This is particularly helpful when you want to understand what the AI changed before deciding whether to restore.

Working Confidently with AI

The bigger benefit is psychological. When you know you can always recover, you're more willing to let the AI try ambitious things. Want to see if it can refactor your entire auth system? Go for it. If it doesn't work out, you're one command away from being back where you started.

This changes how you work with AI assistants. Instead of carefully scoping prompts to minimize risk, you can be more exploratory. Try the aggressive approach first. If it works, great. If not, restore and try something more conservative.

A Note on Git

You might wonder why not just use git for this. Git is excellent for deliberate, discrete commits with meaningful messages for collaboration and code review.

The challenge is that git requires intentional action to capture state. During rapid AI-assisted iteration, stopping to commit breaks your flow. Most developers either skip commits during these sessions (and lose their safety net) or create noisy checkpoint commits that clutter history.

mrq complements git. Use mrq for the messy exploration phase, then commit to git when you're happy with where things landed. You get continuous protection during development without sacrificing a clean git history for collaboration.

Getting Started

mrq is currently in open beta with a free tier that covers most individual developer needs. If you've experienced the frustration of losing AI-assisted work, or find yourself holding back on experiments because recovery feels uncertain, give it a try:

npm install -g mrq-cli@latest
mrq login  
mrq watch

We'd love to hear how it works for your workflow.