What Makes a Great Agent Harness?

Building an AI agent that functions effectively in a multi-user, enterprise environment involves addressing complex challenges beyond initial single-user experimentation. To transition from prototype to production, organizations must focus on three core pillars: security and governance, integration and interoperability, and observability and iteration. Security involves ensuring the agent respects existing access controls and can handle sensitive data securely, while integration emphasizes seamless connections with internal data sources and tools. Observability allows organizations to monitor and refine agent performance over time. Agent harnesses, which serve as the intermediary between text generation and practical computation, are crucial in managing these aspects by facilitating reliable tool calls, context management, and error handling. By leveraging platforms like Credal, enterprises can focus on utilizing their unique organizational knowledge and workflows to create agents that deliver real value, while the platform handles the foundational infrastructure layer.