Overcoming AI Agent Failures in Production with Orchestration

The article discusses the challenges of running AI agents in production, such as frequent crashes, multi-step task failures, and hidden costs. The author presents a solution called Nexus OS, an orchestration layer that brings battle-tested patterns from other industries to AI agents, including supervisors, sagas, cost controllers, and agent identity management.

Details

The article describes the common problems faced when running AI agents in production, such as frequent crashes due to network issues, rate limits, or context window overflows; multi-step tasks that fail halfway through, leaving corrupted state; and invisible costs that can quickly escalate. To address these challenges, the author built Nexus OS, an orchestration layer that brings proven patterns from other industries to the world of AI agents. Nexus OS includes supervisors that automatically restart crashed agents, sagas that handle multi-step tasks with compensation actions, cost controllers to manage budgets and prevent surprise bills, and agent identity management to verify trust levels. The system is built in Rust for performance and security, using WASM sandboxing to isolate agent code and YAML configuration for readability and familiarity. By providing this robust infrastructure, Nexus OS aims to make it easier and more reliable to run AI agents in production environments.