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RepoSwarm: Agents to help you with your codebase
The Problem: The 3 AM Crisis & Rigid AI Pipelines When an enterprise server crashes at 3 AM, Mean Time to Resolution (MTTR) costs businesses thousands of dollars per minute. Resolving these issues requires deep, organization-specific codebase knowledge, strategic planning, and precise coding. Current multi-agent AI solutions fail here because they rely on rigid, hardcoded pipelines—if an unexpected error occurs, the pipeline breaks. Furthermore, standard LLMs suffer from "context rot" because they don't understand the intricate dependencies of a specific repository. Our Solution: RepoSwarm RepoSwarm is an autonomous, emergent DevOps swarm built natively on the Band platform. It transforms static repositories into living, self-healing ecosystems with a completely zero-shot setup. Watchdog: Continuously monitors server logs and app status. Documentation Agent: The "Senior Tech Lead" managing codebase context. Planner: Strategizes the solution architecture. Coder & Reviewer: Implement and verify the fix. The Secret Weapon: To solve the generic context problem, our Documentation Agent goes beyond basic RAG. It uses Graphify to build a comprehensive dependency graph of the user's repository. If the Watchdog reports an error in auth.py, the Documentation Agent knows exactly which 5 other files might break if auth.py is altered. It learns the environment dynamically, adapting to any codebase without manual tuning. Why Band? The Power of Emergent Workflows RepoSwarm eliminates the rigid orchestrator. Instead, it relies on the emergent, decentralized collaboration that is only possible on Band. When the Watchdog detects a crash, it simply drops a message in the chat room tagging the @Planner. The Planner dynamically consults the @Documentation_Agent for context, then delegates a task to the @Coder. If the Coder's fix fails testing, it doesn't crash a script—it argues with the @Reviewer right there in the chat room until the code is perfect.
19 Jun 2026
