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Short summary

Pendo's Chief AI Officer Zain Lakhani demonstrates how LangSmith's tracing dashboard became the core feedback loop for Novus, an AI product agent that automatically instruments applications to surface usage insights. By replacing manual design partner check-ins with automated eval sets, LangSmith catches agent failures before customers encounter them, enabling rapid iteration. This shows how observability tooling can scale product feedback loops in AI applications.

• •Novus is an AI agent that automatically instruments products to surface usage insights and suggest fixes
• •LangSmith's trace dashboard replaced manual design partner feedback with automated eval sets
• •Observability tooling enabled faster iteration and prevented customer-facing failures

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