Source record

Published by LangChain Blog (T1.5 source). The original is at https://www.langchain.com/blog/how-candidly-built-state-aware-agent-harnesses-with-langsmith.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Candidly describes building a state-aware agent harness for their AI financial planner Cait, using LangSmith traces to infer user state at each conversation turn and select response features based on patterns from similar past conversations, rather than judging only at conversation end.

Firsthand production case study on turn-level state inference over partial traces. Provided excerpt stops before the implementation specifics are reached.

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