Building Samba: An Autonomous AI Agent That Fixes Production Errors
How we built an AI coding agent that listens to production errors, analyzes code, and automatically creates pull requests with fixes — all in real-time.
The Problem: Production Errors Never Sleep
Every developer knows the feeling: you're enjoying a peaceful evening when suddenly your phone buzzes with a Sentry alert. A critical error in production. Users are affected. The clock is ticking.
Traditional workflows require developers to manually investigate errors, understand the context, write fixes, test them, and deploy. This process can take hours, especially for complex issues or when the original developer isn't available.
Enter Samba: The Autonomous Code Fixer
Samba is our answer to this problem. It's an AI coding agent that operates completely autonomously, turning production errors into pull requests without human intervention.
How Samba Works:
- Listen: Monitors error tracking services like Sentry, Bugsnag, and PostHog
- Analyze: Uses GPT-5 to understand the error context and locate faulty code
- Fix: Generates contextual code fixes based on the error and surrounding code
- Deploy: Creates pull requests with detailed explanations and test suggestions
Technical Architecture
Building Samba required integrating several complex systems:
Error Signal Processing
We built webhooks that listen to multiple error tracking services. When an error occurs, Samba receives the full stack trace, error context, and affected user information in real-time.
Intelligent Code Analysis
Using GPT-5's advanced reasoning capabilities, Samba analyzes the error alongside the relevant codebase. It understands not just what went wrong, but why it went wrong and how to fix it properly.
Automated Pull Request Generation
Once Samba identifies a fix, it automatically creates a pull request with detailed explanations, test suggestions, and rollback instructions. The PR includes context about the original error and the reasoning behind the fix.
The Future of Autonomous Development
Samba represents a glimpse into the future of software development, where AI agents work alongside developers to maintain and improve codebases autonomously. While we built this as a hackathon project, the implications are profound.
Imagine a world where production errors are fixed before you even know they exist. Where your codebase continuously improves itself. Where developers can focus on building new features instead of firefighting production issues.
Built for YC's AI Coding Agents Hackathon
Samba was created as part of Y Combinator's AI Coding Agents Hackathon, showcasing the potential of autonomous AI systems in software development. While this remains a hackathon project, it demonstrates the exciting possibilities when AI agents are given the tools to understand, analyze, and fix code independently.
Technical Challenges & Solutions
Building an autonomous code-fixing agent presented unique challenges:
Context Understanding
The biggest challenge was helping the AI understand not just the error, but the broader context of the codebase. We solved this by providing GPT-5 with relevant file contents, dependency information, and historical error patterns.
Safety & Reliability
Autonomous code changes require extreme caution. We implemented multiple safety layers, including code review suggestions, rollback instructions, and confidence scoring for each proposed fix.
What's Next?
While Samba was built as a hackathon project, it opens up exciting possibilities for the future of software development. The concept of autonomous code maintenance could revolutionize how we think about production stability and developer productivity.
We're excited to see how the community builds upon these ideas and pushes the boundaries of what's possible with AI coding agents.