Production Bug Auto-Fix
Fixed while sleeping
The Story
A development team was facing frequent production bugs that would wake them up at odd hours. @henrymascot set up OpenClaw as an autonomous bug-fixing agent integrated with their Slack alerts system. The vision was simple: let AI handle the routine bugs while developers focus on complex problems. OpenClaw was trained to diagnose issues, write fixes, test them, and even create pull requests - all without human intervention.
"The bot detected a production bug and fixed it on its own. I woke up to a GitHub notification that it was already resolved."
— @henrymascot
🔧 How It Works
OpenClaw integrates with Sentry for error tracking, analyzes stack traces, writes fixes, runs tests, and creates PRs via GitHub integration.
1. Alert Integration
Connected OpenClaw to Sentry webhooks via Slack to receive real-time production error notifications.
Configured intelligent filtering to distinguish between critical bugs and minor issues that could wait.
2. Error Analysis
When a bug is detected, OpenClaw analyzes the stack trace, error logs, and recent code changes to identify the root cause.
Uses Claude's advanced reasoning to understand complex error patterns and correlate with similar historical issues.
3. Fix Generation
OpenClaw writes code to fix the identified issue, following the project's coding standards and patterns.
Generates multiple potential fixes when uncertain, and tests each one to find the optimal solution.
4. Testing & Deployment
Automated tests run to verify the fix works. Once confident, OpenClaw creates a PR with detailed explanation.
If tests fail, OpenClaw iterates on the fix. Only working solutions are submitted for review.
Tech Stack Used
📊 Results
🛠️ OpenClaw Skills Used
Error Analysis
Analyzes stack traces and error logs
Code Generation
Writes bug fixes following project patterns
Testing
Runs and validates fixes automatically
Git Operations
Creates PRs with detailed descriptions
💡 Tips for Implementation
Start with low-risk bugs to build trust in the system
Always require human review for production deployments
Set clear boundaries for what OpenClaw can fix autonomously
Monitor its decisions closely during the learning phase
Keep detailed logs of all autonomous actions for auditing
💻 Example Configuration
# openclaw/autopilot-fix.md
---
name: autopilot-fix
description: Auto-fix routine production bugs
triggers:
- slack: "#production-alerts"
pattern: "ERROR: *"
severity: "high"
workflow:
1. Analyze Sentry error report
2. Search codebase for similar patterns
3. Generate fix following project conventions
4. Run test suite
5. If tests pass, create PR with "autopilot" label
6. Notify in Slack with PR link
safety:
- require_review: true
- max_changes: 50 lines
- forbidden_paths: ["database/*", "auth/*"]Ready to Build Your Own Automation?
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