LangChain. A guided tour of an LLM trace, project, and dataset by LangChain's co-founder — token cost, latency, error rate, feedback aggregation, drilling into a single retrieval-step span. It's the closest visual analogue to what the article describes when it talks about "every call is a span" and why structured traces beat print logging.
It is a vendor walkthrough — watch it for the trace, project and dataset concepts rather than the product pitch; the 'every call is a span' idea transfers to any tracing stack.
You can navigate traces, projects and datasets in LangSmith and read off token cost, latency, error rate and per-span detail.
Basic familiarity with LLM API calls; you don't need to be a LangChain user to follow the trace concepts.
Last reviewed: May 18, 2026
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