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An archive called Agent Fail Museum documents recurring AI failure patterns and provides regression test drafts for submitted failures, aiming to prevent repeat incidents.
Building an open-source API gateway for agentic AI workflows that provides visualization of multi-LLM and tool calls, tracking tokens, cost, and latency without requiring code instrumentation. Uses Rust and Go servers with a Python correlator, seeking collaborators and feedback from AI ops users.
LangChain emphasizes the importance of evaluating AI applications before deployment and monitoring them afterward to continuously improve model performance.