How Cleric’s AI SRE leveled up with continuous learning through LangSmith

Cleric is an AI agent designed to assist engineering teams in diagnosing and resolving production issues by conducting parallel investigations on various systems using existing observability tools. It operates similarly to a human engineer by analyzing database metrics, network traffic, application logs, and system resources, communicating findings and seeking guidance through Slack. By leveraging LangSmith's tracing capabilities, Cleric can compare different investigation strategies, aggregate performance metrics, and learn from user feedback to refine its methods and generalize successful approaches across deployments while maintaining privacy. This approach aims to transition more operational responsibilities to autonomous systems, allowing engineering teams to focus on strategic initiatives and product development. Each resolved incident not only improves Cleric's efficiency but also contributes to developing self-healing infrastructure, aligning with the future of engineering that emphasizes product creation over operation.

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