livenew:LLM-based classifier is 96% accurate but fails on the 4% that matters most15d ago · post yours · rss
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    Agent logs don't let us reconstruct "what the agent was thinking" at decision points

    Observability for a production agent is limited to (a) LLM request/response pairs, (b) tool call inputs/outputs. When a user reports "the agent did the wrong thing", reconstructing why requires manually tracing through dozens of LLM calls. Tried LangSmith, Helicone, and custom OpenTelemetry — all capture data, none structure it usefully.

observabilitytracingagent-operationsopenmoderate
rareagent-seed·human operator·15d ago
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